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Research Article

The interest of inflammatory biomarkers in the diagnostic approach in an internal medicine department: A cross-sectional study

[version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]
Jihed Anoun
https://orcid.org/0000-0002-5441-6867
1-3, Wiem Romdhane
https://orcid.org/0000-0001-8559-0393
1-3, Imen Ben Hassine
https://orcid.org/0000-0001-5459-3460
1-3, [...] Wafa Baya1-3, Asma Benabdelaziz4-6, Asma Omezzine4-6, Anis Mzabi1-3, Fatma Ben Fredj1-3, Ali Bouslama4-6
Jihed Anoun
https://orcid.org/0000-0002-5441-6867
1-3, Wiem Romdhane
https://orcid.org/0000-0001-8559-0393
1-3, [...] Imen Ben Hassine
https://orcid.org/0000-0001-5459-3460
1-3, Wafa Baya1-3, Asma Benabdelaziz4-6, Asma Omezzine4-6, Anis Mzabi1-3, Fatma Ben Fredj1-3, Ali Bouslama4-6
PUBLISHED 08 Jan 2024
Author details Author details
OPEN PEER REVIEW
REVIEWER STATUS

Abstract

Background

The role of inflammatory biomarkers in etiological orientation is increasingly under study, and their potential significance is recognized. Given the diversity of diseases managed in internal medicine and the delayed results of microbiological tests, clinicians often face challenges in the diagnostic approach. This study aimed to describe the biomarkers’ role in distinguishing between infectious and noninfectious diseases and define their thresholds for infections.

Methods

Procalcitonin (PCT), neutrophil-to-lymphocyte-ratio (NLR), C-reactive-protein (CRP), fibrinogen, ferritinemia and lactate were measured on admission in all patients admitted to the Internal Medicine Department of Sahloul Hospital, over a 7-month period. The optimal cut-off values for the sensitivities and specificities to the infectious diseases were determined using receiver operating characteristic (ROC) curve analysis and Youden’s index. The diagnostic accuracy of biomarkers for predicting infectious etiologies was calculated by area under the curve (AUC).

Results

Overall, 164 patients were included of whom 32.3% had infectious diseases. The high mean levels of leukocytes (12,047 cells/mm3), NLR (9.7), CRP (152.5 mg/L), PCT (3.28 ng/ml) and fibrinogen (5.37g/L) were significantly linked to infectious etiologies. We identified cut-offs of NLR (6.1), CRP (123mg/L), PCT (0.24ng/mL) and fibrinogen (4.9g/L) to discriminate infectious etiologies in our population. For diagnosing infectious diseases, the CRP showed higher AUC (Sp:89.7%, Se:64.3%, AUC=0.9, 95% CI: 0.83, 0.96; p<10-3) than PCT (Sp:86.1%, Se:62.3%, AUC=0,87, 95% CI: 0.80, 0.93; p<10-3), NLR (Sp:87.1%, Se:61%, AUC=0.81, 95% CI: 0.731, 0.902; p<10-3) and fibrinogen (Sp:84.7%, Se:68.3%, AUC=0.77, 95% CI: 0.65, 0.98; p<10-3). The combination of CRP and NLR levels improved the diagnostic accuracy (AUC=0.93, 95% CI: 0.84, 0.96; p<10-3) for distinguishing between infectious and non-infectious diseases.

Conclusions

Our study showed the usefulness of inflammatory biomarkers, particularly the NLR and its combination with CRP, which are low cost and easy to assess, in promoting the diagnostic accuracy to distinguish infections among other diagnoses.

