<?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.165386.1</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>External validation of the clinical score system for early detection of late&#x2013;onset neonatal sepsis</article-title>
                <fn-group content-type="pub-status">
                    <fn>
                        <p>[version 1; peer review: awaiting peer review]</p>
                    </fn>
                </fn-group>
            </title-group>
            <contrib-group>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Harahap</surname>
                        <given-names>Aminuddin</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/">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/">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/">Writing &#x2013; Original Draft Preparation</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="yes">
                    <name>
                        <surname>Miranda</surname>
                        <given-names>Stefani</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Data Curation</role>
                    <role content-type="http://credit.niso.org/">Methodology</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; Review &amp; Editing</role>
                    <uri content-type="orcid">https://orcid.org/0000-0002-2764-6528</uri>
                    <xref ref-type="corresp" rid="c1">a</xref>
                    <xref ref-type="aff" rid="a2">2</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Husada</surname>
                        <given-names>Dominicus</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Conceptualization</role>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Utomo</surname>
                        <given-names>Martono Tri</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <contrib contrib-type="author" corresp="no">
                    <name>
                        <surname>Etika</surname>
                        <given-names>Risa</given-names>
                    </name>
                    <role content-type="http://credit.niso.org/">Methodology</role>
                    <role content-type="http://credit.niso.org/">Supervision</role>
                    <role content-type="http://credit.niso.org/">Writing &#x2013; Review &amp; Editing</role>
                    <xref ref-type="aff" rid="a1">1</xref>
                </contrib>
                <aff id="a1">
                    <label>1</label>Department of Child Health, Universitas Airlangga/Dr. Soetomo Academic General Hospital, Surabaya, East Java, 60286, Indonesia</aff>
                <aff id="a2">
                    <label>2</label>Department of Child Health, dr. Ramelan Navy Central Hospital, Surabaya, East Java, 60244, Indonesia</aff>
            </contrib-group>
            <author-notes>
                <corresp id="c1">
                    <label>a</label>
                    <email xlink:href="mailto:stefmir10@gmail.com">stefmir10@gmail.com</email>
                </corresp>
                <fn fn-type="conflict">
                    <p>No competing interests were disclosed.</p>
                </fn>
            </author-notes>
            <pub-date pub-type="epub">
                <day>22</day>
                <month>7</month>
                <year>2025</year>
            </pub-date>
            <pub-date pub-type="collection">
                <year>2025</year>
            </pub-date>
            <volume>14</volume>
            <elocation-id>720</elocation-id>
            <history>
                <date date-type="accepted">
                    <day>7</day>
                    <month>6</month>
                    <year>2025</year>
                </date>
            </history>
            <permissions>
                <copyright-statement>Copyright: &#x00a9; 2025 Harahap A et al.</copyright-statement>
                <copyright-year>2025</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>
            </permissions>
            <self-uri content-type="pdf" xlink:href="https://f1000research.com/articles/14-720/pdf"/>
            <abstract>
                <sec>
                    <title>Objectives</title>
                    <p>Late-onset neonatal sepsis (LONS) is the leading cause of neonatal mortality. Blood culture as the gold standard has a low sensitivity and is time-consuming. To overcome this concern, Husada D. et al. (2020) have developed a clinical score system to help diagnose LONS. Therefore, we conduct this study to externally validate the clinical score system as a predictor of LONS.</p>
                </sec>
                <sec>
                    <title>Methods</title>
                    <p>This was a validation study with cross-sectional design conducted at Dr. Soetomo Academic General Hospital in Surabaya, Indonesia, from November 1, 2021, to April 31, 2022. The study included all eligible neonates aged more than 7 days who were suspected of suffering LONS in the NICU. Subjects were assessed using Husada D. et al.&#x2019;s (2020) score system. Neonates with positive blood culture were confirmed sepsis. The validation study calculated sensitivity, specificity, positive predictive value, and negative predictive value.</p>
                </sec>
                <sec>
                    <title>Results</title>
                    <p>Out of 90 subjects included in this study, 28 (31.1%) had a positive blood culture, with gram-positives predominant (19/28, 67.9%). The mean birth weight was 1976.22 &#x00b1; 791.87 grams, with a mean gestational age of 34.23 &#x00b1; 3.50 weeks. The area under the curve was 98.8% (
                        <italic toggle="yes">p</italic>-value&lt;0.001; 96.9-100.0), which means neonates with LONS will have a higher prediction score. The sensitivity of this tool was 100%, and the specificity was 96.8%. The positive predictive value was 93.3%, while the negative predictive value was 100%.</p>
                </sec>
                <sec>
                    <title>Conclusion</title>
                    <p>This clinical score system is a valid tool that can be used in bedside scoring for early detection of LONS.</p>
                </sec>
            </abstract>
            <kwd-group kwd-group-type="author">
                <kwd>clinical score system</kwd>
                <kwd>Dr. Soetomo Academic General Hospital</kwd>
                <kwd>external validation</kwd>
                <kwd>Indonesia</kwd>
                <kwd>late-onset neonatal sepsis.</kwd>
            </kwd-group>
            <funding-group>
                <funding-statement>The author(s) declared that no grants were involved in supporting this work.</funding-statement>
            </funding-group>
        </article-meta>
    </front>
    <body>
        <def-list>
            <title>Abbreviations</title>
            <def-item>
                <term id="G1">AUC</term>
                <def>
                    <p>Area Under the Curve</p>
                </def>
            </def-item>
            <def-item>
                <term id="G2">CI</term>
