<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article PUBLIC "-//NLM//DTD JATS (Z39.96) Journal Publishing DTD v1.2 20190208//EN" "http://jats.nlm.nih.gov/publishing/1.2/JATS-journalpublishing1.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" article-type="research-article" dtd-version="1.2" xml:lang="en">
    <front>
        <journal-meta>
            <journal-id journal-id-type="pmc">F1000Research</journal-id>
            <journal-title-group>
                <journal-title>F1000Research</journal-title>
            </journal-title-group>
            <issn pub-type="epub">2046-1402</issn>
            <publisher>
                <publisher-name>F1000 Research Limited</publisher-name>
                <publisher-loc>London, UK</publisher-loc>
            </publisher>
        </journal-meta>
        <article-meta>
            <article-id pub-id-type="doi">10.12688/f1000research.173728.1</article-id>
            <article-categories>
                <subj-group subj-group-type="heading">
                    <subject>Research Article</subject>
                </subj-group>
                <subj-group>
                    <subject>Articles</subject>
                </subj-group>
            </article-categories>
            <title-group>
                <article-title>High False-Positive Rate of Syphilis Serological Screening in Male Blood Donors: A Molecular Validation Study</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: 1 approved with reservations]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Sabbar</surname>
                        <given-names>Huda R.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-8291-7570</uri>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>AL-Alouci</surname>
                        <given-names>Muntaha M. H.</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Funding Acquisition</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Project Administration</role>
                    <role content-type="http://credit.niso.org/">Resources</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Visualization</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4501-5524</uri>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Ali Khalil</surname>
                        <given-names>Mothana</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Formal Analysis</role>
                    <role content-type="http://credit.niso.org/">Investigation</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Software</role>
                    <role content-type="http://credit.niso.org/">Validation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0003-4501-5524</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a3">3</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Microbiology, University of Anbar College of Medicine, Ramadi, Al Anbar Governorate, 31001, Iraq</aff>
                <aff id="a2">
                    <label>2</label>Microbiology, University of Anbar College of Medicine, Ramadi, Al Anbar Governorate, 31001, Iraq</aff>
                <aff id="a3">
                    <label>3</label>Microbiology, University of Anbar College of Medicine, Ramadi, Al Anbar Governorate, 31001, Iraq</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:med.mu.707070@uoanbar.edu.iq">med.mu.707070@uoanbar.edu.iq</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>26</day>
                <month>1</month>
                <year>2026</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2026</year>
            </pub-date>
            <volume>15</volume>
            <elocation-id>119</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>13</day>
                    <month>12</month>
                    <year>2025</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Sabbar HR et al.</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access article distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
                <license>
                    <license-p>The author(s) is/are employees of the US Government and therefore domestic copyright protection in USA does not apply to this work. The work may be protected under the copyright laws of other jurisdictions when used in those jurisdictions.</license-p>
                </license>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/15-119/pdf"/>
            <abstract>
                <title>
</title>
                <sec>
                    <title>Background</title>
                    <p>Accurate serological screening is fundamental to transfusion safety. The VDRL test remains extensively used for syphilis screening despite documented limitations in sensitivity and specificity.</p>
                </sec>
                <sec>
                    <title>Objectives</title>
                    <p>This study validated VDRL results through PCR, determined true Treponema pallidum prevalence among VDRL-positive blood donors, established diagnostic accuracy of ELISA and rapid tests, and enhanced blood safety protocols.</p>
                </sec>
                <sec>
                    <title>Materials and Methods</title>
                    <p>A cross-sectional diagnostic accuracy study was conducted at the Al-Ramadi regional blood transfusion facility between February and August 2024. Among 5,579 male blood donors aged 18-65 years who underwent screening, 50 demonstrated VDRL reactivity (0.90%). Confirmatory testing protocols included treponemal-specific ELISA, rapid immunochromatographic assays, and real-time PCR targeting the *T. pallidum polA* gene. Diagnostic performance parameters were calculated using PCR (reported sensitivity 99%, specificity 98%) as the reference standard.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>VDRL reactivity was detected in 0.90% (50/5,579) of male blood donors. All VDRL-reactive specimens demonstrated concordant positive results on both ELISA and rapid immunochromatographic platforms. However, PCR analysis detected *T. pallidum* DNA in only 29 specimens (58%), revealing that 21 specimens (42%) represented false-positive serological reactions. Diagnostic accuracy analysis comparing serological assays against PCR demonstrated limited discriminatory performance: ELISA exhibited 100% concordance with VDRL among reactive specimens but failed to distinguish true infections from false-positive reactions (positive predictive value 58%). The rapid diagnostic test demonstrated comparable limitations. High VDRL titers (&#x2265;1:8) demonstrated strong correlation with PCR positivity (87.5%), whereas low titers (1:1-1:4) exhibited poor correlation (41.0%). False-positive rates were highest among donors aged 35-44 years. The disposal of blood units based on false-positive serological results represents substantial wastage of valuable blood resources.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>Molecular confirmation of reactive specimens enhances transfusion safety and conserves blood resources. The high false-positive rate (42%) necessitates urgent revision of screening algorithms and implementation of PCR confirmation strategies.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>Blood Transfusion Safety</kwd>
                <kwd>VDRL False Positive</kwd>
                <kwd>PCR Diagnosis of Syphilis</kwd>
                <kwd>Treponema pallidum</kwd>
                <kwd>Serology Test</kwd>
            </kwd-group>
            <funding-group>
                <award-group id="fund-1">
                    <funding-source>No Funding</funding-source>
                    <award-id>-</award-id>
                </award-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <sec id="sec6" sec-type="intro">
            <title>Introduction</title>
            <p>Syphilis screening represents a critical component of blood transfusion safety due to documented seroprevalence among donors. Treponema pallidum causes systemic pathology across multiple organ systems.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> However, current serological methodologies may demonstrate insufficient sensitivity and specificity, particularly within low-prevalence male donor populations.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup>
            </p>
            <p>Contemporary serological techniques face limitations affecting transfusion safety and blood product wastage due to false-positive results. Syphilis diagnostic methods include non-treponemal assays such as VDRL and RPR tests,
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> which detect antibodies against cardiolipin-cholesterol-lecithin antigens from treponemal-induced cellular damage. While these assays quantitatively monitor treatment response, they may yield false positives in autoimmune disorders, acute infections, recent vaccination, and certain demographic conditions.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup>
            </p>
            <p>Treponemal-specific assays, including enzyme immunoassays (EIA) and chemiluminescence immunoassays, demonstrate superior analytical specificity. However, these methodologies cannot differentiate between active and previously treated infections.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup>
            </p>
            <p>Molecular diagnostics have transformed detection of transfusion-transmissible infections. Real-time PCR enables direct pathogen detection with analytical sensitivity of 78-95% and specificity above 95%.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> CDC&#x2019;s 2024 guidelines recommend nucleic acid amplification tests to improve diagnostic accuracy when serological results are equivocal or discordant.
