Diagnostic Value Of Neutrophil-To-Lymphocyte And Platelet-To-Lymphocyte Ratios İn Early- And Late-Onset Neonatal Sepsis: A Retrospective Single-Centre Observational Study

Diagnostic Value Of Neutrophil-To-Lymphocyte And Platelet-To-Lymphocyte Ratios İn Early- And Late-Onset Neonatal Sepsis: A Retrospective Single-Centre Observational Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Diagnostic Value Of Neutrophil-To-Lymphocyte And Platelet-To-Lymphocyte Ratios İn Early- And Late-Onset Neonatal Sepsis: A Retrospective Single-Centre Observational Study Taner Adıgüzel¹, Bahriye Semizoğlu Atasoy¹, Tuba İşcan¹, Gülsüm Kaya² This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8339561/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2026 Read the published version in BMC Pediatrics → Version 1 posted 15 You are reading this latest preprint version Abstract Background Neonatal sepsis remains a leading cause of morbidity and mortality worldwide despite advances in perinatal and intensive care. Early and accurate diagnosis is challenging because clinical signs are often nonspecific and no single biomarker has shown perfect sensitivity and specificity. In recent years, complete blood count–derived indices such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been proposed as inexpensive, readily available markers of systemic inflammation. This study aimed to evaluate the diagnostic value of NLR and PLR in early-onset (EOS) and late-onset sepsis (LOS) compared with jaundiced and healthy neonates, and to compare their performance with that of procalcitonin (PCT) and C-reactive protein (CRP). Methods In this retrospective single-centre study, we reviewed the records of neonates hospitalised in a level III neonatal intensive care unit between March 2022 and March 2025. A total of 446 infants were classified into four groups: EOS (first 3 postnatal days), LOS (≥ 4th day), jaundice without sepsis, and healthy controls. Pre-treatment laboratory data, including complete blood count, CRP and PCT, were extracted. NLR and PLR were calculated by dividing absolute neutrophil and platelet counts by lymphocyte counts, respectively. Group comparisons were performed using non-parametric tests. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of each biomarker for differentiating sepsis-positive (EOS + LOS) from sepsis-negative (jaundice + healthy) infants. Results Of the 446 neonates, 143 (32.1%) had EOS, 101 (22.6%) had LOS, 102 (22.9%) were in the jaundice group and 100 (22.4%) were healthy controls. Median NLR values were significantly higher in the EOS group than in the LOS, jaundice and healthy groups (1.97 vs 0.71, 0.84 and 0.67, respectively; p 0.05). When EOS and LOS were combined as the sepsis-positive group, median NLR was higher in sepsis-positive than in sepsis-negative infants (1.34 vs 0.79; p < 0.001). In ROC analysis, PCT showed the highest diagnostic accuracy for sepsis (area under the curve [AUC] 0.97), followed by CRP (AUC 0.75) and NLR (AUC 0.65), whereas PLR had limited discriminative ability (AUC 0.54). Conclusions NLR is moderately useful for predicting neonatal sepsis, particularly in EOS, and may serve as a supportive parameter when interpreted alongside PCT, CRP and clinical findings. In this cohort, PLR did not provide meaningful additional diagnostic value. The combined use of CBC-derived ratios and conventional biomarkers may support early decision-making and help reduce unnecessary antibiotic exposure in neonates. neonatal sepsis early-onset sepsis late-onset sepsis neutrophil-to-lymphocyte ratio platelet-to-lymphocyte ratio procalcitonin C-reactive protein Figures Figure 1 Background Neonatal sepsis is a systemic infectious syndrome occurring in the first 28 days of life and remains one of the leading causes of neonatal morbidity and mortality worldwide [ 10 , 16 ]. Clinically, neonatal sepsis is usually categorised into early-onset sepsis (EOS), in which symptoms develop within the first 72 hours of life, and late-onset sepsis (LOS), occurring thereafter [ 14 , 16 ]. EOS is most often related to vertical transmission of microorganisms from the mother during pregnancy or the perinatal period, whereas LOS is more frequently associated with environmental and nosocomial pathogens acquired after birth [ 12 , 15 ]. In high-income countries, reported incidence rates of culture-proven neonatal sepsis range from 1 to 8 per 1000 live births, whereas in low- and middle-income settings the incidence and case-fatality rates are considerably higher [ 10 , 21 ]. Early recognition and timely initiation of appropriate antimicrobial therapy are crucial to reduce adverse outcomes such as neurodevelopmental impairment, multi-organ failure and death [ 11 , 16 ]. However, the clinical signs of neonatal sepsis—poor feeding, apnoea, respiratory distress, lethargy, temperature instability and others—are often subtle and nonspecific, and overlap with many non-infectious conditions [ 12 , 15 ]. Blood culture remains the diagnostic gold standard but has several limitations in neonates: the time required to obtain results, the low level of bacteraemia, the small blood volumes that can be safely drawn and prior antibiotic exposure all reduce its sensitivity [ 5 , 16 ]. Consequently, clinicians frequently initiate broad-spectrum antibiotics when sepsis is suspected but cannot be confidently excluded, leading to overtreatment, longer hospital stays, increased costs and the development of antimicrobial resistance [ 5 , 19 ]. Among laboratory tests, C-reactive protein (CRP) and procalcitonin (PCT) are the most widely used biomarkers for the diagnosis and follow-up of neonatal sepsis. However, both markers have variable sensitivity and specificity across studies; their performance is influenced by postnatal age, perinatal factors and the presence of non-infectious inflammatory conditions [ 4 , 8 , 17 ]. In a secondary analysis of the NeoPInS trial, the combination of CRP, PCT and white blood cell (WBC) count improved the ability to rule out EOS, but no single biomarker could safely exclude sepsis on its own [ 19 ]. Systematic reviews similarly conclude that CRP and PCT are useful but should always be interpreted alongside clinical findings and other laboratory data [ 4 , 17 ]. Therefore, there is increasing interest in additional, inexpensive biomarkers that can support early risk stratification. Complete blood count (CBC) is routinely obtained in almost all infants admitted to neonatal intensive care units, making derived indices attractive candidates. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been proposed as simple markers that integrate innate and adaptive immune responses and the haemostatic response to systemic inflammation [ 1 , 22 ]. Several studies in neonatal sepsis suggest that these ratios may help distinguish infected from non-infected infants [ 13 , 20 ]. Arcagok and Karabulut [ 1 ] reported significantly increased PLR values in EOS cases compared with healthy controls and proposed PLR as a predictor of EOS. In systematic reviews of hematologic indices, NLR has shown area under the ROC curve (AUC) values exceeding 0.80 in some cohorts, although authors emphasise that NLR should be interpreted as an adjunct rather than a stand-alone diagnostic test [ 3 , 20 ]. More recent work has extended the evaluation of CBC-derived ratios to LOS and preterm infants, but results have been heterogeneous across centres [ 6 , 18 ]. Despite this growing literature, there are still relatively few studies that assess NLR and PLR simultaneously in the same cohort, across both EOS and LOS, while also including jaundiced and healthy controls and comparing these ratios directly with conventional biomarkers such as CRP and PCT. Understanding the relative and complementary contribution of CBC-derived ratios and established biomarkers could help refine diagnostic algorithms and reduce unnecessary antibiotic exposure. In this context, the present study aimed to (i) compare NLR and PLR values among neonates with EOS, LOS, jaundice and healthy controls; and (ii) evaluate the diagnostic performance of NLR and PLR for predicting sepsis when used alongside CRP and PCT in a single-centre cohort. Methods Study design and setting This retrospective, single-centre, observational study was conducted in the level III neonatal intensive care unit (NICU) of Yalova University Training and Research Hospital, Yalova, Türkiye. Clinical and laboratory data were obtained from the hospital’s electronic medical records system. Study population and groups We reviewed the records of all neonates hospitalised in the NICU