                <def>
                    <p>Confidence Interval</p>
                </def>
            </def-item>
            <def-item>
                <term id="G3">LONS</term>
                <def>
                    <p>Late-Onset Neonatal Sepsis</p>
                </def>
            </def-item>
            <def-item>
                <term id="G4">LR+</term>
                <def>
                    <p>Positive Likelihood Ratio</p>
                </def>
            </def-item>
            <def-item>
                <term id="G5">LR&#x2013;</term>
                <def>
                    <p>Negative Likelihood Ratio</p>
                </def>
            </def-item>
            <def-item>
                <term id="G6">NICHD</term>
                <def>
                    <p>National Institute of Child Health and Human Development</p>
                </def>
            </def-item>
            <def-item>
                <term id="G7">NICU</term>
                <def>
                    <p>Neonatal Intensive Care Unit</p>
                </def>
            </def-item>
            <def-item>
                <term id="G8">NPV</term>
                <def>
                    <p>Negative Predictive Value</p>
                </def>
            </def-item>
            <def-item>
                <term id="G9">pH</term>
                <def>
                    <p>potential Hydrogen</p>
                </def>
            </def-item>
            <def-item>
                <term id="G10">PPV</term>
                <def>
                    <p>Positive Predictive Value</p>
                </def>
            </def-item>
            <def-item>
                <term id="G11">ROC</term>
                <def>
                    <p>Receiver Operating Characteristic</p>
                </def>
            </def-item>
            <def-item>
                <term id="G12">SPSS</term>
                <def>
                    <p>Statistical Package for the Social Sciences</p>
                </def>
            </def-item>
            <def-item>
                <term id="G13">WHO</term>
                <def>
                    <p>World Health Organization</p>
                </def>
            </def-item>
        </def-list>
        <sec id="sec5">
            <title>Highlights
</title>
            <p>

                <list list-type="bullet">
                    <list-item>
                        <label>&#x2022;</label>
                        <p>Husada D. et al.&#x2019;s scoring system is a valid tool for early detection of LONS.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>Neonates with LONS have a higher prediction score.</p>
                    </list-item>
                    <list-item>
                        <label>&#x2022;</label>
                        <p>In LONS, most of the pathogenic bacteria were gram-positive.</p>
                    </list-item>
                </list>
            </p>
        </sec>
        <sec id="sec6" sec-type="intro">
            <title>1. Introduction</title>
            <p>Neonatal sepsis is the main cause of newborn death worldwide and one of the main factors contributing to the high neonatal mortality rate.
                <sup>
                    <xref ref-type="bibr" rid="ref1">1</xref>
                </sup> The clinical signs and symptoms of neonatal sepsis are non-specific, and the differential diagnosis is vast.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> Many diagnostic biomarkers have been studied, but none are of sufficient quality to be applied in daily clinical practice.
                <sup>
                    <xref ref-type="bibr" rid="ref3">3</xref>
                </sup> A clinical scoring system approach makes it possible for clinicians, especially in resource-limited settings, to make diagnoses other than microbiological culture.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> Husada D. et al. developed a very practical late-onset neonatal sepsis score system using six parameters that was published in 2020, based on the data from Queen Sirikit National Institute of Child Health in Bangkok. This scoring system has never been validated externally.</p>
            <p>The number of neonatal sepsis cases worldwide is estimated to be around three million per year.
                <sup>
                    <xref ref-type="bibr" rid="ref5">5</xref>
                </sup> According to the World Health Organization (WHO), neonatal sepsis caused approximately 430,000 neonatal deaths in 2013, accounting for an estimated 15% of all neonatal deaths worldwide.
                <sup>
                    <xref ref-type="bibr" rid="ref6">6</xref>
                </sup> Meanwhile, Nyma Z. et al. (2020) reported that neonatal sepsis is currently responsible for approximately 1.6 million neonatal deaths worldwide, with developing countries accounting for 99% of cases (an incidence rate of 38 per 1000 live births).
                <sup>
                    <xref ref-type="bibr" rid="ref7">7</xref>
                </sup> Blood culture has a 60% false-negative rate; hence, it cannot be utilized as a sole diagnostic tool. In contrast, Wirschafter DD. et al. (2011) discovered that the ratio of antibiotics given to positive cultures was 14:1, leading to an overuse of antibiotics.
                <sup>
                    <xref ref-type="bibr" rid="ref8">8</xref>
                </sup>
            </p>
            <p>There are two types of neonatal sepsis based on the age of presentation: early-onset and late-onset neonatal sepsis.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> The age limit to differentiate between early-onset and late-onset neonatal sepsis ranges from 3 to 7 days.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>,
                    <xref ref-type="bibr" rid="ref9">9</xref>&#x2013;
                    <xref ref-type="bibr" rid="ref14">14</xref>
                </sup> Some literature uses 7&#x2009;days as the limit.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>,
                    <xref ref-type="bibr" rid="ref14">14</xref>,
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> Early-onset neonatal sepsis occurs before 7 days of age, while LONS occurs after 7 days of age.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> LONS is typically caused by organisms inferred after delivery and is categorized as a nosocomial community-acquired infection.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>,
                    <xref ref-type="bibr" rid="ref11">11</xref>,
                    <xref ref-type="bibr" rid="ref13">13</xref>,
                    <xref ref-type="bibr" rid="ref15">15</xref>,
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> LONS often presents with more subtle symptoms, such as feeding intolerance, vomiting, diarrhoea, abdominal distention, ABD (apnea, bradycardia, desaturation) spells, and hypoglycaemia. Focal infections such as omphalitis, meningitis, or osteomyelitis may precede or accompany LONS.