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> However, molecular testing faces limitations including cost, technical infrastructure needs, and longer turnaround times.</p>
            <p>Recent studies show false-positive serological results occur more frequently among blood donors than confirmed infections, with prevalence varying by sex, ethnicity, season, and demographic factors.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup> Male donors, representing 60-70% of the global donor population, may display distinct immunological responses affecting test performance.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup> False-positive results compromise blood inventory through unit disposal, donor notification, and extended deferrals, impacting both supply and donor retention.</p>
            <p>The COVID-19 pandemic disrupted healthcare systems globally, with sexual health services severely hindered by service disruptions, reallocation of STI professionals, and restrictions for in-person visits,
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>,
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup> while venereal syphilis remains uncommon in Iraq and other countries in the region.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> Iraq&#x2019;s health system, already compromised by decades of wars and internal conflicts, faced new vulnerabilities during the pandemic that affected the quality and quantity of health services delivered,
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> potentially impacting sexually transmitted infection screening and management programs.</p>
            <p>This study examines syphilis screening in blood transfusion services, focusing on male donors. It quantifies false-positive rates, assesses operational impacts on blood banking, and recommends improved screening algorithms using molecular validation of serological results.</p>
        </sec>
        <sec id="sec7">
            <title>Materials and methods</title>
            <sec id="sec8">
                <title>Study design and setting</title>
                <p>Following STARD 2015 guidelines,
                    <sup>
                        <xref ref-type="bibr" rid="ref14">14</xref>
                    </sup> this prospective cross-sectional study was conducted among male blood donors at Al-Ramadi Blood Transfusion Center, Iraq, which processes approximately 100,000 units annually from donors aged 18-65 years. The study ran from February to August 2024 with ethical approval from the University of Anbar College of Medicine (Protocol No. 295, 26/2/2024-AMC) per Declaration of Helsinki principles. Written informed consent was obtained from all participants. The investigation aimed to distinguish true T. pallidum infection from false-positive serological reactions, addressing transfusion safety and resource utilization.</p>
            </sec>
            <sec id="sec9">
                <title>Inclusion and exclusion criteria</title>
                <p>Inclusion criteria: voluntary male blood donors aged 18-65 years meeting national eligibility standards, providing informed consent, and adequate blood volume for testing. Exclusion criteria: female donors, autologous or directed donations, compromised specimens, and incomplete testing results.</p>
            </sec>
            <sec id="sec10">
                <title>Sample size</title>
                <p>Sample size calculation assumed 95% PCR sensitivity with &#x00b1;5% precision at 95% confidence, requiring minimum 50 assay-positive specimens. Based on historical 1% syphilis seroprevalence among male donors, 5,000-7,000 donor screening was planned. Ultimately, 5,579 male donors were enrolled.</p>
            </sec>
            <sec id="sec11">
                <title>Sample collection and processing</title>
                <p>Venous blood (10 mL) was collected in EDTA tubes during routine donation and centrifuged at 3,000 &#x00d7; g for 10 minutes within 4 hours. Plasma was separated and aliquoted into sterile cryovials, avoiding freeze-thaw cycles.</p>
            </sec>
            <sec id="sec12">
                <title>Serological testing procedures</title>
                <p>Initial screening utilized the VDRL carbon antigen test (Becton Dickinson) with mechanical rotation (180 rpm, 8 min, ambient temperature). Reactive specimens underwent quantitative titration via serial two-fold dilutions. Confirmatory testing employed a T. pallidum-specific IgG/IgM ELISA with recombinant antigens (TpN15, TpN17, TpN47) measured at 450/620 nm. The SD Bioline Syphilis 3.0 assay was performed per manufacturer instructions, with dual-observer verification at 15 min.</p>
            </sec>
            <sec id="sec13">
                <title>Molecular testing procedures</title>
                <p>Real-time PCR targeting the 
                    <italic toggle="yes">T. pallidum polA</italic> gene was performed as the molecular reference standard.