between March 2022 and March 2025. A total of 446 infants who met the predefined eligibility criteria were included and classified into four groups: Early-onset sepsis (EOS) group : infants with clinical and/or laboratory evidence of sepsis within the first 3 postnatal days. Late-onset sepsis (LOS) group : infants with sepsis diagnosed on or after the 4th postnatal day. Jaundice group : infants with “jaundice” documented as the primary diagnosis, hospitalised for neonatal jaundice without clinical or laboratory signs of sepsis. Healthy control group : infants with “healthy” recorded in the file, hospitalised for routine observation or non-infectious reasons, without sepsis or jaundice. The distinction between EOS and LOS was based on the timing of symptom onset, in accordance with commonly used clinical definitions [ 15 , 16 ]. Inclusion and exclusion criteria were specified a priori in the ethics committee application and applied during chart review. Infants with major congenital anomalies, inherited immune or haematologic disorders or missing key laboratory data were excluded. Data collection and variables For each infant, demographic, clinical and laboratory data were extracted using a standardised data collection form. The following variables were recorded: Demographic and perinatal variables : sex, mode of delivery (vaginal vs caesarean), birth weight and postnatal age at the time of sampling. Laboratory parameters : C-reactive protein (CRP), procalcitonin (PCT), white blood cell (WBC) count, platelet count, absolute neutrophil count and absolute lymphocyte count. Only pre-treatment laboratory values obtained before the initiation of antibiotic therapy were included in the analysis. NLR was calculated as the ratio of absolute neutrophil count to absolute lymphocyte count, and PLR as the ratio of platelet count to absolute lymphocyte count. NLR and PLR were evaluated as secondary biomarkers, as pre-specified in the ethics protocol. The diagnosis of sepsis was made by neonatologists and paediatricians based on clinical signs, laboratory results and, when available, blood culture findings, in accordance with national and international guidelines [ 12 , 15 ]. Ethical approval The study was approved by the Ethics Committee of Yalova University on 7 May 2025 (decision number 2025/174). Owing to the retrospective design, individual informed consent was waived. All data were anonymised before analysis and used solely for research purposes. Statistical analysis Statistical analyses were performed using SPSS for Windows, version 22.0 (IBM Corp., Armonk, NY, USA). The distribution of continuous variables was assessed visually (histograms, Q–Q plots) and analytically. Continuous variables were summarised as mean ± standard deviation (SD) or median and interquartile range (IQR), as appropriate, whereas categorical variables were presented as counts and percentages. Group comparisons for continuous variables were performed using non-parametric tests. Differences among the four study groups (EOS, LOS, jaundice, healthy controls) were examined using the Kruskal–Wallis test. Where appropriate, pairwise comparisons were conducted using the Mann–Whitney U test, with Bonferroni correction applied to control for type I error. For categorical variables, group differences were analysed using the chi-square test. To evaluate the diagnostic performance of biomarkers, EOS and LOS groups were combined as the sepsis-positive group, and the jaundice and healthy control groups were combined as the sepsis-negative group. Receiver operating characteristic (ROC) curves were generated for CRP, PCT, WBC, absolute neutrophil count, NLR and PLR. For each marker, the area under the ROC curve (AUC), optimal cut-off value, sensitivity and specificity were calculated [1,3]. A two-sided p value <0.05 was considered statistically significant. Use of artificial intelligence tools A large language model–based assistant (ChatGPT, OpenAI) was used to improve the clarity and fluency of the English language of the manuscript. All content was reviewed, edited and approved by the authors, who take full responsibility for the final version of the text. Results Baseline characteristics A total of 446 neonates were included: 143 (32.1%) in the EOS group, 101 (22.6%) in the LOS group, 102 (22.9%) in the jaundice group and 100 (22.4%) in the healthy control group. Sex distribution and mode of delivery (vaginal vs caesarean section) were similar across groups (p>0.05). The proportions of female and male infants and of vaginal and caesarean deliveries did not differ significantly between groups. Median postnatal age at sampling was 1 day in the EOS group, 13 days in the LOS group, 4 days in the jaundice group and 6 days in the healthy control group. Birth weight distributions were clinically comparable across groups, and no statistically significant differences in mean birth weight were observed. Detailed demographic and perinatal characteristics are presented in Table 1. Laboratory parameters across groups When laboratory parameters were compared across the four groups, CRP and PCT levels were significantly higher in both EOS and LOS groups than in the jaundice and healthy control groups (p<0.001; Table 2). In the sepsis groups, particularly in EOS, WBC and absolute neutrophil counts tended to be higher, whereas lymphocyte counts were relatively lower. NLR differed significantly among the groups. Median NLR was 1.97 in the EOS group, 0.71 in the LOS group, 0.84 in the jaundice group and 0.67 in the healthy control group (p<0.001). This pattern indicates a more pronounced neutrophil-predominant inflammatory response in early-onset sepsis compared with LOS and non-septic conditions. In contrast, PLR did not differ significantly among the four groups. Median PLR values ranged between approximately 63 and 74 across EOS, LOS, jaundice and healthy infants, with no statistically significant difference (p>0.05). Platelet counts were highest in the LOS group but were within clinically comparable ranges in the other groups. Detailed distributions of CRP, PCT, WBC, neutrophils, lymphocytes, platelets, NLR and PLR by group are shown in Table 2. Sepsis-positive versus sepsis-negative infants For ROC analysis, EOS and LOS infants were combined into a sepsis-positive group (n=244), and jaundice and healthy control infants into a sepsis-negative group (n=202). In this classification, median NLR was significantly higher in the sepsis-positive than in the sepsis-negative group (1.34 vs 0.79; p<0.001). CRP, PCT, WBC and absolute neutrophil counts were also significantly elevated in sepsis-positive infants, whereas lymphocyte counts were relatively lower. PLR showed no significant difference between sepsis-positive and sepsis-negative groups. Diagnostic performance of biomarkers (ROC analysis) ROC curve analysis was used to assess the ability of each biomarker to discriminate sepsis-positive from sepsis-negative infants (Table 3; Figure 1). Procalcitonin had the highest diagnostic accuracy, with an AUC of 0.971 (95% CI 0.958–0.983). At a cut-off value of 0.109 ng/mL, PCT achieved a sensitivity of approximately 90.9% and a specificity of 90.1%. CRP showed an AUC of 0.746 (95% CI 0.700–0.792), indicating moderate discriminative ability. NLR and WBC both had AUC values around 0.65 (0.649 and 0.653, respectively), indicating moderate diagnostic performance. Absolute neutrophil count had an AUC of 0.68, also in the moderate range. PLR had the lowest discriminative value with an AUC of 0.542 (95% CI 0.489–0.596), providing only marginal separation between sepsis-positive and sepsis-negative groups. Discussion In this single-centre retrospective study, we evaluated the diagnostic value of NLR and PLR for early identification of neonatal sepsis in a cohort that included EOS, LOS, jaundice and healthy control infants, and compared these indices with conventional biomarkers PCT and CRP. Overall, our main findings were that (i) NLR was significantly increased in sepsis, particularly in EOS, and showed moderate diagnostic accuracy (AUC 0.65); (ii) PLR had limited diagnostic value in this population (AUC 0.54); (iii) PCT provided excellent discriminative performance (AUC 0.97); and (iv) CRP demonstrated moderate accuracy with relatively high specificity (AUC 0.75). These results support the use of NLR as a low-cost adjunctive marker—especially in EOS—while underlining the dominant role of PCT and the complementary, but not stand-alone, role of CRP. CRP and PCT: conventional biomarkers in context In our cohort, CRP levels were significantly higher in sepsis-positive