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>
                </sup> The most common pathogens causing LONS are 
                <italic toggle="yes">Pseudomonas, Serratia, Escherichia coli</italic>, and 
                <italic toggle="yes">Staphylococcus aureus.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref2">2</xref>,
                    <xref ref-type="bibr" rid="ref13">13</xref>,
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup>
            </p>
            <p>Neonates are very susceptible to infection due to their immature immune system, and they become even more vulnerable at a smaller gestational age due to a lack of maternal antibody transfer in the last trimester.
                <sup>
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> The diagnosis of neonatal sepsis is difficult because the clinical presentations are non-specific. In addition, specific laboratory tests for sepsis markers are still not available in all health facilities. The clinical score system is a method used to assess the likelihood of neonatal sepsis based on clinical indicators.
                <sup>
                    <xref ref-type="bibr" rid="ref4">4</xref>
                </sup> The application of a clinical score system based on clinical presentations was shown to reduce excessive laboratory examination and antibiotic administration.
                <sup>
                    <xref ref-type="bibr" rid="ref13">13</xref>
                </sup> Husada D. et al. (2020) have published a scoring system with six clinical parameters. This clinical score system is simple and practical for a clinician to use in making medical decisions. However, external validation of this scoring system has not been carried out. This prompted the idea for this study, which aimed to validate the score system as a diagnostic tool for LONS.</p>
        </sec>
        <sec id="sec7" sec-type="methods">
            <title>2. Methods</title>
            <sec id="sec8">
                <title>2.1 Study overview</title>
                <p>This was an observational cross-sectional study conducted at the NICU of Dr. Soetomo Academic General Hospital in Surabaya, Indonesia, from November 2021 to April 2022. This hospital is the largest and top referral hospital in eastern Indonesia. It is acknowledged by the WHO as a baby-friendly hospital and boasts a staff of 59 paediatricians. The NICU at this hospital has 36 beds and accommodates 859 neonates annually.</p>
            </sec>
            <sec id="sec9">
                <title>2.2 Population and samples</title>
                <p>

                    <bold>2.2.1 Inclusion criteria</bold>
                </p>
                <p>All neonates older than seven days with suspicions of late-onset neonatal sepsis were included in this study. Neonates presented with temperature instability, lethargy, irritability, poor peripheral perfusion, pallor, petechiae, rashes, sclerema, jaundice, feeding intolerance, vomiting, diarrhoea, abdominal distention with or without visible bowel loops, tachypnea, respiratory distress (grunting, flaring, and retractions), new onset of apnea, bradycardia, and desaturation episodes (ABD [apnea, bradycardia, desaturation] spells), tachycardia, or hypotension were suspected of having LONS.
                    <sup>
                        <xref ref-type="bibr" rid="ref2">2</xref>
                    </sup>
                </p>
                <p>

                    <bold>2.2.2 Exclusion criteria</bold>
                </p>
                <p>Neonates with major congenital malformations (hydrocephalus, atresia, and anencephaly), neonates who died less than 24 hours after the onset of clinical symptoms of sepsis, surgical procedures prior to the diagnosis of sepsis, and culture results of viral or fungal infections were excluded from this study.</p>
                <p>

                    <bold>2.2.3 Definitions</bold>
                </p>
                <p>Late-onset neonatal sepsis: blood culture&#x2013;proven infection occurring in the newborn after 7 days of age caused by a postnatal acquisition (nosocomial or community sources).
                    <sup>
                        <xref ref-type="bibr" rid="ref2">2</xref>
                    </sup>
                </p>
                <p>Neonate: a newborn or an infant within its first 28 days.</p>
                <p>Neonatal sepsis: a clinical syndrome of systemic illness accompanied by bacteremia that occurs in the first month of life.
                    <sup>
                        <xref ref-type="bibr" rid="ref2">2</xref>
                    </sup>
                </p>
                <p>

                    <bold>2.2.4 Sample size determination</bold>
                </p>
                <p>The sample size for this study was calculated using Buderer&#x2019;s formula.
                    <sup>
                        <xref ref-type="bibr" rid="ref18">18</xref>
                    </sup> The prevalence of neonatal sepsis was derived from a study conducted in Philippines, which had a prevalence of 50%.