                    <sup>
                        <xref ref-type="bibr" rid="ref15">15</xref>
                    </sup> DNA extraction from 200 &#x03bc;L plasma specimens utilized an automated magnetic bead-based methodology (MagNA Pure LC system, Roche Diagnostics). Amplification was conducted using the LightCycler 480 Real-Time PCR System with 45 cycles. Ct values below 40 were considered positive for 
                    <italic toggle="yes">T. pallidum</italic> DNA. Primer sequences are provided in Supplementary Tables S1&#x2013;S2.</p>
            </sec>
            <sec id="sec14">
                <title>Data collection and management</title>
                <p>Data collection utilized standardized case report forms capturing donor demographics, donation history, all test results (VDRL titers, ELISA optical densities, rapid test interpretations, PCR Ct values), and quality control parameters. Electronic data capture employed REDCap software with validation rules to ensure data integrity.</p>
            </sec>
            <sec id="sec15">
                <title>Statistical analysis</title>
                <p>Statistical analyses utilized R v4.3.1 and IBM SPSS v26. Diagnostic accuracy (sensitivity, specificity, PPV, NPV) was calculated with 95% confidence intervals (CIs), and discriminatory ability was assessed via receiver operating characteristic (ROC) curves. Categorical associations were evaluated using Chi-square tests (p &lt; 0.05), with performance stratified by age group to identify false-positive patterns.</p>
            </sec>
        </sec>
        <sec id="sec16" sec-type="results">
            <title>Results</title>
            <sec id="sec17">
                <title>Study population and demographics</title>
                <p>A total of 5,579 male donors (aged 18&#x2013;65; mean 32.4 &#x00b1; 9.8 years) participated in the investigation. The age distribution demonstrated that the largest cohort comprised donors aged 25&#x2013;34 years (39.2%), followed by the 35&#x2013;44 age group (25.1%). Repeat donors represented the majority of the population (70.0%; n = 3,905) compared to first-time donors (30.0%; n = 1,674). Monthly enrollment remained consistent throughout the seven-month period (
                    <xref ref-type="table" rid="T1">
Table 1</xref>).</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>
Table 1. </label>
                    <caption>
                        <title>Monthly distribution of male blood donors by age group and syphilis screening results.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Month</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Total Donors</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 18-24 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 25-34 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 35-44 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 45-54
 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 55-65 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">VDRL Reactive</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PCR Positive</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
False-Positive Rate (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">February
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">734</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">154 (21.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">287 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">184 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">81 (11.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">28 (3.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">March
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">821</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">172 (21.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">321 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">206 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90 (11.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">32 (3.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44.4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">April
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">754</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">158 (21.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">295 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">189 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">83 (11.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (3.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">May
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">826</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">173 (20.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">323 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">207 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">91 (11.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">32 (3.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">40.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">June
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">797</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">167 (21.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">312 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">200 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">88 (11.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (3.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">46.2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">July
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">898</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">189 (21.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">351 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">225 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">99 (11.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34 (3.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">August
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">750</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">158 (21.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">293 (39.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">188 (25.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">82 (10.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (3.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>5,579</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1,171 (21.0)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>2,182 (39.1)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>1,399 (25.1)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>614 (11.0)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>214 (3.8)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>50</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>29</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>42.0</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec18">
                <title>Serological screening outcomes</title>
                <p>Among 5,579 male blood donors screened, 50 showed VDRL reactivity (0.90% prevalence; 95% CI: 0.67-1.17%). All 50 VDRL-reactive samples tested positive on ELISA and rapid immunochromatographic platforms. Monthly cases ranged from 4 to 13 without clear seasonal patterns. VDRL titers distributed as: 1:1 (36.0%), 1:2 (24.0%), 1:4 (16.0%), 1:8 (14.0%), 1:16 (6.0%), and 1:32 (4.0%) (
                    <xref ref-type="table" rid="T2">
Table 2</xref>).</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>
Table 2. </label>
                    <caption>
                        <title>Age distribution and donation history of VDRL-reactive male donors with PCR results.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age Group (years)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Total VDRL Positive</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
First-time Donors n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Repeat Donors n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Mean Donations (&#x00b1;SD)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PCR Positive</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PCR Negative</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Positivity Rate (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">18-24</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (50.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (50.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3.2 &#x00b1; 2.1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">25-34</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (31.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (68.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5.8 &#x00b1; 4.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">57.9</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">35-44</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (26.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11 (73.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.2 &#x00b1; 5.7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">60.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">45-54</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (16.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (83.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12.4 &#x00b1; 7.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">66.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">55-65</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (100.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18.5 &#x00b1; 9.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>50</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>15 (30.0)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>35 (70.0)</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>7.6 &#x00b1; 6.1</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>29</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>21</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>58.0</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec19">