infants than in jaundiced and healthy controls, and the AUC for CRP was 0.75. This is consistent with previous reports describing CRP as a marker with relatively high specificity but limited sensitivity in the early phase of infection [2,4]. The kinetics of CRP provide a physiological explanation: as an acute-phase protein synthesised mainly by hepatocytes in response to interleukin-6 and other proinflammatory cytokines, CRP typically requires 10–12 hours after the onset of infection to show a significant rise, with peak levels occurring at 24–48 hours [4,17]. Consequently, CRP values may remain normal or only mildly elevated during the very early hours of sepsis, limiting sensitivity at presentation. Moreover, non-infectious conditions such as birth stress, perinatal asphyxia, meconium aspiration and surgical procedures can lead to elevated CRP, reducing specificity in the neonatal period [2,12]. Our findings align with literature suggesting that CRP is more useful for monitoring the evolution of infection and response to therapy through serial measurements, rather than as a single, definitive diagnostic test. PCT, in contrast, showed the highest AUC in our study (0.97), with both high sensitivity and specificity at a relatively low cut-off. PCT is the prohormone of calcitonin and is produced at low levels by thyroid C cells under physiological conditions. During systemic bacterial infection, however, PCT synthesis is upregulated in multiple extra-thyroid tissues, including the lungs, liver, intestine and cells of the monocyte–macrophage system [5,9]. Serum PCT levels begin to rise within 3–4 hours of symptom onset, peak at around 24 hours and then gradually fall as infection is controlled [8,11]. These kinetics make PCT particularly advantageous in the early phase of sepsis, when CRP may still be normal. Several studies and reviews have highlighted the value of PCT in neonatal sepsis, both for early diagnosis and for guiding antibiotic initiation and discontinuation [5,8,17]. Our results are consistent with these data and support the concept of PCT as a first-line biomarker for ruling in or ruling out sepsis, especially in EOS. NLR: a supportive marker, particularly in EOS In the present study, NLR was significantly higher in sepsis-positive infants than in sepsis-negative infants, and especially elevated in the EOS group compared with LOS, jaundice and healthy controls. The AUC of 0.65 indicates modest but clinically relevant discriminative ability. This pattern is in line with the expected physiological response, in which systemic infection triggers neutrophilia and relative lymphopenia, thereby increasing NLR as a combined indicator of innate and adaptive immune activation. Our findings are consistent with prior work demonstrating higher NLR values in neonates with sepsis compared with healthy controls [13,20]. In their systematic review and meta-analysis, Xin et al. [20] reported that NLR had overall “good-to-moderate” diagnostic performance in neonatal sepsis, although AUC values varied widely between studies. The AUC observed in our cohort lies in the mid-range of this reported spectrum, supporting the concept that NLR can serve as a useful adjunctive marker rather than a stand-alone test. A notable aspect of our study is the separate analysis of EOS and LOS. We observed that NLR was markedly higher in EOS than in LOS, with values in the LOS group approaching those seen in jaundiced and healthy infants. This suggests that in the very early days of life, the neutrophil-dominant inflammatory response to infection may be more pronounced, whereas in LOS, the haematological response may be modulated by multiple factors such as nosocomial pathogens, comorbidities and prior interventions. Rana et al. [13] similarly reported that haematologic ratios, particularly NLR, can be sensitive indicators of EOS. Our findings support the use of NLR as an additional “warning sign” pointing towards EOS when interpreted alongside clinical findings, CRP and PCT. Conversely, the convergence of NLR values between LOS and non-septic groups in our cohort suggests that NLR is less reliable as a single discriminator in LOS, possibly because of overlapping inflammatory and haematological influences in older, hospitalised neonates [6,18]. Taken together, these observations indicate that NLR may be most informative in the context of suspected EOS, while in LOS it should be considered only as part of an integrated assessment. PLR: limited diagnostic value in this cohort In contrast to NLR, PLR did not differ significantly among EOS, LOS, jaundice and healthy infants in our study, and its AUC for predicting sepsis was only 0.54, indicating poor discriminative performance. These findings do not reproduce the results of Arcagok and Karabulut [1], who reported significantly higher PLR values in EOS compared with healthy controls and proposed PLR as a useful predictor of EOS. Discrepancies between studies may reflect differences in study design, population characteristics (including gestational age and prematurity rates), the inclusion of both EOS and LOS, and the presence of comorbid conditions. It is also important to consider the dynamic nature of platelet kinetics. Thrombocytopenia or thrombocytosis often develop over time rather than at a single time point, and PLR values based on a single pre-treatment measurement may not capture these changes fully. Moreover, platelet counts can be influenced by a variety of non-infectious factors, such as perinatal asphyxia, intrauterine growth restriction, maternal hypertension, bleeding episodes and transfusions [7,22]. Residual confounding by these factors may have attenuated any sepsis-related signal in PLR in our cohort. Although some EOS cohorts and meta-analyses have reported promising results for PLR [1,13], our findings suggest that PLR does not have consistent diagnostic utility across different centres and patient populations. Future research using prospective designs, serial measurements and more homogeneous subgroups (e.g. stratified by gestational age or comorbidities) will be needed to clarify the true value of PLR in neonatal sepsis. Clinical implications From a clinical standpoint, one of the key challenges in neonatal sepsis management is balancing the risk of undertreatment against the harms of overtreatment. Broad-spectrum antibiotics are often started before sepsis can be confidently excluded, and many culture-negative infants receive prolonged courses [5,11]. Our data reinforce the central role of PCT as the most accurate biomarker in this setting, with CRP contributing valuable information when interpreted in serial measurements. Within this framework, NLR may provide additional, low-cost support, particularly for suspected EOS. Because NLR is derived from a routine CBC with no extra cost or blood volume, it can be easily incorporated into existing diagnostic pathways. For clinically stable neonates with low NLR and low PCT/CRP values, clinicians may feel more confident in limiting or withholding empiric antibiotics, whereas a high NLR in the context of suspected EOS and elevated PCT may strengthen the case for early and aggressive treatment. However, NLR and other haematologic indices should always be interpreted alongside the full clinical picture and microbiological results, and not used as sole decision-making tools. In contrast, the lack of significant diagnostic contribution from PLR in our cohort suggests that PLR should not be used routinely to guide antibiotic decisions in neonatal sepsis until more robust and consistent evidence becomes available. Strengths and limitations This study has several strengths. First, it evaluates NLR and PLR simultaneously in a relatively large single-centre cohort including both EOS and LOS, as well as jaundiced and healthy control infants. Second, it directly compares these haematologic ratios with widely used biomarkers (PCT and CRP) within the same population. Third, the sample size is larger than in many prior single-centre studies, which may enhance the reliability of the estimates [1,13]. Several limitations should also be acknowledged. The retrospective design may have led to incomplete or heterogeneous documentation of clinical findings and microbiological data. NLR and PLR were assessed at a single pre-treatment time point, and serial measurements were not available; this is particularly relevant for PLR, which may show more informative trends over time. The study was also conducted in a single centre, and our findings may not be generalisable to settings with different pathogen spectra, prematurity