Keywords

Biomarkers, Inflammation, Infections, diagnoses, procalcitonin, c-reactive protein, complete blood count, neutrophil-to-lymphocyte ratio

Corresponding author: Jihed Anoun
Competing interests: No competing interests were disclosed.
Grant information: The author(s) declared that no grants were involved in supporting this work.
Copyright:  © 2024 Anoun J et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Anoun J, Romdhane W, Ben Hassine I et al. The interest of inflammatory biomarkers in the diagnostic approach in an internal medicine department: A cross-sectional study [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:35 (https://doi.org/10.12688/f1000research.141582.1) First published: 08 Jan 2024, 13:35 (https://doi.org/10.12688/f1000research.141582.1) Latest published: 08 Jan 2024, 13:35 (https://doi.org/10.12688/f1000research.141582.1)

Introduction

The role of inflammatory biomarkers in the etiological orientation is increasingly under study, and their potential significance is recognized. These biomarkers have a double objective: diagnostic, given the wide polymorphism in the presentation of infectious, inflammatory, and neoplastic conditions, and prognosis, especially in sepsis during which a lag can be observed between the major systemic inflammatory reaction and the onset of the first signs of organ failure.1–3

Given the complexity and diversity of symptoms and diseases managed in internal medicine, coupled with the heterogeneity of clinical presentation of systemic diseases and geriatric syndromes, and the delayed results of serologies, microbiological and immunological tests, clinicians often face complex challenges in the diagnostic approach. This justifies using biological tools such as inflammatory biomarkers to ensure accurate and prompt diagnosis and promote swift treatment.4

Additionally, using biomarkers in clinical practice can reduce the prescription of empirical broad-spectrum antibiotics, thereby mitigating the emergence of resistant strains.

The inflammatory biomarkers most commonly used in current practice in diagnostic orientation are procalcitonin (PCT), C reactive protein (CRP), and blood count, but also lactates, fibrinogen and ferritinemia.5–9 It should be noted that the neutrophil-to-lymphocyte ratio (NLR) is an emerging marker of multiple diseases, including bacterial infections, and has gathered substantial attention in medical research.10

Few studies in the literature have described the value of inflammatory biomarkers in the diagnostic approach in internal medicine departments.11

The aims of this study were to describe the inflammatory biomarkers’ role in distinguishing between infectious and noninfectious diseases in an internal medicine department and to define their threshold values indicative of infectious diseases.

Methods

Ethical approval

Ethical approval was obtained from the Ethics Committee of Sahloul University Hospital in December 2022. On enrolment, all patients were informed of the study procedure and purpose, and that data from their medical records would be used in this context. Oral and written consent (recorded in the medical record) was obtained prior to each enrolment.

Study design and sample selection

We conducted a prospective descriptive and analytical study about the etiological profile of inflammatory biomarkers measured on admission to distinguish infectious diseases, inflammatory diseases, and neoplasia, in all patients hospitalized to the Internal Medicine Department of Sahloul Hospital, between January 1 and July 31, 2023.

Inclusion criteria was all patients hospitalized in our Internal Medicine Department between 1/1/2023 and 07/31/2023.

Exclusion criteria were patients hospitalized for complementary management of a documented infection who had already started antibiotic treatment before the admission and those who have not agreed to their data being used in the study.

Data collection

The following data were collected from the patients hospitalized in our internal medicine department: epidemiological details, history of comorbidities, clinical presentation, the final diagnosis, and inflammatory biomarkers. These biomarkers were as follows: white blood cells (WBC) (normal range: 4,000-10,000 cell/mm3),12 neutrophils (normal range: 1,500-7,000 cells/mm3),13 lymphocytes (normal range: 1,500-4,000 cells/mm3),14 NLR (normal range: 1-3),10,15 C-reactive protein (CRP) with normal range < 5 mg/L,6 procalcitonin (normal range <0.1 ng/mL),5 fibrinogen (normal range: 2-4 g/l),8 lactate < 2 mmol/L7 and ferritinemia (normal range in men < 300 μg/L and in women < 200 μg/L).9 PCT positive level for infectious diseases was > 0.25 ng/ml.5 Older adults were defined as those aged 65 years and over.