                    <sup>
                        <xref ref-type="bibr" rid="ref16">16</xref>
                    </sup> With an estimated sensitivity of 97% and an estimation error of 0.05. The alpha (&#x03b1;) was set at 0.05. This study&#x2019;s final sample size was 90 neonates.</p>
                <p>

                    <bold>2.2.5 Sampling techniques</bold>
                </p>
                <p>Total sampling was used as the sampling technique. We included all neonates admitted to our NICU between November 1, 2021, and April 31, 2022 who met the inclusion and exclusion criteria, as we could meet the sample size previously estimated for this study.</p>
            </sec>
            <sec id="sec10">
                <title>2.3 Data collection and management</title>
                <p>All neonates who met the eligibility criteria were set as this research&#x2019;s subjects. A physical examination, routine blood tests, blood gas analysis, and blood culture examination were performed on those neonates. The patient&#x2019;s clinical and laboratory data were then inputted into Husada D. et al.&#x2019;s sepsis score. The following patient characteristics were collected over a six-month period: gender, birth weight, gestational age, Lubchenco curve, mode of delivery, congenital malformations, admission type, length of hospital stay before sepsis, age at examination, and type of medical device used. The data was then transferred to the Statistical Package for the Social Sciences (SPSS) database.</p>
            </sec>
            <sec id="sec11">
                <title>2.4 Data analysis</title>
                <p>Husada D. et al.&#x2019;s (2020) clinical scoring system assesses six clinical parameters in neonates suspected of having sepsis, including poor feeding, abnormal pulse (outside the range of 100-180 beats/minute), abnormal body temperature (outside the range of 36-37.9
                    <sup>o</sup>C), abnormal oxygen saturation (&lt; 92%), abnormal leukocytes based on Manroe&#x2019;s criteria by age,
                    <sup>
                        <xref ref-type="bibr" rid="ref19">19</xref>
                    </sup> and abnormal pH (outside the pH range 7.27-7.45), as seen in 
                    <xref ref-type="table" rid="T1">
Table 1</xref>. This scoring system is divided into four categories in clinical practice: (1) low probability (score 0-2=0-20%), (2) medium probability (score 3-4=21-75%), (3) high probability (score 5-6 = 76-95%), and (4) very high probability (score 7-14 = 96-100%). The recommendation of this scoring system is to give antibiotics to the high and very high probability groups but not to the low probability group. Meanwhile, in the medium probability group, antibiotic administration is determined by the attending clinician based on each patient&#x2019;s condition.</p>
                <table-wrap id="T1" orientation="portrait" position="float">
                    <label>
Table 1. </label>
                    <caption>
                        <title>Husada D. et al.&#x2019;s (2020) clinical scoring system.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Score</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Poor feeding</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Yes = 2
                                    <break/>No = 0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Abnormal heart rate (Normal range 100&#x2013;180 x/minute)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Yes = 3
                                    <break/>No = 0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Abnormal temperature (Normal range 36&#x2013;37.9&#x2009;&#x00b0;C)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Yes = 4
                                    <break/>No = 0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Abnormal oxygen saturation (&lt;&#x2009;92%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Yes = 1
                                    <break/>No = 0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Abnormal leucocytes &#x2794; Normal range:
                                    <break/>&lt;&#x2009;7&#x2009;days of age: 9000&#x2013;30,000/cmm
                                    <break/>7&#x2013;14&#x2009;days of age: 5000&#x2013;21,000/cmm
                                    <break/>&gt; 14&#x2009;days of age: 5000&#x2013;20,000/cmm</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Yes = 2
                                    <break/>No = 0</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Abnormal pH (Normal range: 7.27&#x2013;7.45)</td>
                                <td align="left" colspan="1" rowspan="1" valign="middle">Yes = 2
                                    <break/>No = 0</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Notes: Source
                            <sup>
                                <xref ref-type="bibr" rid="ref4">4</xref>
                            </sup>: </p>
                        <p>The maximum score was 14.</p>
                        <p>The score equal with the probability in the range: </p>
                        <p>Low: 0&#x2013;2&#x2009;=&#x2009;0&#x2013;20%; </p>
                        <p>Medium: 3&#x2013;4&#x2009;=&#x2009;21&#x2013;75%; </p>
                        <p>High: 5&#x2013;6&#x2009;=&#x2009;76&#x2013;95%; </p>
                        <p>Very High: 7&#x2013;14&#x2009;=&#x2009;96&#x2013;100%.</p>
                    </table-wrap-foot>
                </table-wrap>
                <p>Descriptive analysis was performed to obtain the characteristics of the study&#x2019;s population and assessment results based on the clinical scoring system and culture results by describing the distribution and frequency of each variable. The trend of the relationship between assessment results with the clinical scoring system and culture results was explained with cross-tabulation. The chi-square test was carried out on categorical data to assess differences in variables based on the culture results, while the independent sample t-test and Mann-Whitney U test were used on continuous data.</p>
                <p>The validation study was conducted by calculating the sensitivity, specificity, positive predictive value, and negative predictive value with the cross-tabulation test. The area under the curve (AUC) is obtained by calculating the strength of the diagnostic value using the receiver operating characteristic (ROC) curve. The optimal cut-off point between the sensitivity and specificity curves is calculated to obtain the recommended values. The level of significance (&#x03b1;) was set at 5%. SPSS Version 23 (SPSS Inc., Chicago, IL) was used to aid with data analysis.</p>
            </sec>
            <sec id="sec12">
                <title>2.5 Ethical clearance</title>
                <p>The Health Research Ethics Committee of Dr. Soetomo Academic General Hospital issued the ethical approval (0313/KEPK/XI/2021). Written informed consent for this study was obtained from the patient&#x2019;s parents (because the patients were neonates) following an explanation of the research processes.</p>
            </sec>
        </sec>
        <sec id="sec13" sec-type="results">
            <title>3. Results</title>
            <sec id="sec14">
                <title>3.1 Subject enrolment</title>
                <p>During the research period, 370 neonates were treated at the NICU of Dr. Soetomo Academic General Hospital. There were 31.9% (118/370) neonates suspected of having late-onset neonatal sepsis. Twenty-eight of the 118 neonates suspected of having sepsis were excluded from this study, namely 19 neonates with major congenital malformations and 9 neonates who had surgery prior to the diagnosis of sepsis, leaving 90 neonates who met both the inclusion and exclusion criteria (
                    <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>Enrolment of subjects.</title>
                    </caption>
                    <graphic id="gr1" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/182015/67fb462c-b38d-4368-a2c6-bfe79c07ab0e_figure1.gif"/>
                </fig>
            </sec>
            <sec id="sec15">
                <title>3.2 Patient characteristics</title>
                <p>This study&#x2019;s population was predominantly low-birth-weight neonates (&lt;2500 grams, 67/90, 74.4%). The average birth weight was 1976.22 &#x00b1; 791.87 grams, with the culture-positive group having a lower average birth weight (1827.14 &#x00b1; 798.63 grams) than the culture-negative group (2043.55 &#x00b1; 785.98 grams). Premature neonates (&lt;37 weeks) were predominant (65/90, 72.2%). The average gestational age was 34.23 &#x00b1; 3.50 weeks, with the average gestational age in the culture-positive group nearly matching that of the culture-negative group, namely 34.25 &#x00b1; 3.66 grams and 34.23 &#x00b1; 3.50 grams. 