rates or treatment protocols [3,22]. Finally, we did not perform multivariable modelling to adjust for potential confounders such as gestational age or specific comorbidities, which could further refine the interpretation of NLR and PLR. Conclusions In summary, this single-centre retrospective study shows that PCT, CRP, NLR and PLR fulfil complementary but unequal roles in the diagnostic assessment of neonatal sepsis. PCT emerged as the most accurate biomarker for both EOS and LOS and appears suitable as a primary marker for early diagnosis and for ruling out sepsis. CRP provided moderate diagnostic accuracy and remains useful for monitoring infection burden and treatment response through serial measurements. NLR, easily calculated from a routine CBC, was particularly elevated in EOS and offered moderate additional discriminative value, suggesting that it may serve as a supportive marker that reinforces clinical suspicion and helps guide decision-making in early-onset disease. In contrast, PLR showed limited diagnostic performance in this cohort and does not currently appear to be a reliable stand-alone indicator for sepsis. Neonatal sepsis should continue to be evaluated primarily on the basis of clinical findings and microbiological results. PCT, CRP and NLR may help reduce unnecessary initiation or prolonged use of antibiotics when interpreted together and within a structured clinical pathway. These findings warrant confirmation in larger, multicentre prospective studies using standardised definitions and serial biomarker measurements. Abbreviations AUC area under the curve CBC complete blood count CI confidence interval CRP C-reactive protein EOS early-onset sepsis IQR interquartile range LOS late-onset sepsis NICU neonatal intensive care unit NLR neutrophil-to-lymphocyte ratio PCT procalcitonin PLR platelet-to-lymphocyte ratio ROC receiver operating characteristic SD standard deviation WBC white blood cell count Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Yalova University (decision number 2025/174; date: 7 May 2025). Owing to the retrospective design, the requirement for written informed consent was waived. All procedures were conducted in accordance with the Declaration of Helsinki and relevant national regulations. Consent for publication Not applicable. The manuscript does not contain any individual person’s identifiable data. Availability of data and materials The datasets used and analysed during the current study are available from the corresponding author on reasonable request. Competing interests The authors declare that they have no competing interests. Funding No specific funding was received for this study. Authors’ contributions TA conceived the study, supervised data collection and drafted the initial manuscript. BSA and Tİ contributed to study design, data collection and interpretation of the results. GK supervised microbiological data collection and contributed to data interpretation. All authors critically revised the manuscript, approved the final version and agree to be accountable for all aspects of the work. Acknowledgements The authors thank the medical and nursing staff of the neonatal intensive care unit at Yalova University Training and Research Hospital for their support in patient care and data recording. References Arcagok BC, Karabulut B. 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Review of the predictive value of biomarkers in sepsis. J Immunol Res. 2024;2024:2715606. 10.1155/2024/2715606 . Tables Table 1. Baseline demographic and perinatal characteristics of the study population Characteristic Total (n = 446) EOS (n = 143) LOS (n = 101) Jaundice (n = 102) Healthy controls (n = 100) Age at sampling (days), mean ± SD 6.3 ± 6.7 1.1 ± 1.1 13.8 ± 7.7 4.5 ± 2.1 7.9 ± 5.9 Sex, n (%) Female 214 (48.0) 72 (50.3) 43 (42.6) 49 (48.0) 50 (50.0) Male 232 (52.0) 71 (49.7) 58 (57.4) 53 (52.0) 50 (50.0) Mode of delivery, n (%) Vaginal 178 (39.9) 55 (38.5) 41 (40.6) 34 (33.3) 48 (48.0) Caesarean section 268 (60.1) 88 (61.5) 60 (59.4) 68 (66.7) 52 (52.0) Birth weight (g), mean ± SD 3193.8 ± 528.0 3195.1 ± 578.2 3248.0 ± 524.6 3152.9 ± 496.0 3178.9 ± 489.5 Birth weight categories (g), n (%) ≤2000 10 (2.2) 6 (4.2) 3 (3.0) 1 (1.0) 0 (0.0) 2001–2500 33 (7.4) 9 (6.3) 1 (1.0) 11 (10.8) 12 (12.0) 2501–3000 110 (24.7) 33 (23.1) 30 (29.7) 24 (23.5) 23 (23.0) 3001–3500 181 (40.6) 57 (39.9) 37 (36.6) 44 (43.1) 43 (43.0) ≥3501 112 (25.1) 38 (26.6) 30 (29.7) 22 (21.6) 22 (22.0) Data are presented as mean ± standard deviation or n (%), as appropriate. EOS, early-onset sepsis; LOS, late-onset sepsis; SD, standard deviation. Table 2. Laboratory parameters by study group Parameter EOS (n = 143) LOS (n = 101) Jaundice (n = 102) Healthy controls (n = 100) p value* CRP (mg/L) 12.2 ± 15.1 7.2 ± 13.1 0.6 ± 0.6 0.9 ± 0.7 0.001 PCT (ng/mL) 5.3 ± 8.7 6.8 ± 38.1 0.01 ± 0.02 0.04 ± 0.08 0.001 WBC (×10⁹/L) 37.9 ± 204.5 12.5 ± 4.6 11.6 ± 4.1 21.0 ± 104.2 0.001 Platelets (×10⁹/L) 281.3 ± 82.7 401.5 ± 146.8 292.7 ± 97.6 326.7 ± 106.3 0.001 Neutrophils (×10⁹/L) 8.0 ± 4.1 4.8 ± 3.2 5.2 ± 3.6 3.8 ± 1.8 0.001 Lymphocytes (×10⁹/L) 4.4 ± 2.2 5.5 ± 2.4 4.6 ± 1.7 4.9 ± 1.7 0.001 PLR 74.0 ± 37.6 122.2 ± 334.7 69.3 ± 34.3 72.6 ± 30.0 0.133 NLR 2.1 ± 1.4 1.4 ± 3.2 1.2 ± 1.0 0.9 ± 0.6 0.001 p values from Kruskal–Wallis test; p<0.05 was considered statistically significant. CRP, C-reactive protein; PCT, procalcitonin; WBC, white blood cell count; PLR, platelet-to-lymphocyte ratio; NLR, neutrophil-to-lymphocyte ratio; EOS, early-onset sepsis; LOS, late-onset sepsis. Table 3. ROC analysis of CRP, procalcitonin, WBC, PLR and NLR for predicting neonatal sepsis Test variable AUC (95% CI) Cut-off value p value Sensitivity (%) Specificity (%) CRP (mg/L) 0.746 (0.700–0.792) 0.9700 0.000 67.5 43.1 PCT (ng/mL) 0.971 (0.958–0.983) 0.1090 0.000 90.9 90.1 WBC (×10⁹/L) 0.653 (0.602–0.703) 13.3400 0.000 43.6 80.2 PLR 0.542 (0.489–0.596) 71.7675 0.125 52.3 62.9 NLR 0.649 (0.598–0.700) 1.4421 0.000 46.9 77.2 AUC, area under the curve; CI, confidence interval; CRP, C-reactive protein; PCT, procalcitonin; WBC, white blood cell count; PLR, platelet-to-lymphocyte ratio; NLR, neutrophil-to-lymphocyte ratio. Biomarkers were analysed for discriminating sepsis-positive (EOS+LOS) from sepsis-negative (jaundice+healthy) infants. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Feb, 2026 Read the published version in BMC Pediatrics → Version 1 posted Editorial decision: Revision requested 05 Jan, 2026 Reviews received at journal 04 Jan, 2026 Reviews received at journal 02 Jan, 2026 Reviews received at journal 31 Dec, 2025 Reviews received at journal 31 Dec, 2025 Reviewers agreed at journal 30 Dec, 2025 Reviewers agreed at journal 28 Dec, 2025 Reviewers agreed at journal 28 Dec, 2025 Reviewers agreed at journal 28 Dec, 2025 Reviewers agreed at journal 28 Dec, 2025 Reviewers invited by journal 27 Dec, 2025 Editor invited by journal 15 Dec, 2025 Editor assigned by journal 13 Dec, 2025 Submission checks completed at journal 13 Dec, 2025 First submitted to journal 11 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Adıgüzel¹","email":"data:image/png;base64,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","orcid":"","institution":"Faculty of Medicine, Yalova University, Yalova, Turkey","correspondingAuthor":true,"prefix":"","firstName":"Taner","middleName":"","lastName":"Adıgüzel¹","suffix":""},{"id":569033354,"identity":"403dc8a8-a0ba-46d3-b17a-0e41b5088110","order_by":1,"name":"Bahriye Semizoğlu Atasoy¹","email":"","orcid":"","institution":"Faculty of Medicine, Yalova University, Yalova, Turkey","correspondingAuthor":false,"prefix":"","firstName":"Bahriye","middleName":"Semizoğlu","lastName":"Atasoy¹","suffix":""},{"id":569033355,"identity":"2af4fba5-7b57-496d-8ce0-64ba607ccc2f","order_by":2,"name":"Tuba İşcan¹","email":"","orcid":"","institution":"Faculty of Medicine, Yalova University, Yalova, Turkey","correspondingAuthor":false,"prefix":"","firstName":"Tuba","middleName":"","lastName":"İşcan¹","suffix":""},{"id":569033356,"identity":"a55392ed-415a-48f0-bcfe-8cfeebcffee8","order_by":3,"name":"Gülsüm Kaya²","email":"","orcid":"","institution":"Faculty of Medicine, Yalova University, Yalova, Turkey","correspondingAuthor":false,"prefix":"","firstName":"Gülsüm","middleName":"","lastName":"Kaya²","suffix":""}],"badges":[],"createdAt":"2025-12-11 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06:12:04","extension":"html","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":103922,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8339561/v1/5a845d8be6b18a7b1a1315f0.html"},{"id":99495298,"identity":"f685ec13-bbb8-43a6-9d81-034910d8a86a","added_by":"auto","created_at":"2026-01-05 06:12:04","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":129990,"visible":true,"origin":"","legend":"\u003cp\u003eReceiver operating characteristic (ROC) curves of CRP, procalcitonin, WBC, PLR and NLR for discriminating sepsis-positive (EOS+LOS) and sepsis-negative (jaundice+healthy) neonates.