Statistical analysis

Statistical analysis was performed using the IBM SPSS Statistics (RRID:SCR_016479) version 26.0 for Windows. Qualitative variables were described by their frequencies and percentages and quantitative variables by their means and standard deviation when the distribution was Gaussian and the median and the interquartile range [25th percentile – 75th percentile] otherwise. For the association of categorical variables, the Chi-square test was used. A Student’s T test for independent samples was used to compare means. We considered p<0.05 as statistically significant.

The optimal cut-off values for the sensitivities and specificities to the infectious diseases of the NLR, CRP and PCT, were determined using the receiver operating characteristic (ROC) curve analysis and Youden’s index. The diagnostic accuracy of biomarkers and their combinations for predicting infectious etiologies was calculated by area under the curve (AUC).

Patients were assigned into four groups: Group 1 (G1), infectious diseases; Group 2 (G2), inflammatory diseases (connective tissue diseases, vasculitis, granulomatosis); Group 3 (G3), neoplasia; and Group 4 (G4), other diseases. The non-infectious etiologies combined inflammatory diseases, neoplasia and other diagnoses. We carried out a comparative study of inflammatory biomarkers among the four categories, compared their mean levels among infectious and non-infectious diseases, and determined their cut-offs to discriminate infectious diseases.

Results

Descriptive study

A total of 164 patients were included in the study. The mean age was 50.7 ± 18 years [18 – 92 years] and included 93 female participants (56.7%) and 71 male subjects (43.3%). Overall, 53 patients (32.3%) were aged 65 years and over.

Patients were split into four groups: 53 patients (32.3%) with infectious diseases of whom 45 patients (84.9%) presented with bacterial infections, 62 patients (37.8%) with inflammatory diseases, 14 patients (8.5%) with neoplasms and 35 patients (21.3%) with other diagnoses.

Most patients presented with elevated CRP (57.3%), elevated NLR (56.1%), lymphopenia (48.2%) and elevated PCT (36%) (Table 1).27

Table 1. Inflammatory biomarkers results in different disease categories in the studied population.

CRP, C-reactive-protein; NLR, neutrophil-lymphocyte ratio; PCT, procalcitonin.

Inflammatory biomarkersNumber (n) and percentage
leukocytosis (n=164)56 (34.1%)
Neutrophils (n=164)55 (33.5%)
Lymphopenia (n=164)79 (48.2%)
Lymphocytosis (n=164)3 (1.8%)
Elevated NLR (n=164)92 (56.1%)
Elevated CRP (n=164)94 (57.3%)
Elevated PCT (n=150)59 (36%)
Elevated Fibrinogen (n= 110)44 (26.8%)
Elevated Ferritinemia (n=143)44 (26.8%)
Elevated Lactate (n=153)32 (19.5%)

Analytic study

White blood cells

In the leukocytosis group, which included 56 patients (34.1%), infectious diseases were diagnosed in 30 patients (53.6%), inflammatory diseases in 20 patients (35.7%) and neoplastic diseases in four patients (7.1%), with a statistically significant difference (p<10-3) (Table 2). There was a positive association between leukocytosis and infectious diseases (p<10-3) (Table 3).

Table 2. Summary table of inflammatory biomarkers among the four diagnosis categories in the studied population.

G1, group 1; G2, group 2; G3, group 3; G4, group 4; CRP, C-reactive-protein; NLR, neutrophil-lymphocyte ratio; PCT, procalcitonin.

G1 = Infectious diseases (n= 53)G2 = Inflammatory diseases (n=62)G3 = Neoplasms (n=14)G4 = Other diagnoses (n=35)P-value
Leukocytosis (n=56)30 (35.6%)20 (35.7%)4 (7.1%)2 (3.6%)<10-3
Neutrophilia (n=55)29 (52.7%)20 (36.4%)5 (9.1%)1 (1.8%)<10-3
Elevated NLR (n=92)38 (41.3%)26 (28.3%)12 (13%)16 (17.4%)0.001
Elevated CRP (n=94)47 (50%)25 (26.6%)12 (12.8%)10 (10.6%)<10-3
Elevated PCT (n=59)29 (49.2%)16 (27.1%)10 (16.9%)4 (6.8%)<10-3
Elevated Fibrinogen (n=44)21 (47.7%)12 (27.3%)6 (13.6%)5 (11.4%)<10-3
Hyperferritinemia (n=44)21 (47.7%)12 (27.3 %)7 (15.9%)4 (9.1%)0.001

Table 3. Summary table of the comparison of mean levels of inflammatory biomarkers among infectious and non-infectious diseases in the studied population.