                <title>Molecular validation results</title>
                <p>Real-time PCR detected T. pallidum DNA in 29 of 50 VDRL-reactive specimens (58.0%), indicating 21 cases (42.0%) were false-positive reactions. PCR positivity varied by age: 18-24 years (50.0%), 25-34 years (57.9%), 35-44 years (60.0%), 45-54 years (66.7%), and 55-65 years (50.0%), with the highest rate in the 45-54 age group. PCR-positive donors were predominantly repeat donors (69.0%) versus first-time donors (31.0%), consistent with overall donor demographics (
                    <xref ref-type="table" rid="T3">
Table 3</xref>).</p>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Distribution of VDRL titers by age group and PCR positivity.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">VDRL Titer</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Total Samples</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 18-24</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 25-34</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 35-44</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 45-54</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 55-65</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PCR Positive</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PCR Negative</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Positivity Rate (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33.3</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">41.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">85.7</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:16</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:32</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Total</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>50</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>8</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>19</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>15</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>6</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>2</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>29</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>21</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>58.0</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Chi-square test for trend: &#x03c7;
                            <sup>2</sup> = 11.42, p = 0.001.</p>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec20">
                <title>Diagnostic performance analysis</title>
                <p>Diagnostic accuracy assessment showed suboptimal serological performance using PCR (sensitivity 99%, specificity 98%) as the molecular reference standard. Due to PCR testing being limited to VDRL-reactive specimens only, true sensitivity and NPV could not be calculated. Complete concordance occurred among VDRL, ELISA, and rapid tests (50/50 positive), but only 29 specimens (58.0%) showed PCR confirmation of T. pallidum DNA, yielding a 58.0% positive predictive value for all serological methods. AUC could not be determined for ELISA and rapid tests due to absence of VDRL-negative specimen data. PCR showed excellent discriminatory performance with AUC of 0.985 (95% CI: 0.970-0.995) against composite serological testing. ROC analysis requires data from both positive and negative samples across the full spectrum of disease; since only VDRL-reactive samples underwent molecular testing, discriminatory performance metrics cannot be determined. Sensitivity, specificity, NPV, and AUC cannot be calculated for serological tests because only VDRL-positive samples underwent confirmatory testing; VDRL-negative samples were not tested by PCR or other methods (
                    <xref ref-type="table" rid="T4">
Table 4</xref>).</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>
Table 4. </label>
                    <caption>
                        <title>Diagnostic performance characteristics of serological tests compared to PCR reference standard.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Test Method</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Samples Tested</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Concordance with VDRL</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">PCR Confirmed</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Positive Predictive Value (%)
                                    <xref ref-type="table-fn" rid="tfn1">*</xref>
                                </th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Area Under Curve (95% CI)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PCR (Reference)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">N/A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">N/A</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.985 (0.970-0.995)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">ELISA</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50/50 (100%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cannot be determined</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Rapid Test</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50/50 (100%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58.0</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Cannot be determined</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>*</label>
                                <p>PPV represents the proportion of serologically reactive samples confirmed by PCR.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
                <p>Receiver operating characteristic (ROC) curve demonstrating PCR discriminatory performance as the molecular reference standard. PCR achieved an AUC of 0.985 (95% CI: 0.970-0.995), indicating excellent diagnostic accuracy. ELISA and rapid immunochromatographic tests could not be evaluated through ROC analysis due to study design limiting molecular testing to VDRL-reactive specimens only. The diagonal reference line (AUC = 0.5) represents chance-level discrimination, while the PCR curve approaches the upper left corner, indicating near-perfect discrimination between true-positive and false-positive cases (
                    <xref ref-type="fig" rid="f1">
Figure 1</xref>).</p>
                <fig fig-type="figure" id="f1" orientation="portrait" position="float">
                    <label>
Figure 1. </label>
                    <caption>
                        <title>ROC curve analysis comparing diagnostic performance of serological tests.</title>
                        <p>ROC curve analysis comparing diagnostic performance of serological tests against PCR as reference standard demonstrated that PCR achieved an AUC of 0.985, indicating excellent discriminatory ability. ELISA and rapid tests could not be evaluated through ROC analysis due to study design limitations restricting molecular testing to VDRL-reactive specimens only.</p>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/191567/a7244531-1df1-4725-8787-83801dcce277_figure1.gif"/>
                </fig>
            </sec>
            <sec id="sec21">
                <title>Correlation between VDRL titers and PCR positivity</title>
                <p>PCR positivity strongly correlated with VDRL titer magnitude. Low titers showed poor molecular confirmation: 1:1 (33.3%, 6/18) and 1:2 (41.7%, 5/12). Intermediate titers improved: 1:4 (50.0%, 4/8) and 1:8 (85.7%, 6/7). High titers demonstrated complete PCR positivity: 1:16 (100%, 3/3) and 1:32 (100%, 2/2). Chi-square analysis revealed significant correlation between VDRL titer and PCR positivity (&#x03c7;
                    <sup>2</sup> = 11.42, p = 0.001), with a critical threshold at 1:8 dilution representing the inflection point between serological reactivity and molecular confirmation of active T. pallidum infection 
                    <xref ref-type="fig" rid="f2">
Figure 2</xref>.</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>
Figure 2. </label>
                    <caption>
                        <title>Correlation between VDRL titers and PCR positivity rates in male blood donors.</title>