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8339561/v1/dc73f8586376dc7c826b5559.png"},{"id":102785160,"identity":"b5d947e6-aea8-48a2-93d2-e5e5cacd83c0","added_by":"auto","created_at":"2026-02-16 16:00:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1195059,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8339561/v1/8c0602d3-53ff-4ead-aefa-e0dc85716138.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Diagnostic Value Of Neutrophil-To-Lymphocyte And Platelet-To-Lymphocyte Ratios İn Early- And Late-Onset Neonatal Sepsis: A Retrospective Single-Centre Observational Study","fulltext":[{"header":"Background","content":"\u003cp\u003eNeonatal sepsis is a systemic infectious syndrome occurring in the first 28 days of life and remains one of the leading causes of neonatal morbidity and mortality worldwide [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Clinically, neonatal sepsis is usually categorised into early-onset sepsis (EOS), in which symptoms develop within the first 72 hours of life, and late-onset sepsis (LOS), occurring thereafter [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. EOS is most often related to vertical transmission of microorganisms from the mother during pregnancy or the perinatal period, whereas LOS is more frequently associated with environmental and nosocomial pathogens acquired after birth [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn high-income countries, reported incidence rates of culture-proven neonatal sepsis range from 1 to 8 per 1000 live births, whereas in low- and middle-income settings the incidence and case-fatality rates are considerably higher [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Early recognition and timely initiation of appropriate antimicrobial therapy are crucial to reduce adverse outcomes such as neurodevelopmental impairment, multi-organ failure and death [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. However, the clinical signs of neonatal sepsis\u0026mdash;poor feeding, apnoea, respiratory distress, lethargy, temperature instability and others\u0026mdash;are often subtle and nonspecific, and overlap with many non-infectious conditions [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBlood culture remains the diagnostic gold standard but has several limitations in neonates: the time required to obtain results, the low level of bacteraemia, the small blood volumes that can be safely drawn and prior antibiotic exposure all reduce its sensitivity [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Consequently, clinicians frequently initiate broad-spectrum antibiotics when sepsis is suspected but cannot be confidently excluded, leading to overtreatment, longer hospital stays, increased costs and the development of antimicrobial resistance [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAmong laboratory tests, C-reactive protein (CRP) and procalcitonin (PCT) are the most widely used biomarkers for the diagnosis and follow-up of neonatal sepsis. However, both markers have variable sensitivity and specificity across studies; their performance is influenced by postnatal age, perinatal factors and the presence of non-infectious inflammatory conditions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. In a secondary analysis of the NeoPInS trial, the combination of CRP, PCT and white blood cell (WBC) count improved the ability to rule out EOS, but no single biomarker could safely exclude sepsis on its own [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Systematic reviews similarly conclude that CRP and PCT are useful but should always be interpreted alongside clinical findings and other laboratory data [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Therefore, there is increasing interest in additional, inexpensive biomarkers that can support early risk stratification.\u003c/p\u003e \u003cp\u003eComplete blood count (CBC) is routinely obtained in almost all infants admitted to neonatal intensive care units, making derived indices attractive candidates. The neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been proposed as simple markers that integrate innate and adaptive immune responses and the haemostatic response to systemic inflammation [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Several studies in neonatal sepsis suggest that these ratios may help distinguish infected from non-infected infants [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Arcagok and Karabulut [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] reported significantly increased PLR values in EOS cases compared with healthy controls and proposed PLR as a predictor of EOS. In systematic reviews of hematologic indices, NLR has shown area under the ROC curve (AUC) values exceeding 0.80 in some cohorts, although authors emphasise that NLR should be interpreted as an adjunct rather than a stand-alone diagnostic test [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. More recent work has extended the evaluation of CBC-derived ratios to LOS and preterm infants, but results have been heterogeneous across centres [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite this growing literature, there are still relatively few studies that assess NLR and PLR simultaneously in the same cohort, across both EOS and LOS, while also including jaundiced and healthy controls and comparing these ratios directly with conventional biomarkers such as CRP and PCT. Understanding the relative and complementary contribution of CBC-derived ratios and established biomarkers could help refine diagnostic algorithms and reduce unnecessary antibiotic exposure.\u003c/p\u003e \u003cp\u003eIn this context, the present study aimed to (i) compare NLR and PLR values among neonates with EOS, LOS, jaundice and healthy controls; and (ii) evaluate the diagnostic performance of NLR and PLR for predicting sepsis when used alongside CRP and PCT in a single-centre cohort.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003e This retrospective, single-centre, observational study was conducted in the level III neonatal intensive care unit (NICU) of Yalova University Training and Research Hospital, Yalova, T\u0026uuml;rkiye. Clinical and laboratory data were obtained from the hospital\u0026rsquo;s electronic medical records system.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population and groups\u003c/h3\u003e\n\u003cp\u003eWe reviewed the records of all neonates hospitalised in the NICU between March 2022 and March 2025. A total of 446 infants who met the predefined eligibility criteria were included and classified into four groups:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEarly-onset sepsis (EOS) group\u003c/b\u003e: infants with clinical and/or laboratory evidence of sepsis within the first 3 postnatal days.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLate-onset sepsis (LOS) group\u003c/b\u003e: infants with sepsis diagnosed on or after the 4th postnatal day.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eJaundice group\u003c/b\u003e: infants with \u0026ldquo;jaundice\u0026rdquo; documented as the primary diagnosis, hospitalised for neonatal jaundice without clinical or laboratory signs of sepsis.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eHealthy control group\u003c/b\u003e: infants with \u0026ldquo;healthy\u0026rdquo; recorded in the file, hospitalised for routine observation or non-infectious reasons, without sepsis or jaundice.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eThe distinction between EOS and LOS was based on the timing of symptom onset, in accordance with commonly used clinical definitions [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Inclusion and exclusion criteria were specified a priori in the ethics committee application and applied during chart review. Infants with major congenital anomalies, inherited immune or haematologic disorders or missing key laboratory data were excluded.\u003c/p\u003e\n\u003ch3\u003eData collection and variables\u003c/h3\u003e\n\u003cp\u003eFor each infant, demographic, clinical and laboratory data were extracted using a standardised data collection form. The following variables were recorded:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eDemographic and perinatal variables\u003c/b\u003e: sex, mode of delivery (vaginal vs caesarean), birth weight and postnatal age at the time of sampling.