                    <xref ref-type="table" rid="T2">
Table 2</xref> shows the characteristics of the studied neonates. Both positive- and negative-culture groups showed comparable data (
                    <italic toggle="yes">p</italic>-value &gt; 0.05), except for the type of vascular access and ventilation support (
                    <xref ref-type="table" rid="T3">
Table 3</xref>).</p>
                <table-wrap id="T2" orientation="portrait" position="float">
                    <label>
Table 2. </label>
                    <caption>
                        <title>Baseline characteristics of the study population.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="2" valign="top">Variables</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Frequency</th>
                                <th align="left" colspan="2" rowspan="1" valign="top">Culture result</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">(n = 90)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Positive</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Negative</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Gender</td>
                                <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">&#x2003;Male, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">47 (52.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (29.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33 (70.2)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Female, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">43 (47.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (32.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (67.4)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Gestational age</td>
                                <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">&#x2003;&lt; 28 weeks, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (2.2)</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>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;28-31 weeks, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17 (18.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (35.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11 (64.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;32-33 weeks, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18 (20.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12 (66.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;34-36 weeks, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">28 (31.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (32.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19 (67.9)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&#x2265; 37 weeks, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25 (27.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (28.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18 (72.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Birth weight</td>
                                <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">&#x2003;&lt; 800 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (1.1)</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">&#x2003;801-1000 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (7.8)</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>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;1001-1500 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">24 (26.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16 (66.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;1501 &#x2013; 2499 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">35 (38.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (22.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27 (77.1)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;2500 &#x2013; 3999 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">21 (23.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (66.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&#x2265; 4000 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (2.2)</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>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;CVC, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10 (11.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4 (40.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (60.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Mode of delivery</td>
                                <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">&#x2003;Spontaneous, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15 (16.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (20.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12 (80.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Caesarean section, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">75 (83.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50 (66.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Age at examination</td>
                                <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">&#x2003;8-14 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">70 (77.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19 (27.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">51 (72.9)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;15-30 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20 (22.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (45.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11 (55.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Total length of hospital stays</td>
                                <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">&#x2003;&lt; 7 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23 (25.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (21.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18 (78.3)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;7-14 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">55 (61.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16 (29.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">39 (70.9)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;15-30 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12 (13.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (58.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (41.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Congenital malformations</td>
                                <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">&#x2003;Yes, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (32.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (31.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20 (69.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;No, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">61 (67.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19 (31.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">42 (68.9)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Vascular access</td>
                                <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">&#x2003;Peripheral, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">34 (37.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (14.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (85.3)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Umbilical, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">31 (34.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10 (32.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">21 (67.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;PICC, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15 (16.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (60.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6 (40.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Respiratory support device</td>
                                <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">&#x2003;Room air, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10 (11.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2 (20.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (80.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Nasal, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20 (22.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (15.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17 (85.0)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;CPAP, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33 (36.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">10 (30.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23 (69.7)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Ventilator, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">27 (30.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (48.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (51.9)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Notes: PICC: Peripherally inserted central catheter; CVC: Central venous catheter; CPAP: Continuous positive airway pressure.</p>
                    </table-wrap-foot>
                </table-wrap>
                <table-wrap id="T3" orientation="portrait" position="float">