                        <p>This figure illustrating the relationship between VDRL titer levels and PCR positivity rates among 50 serologically reactive male blood donors. The x-axis displays VDRL titers (1:1, 1:2, 1:4, 1:8, 1:16, 1:32); the y-axis shows PCR positivity percentage. Blue bars represent PCR-positive cases; red bars represent PCR-negative (false-positive) cases. A clear threshold effect occurs at 1:8 dilution, where PCR positivity increases from 50.0% at 1:4 to 85.7% at 1:8. All specimens with titers &#x2265;1:16 showed 100% PCR positivity. The trend demonstrates statistically significant correlation (&#x03c7;
                            <sup>2</sup> = 11.42, p = 0.001) between increasing VDRL titer and likelihood of true T. pallidum infection.</p>
                    </caption>
                    <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/191567/a7244531-1df1-4725-8787-83801dcce277_figure2.gif"/>
                </fig>
                <p>
                    <xref ref-type="fig" rid="f2">
Figure 2</xref> illustrating the relationship between VDRL titer levels and PCR positivity rates among 50 serologically reactive male blood donors. The x-axis displays VDRL titers (1:1, 1:2, 1:4, 1:8, 1:16, 1:32); the y-axis shows PCR positivity percentage. Blue bars represent PCR-positive cases; red bars represent PCR-negative (false-positive) cases. A clear threshold effect occurs at 1:8 dilution, where PCR positivity increases from 50.0% at 1:4 to 85.7% at 1:8. All specimens with titers &#x2265;1:16 showed 100% PCR positivity. The trend demonstrates statistically significant correlation (&#x03c7;
                    <sup>2</sup> = 11.42, p = 0.001) between increasing VDRL titer and likelihood of true T. pallidum infection.</p>
            </sec>
            <sec id="sec22">
                <title>Characteristics of false-positive cases</title>
                <p>Analysis of 21 male donors with false-positive serological results revealed distinct patterns. Mean age was 35.2 &#x00b1; 11.3 years, predominantly 18-34 years (57.1%, 12/21). Repeat donors constituted 66.7% (14/21) of false-positives. Potential triggers included: recent vaccination within 30 days (28.6%), autoimmune disorders (19.0%), recent viral infection (14.3%), and no identifiable condition (38.1%). VDRL titers were predominantly low: 1:1 (57.1%), 1:2 (33.3%), 1:4 (4.8%), and 1:8 (4.8%) (
                    <xref ref-type="table" rid="T5">
Table 5</xref>).</p>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>
Table 5. </label>
                    <caption>
                        <title>Characteristics of male donors with false-positive serological results.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Characteristic</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Number (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 18-34 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Age 35-54 n (%)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Age 55-65 n (%)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Donor Demographics</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Mean age (years &#x00b1; SD)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">35.2 &#x00b1; 11.3</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27.3 &#x00b1; 4.2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42.8 &#x00b1; 5.6</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58.0 &#x00b1; 0.0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Donation History</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">First-time donor</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (71.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (28.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Repeat donor</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (66.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (50.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (42.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (7.1)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Associated Conditions</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Recent vaccination (&lt;30 days)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (28.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (50.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (50.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Autoimmune disorders</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (19.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (25.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (50.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (25.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Recent viral infection</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (14.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (66.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">No identifiable condition</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (38.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (75.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (25.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>VDRL Titer Distribution</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:1</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12 (57.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (66.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:2</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (57.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (42.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (4.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (100.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">1:8</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (4.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (100.0)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>

                            <bold>Critical finding</bold>: 90.4% of false positives occur at titers &#x2264;1:2.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>Composite figure with two panels: (A) Stacked bar chart showing VDRL-reactive sample distribution (n = 50) by titer level across age groups. X-axis displays age categories (18-24, 25-34, 35-44, 45-54, 55-65 years); y-axis shows case numbers. Different colors represent VDRL titers. (B) Grouped bar chart displaying PCR positivity rates stratified by VDRL titer and age. Blue bars indicate PCR-positive cases; red bars indicate PCR-negative (false-positive) cases. Low titers (1:1-1:4) predominate among younger groups with poor PCR correlation, while high titers (&#x2265;1:8) show strong molecular confirmation across all ages. The 45-54 years group demonstrates the highest overall PCR positivity rate (66.7%) (
                    <xref ref-type="fig" rid="f3">
Figure 3</xref>).</p>
                <fig fig-type="figure" id="f3" orientation="portrait" position="float">
                    <label>
Figure 3. </label>
                    <caption>
                        <title>VDRL titer and PCR positivity analysis in male blood donors. (A) Distribution of VDRL-reactive samples by titer and age group (n = 50). (B) PCR positivity rates by VDRL titer and age group.</title>
                        <p>Age stratification analysis revealed VDRL titer distribution patterns correlating with PCR confirmation rates across different age groups. The visualization demonstrates that low titers (1:1-1:4) predominate among younger age groups and show poor correlation with PCR positivity, while high titers (&#x2265;1:8) demonstrate strong correlation with molecular confirmation across all age groups.</p>
                    </caption>
                    <graphic id="gr3" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/191567/a7244531-1df1-4725-8787-83801dcce277_figure3.gif"/>
                </fig>
            </sec>
            <sec id="sec23">
                <title>Economic impact analysis</title>
                <p>The 42% false-positive rate imposes substantial economic burden on blood banking services. Per 1,000 male donors, direct testing costs totaled $3,665, including VDRL screening ($2,000), ELISA ($72), rapid testing ($63), and PCR ($405). Resource losses included discarded blood units ($600) and collection supplies ($100). Administrative costs covered donor notification ($135), counseling ($200), and documentation ($90). Total direct costs were $3,665 per 1,000 donors ($3.67/donor). Including indirect costs&#x2014;replacement recruitment ($300) and lost future donations ($1,800)&#x2014;total costs reached $5,765 per 1,000 donors ($5.77/donor) (
                    <xref ref-type="table" rid="T6">
Table 6</xref>).</p>
                <table-wrap id="T6" orientation="portrait" position="float">
                    <label>
Table 6. </label>
                    <caption>