\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eLaboratory parameters\u003c/b\u003e: C-reactive protein (CRP), procalcitonin (PCT), white blood cell (WBC) count, platelet count, absolute neutrophil count and absolute lymphocyte count.\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cp\u003eOnly pre-treatment laboratory values obtained before the initiation of antibiotic therapy were included in the analysis. NLR was calculated as the ratio of absolute neutrophil count to absolute lymphocyte count, and PLR as the ratio of platelet count to absolute lymphocyte count. NLR and PLR were evaluated as secondary biomarkers, as pre-specified in the ethics protocol.\u003c/p\u003e \u003cp\u003eThe diagnosis of sepsis was made by neonatologists and paediatricians based on clinical signs, laboratory results and, when available, blood culture findings, in accordance with national and international guidelines [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e\n\u003ch4\u003eEthical approval\u003c/h4\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of Yalova University on 7 May 2025 (decision number 2025/174). Owing to the retrospective design, individual informed consent was waived. All data were anonymised before analysis and used solely for research purposes.\u003c/p\u003e\n\u003ch4\u003eStatistical analysis\u003c/h4\u003e\n\u003cp\u003eStatistical analyses were performed using SPSS for Windows, version 22.0 (IBM Corp., Armonk, NY, USA). The distribution of continuous variables was assessed visually (histograms, Q\u0026ndash;Q plots) and analytically. Continuous variables were summarised as mean \u0026plusmn; standard deviation (SD) or median and interquartile range (IQR), as appropriate, whereas categorical variables were presented as counts and percentages.\u003c/p\u003e\n\u003cp\u003eGroup comparisons for continuous variables were performed using non-parametric tests. Differences among the four study groups (EOS, LOS, jaundice, healthy controls) were examined using the Kruskal\u0026ndash;Wallis test. Where appropriate, pairwise comparisons were conducted using the Mann\u0026ndash;Whitney U test, with Bonferroni correction applied to control for type I error.\u003c/p\u003e\n\u003cp\u003eFor categorical variables, group differences were analysed using the chi-square test. To evaluate the diagnostic performance of biomarkers, EOS and LOS groups were combined as the sepsis-positive group, and the jaundice and healthy control groups were combined as the sepsis-negative group. Receiver operating characteristic (ROC) curves were generated for CRP, PCT, WBC, absolute neutrophil count, NLR and PLR. For each marker, the area under the ROC curve (AUC), optimal cut-off value, sensitivity and specificity were calculated [1,3]. A two-sided p value \u0026lt;0.05 was considered statistically significant.\u003c/p\u003e\n\u003ch4\u003eUse of artificial intelligence tools\u003c/h4\u003e\n\u003cp\u003eA large language model\u0026ndash;based assistant (ChatGPT, OpenAI) was used to improve the clarity and fluency of the English language of the manuscript. All content was reviewed, edited and approved by the authors, who take full responsibility for the final version of the text.\u003c/p\u003e"},{"header":"Results","content":"\u003ch4\u003eBaseline characteristics\u003c/h4\u003e\n\u003cp\u003eA total of 446 neonates were included: 143 (32.1%) in the EOS group, 101 (22.6%) in the LOS group, 102 (22.9%) in the jaundice group and 100 (22.4%) in the healthy control group. Sex distribution and mode of delivery (vaginal vs caesarean section) were similar across groups (p\u0026gt;0.05). The proportions of female and male infants and of vaginal and caesarean deliveries did not differ significantly between groups.\u003c/p\u003e\n\u003cp\u003eMedian postnatal age at sampling was 1 day in the EOS group, 13 days in the LOS group, 4 days in the jaundice group and 6 days in the healthy control group. Birth weight distributions were clinically comparable across groups, and no statistically significant differences in mean birth weight were observed. Detailed demographic and perinatal characteristics are presented in Table 1.\u003c/p\u003e\n\u003ch4\u003eLaboratory parameters across groups\u003c/h4\u003e\n\u003cp\u003eWhen laboratory parameters were compared across the four groups, CRP and PCT levels were significantly higher in both EOS and LOS groups than in the jaundice and healthy control groups (p\u0026lt;0.001; Table 2). In the sepsis groups, particularly in EOS, WBC and absolute neutrophil counts tended to be higher, whereas lymphocyte counts were relatively lower.\u003c/p\u003e\n\u003cp\u003eNLR differed significantly among the groups. Median NLR was 1.97 in the EOS group, 0.71 in the LOS group, 0.84 in the jaundice group and 0.67 in the healthy control group (p\u0026lt;0.001). This pattern indicates a more pronounced neutrophil-predominant inflammatory response in early-onset sepsis compared with LOS and non-septic conditions.\u003c/p\u003e\n\u003cp\u003eIn contrast, PLR did not differ significantly among the four groups. Median PLR values ranged between approximately 63 and 74 across EOS, LOS, jaundice and healthy infants, with no statistically significant difference (p\u0026gt;0.05). Platelet counts were highest in the LOS group but were within clinically comparable ranges in the other groups. Detailed distributions of CRP, PCT, WBC, neutrophils, lymphocytes, platelets, NLR and PLR by group are shown in Table 2.\u003c/p\u003e\n\u003ch4\u003eSepsis-positive versus sepsis-negative infants\u003c/h4\u003e\n\u003cp\u003eFor ROC analysis, EOS and LOS infants were combined into a sepsis-positive group (n=244), and jaundice and healthy control infants into a sepsis-negative group (n=202). In this classification, median NLR was significantly higher in the sepsis-positive than in the sepsis-negative group (1.34 vs 0.79; p\u0026lt;0.001). CRP, PCT, WBC and absolute neutrophil counts were also significantly elevated in sepsis-positive infants, whereas lymphocyte counts were relatively lower. PLR showed no significant difference between sepsis-positive and sepsis-negative groups.\u003c/p\u003e\n\u003ch4\u003eDiagnostic performance of biomarkers (ROC analysis)\u003c/h4\u003e\n\u003cp\u003eROC curve analysis was used to assess the ability of each biomarker to discriminate sepsis-positive from sepsis-negative infants (Table 3; Figure 1).\u003c/p\u003e\n\u003cul class=\"decimal_type\"\u003e\n \u003cli\u003eProcalcitonin had the highest diagnostic accuracy, with an AUC of 0.971 (95% CI 0.958\u0026ndash;0.983). At a cut-off value of 0.109 ng/mL, PCT achieved a sensitivity of approximately 90.9% and a specificity of 90.1%.\u003c/li\u003e\n \u003cli\u003eCRP showed an AUC of 0.746 (95% CI 0.700\u0026ndash;0.792), indicating moderate discriminative ability.\u003c/li\u003e\n \u003cli\u003eNLR and WBC both had AUC values around 0.65 (0.649 and 0.653, respectively), indicating moderate diagnostic performance.\u003c/li\u003e\n \u003cli\u003eAbsolute neutrophil count had an AUC of 0.68, also in the moderate range.\u003c/li\u003e\n \u003cli\u003ePLR had the lowest discriminative value with an AUC of 0.542 (95% CI 0.489\u0026ndash;0.596), providing only marginal separation between sepsis-positive and sepsis-negative groups.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this single-centre retrospective study, we evaluated the diagnostic value of NLR and PLR for early identification of neonatal sepsis in a cohort that included EOS, LOS, jaundice and healthy control infants, and compared these indices with conventional biomarkers PCT and CRP. Overall, our main findings were that (i) NLR was significantly increased in sepsis, particularly in EOS, and showed moderate diagnostic accuracy (AUC 0.65); (ii) PLR had limited diagnostic value in this population (AUC 0.54); (iii) PCT provided excellent discriminative performance (AUC 0.97); and (iv) CRP demonstrated moderate accuracy with relatively high specificity (AUC 0.75). These results support the use of NLR as a low-cost adjunctive marker\u0026mdash;especially in EOS\u0026mdash;while underlining the dominant role of PCT and the complementary, but not stand-alone, role of CRP.