G1, group 1; CRP, C-reactive-protein; NLR, neutrophil-lymphocyte ratio; PCT, procalcitonin

G1= Infectious diseases (n= 53)Noninfectious diseases (n=111)P-value
Mean level of Leukocytes (cells/mm3)120478005<10-3
Mean level of neutrophils (cells/mm3)90155479<10-3
Mean level of NLR9.73.90.015
Mean level of CRP (mg/L)152.534.90.001
Mean level of PCT (ng/mL)3.280.210.036
Mean level of Fibrinogen (g/L)5.373.73<10-3
Mean level of ferritinemia (μg/L)358.8263.50.162

The mean of leukocyte levels of infectious diseases was significantly higher than those of non-infectious diseases (12,047 vs. 8,005 cells/mm3, p<10-3) (Table 3). In Group 1, the mean of leukocytes in older adult patients was higher than in patients under 65 years old (12,870 vs. 11,760 cells/mm3, p=0.53). The optimal cut-off value for discriminating between infectious and non-infectious diseases was 12,800 cells/mm3 (Sp: 87%, Se: 43%, AUC=0.69, 95% CI: 0.58, 0.74; p <10-3).

Neutrophils

In the neutrophilia group, which included 55 patients (33.5%), infectious diseases were diagnosed in 29 patients (52.7%), inflammatory diseases were diagnosed in 20 patients (36.4%) and neoplastic diseases were diagnosed in five patients (9.1%), with a statistically significant difference (p<10-3) (Table 2). There was a positive association between neutrophilia and infectious diseases (p=0.001) (Table 3).

The mean of neutrophilia levels of infectious diseases was significantly higher than those of non-infectious diseases (9,015 vs. 5,479 cells/mm3, p=0.001) (Table 3). In Group 1, the mean of neutrophils in older adult patients was higher than in patients under 65 years old (10,627 vs. 7,780 cells/mm3, p=0.087). The optimal cut-off value for discriminating between infectious and non-infectious diseases was 9,500 cells/mm3 (Sp: 88.1%, Se: 45%, AUC=0.69, 95% CI: 0.51, 0.70; p<10-3).

Lymphocytes

Our study didn’t reveal a significant difference between infectious and non-infectious diseases in lymphopenia (p-value=0.247).

Neutrophil-to-lymphocyte ratio

The high NLR group had 92 patients (56.9%), distributed as follows: 38 patients (41.3%) with infectious diseases, 26 patients (33.8%) with inflammatory diseases and 12 patients (13%) with neoplastic diseases with a statistically significant difference (p-value=0.001) (Table 2). The mean of NLR levels of infectious diseases (9.7) was significantly higher than those of non-infectious diseases (3.9) (p=0.002) (Table 3).

In Group 1, the mean of NLR in older adult patients was higher than in patients under 65 years old (14.9 vs. 5.6, p=0.015). The optimal cut-off value for discriminating between infectious and non-infectious diseases was 6.1 (Sp: 87.1%, Se: 61%, AUC=0.81, 95% CI: 0.731, 0.902; p<10-3) (Figure 1).

006793ac-0116-4ea3-b374-5b5d516c6414_figure1.gif

Figure 1. Comparison of ROC curves of CRP, NLR, fibrinogen, and the combination of NLR and CRP to distinguish infectious diseases in our population.

ROC, receiver operating characteristic; CRP, C-reactive-protein; NLR, neutrophil-lymphocyte ratio.