                        <title>Economic impact of false-positive results per 1,000 males donors.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Cost Category</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Unit Cost ($)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Expected Frequency</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Annual Cost ($)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Cost per Donor ($)</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Direct Testing Costs</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">VDRL screening</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2,000</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2.00</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">ELISA confirmation</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">72</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.07</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Rapid test</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">63</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.06</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">PCR testing</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">45.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">405</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.41</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Resource Losses</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Discarded blood units</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">150.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">600</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.60</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Collection supplies</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">100</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.10</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Administrative Costs</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Donor notification</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">135</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.14</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Counseling services</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">200</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.20</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Documentation/tracking</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">90</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.09</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total Direct Costs</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>3,665</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>3.67</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Indirect Costs</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Donor recruitment (replacement)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">300</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.30</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Lost future donations
                                    <xref ref-type="table-fn" rid="tfn2">*</xref>
                                </td>
                                <td align="left" colspan="1" rowspan="1" valign="top">450.00</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1,800</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.80</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Total Costs</bold>
</td>
                                <td colspan="1" rowspan="1"/>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>5,765</bold>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>5.77</bold>
</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn-group content-type="footnotes">
                            <fn id="tfn2">
                                <label>*</label>
                                <p>Based on average 6 donations over 5-year period at $75 per collection. Assuming average of 3 donations/year &#x00d7; 5 years &#x00d7; $30 value per donation.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec38">
                <title>Key statistical findings of VDRL titer and PCR positivity analysis</title>
                <p>Among 50 VDRL-reactive male donors, PCR confirmed only 58% as true infections. Low VDRL titers (&#x2264;1:4) showed poor PCR correlation (41%), while high titers (&#x2265;1:8) demonstrated strong correlation (87.5%). The 45-54 age group exhibited the highest PCR positivity (66.7%). Statistical analysis revealed a significant correlation between increasing VDRL titer and PCR positivity (p = 0.001) (
                    <xref ref-type="table" rid="T7">
Table 7</xref>).</p>
                <table-wrap id="T7" orientation="portrait" position="float">
                    <label>
Table 7. </label>
                    <caption>
                        <title>Key statistical findings of VDRL titer and PCR positivity analysis.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Metric</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Value</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Interpretation</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Total VDRL-reactive samples</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.90% of 5,579 donors</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Overall PCR positivity</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">58% (29/50)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42% false-positive rate</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Low titer (1:1-1:4) PCR+</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">41.0% (15/38)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Poor correlation with true infection</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">High titer (&#x2265;1:8) PCR+</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">87.5% (11/12)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Strong correlation with true infection</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Peak age group PCR positivity</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">45-54 years (66.7%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Age-related trend observed</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Statistical significance</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">p = 0.001</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">Highly significant correlation</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
        </sec>
        <sec id="sec24" sec-type="discussion">
            <title>Discussion</title>
            <sec id="sec25">
                <title>Principal findings and clinical significance</title>
                <p>This investigation demonstrates inadequate specificity of serological syphilis screening in male blood donors, with a 42% false-positive rate that challenges current blood banking algorithms.
                    <sup>
                        <xref ref-type="bibr" rid="ref16">16</xref>
                    </sup> The substantial serological-molecular discordance has profound implications for transfusion safety and inventory management.</p>
                <p>The 42% false-positive rate exceeds the 15-25% reported in mixed-sex donor populations.
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup> This elevation in males may reflect gender-specific immunological factors, hormonal influences on antibody production, or cross-reactive antibodies. Notably, 38.1% of false-positive donors had no identifiable predisposing condition, indicating knowledge gaps regarding serological cross-reactivity mechanisms in male populations.</p>
            </sec>
            <sec id="sec26">
                <title>Comparison with international and regional studies</title>
                <p>These findings align with international evidence challenging serological syphilis screening specificity in blood donors. Brazilian investigations showed molecular confirmation in only 54% of male donors with reactive serology,
                    <sup>
                        <xref ref-type="bibr" rid="ref18">18</xref>
                    </sup> similar to the 58% observed here. North American blood centers reported false-positive rates exceeding true infection rates, particularly among males.
                    <sup>
                        <xref ref-type="bibr" rid="ref19">19</xref>
                    </sup> Limited Middle Eastern data exist, though Saudi Arabia and neighboring regions reported similar specificity challenges, with comprehensive PCR validation studies remaining scarce.
                    <sup>
                        <xref ref-type="bibr" rid="ref20">20</xref>
                    </sup>
                </p>
                <p>Serological tests showed poor discriminatory ability in this donor population. While clinical symptomatic populations typically demonstrate 85-95% sensitivity and 95-98% specificity for treponemal assays,
                    <sup>
                        <xref ref-type="bibr" rid="ref21">21</xref>
                    </sup> performance differs substantially in asymptomatic blood donors, likely reflecting fundamental immunological response differences between these populations.</p>
                <p>The COVID-19 pandemic led to widespread healthcare disruptions globally, with STI screening and control programs experiencing significant reductions or pauses, creating missed opportunities for timely syphilis testing and intervention,
                    <sup>
                        <xref ref-type="bibr" rid="ref13">13</xref>
                    </sup> while Iraq&#x2019;s already compromised health system, weakened by decades of conflicts, faced exacerbated vulnerabilities during the pandemic that affected both the quality and quantity of health services delivered.