                    <label>
Table 3. </label>
                    <caption>
                        <title>Comparison between positive- and negative-culture groups.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Variables</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Positive-culture result (n = 28)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Negative-culture result (n = 62)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">

                                    <italic toggle="yes">p</italic> value</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Gender</td>
                                <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">&#x2003;Male, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (29.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33 (70.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.956</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Female, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (32.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (67.4)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Gestational age</td>
                                <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">&#x2003;Preterm, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19 (30.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">44 (69.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.836</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Term, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">18 (66.7)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Lubchenco curve</td>
                                <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">&#x2003;SGA, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20 (26.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">55 (73.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.065</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;AGA, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (53.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (46.7)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Birth weight</td>
                                <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">&#x2003;&lt; 2500 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">21 (31.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">46 (68.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.000</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&#x2265; 2500 grams, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">7 (30.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">16 (69.6)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Mode of delivery</td>
                                <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">&#x2003;Spontaneous, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">3 (20.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">12 (80.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.375</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Caesarean section, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">25 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">50 (66.7)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Admission type</td>
                                <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">&#x2003;Inborn, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">17 (30.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">38 (69.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1.000</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Outborn, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11 (31.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">24 (68.6)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Age at examination</td>
                                <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">&#x2003;8-14 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19 (27.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">51 (72.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.212</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;15-30 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (45.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">11 (55.0)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Total length of hospital stays</td>
                                <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">&#x2003;&lt; 7 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (20.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">19 (79.2)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0.311</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;&#x2265; 7 days, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23 (34.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">43 (65.2)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Vascular access</td>
                                <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">&#x2003;Peripheral vascular access, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">5 (14.7)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">29 (85.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.017
                                        <xref ref-type="table-fn" rid="tfn1">*</xref>
                                    </bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Central vascular access, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">23 (41.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">33 (58.9)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Respiratory support device</td>
                                <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">&#x2003;Invasive ventilation, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">13 (48.1)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">14 (51.9)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>0.042
                                        <xref ref-type="table-fn" rid="tfn1">*</xref>
                                    </bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">&#x2003;Non-invasive ventilation, n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">15 (23.8)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">48 (76.2)</td>
                                <td colspan="1" rowspan="1"/>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <p>Notes: SGA: Small for gestational age, AGA: Appropriate for gestational age.</p>
                        <fn-group content-type="footnotes">
                            <fn id="tfn1">
                                <label>*</label>
                                <p>Statistically significant at p &lt; 0.05.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
            </sec>
            <sec id="sec16">
                <title>3.3 The microbial pattern</title>
                <p>Gram-positive bacteria were predominant in this study (19/28, 67.9%). 
                    <italic toggle="yes">Staphylococcus spp.</italic> is the most prevalent type of bacteria (18/28, 64.3%) from the gram-positive group, with 
                    <italic toggle="yes">Staphylococcus epidermidis</italic> and 
                    <italic toggle="yes">Staphylococcus haemolyticus</italic> being the main species. Meanwhile, the majority of gram-negative bacteria were 
                    <italic toggle="yes">Klebsiella spp.</italic> (4/28, 14.3%), followed by 
                    <italic toggle="yes">Acinetobacter baumannii</italic> (
                    <xref ref-type="table" rid="T4">
Table 4</xref>).</p>
                <table-wrap id="T4" orientation="portrait" position="float">
                    <label>
Table 4. </label>
                    <caption>
                        <title>Pathogen distribution in late-onset neonatal sepsis at Dr. Soetomo Academic General Hospital.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="2" valign="top">Pathogen</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Frequency (n = 28)</th>
                            </tr>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">Gram-positive bacteria</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Coagulase-negative staphylococci</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Staphylococcus epidermidis</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Staphylococcus capitis</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Staphylococcus hominis</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">4</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Staphylococcus haemolyticus</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">6</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Streptococcus dysgalactiae</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td colspan="1" rowspan="1"/>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <bold>Gram-negative bacteria</bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Klebsiella aerogenes</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Klebsiella pneumoniae</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Klebsiella oxytoca</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Acinetobacter baumannii</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">2</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Burkholderia cepacia complex</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Serratia plymuthica</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">