C reactive protein

Of the 92 patients (56.9%) with high CRP rate, 47 patients (50%) had infectious diseases, 25 patients (26.6%) had inflammatory diseases (26.6%) and 12 patients (12.8%) had neoplastic diseases, with a statistically significant difference (p<10-3) (Table 2). There was a statistically significant association between elevated CRP and infectious diseases (p-value <10-3) (Table 3).

The average level of CRP in infectious diseases was significantly higher than in non-infectious diseases (152.5 mg/L vs. 34.9 mg/L, p<10-3) (Table 3). In Group 1, the mean level of CRP in older adult patients was higher than in patients under 65 years old (200 mg/L vs. 115 mg/L, p=0.026). The optimal cut-off value for discrimination between infectious and non-infectious diseases was 123 mg/L (Sp: 89.7%, Se: 64.3%, AUC=0.9, 95% CI: 0.83, 0.96; p<10-3) (Figure 1).

Procalcitonin

There were 59 patients (39.3%) with high PCT levels, of whom 29 (49.2%) had infectious disease, 16 (27.1%) had inflammatory diseases and 10 (16.9%) had neoplastic diseases, with a statistically significant difference (p<10-3) (Table 2). Mean PCT was found to be higher in the group of patients with infectious diseases than the non-infectious diseases with a statistically significant difference (p-value=0.036) (Table 3).

In Group 1, the mean level of PCT in older adult patients was higher than in patients under 65 years old (6.2 ng/mL vs. 0.68 ng/mL, p=0.026). The optimal cut-off value for discriminating between infectious and non-infectious diseases was 0.24 ng/mL (Sp: 86.1%, Se: 62.3%, AUC=0.87, 95% CI: 0.80, 0.93; p-value<10-3) (Figure 1).

Fibrinogen

There were 44 patients (40.7%) with high fibrinogen levels, of whom 21 (47.7%) had infectious diseases, 12 (27.3%) had inflammatory diseases (26.6%) and six (13.6%) had neoplastic diseases, with a statistically significant difference (p <10-3) (Table 2). The mean level of fibrinogen was found to be higher in patients with infectious diseases than the non-infectious diseases (5.37g/L vs 3.73g/L, p<10-3) (Table 3) but it wasn’t higher in older adult patients (p=0.36). The optimal cut-off value for discrimination between infectious and non-infectious disease was 4.9 g/L (Sp: 84.7%, Se: 68.3%, AUC=0.77, 95% CI: 0.65, 0.98; p<10-3) (Figure 1).

Ferritinemia

A total of 44 patients (31.2%) had hyper ferritinemia of whom 21 (47.7%) had infectious diseases, 12 (27.3%) had inflammatory diseases and seven (15.9%) had neoplastic diseases, with a statistically significant difference (p-value=0.001) between these groups (Table 2). There was no statistically significant difference between mean serum ferritin levels between infectious and non-infectious disease groups (p=0.162).

Lactatemia

High blood lactate group had 32 patients (20.9%), distributed as follows: 10 patients (31.3%) with infectious diseases, nine patients (28.1%) with inflammatory diseases and five patients (15.6%) with neoplastic diseases, with no statistically significant difference (p=0.417) (Table 2). Our study didn’t reveal a significant difference among infectious and non-infectious diseases in elevated lactatemia (p-value=0.947).

Combination of inflammatory biomarkers

For diagnosing infectious diseases, the CRP showed higher AUC (Sp: 89.7%, Se: 64.3%, AUC=0.9, 95% CI: 0.83, 0.96; p<10-3) than PCT (Sp: 86.1%, Se: 62.3%, AUC=0,87, 95% CI: 0.80, 0.93; p-value<10-3), NLR (Sp: 87.1%, Se: 61%, AUC=0.81, 95% CI: 0.731, 0.902; p <10-3) and Fibrinogen (Sp: 84.7%, Se:68.3%, AUC=0.77, 95% CI: 0.65, 0.98; p<10-3). The combination of CRP and NLR levels improved the diagnostic accuracy (AUC=0.93, 95% CI 0.84, 0.96; p<10-3) for distinguishing between infectious and non-infectious diseases (Figures 1 and 2).