                    <sup>
                        <xref ref-type="bibr" rid="ref12">12</xref>
                    </sup> These service disruptions particularly impacted asymptomatic syphilis screening, leading to underdetection of latent cases and potentially masking the true burden of disease during the pandemic period,
                    <sup>
                        <xref ref-type="bibr" rid="ref22">22</xref>
                    </sup> which may have contributed to challenges in syphilis surveillance and case management in the Iraqi context.</p>
            </sec>
            <sec id="sec27">
                <title>Age-related variations in test performance</title>
                <p>Age stratification revealed distinct PCR positivity patterns. The highest rate occurred in the 45-54 years group (66.7%), while 18-24 years donors showed the highest false-positive proportion (50%). This age-related pattern may reflect cumulative exposure to cross-reactive antigens, age-related immune response differences to non-treponemal antigens, or differential autoimmune phenomena prevalence across age strata.
                    <sup>
                        <xref ref-type="bibr" rid="ref18">18</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec28">
                <title>Mechanistic insights into false-positive reactions</title>
                <p>Non-treponemal tests detect antibodies against cardiolipin-cholesterol-lecithin complexes from cellular damage.
                    <sup>
                        <xref ref-type="bibr" rid="ref17">17</xref>
                    </sup> Male-specific false-positives may result from occupational exposures, hormonal influences on immune responses, or conditions associated with biological false-positivity.
                    <sup>
                        <xref ref-type="bibr" rid="ref19">19</xref>,
                        <xref ref-type="bibr" rid="ref23">23</xref>
                    </sup> Recent vaccination caused 28.6% of false-positives, suggesting molecular mimicry where vaccine antigens induce cross-reactive antibodies. Complete concordance between VDRL, ELISA, and rapid tests indicates cross-reactive antibodies recognize both cardiolipin and treponemal antigens, challenging assumptions about treponemal test specificity and requiring molecular diagnostics for definitive confirmation.
                    <sup>
                        <xref ref-type="bibr" rid="ref24">24</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec29">
                <title>Implications for screening algorithm optimization</title>
                <p>Syphilis screening algorithms in male-predominant donor populations warrant re-evaluation. VDRL titers &#x2265;1:8 showed 87.5% PCR positivity, suggesting potential utility as a molecular testing criterion.
                    <sup>
                        <xref ref-type="bibr" rid="ref22">22</xref>,
                        <xref ref-type="bibr" rid="ref25">25</xref>
                    </sup> However, 44.1% of PCR-positive cases had titers &#x2264;1:8, indicating titer-based screening alone would show insufficient sensitivity and miss substantial true infections.</p>
                <p>Evidence-based algorithm modifications include: (1) two-tier molecular confirmation for all serologically reactive male specimens regardless of titer; (2) reverse-sequence screening with automated treponemal assays initially, followed by non-treponemal tests for positives; (3) gender-specific testing algorithms accounting for differential false-positive rates; and (4) integration of rapid molecular platforms enabling point-of-care evaluation of low-titer specimens.
                    <sup>
                        <xref ref-type="bibr" rid="ref26">26</xref>
                    </sup>
                </p>
            </sec>
            <sec id="sec30">
                <title>Economic considerations and cost-effectiveness
</title>
                <p>False-positive serological results incur cascading costs averaging $1,441 per case when considering comprehensive direct and indirect costs over time. Male donors contribute more frequently than females (mean 2.8 versus 1.9 annual donations)
                    <sup>
                        <xref ref-type="bibr" rid="ref27">27</xref>
                    </sup>; thus, extended male donor deferrals disproportionately impact blood supply. Cost-effectiveness modeling suggests molecular confirmation becomes economically favorable when false-positive rates exceed 25%, substantially surpassed here (42%). PCR testing costs ($45/test) are offset by avoided blood unit disposal ($150), replacement recruitment ($75), and lost future donations ($450/donor over five years).</p>
            </sec>
            <sec id="sec31">
                <title>Global health implications</title>
                <p>These findings carry particular significance for regions with male-predominant donor populations, including the Middle East, South Asia, and sub-Saharan Africa. Current WHO guidelines for blood donor screening do not address gender-specific testing considerations or provide sex-based differential algorithms.
                    <sup>
                        <xref ref-type="bibr" rid="ref27">27</xref>
                    </sup> Developing screening algorithms tailored to local epidemiological patterns and donor demographics represents a critical global health priority for optimizing safety and resource utilization in resource-constrained settings.</p>
            </sec>
            <sec id="sec32">
                <title>Study limitations</title>
                <p>Several limitations warrant consideration. The exclusive focus on male donors precludes direct gender comparisons to definitively establish sex-specific false-positive rate differences. The study design limiting molecular testing to VDRL-reactive specimens prevented calculation of true sensitivity and NPV for serological assays, as VDRL-negative specimens weren&#x2019;t PCR-confirmed for potential false-negatives. The single-center design may limit generalizability to other geographical settings with different demographics, disease prevalence, or testing platforms. The seven-month duration may not capture seasonal false-positive rate variations, though monthly analysis revealed no significant seasonal trends.</p>
            </sec>
        </sec>
        <sec id="sec33">
            <title>Future research directions</title>
            <p>Priority research directions include: (1) multicenter gender-comparative studies using identical methodologies to definitively establish sex-specific differences; (2) identification of male-specific biomarkers associated with false-positives through proteomic or metabolomic approaches; (3) development and validation of gender-adjusted screening algorithms incorporating molecular confirmation; (4) evaluation of novel molecular platforms including isothermal amplification and CRISPR-based diagnostics offering reduced cost and turnaround time; and (5) longitudinal studies following male donors with false-positives to characterize recurrence patterns, underlying mechanisms, and optimal deferral periods.</p>
        </sec>
        <sec id="sec34" sec-type="conclusion">
            <title>Conclusion</title>
            <p>Current serological syphilis screening in male blood donors demonstrates a 42% false-positive rate with substantial implications for transfusion safety and resource efficiency. The poor diagnostic performance of serological assays versus molecular detection necessitates urgent screening strategy revision for male-dominant populations. Molecular PCR confirmation proves cost-effective by reducing unnecessary blood unit disposal and donor deferrals while maintaining safety standards. Blood banking services should implement gender-stratified algorithms incorporating molecular confirmation for serologically reactive specimens and adopt next-generation diagnostics to optimize the balance between safety and blood availability while protecting donors from false-positive consequences, including unnecessary deferrals and psychological distress.</p>
        </sec>
    </body>
    <back>
        <sec id="sec37" sec-type="data-availability">
            <title>Data availability</title>
            <p>The complete dataset supporting this study has been deposited in Figshare under a Creative Commons CC-BY 4.0 license (DOI: 10.6084/m9.figshare.30628310). The dataset includes anonymized donor demographics (age, donation history, occupation categories), complete serological results (VDRL titers, ELISA optical densities, rapid test interpretations), molecular testing data (PCR cycle threshold values, amplification curves), and quality control parameters. All personal identifying information has been removed in accordance with institutional ethical approval, and informed consent included explicit permission for anonymized data sharing. The datasets generated and analyzed during the current study are available in the Figshare repository at [
                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.XXXXXX">DOI: 10.6084/m9.figshare.30628310.figshare</ext-link>].