                                    <italic toggle="yes">Pseudomonas stutzeri</italic>
</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1</td>
                            </tr>
                        </tbody>
                    </table>
                </table-wrap>
            </sec>
            <sec id="sec17">
                <title>3.4 Validity results</title>
                <p>The six parameters of the Husada D. et al. (2020) score are used to assess neonates suspected of having sepsis. The majority of the participants in this study, 66.7% (60/90), had a sepsis score &lt;5, while the remaining 33.3% had a score &#x2265;5. 
                    <xref ref-type="table" rid="T5">
Table 5</xref> revealed that neonates with low and medium scores had culture-negative results. Contrary to this, neonates with high and very high scores had culture-positive results. The results showed that this scoring system had a very good sensitivity value of 100.0% (87.6-100%), very good specificity of 96.8% (88.8-99.6%), PPV 93.3% (78.1-98.2%), NPV 100.0%, LR+ 31.0 (7.9-121.1), and LR&#x2013; 0.0 with accuracy of 97.8% (92.2-99.7%).</p>
                <table-wrap id="T5" orientation="portrait" position="float">
                    <label>
Table 5. </label>
                    <caption>
                        <title>Distribution of score criteria based on blood culture results.</title>
                    </caption>
                    <table content-type="article-table" frame="hsides">
                        <thead>
                            <tr>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Score criteria</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">
Frequency (n = 90)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Positive-culture result (n = 28)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">Negative-culture result (n = 62)</th>
                                <th align="left" colspan="1" rowspan="1" valign="top">

                                    <italic toggle="yes">p</italic> value</th>
                            </tr>
                        </thead>
                        <tbody>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Low (0-2), n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (48.4)</td>
                                <td align="left" colspan="1" rowspan="4" valign="middle">
                                    <bold>&lt; 0.001
                                        <xref ref-type="table-fn" rid="tfn2">*</xref>
                                    </bold>
</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Medium (3-4), n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (33.3)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">0 (0.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">30 (48.4)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">High (5-6), n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">9 (10.0)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">8 (28.6)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (1.6)</td>
                            </tr>
                            <tr>
                                <td align="left" colspan="1" rowspan="1" valign="top">Very high (7-14), n (%)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">21 (23.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">20 (71.4)</td>
                                <td align="left" colspan="1" rowspan="1" valign="top">1 (1.6)</td>
                            </tr>
                        </tbody>
                    </table>
                    <table-wrap-foot>
                        <fn-group content-type="footnotes">
                            <fn id="tfn2">
                                <label>*</label>
                                <p>Statistically significant at p &lt; 0.05.</p>
                            </fn>
                        </fn-group>
                    </table-wrap-foot>
                </table-wrap>
                <p>The ROC curve demonstrates that Husada D. et al.&#x2019;s (2020) late-onset neonatal sepsis score has a good diagnostic value because the curve is far from the 50% line and approaches 100%. The AUC in this study was 98.8% (95% CI: 96.9-100.0, 
                    <italic toggle="yes">p</italic>-value &lt; 0.001), as shown in 
                    <xref ref-type="fig" rid="f2">
Figure 2</xref>. The AUC value of 98.8% is statistically classified as very strong.</p>
                <fig fig-type="figure" id="f2" orientation="portrait" position="float">
                    <label>
Figure 2. </label>
                    <caption>
                        <title>ROC curve of Husada D. et al.&#x2019;s sepsis score.</title>
                    </caption>
                    <graphic id="gr2" orientation="portrait" position="float" xlink:href="https://f1000research-files.f1000.com/manuscripts/182015/67fb462c-b38d-4368-a2c6-bfe79c07ab0e_figure2.gif"/>
                </fig>
            </sec>
        </sec>
        <sec id="sec18" sec-type="discussion">
            <title>4. Discussion</title>
            <p>During the study period, 31.1% (28/90) sepsis neonates were found in the suspected-sepsis population. There are more males than females. According to a study conducted in Lahore by Sheikh AM. et al. (2010), male neonates are more likely to have neonatal sepsis. This could be due to sex-related factors in host vulnerability to infection.
                <sup>
                    <xref ref-type="bibr" rid="ref12">12</xref>
                </sup> Jaya IGA. et al. (2019) stated that the X chromosome has genes that influence the function of the thymus gland and the synthesis of immunoglobulins. Males are more susceptible to infection since they have only one X chromosome as opposed to two in females.
                <sup>
                    <xref ref-type="bibr" rid="ref20">20</xref>
                </sup> Xiao T. et al. (2017) revealed that the incidence of sepsis was higher in male neonates, particularly 52.1% neonates (100/192, 
                <italic toggle="yes">p</italic>-value 0.930).
                <sup>
                    <xref ref-type="bibr" rid="ref21">21</xref>
                </sup>
            </p>
            <p>In this study, the culture-positive group had a lower average birth weight (1827.14 &#x00b1; 798.63 grams) than the culture-negative group (2043.55 &#x00b1; 785.98 grams). Verstraete EH. et al. (2015) found that very-low-birth-weight was not a significant predictor (
                <italic toggle="yes">p</italic>-value 0.205) despite being related to nosocomial bloodstream infections.
                <sup>
                    <xref ref-type="bibr" rid="ref22">22</xref>
                </sup> Belachew A. and Tewabe T. (2020) reported that neonates with a birth weight less than 2.5 kg are 1.42 times more likely to have sepsis than neonates with a birth weight greater than 2.5 kg.
                <sup>
                    <xref ref-type="bibr" rid="ref23">23</xref>
                </sup>
            </p>
            <p>Raguindin PFN. et al. conducted a validation study on the Okascharoen score in 2014.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>,
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> The Okascharoen score predicts late-onset neonatal sepsis infection based on three clinical parameters (hypotension, abnormal temperature, and poor breathing) and three laboratory parameters (neutrophil bandemia &gt; 1%, thrombocytopenia &lt; 150000, and use of an umbilical catheter).
                <sup>
                    <xref ref-type="bibr" rid="ref24">24</xref>
                </sup> The validation study was performed on neonates aged 2 to 90 days in the NICU of Philippine General Hospital. According to the study, 50% (59/119) of the research subjects experienced sepsis. Males predominate in the culture-negative group. The average birth weight in the culture-negative group was lower than in the culture-positive group (1624 &#x00b1; 942 grams vs. 1905 &#x00b1; 887 grams). The gestational age in the two groups was relatively close, namely 33.93 &#x00b1; 3.9 weeks in the culture-negative group and 34.08 &#x00b1; 3.8 weeks in the culture-positive group.
                <sup>
                    <xref ref-type="bibr" rid="ref16">16</xref>
                </sup> The results of the study reported by Raguindin PFN. et al. (2014) are comparable to those of this study in that LONS was not significantly correlated with gender, gestational age, or birth weight.</p>
            <p>This study found 28 positive-culture results, with the majority of late-onset neonatal sepsis pathogens being gram-positive (19/28, 67.9%), and the remainder being gram-negative (32.1%). According to NICHD Neonatal Research Network data, gram-positive bacteria cause around 79% of LONS, while gram-negative bacteria account for 18%.