\u003c/p\u003e\n\u003ch4\u003eCRP and PCT: conventional biomarkers in context\u003c/h4\u003e\n\u003cp\u003eIn our cohort, CRP levels were significantly higher in sepsis-positive infants than in jaundiced and healthy controls, and the AUC for CRP was 0.75. This is consistent with previous reports describing CRP as a marker with relatively high specificity but limited sensitivity in the early phase of infection [2,4]. The kinetics of CRP provide a physiological explanation: as an acute-phase protein synthesised mainly by hepatocytes in response to interleukin-6 and other proinflammatory cytokines, CRP typically requires 10\u0026ndash;12 hours after the onset of infection to show a significant rise, with peak levels occurring at 24\u0026ndash;48 hours [4,17]. Consequently, CRP values may remain normal or only mildly elevated during the very early hours of sepsis, limiting sensitivity at presentation. Moreover, non-infectious conditions such as birth stress, perinatal asphyxia, meconium aspiration and surgical procedures can lead to elevated CRP, reducing specificity in the neonatal period [2,12]. Our findings align with literature suggesting that CRP is more useful for monitoring the evolution of infection and response to therapy through serial measurements, rather than as a single, definitive diagnostic test.\u003c/p\u003e\n\u003cp\u003ePCT, in contrast, showed the highest AUC in our study (0.97), with both high sensitivity and specificity at a relatively low cut-off. PCT is the prohormone of calcitonin and is produced at low levels by thyroid C cells under physiological conditions. During systemic bacterial infection, however, PCT synthesis is upregulated in multiple extra-thyroid tissues, including the lungs, liver, intestine and cells of the monocyte\u0026ndash;macrophage system [5,9]. Serum PCT levels begin to rise within 3\u0026ndash;4 hours of symptom onset, peak at around 24 hours and then gradually fall as infection is controlled [8,11]. These kinetics make PCT particularly advantageous in the early phase of sepsis, when CRP may still be normal. Several studies and reviews have highlighted the value of PCT in neonatal sepsis, both for early diagnosis and for guiding antibiotic initiation and discontinuation [5,8,17]. Our results are consistent with these data and support the concept of PCT as a first-line biomarker for ruling in or ruling out sepsis, especially in EOS.\u003c/p\u003e\n\u003ch4\u003eNLR: a supportive marker, particularly in EOS\u003c/h4\u003e\n\u003cp\u003eIn the present study, NLR was significantly higher in sepsis-positive infants than in sepsis-negative infants, and especially elevated in the EOS group compared with LOS, jaundice and healthy controls. The AUC of 0.65 indicates modest but clinically relevant discriminative ability. This pattern is in line with the expected physiological response, in which systemic infection triggers neutrophilia and relative lymphopenia, thereby increasing NLR as a combined indicator of innate and adaptive immune activation.\u003c/p\u003e\n\u003cp\u003eOur findings are consistent with prior work demonstrating higher NLR values in neonates with sepsis compared with healthy controls [13,20]. In their systematic review and meta-analysis, Xin et al. [20] reported that NLR had overall \u0026ldquo;good-to-moderate\u0026rdquo; diagnostic performance in neonatal sepsis, although AUC values varied widely between studies. The AUC observed in our cohort lies in the mid-range of this reported spectrum, supporting the concept that NLR can serve as a useful adjunctive marker rather than a stand-alone test.\u003c/p\u003e\n\u003cp\u003eA notable aspect of our study is the separate analysis of EOS and LOS. We observed that NLR was markedly higher in EOS than in LOS, with values in the LOS group approaching those seen in jaundiced and healthy infants. This suggests that in the very early days of life, the neutrophil-dominant inflammatory response to infection may be more pronounced, whereas in LOS, the haematological response may be modulated by multiple factors such as nosocomial pathogens, comorbidities and prior interventions. Rana et al. [13] similarly reported that haematologic ratios, particularly NLR, can be sensitive indicators of EOS. Our findings support the use of NLR as an additional \u0026ldquo;warning sign\u0026rdquo; pointing towards EOS when interpreted alongside clinical findings, CRP and PCT.\u003c/p\u003e\n\u003cp\u003eConversely, the convergence of NLR values between LOS and non-septic groups in our cohort suggests that NLR is less reliable as a single discriminator in LOS, possibly because of overlapping inflammatory and haematological influences in older, hospitalised neonates [6,18]. Taken together, these observations indicate that NLR may be most informative in the context of suspected EOS, while in LOS it should be considered only as part of an integrated assessment.\u003c/p\u003e\n\u003ch4\u003ePLR: limited diagnostic value in this cohort\u003c/h4\u003e\n\u003cp\u003eIn contrast to NLR, PLR did not differ significantly among EOS, LOS, jaundice and healthy infants in our study, and its AUC for predicting sepsis was only 0.54, indicating poor discriminative performance. These findings do not reproduce the results of Arcagok and Karabulut [1], who reported significantly higher PLR values in EOS compared with healthy controls and proposed PLR as a useful predictor of EOS. Discrepancies between studies may reflect differences in study design, population characteristics (including gestational age and prematurity rates), the inclusion of both EOS and LOS, and the presence of comorbid conditions.\u003c/p\u003e\n\u003cp\u003eIt is also important to consider the dynamic nature of platelet kinetics. Thrombocytopenia or thrombocytosis often develop over time rather than at a single time point, and PLR values based on a single pre-treatment measurement may not capture these changes fully. Moreover, platelet counts can be influenced by a variety of non-infectious factors, such as perinatal asphyxia, intrauterine growth restriction, maternal hypertension, bleeding episodes and transfusions [7,22]. Residual confounding by these factors may have attenuated any sepsis-related signal in PLR in our cohort.\u003c/p\u003e\n\u003cp\u003eAlthough some EOS cohorts and meta-analyses have reported promising results for PLR [1,13], our findings suggest that PLR does not have consistent diagnostic utility across different centres and patient populations. Future research using prospective designs, serial measurements and more homogeneous subgroups (e.g. stratified by gestational age or comorbidities) will be needed to clarify the true value of PLR in neonatal sepsis.\u003c/p\u003e\n\u003ch4\u003eClinical implications\u003c/h4\u003e\n\u003cp\u003eFrom a clinical standpoint, one of the key challenges in neonatal sepsis management is balancing the risk of undertreatment against the harms of overtreatment. Broad-spectrum antibiotics are often started before sepsis can be confidently excluded, and many culture-negative infants receive prolonged courses [5,11]. Our data reinforce the central role of PCT as the most accurate biomarker in this setting, with CRP contributing valuable information when interpreted in serial measurements.\u003c/p\u003e\n\u003cp\u003eWithin this framework, NLR may provide additional, low-cost support, particularly for suspected EOS. Because NLR is derived from a routine CBC with no extra cost or blood volume, it can be easily incorporated into existing diagnostic pathways. For clinically stable neonates with low NLR and low PCT/CRP values, clinicians may feel more confident in limiting or withholding empiric antibiotics, whereas a high NLR in the context of suspected EOS and elevated PCT may strengthen the case for early and aggressive treatment. However, NLR and other haematologic indices should always be interpreted alongside the full clinical picture and microbiological results, and not used as sole decision-making tools.\u003c/p\u003e\n\u003cp\u003eIn contrast, the lack of significant diagnostic contribution from PLR in our cohort suggests that PLR should not be used routinely to guide antibiotic decisions in neonatal sepsis until more robust and consistent evidence becomes available.\u003c/p\u003e\n\u003ch4\u003eStrengths and limitations\u003c/h4\u003e\n\u003cp\u003eThis study has several strengths. First, it evaluates NLR and PLR simultaneously in a relatively large single-centre cohort including both EOS and LOS, as well as jaundiced and healthy control infants. Second, it directly compares these haematologic ratios with widely used biomarkers (PCT and CRP) within the same population. Third, the sample size is larger than in many prior single-centre studies, which may enhance the reliability of the estimates [1,13].