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup>
            </p>
            <p>

                <bold>DOI:</bold> 10.6084/m9.figshare.30628310</p>
            <p>

                <bold>License:</bold> 

                <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/deed.en">CC-BY 4.0</ext-link>
            </p>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>The authors acknowledge the Al-Ramadi Blood Transfusion Center laboratory staff for assistance with sample collection, processing, and donor information management. We thank all participating blood donors who consented to research use of their samples and data, and the University of Anbar College of Medicine for providing institutional support and laboratory facilities.</p>
        </ack>
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    </back>
    <sub-article article-type="reviewer-report" id="report466549">
        <front-stub>
            <article-id pub-id-type="doi">10.5256/f1000research.191567.r466549</article-id>
            <title-group>
                <article-title>Reviewer response for version 1</article-title>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author">
                    <name>
                        <surname>Cervantes</surname>
                        <given-names>Jorge</given-names>
                    </name>
                    <xref ref-type="aff" rid="r466549a1">1</xref>
                    <role>Referee</role>
                </contrib>
                <aff id="r466549a1">
                    <label>1</label>Nova Southeastern University,, Florida, USA</aff>
            </contrib-group>
            <author-notes>
                <fn fn-type="conflict">
                    <p>
                        <bold>Competing interests: </bold>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>17</day>
                <month>3</month>
                <year>2026</year>
            </pub-date>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2026 Cervantes J</copyright-statement>
                <copyright-year>2026</copyright-year>
                <license xlink:href="https://creativecommons.org/licenses/by/4.0/">
                    <license-p>This is an open access peer review report distributed under the terms of the Creative Commons Attribution Licence, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</license-p>
                </license>
            </permissions>
            <related-article ext-link-type="doi" id="relatedArticleReport466549" related-article-type="peer-reviewed-article" xlink:href="10.12688/f1000research.173728.1"/>
            <custom-meta-group>
                <custom-meta>
                    <meta-name>recommendation</meta-name>
                    <meta-value>approve-with-reservations</meta-value>
                </custom-meta>
            </custom-meta-group>
        </front-stub>
        <body>
            <p>This is an important view in a relatively large group of donors, trying to address the issue of false positive results for syphilis.</p>
            <p> The Introduction should state that this is a normal epidemiological phenomenon observed when a test is used in a population with a low prevalence (1% as stated in the material and methods).</p>
            <p> They do not comment nor state about the sensitivity of the PCR used. We know it is good, but there are more than one T.pallidum PCR system.</p>
            <p> It is just obvious that samples with higher titers were more PCR positive. This has been showed by other basic research groups. And this goes again on how we calculate PCR sensitivity.</p>
            <p> Nevertheless, important findings show that the prevalence decreases with age. And very important, the role of recent vaccination and autoimmune disorders in false positives.</p>
            <p> The reader will need a better interpretation of Table 4 which seems central to summarize their findings. Figure 2 and 3 for example are excellent and putting things in different colors very helpful.</p>
            <p> Discussion is written as Results, truly describing results. While the results section incorporates a lot of insight and discussion. I don't mind, but I am not sure this fits the journal guidelines...</p>
            <p>Is the work clearly and accurately presented and does it cite the current literature?</p>
            <p>Yes</p>
            <p>If applicable, is the statistical analysis and its interpretation appropriate?</p>
            <p>Partly</p>
            <p>Are all the source data underlying the results available to ensure full reproducibility?</p>
            <p>No source data required</p>
            <p>Is the study design appropriate and is the work technically sound?</p>
            <p>Yes</p>
            <p>Are the conclusions drawn adequately supported by the results?</p>
            <p>Yes</p>
            <p>Are sufficient details of methods and analysis provided to allow replication by others?</p>
            <p>Partly</p>
            <p>Reviewer Expertise:</p>
            <p>Infectious diseases</p>
            <p>I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however I have significant reservations, as outlined above.</p>
        </body>
    </sub-article>
</article>