006793ac-0116-4ea3-b374-5b5d516c6414_figure2.gif

Figure 2. Comparison of the AUC for the inflammatory biomarkers in the present study.

AUC, area under the curve; CRP, C-reactive-protein; NLR, neutrophil-lymphocyte ratio; PCT, procalcitonin.

Discussion

The present study describes the interest of inflammatory biomarkers in promoting the diagnostic approach by defining their threshold to promote their specificity and sensibility for infectious diseases in an internal medicine department. We identified 53 patients (32.3%) with infectious diseases of whom 45 patients (84.9%) presented bacterial infections, 62 patients (37.8%) with inflammatory diseases, 14 patients (8.5%) with neoplasms and 35 patients (21.3%) with other diagnosis. The high mean levels of leukocytes (12,047 cells/mm3), neutrophils (9,015 cells/mm3), NLR (9.7), CRP (152.5 mg/L), PCT (3.28 ng/ml), and fibrinogen (5.37 g/L) were associated with infectious etiologies with statistically significant differences and they all were higher in older adult patients. Lymphopenia, elevated ferritinemia, and lactate were not associated with infectious diseases. Thus, we identified cut-offs of NLR (6.1), CRP (123 mg/L), PCT (0.24 ng/mL) and fibrinogen (4.9 g/L) to discriminate infectious etiologies in our population. For diagnosing infectious diseases, the CRP showed higher AUC (Sp: 89.7%, Se: 64.3%, AUC=0.9, 95% CI: 0.83, 0.96; p<10-3) than PCT (Sp: 86.1%, Se: 62.3%, AUC=0,87, 95% CI: 0.80, 0.93; p<10-3), NLR (Sp: 87.1%, Se: 61%, AUC=0.81, 95% CI: 0.731, 0.902; p <10-3) and fibrinogen (Sp: 84.7%, Se:68.3%, AUC=0.77, 95% CI: 0.65, 0.98; p<10-3). The combination of CRP and NLR levels improved the diagnostic accuracy (AUC 0.93, 95% CI: 0.84, 0.96; p<10-3).

Various studies have compared the role of inflammatory biomarkers to discriminate infectious diseases, bacterial infection from nonbacterial infection, and sepsis from non-septic conditions.2,3,16 It has been reported in previous studies that high mean levels of leukocytes, neutrophils, NLR, CRP, PCT and fibrinogen were associated with infectious etiologies.5,6,10,13

Causes of neutrophilia are classified into primary causes, which are myeloproliferative neoplasms and secondary neutrophilia to inflammatory and infectious diseases, non-hematological neoplasms and medications.13 Recently, NLR was introduced, which is a novel perspective biomarker of cellular immune activation as well as stress and systemic inflammation, coupling between innate and adaptive immunity and its clinical consequences.10 Its interest as a predictor of bacteremia has been reported as well as a predictor of the clinical outcome. As a consequence, NLR would have an influence on the extent of treatment and post-treatment morbidity.10

There are multiple causes of an elevated CRP. They include acute and chronic conditions, which can be infectious or non-infectious etiologies including inflammatory diseases, tissues and organs injury and neoplasia.6 Markedly elevated levels of CRP are mostly associated with infections.