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>,
                    <xref ref-type="bibr" rid="ref17">17</xref>
                </sup> 
                <italic toggle="yes">Staphylococcus spp.</italic> is the most prevalent type of bacteria (67.86%) in the gram-positive group, which is dominated by 
                <italic toggle="yes">Staphylococcus epidermidis</italic> and 
                <italic toggle="yes">Staphylococcus haemolyticus.</italic> 
                <italic toggle="yes">Staphylococcus epidermidis</italic> is the most common pathogen detected in hospital-acquired infections, followed by 
                <italic toggle="yes">Staphylococcus aureus, Staphylococcus capitis, Staphylococcus haemolyticus</italic> and 
                <italic toggle="yes">Staphylococcus homini.</italic>
                <sup>
                    <xref ref-type="bibr" rid="ref25">25</xref>
                </sup> 
                <italic toggle="yes">Coagulase-negative staphylococci</italic> are the most abundant gram-positive bacteria (68%).
                <sup>
                    <xref ref-type="bibr" rid="ref15">15</xref>
                </sup> 
                <italic toggle="yes">Staphyloccus epidermidis</italic> is a common colonizer of human skin and mucous membranes that seldom causes infection in healthy tissue. However, it can attach and reproduce on the plastic surface of medical devices, forming a biofilm that is resistant to antibiotics and the immune system.
                <sup>
                    <xref ref-type="bibr" rid="ref26">26</xref>
                </sup>
            </p>
            <p>Clinical score system have various performance in different settings and should be validated locally before being used routinely. A clinician must consider the diagnostic accuracy of a clinical score system while utilizing it to avoid improper or unnecessary antibiotic therapy, which may increase the development of antimicrobial resistance, gastrointestinal imbalance, and adverse clinical consequences. Numerous clinical score systems are available as screening tests for hospital-acquired infections in neonates. Lloyd LG. et al. (2022) discovered eleven clinical score systems in a literature review.
                <sup>
                    <xref ref-type="bibr" rid="ref11">11</xref>
                </sup>
            </p>
            <p>Blood culture, as the imperfect gold standard, acts as the strength as well as the limitation of this study. A negative blood culture cannot rule out the diagnosis of neonatal sepsis if clinical and other examinations are supportive.
                <sup>
                    <xref ref-type="bibr" rid="ref27">27</xref>
                </sup> The ideal gold standard always conveys positive results to all subjects with disease and negative results to all subjects without disease.
                <sup>
                    <xref ref-type="bibr" rid="ref28">28</xref>
                </sup> Even though blood culture yields positive results in only 41.4% of sepsis cases, it remains the best tool for diagnosing neonatal sepsis as it serves as a strong reliance for the sepsis group.
                <sup>
                    <xref ref-type="bibr" rid="ref10">10</xref>
                </sup> Furthermore, blood cultures were only conducted on one side in this study. The recommendation for blood sampling should be at two different locations. Pathogens are more likely to be detected when two specimens are collected. As central venous catheters are currently often utilized in level III NICUs, it is favourable to obtain blood cultures simultaneously in peripheral and central vascular catheters for more accurate results.
                <sup>
                    <xref ref-type="bibr" rid="ref9">9</xref>
                </sup>
            </p>
        </sec>
        <sec id="sec19" sec-type="conclusion">
            <title>5. Conclusion</title>
            <p>Husada D. et al.&#x2019;s (2020) sepsis score is valid as a predictor of late-onset neonatal sepsis at Dr. Soetomo Academic General Hospital. Husada D. et al.&#x2019;s sepsis score can be useful in the diagnosis of LONS. Further research on Husada D. et al.&#x2019;s sepsis score with five parameters (without blood pH) is needed to develop a clinical score system of LONS in limited facilities.</p>
        </sec>
        <sec id="sec20">
            <title>Ethical statement</title>
            <sec id="sec21">
                <title>Ethical approval statement</title>
                <p>The study proposal was approved by the Health Research Ethics Committee of Dr. Soetomo Academic General Hospital (0313/KEPK/XI/2021) from November 24
                    <sup>th</sup>, 2021 to November 24
                    <sup>th</sup>, 2022.</p>
            </sec>
        </sec>
    </body>
    <back>
        <sec id="sec24" sec-type="data-availability">
            <title>Data availability statement</title>
            <sec id="sec25">
                <title>Underlying data</title>
                <p>No data are associated with this article.</p>
            </sec>
            <sec id="sec26">
                <title>Extended data</title>
                <p>Figshare: External validation of the clinical score system for early detection of late&#x2013;onset neonatal sepsis. The project contains the following extended data:
                    <list list-type="bullet">
                        <list-item>
                            <label>&#x2022;</label>
                            <p>
Figure 1 Enrolment of subjects. DOI: 
                                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.29044931">https://doi.org/10.6084/m9.figshare.29044931</ext-link>.
                                <sup>
                                    <xref ref-type="bibr" rid="ref29">29</xref>
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                            </p>
                        </list-item>
                        <list-item>
                            <label>&#x2022;</label>
                            <p>
Figure 2 ROC. DOI: 
                                <ext-link ext-link-type="uri" xlink:href="https://doi.org/10.6084/m9.figshare.29045018">https://doi.org/10.6084/m9.figshare.29045018</ext-link>.
                                <sup>
                                    <xref ref-type="bibr" rid="ref30">30</xref>
                                </sup>
                            </p>
                        </list-item>
                    </list>
                </p>
                <p>Data are available under the terms of the 
                    <ext-link ext-link-type="uri" xlink:href="https://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International license</ext-link> (CC-BY 4.0).</p>
            </sec>
        </sec>
        <ack>
            <title>Acknowledgements</title>
            <p>Not applicable.</p>
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