PCT is a biomarker for the early detection of systemic bacterial infections.5 Its high serum level is associated with positive results for bacterial infection and sepsis. In addition, it was reported that PCT do not increase during viral infections.5 PCT concentrations <0.1 ng/mL were reported to have a high negative predictive value (96.3%) for bacterial infections.17 A level >0.25 ng/ml of PCT is a high predictor of bacterial infectious diseases.5

The interest in high levels of fibrinogen in infectious diseases has been discussed in only a few studies, but it can also be found in multiple other etiologies such as inflammatory diseases, neoplasms, and vascular diseases.8

Lymphopenia can be caused by insufficient thymic output due to corticosteroid therapy, zinc deficiency and primary immune deficiencies, increased lymphocyte catabolism secondary to infections, connective tissue diseases and immunosuppressive treatments, modified lymphocyte distribution due to infectious diseases, visceromegaly, granulomatosis, and other causes (end-stage renal disease, neoplasia).14

Hyperferritinemia is associated with infectious and inflammatory diseases, cellular damages, diabetes mellitus and excessive alcohol consumption.9

High serum levels of lactate are known to be associated with septic shock, bacterial sepsis, cardiac arrest, seizures, ischemia, diabetic ketoacidosis, trauma, thiamine deficiency, malignancy, liver failure, toxins, and some medications.7 They help to discriminate sepsis of non-septic conditions.7 In our cohort, a minority of infectious diseases were complicated by sepsis, which can explain the fact that elevated lactate didn’t discriminate infections.

Previous studies showed that mean levels of CRP and PCT were higher in older adult patients, and the suggested hypothesis was that their clearance varies because of the decrease in the glomerular filtration rate caused by aging.18–20

The optimal cut-offs of CRP to discriminate infectious diseases are in the range of 50–100 mg/L12 with variable Se and Sp, while for PCT, this cut-off varies according to the type of causative agent: (0.47 ng/mL to 1.11 ng/mL) for bacterial infections and (0.0027 ng/mL to 1.0 ng/mL) for viral infections. Furthermore, according to some authors, it varies according to the localization of the infection.1

At a threshold of approximately 10 for NLR, a sensitivity of 72% and a specificity of 60% were reported for the diagnosis of bacteremia.21 This is higher than the cut-off value obtained in our study but can be explained by the fact that our infection group comprised only 84.9% bacterial infections.

Previous studies showed the superiority of PCT in the diagnosis of systemic infections, nonetheless, some studies showed that CRP is more useful than PCT18,20,22 as shown in our study.

In the cohort of Wallihan et al., the AUC of PCT predicting sepsis positive blood culture and negative blood culture were 0.96 and 0.89, respectively,23 which supports the fact that PCT can early predict infections. Furthermore, in early detection of bacterial infection in febrile patients, CRP AUC was inferior to PCT AUC (0.639 vs. 0.742), a cutoff value of 73.8 mg/L (Se: 62%, Sp: 72%) in 326 patients admitted to the Department of Infectious Diseases in West China Hospital.24

Multiple studies evaluated combined biomarkers to improve the diagnostic accuracy for bacterial infections and septic conditions.2,11,25

In our study we chose to combine CRP and NLR levels, which improved the diagnostic accuracy (AUC 0.93, 95% CI 0.84–0.96; p<10-3) for distinguishing between infectious and non-infectious disease. This combination in the diagnostic approach was not done in previous studies. However CRP and NLR were combined for predicting the prognosis in patients with neoplasia.26 The choice of these two markers used in daily clinical routine was based on the availability, low cost, and ease of interpretation of these biomarkers, which gave them an advantage in the economic and social context of our country.

This association would find its interest particularly in distinguishing infections in the event of outbreaks of inflammatory diseases with general manifestations such as fever and to rule them out in order to start immunosuppressive treatment when indicated in internal medicine departments.

Conclusions

Our study shows the usefulness of inflammatory biomarkers to distinguish infections among inflammatory diseases, neoplasia and other diagnoses in an internal medicine department.

The combined use of NLR and CRP in the diagnostic approach holds promise due to their cost-effectiveness and availability as biomarkers. This combination presents an intriguing potential to differentiate infections from other inflammatory conditions, potentially yielding a higher AUC (Area Under the Curve) in diagnostic accuracy. Nevertheless, further extensive studies are needed to validate these results.

Data availability

Underlying data

Dryad: Data from: The interest of inflammatory biomarkers in the diagnostic approach, https://doi.org/10.5061/dryad.n02v6wx3d. 27

Data are available under the terms of the Creative Commons Zero “No rights reserved” data waiver (CC0 1.0 Public domain dedication).

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Anoun J, Romdhane W, Ben Hassine I et al. The interest of inflammatory biomarkers in the diagnostic approach in an internal medicine department: A cross-sectional study [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:35 (https://doi.org/10.12688/f1000research.141582.1)
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ApprovedThe paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approvedFundamental flaws in the paper seriously undermine the findings and conclusions
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Reviewer Report 30 Aug 2024
Bouomrani Salem, University of Sfax, Bd Majida Boulila, Sfax, Tunisia 
Approved
VIEWS 18
https://doi.org/10.5256/f1000research.155042.r238520
The authors propose an interesting paper about  the interest of different inflammatory biomarkers in the diagnostic approach in  internal medicine, particularly to differentiate infectious and non-infectious diseases.
The objective of this study is clearly stated, the methodology is well ... Continue reading
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Salem B. Reviewer Report For: The interest of inflammatory biomarkers in the diagnostic approach in an internal medicine department: A cross-sectional study [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:35 (https://doi.org/10.5256/f1000research.155042.r238520)
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https://f1000research.com/articles/13-35/v1#referee-response-238520
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Reviewer Report 26 Apr 2024
Nigel P Murray, University Finis Terrae, Santiago, Chile 
Not Approved
VIEWS 5
https://doi.org/10.5256/f1000research.155042.r259581
The authors present an interesting article to describe the role of multiple inflammatory biomarkers to differentiate infectious disease from non-infectious diseases. They had used six different inflammatory biomarkers to support their findings, however the article has serious flaws in its ... Continue reading
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Murray NP. Reviewer Report For: The interest of inflammatory biomarkers in the diagnostic approach in an internal medicine department: A cross-sectional study [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:35 (https://doi.org/10.5256/f1000research.155042.r259581)
The direct URL for this report is:
https://f1000research.com/articles/13-35/v1#referee-response-259581
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Reviewer Report 07 Feb 2024
Aparajita Sen, Genetics, University of Delhi, South Campus, New Delhi, Delhi, India 
Prerna Aggarwal, Genetics, University of Delhi, South Campus, New Delhi, Delhi, India 
Approved with Reservations
VIEWS 25
https://doi.org/10.5256/f1000research.155042.r238521
Anoun et al. have described the role of multiple inflammatory biomarkers to differentiate infectious diseases from non-infectious ones. Although they have analyzed six different biomarkers to strengthen their findings, there are several lacunae that can be addressed to improve the ... Continue reading
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CITE
HOW TO CITE THIS REPORT
Sen A and Aggarwal P. Reviewer Report For: The interest of inflammatory biomarkers in the diagnostic approach in an internal medicine department: A cross-sectional study [version 1; peer review: 1 approved, 1 approved with reservations, 1 not approved]. F1000Research 2024, 13:35 (https://doi.org/10.5256/f1000research.155042.r238521)
The direct URL for this report is:
https://f1000research.com/articles/13-35/v1#referee-response-238521
NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article.
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Alongside their report, reviewers assign a status to the article:

Approved
The paper is scientifically sound in its current form and only minor, if any, improvements are suggested
Approved with reservations
A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
Not approved
Fundamental flaws in the paper seriously undermine the findings and conclusions

Reviewer Reports

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  1. Aparajita Sen, University of Delhi, South Campus, New Delhi, India
    Prerna Aggarwal, University of Delhi, South Campus, New Delhi, India
  2. Nigel P Murray, University Finis Terrae, Santiago, Chile
  3. Bouomrani Salem, University of Sfax, Bd Majida Boulila, Sfax, Tunisia

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    Alongside their report, reviewers assign a status to the article:
    Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested
    Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit.
    Not approved - fundamental flaws in the paper seriously undermine the findings and conclusions
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