\u003c/p\u003e\n\u003cp\u003eSeveral limitations should also be acknowledged. The retrospective design may have led to incomplete or heterogeneous documentation of clinical findings and microbiological data. NLR and PLR were assessed at a single pre-treatment time point, and serial measurements were not available; this is particularly relevant for PLR, which may show more informative trends over time. The study was also conducted in a single centre, and our findings may not be generalisable to settings with different pathogen spectra, prematurity rates or treatment protocols [3,22]. Finally, we did not perform multivariable modelling to adjust for potential confounders such as gestational age or specific comorbidities, which could further refine the interpretation of NLR and PLR.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn summary, this single-centre retrospective study shows that PCT, CRP, NLR and PLR fulfil complementary but unequal roles in the diagnostic assessment of neonatal sepsis. PCT emerged as the most accurate biomarker for both EOS and LOS and appears suitable as a primary marker for early diagnosis and for ruling out sepsis. CRP provided moderate diagnostic accuracy and remains useful for monitoring infection burden and treatment response through serial measurements. NLR, easily calculated from a routine CBC, was particularly elevated in EOS and offered moderate additional discriminative value, suggesting that it may serve as a supportive marker that reinforces clinical suspicion and helps guide decision-making in early-onset disease. In contrast, PLR showed limited diagnostic performance in this cohort and does not currently appear to be a reliable stand-alone indicator for sepsis.\u003c/p\u003e\n\u003cp\u003eNeonatal sepsis should continue to be evaluated primarily on the basis of clinical findings and microbiological results. PCT, CRP and NLR may help reduce unnecessary initiation or prolonged use of antibiotics when interpreted together and within a structured clinical pathway. These findings warrant confirmation in larger, multicentre prospective studies using standardised definitions and serial biomarker measurements.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003earea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecomplete blood count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCRP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eC-reactive protein\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eEOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eearly-onset sepsis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eLOS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003elate-onset sepsis\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNICU\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneonatal intensive care unit\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNLR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eneutrophil-to-lymphocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprocalcitonin\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eplatelet-to-lymphocyte ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWBC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ewhite blood cell count\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Yalova University (decision number 2025/174; date: 7 May 2025). Owing to the retrospective design, the requirement for written informed consent was waived. All procedures were conducted in accordance with the Declaration of Helsinki and relevant national regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. The manuscript does not contain any individual person\u0026rsquo;s identifiable data.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used and analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003cbr\u003e\u0026nbsp;No specific funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTA conceived the study, supervised data collection and drafted the initial manuscript. BSA and Tİ contributed to study design, data collection and interpretation of the results. GK supervised microbiological data collection and contributed to data interpretation. All authors critically revised the manuscript, approved the final version and agree to be accountable for all aspects of the work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;The authors thank the medical and nursing staff of the neonatal intensive care unit at Yalova University Training and Research Hospital for their support in patient care and data recording.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eArcagok BC, Karabulut B. Platelet to lymphocyte ratio in neonates: a predictor of early onset neonatal sepsis. 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J Immunol Res. 2024;2024:2715606. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2024/2715606\u003c/span\u003e\u003cspan address=\"10.1155/2024/2715606\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Baseline demographic and perinatal characteristics of the study population\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n = 446)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEOS (n = 143)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (n = 101)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJaundice (n = 102)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy controls (n = 100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge at sampling (days), mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.3 \u0026plusmn; 6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.1 \u0026plusmn; 1.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.8 \u0026plusmn; 7.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.5 \u0026plusmn; 2.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.9 \u0026plusmn; 5.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSex, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e214 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72 (50.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e232 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71 (49.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e58 (57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e53 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMode of delivery, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;Vaginal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e178 (39.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e55 (38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e41 (40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48 (48.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;Caesarean section\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e268 (60.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e88 (61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e60 (59.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e68 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (52.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBirth weight (g), mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3193.8 \u0026plusmn; 528.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3195.1 \u0026plusmn; 578.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3248.0 \u0026plusmn; 524.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3152.9 \u0026plusmn; 496.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3178.9 \u0026plusmn; 489.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eBirth weight categories (g), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;\u0026le;2000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (2.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;2001\u0026ndash;2500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (6.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;2501\u0026ndash;3000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e110 (24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (23.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (23.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;3001\u0026ndash;3500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e181 (40.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57 (39.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43 (43.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026emsp;\u0026ge;3501\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e112 (25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e38 (26.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (29.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eData are presented as mean \u0026plusmn; standard deviation or n (%), as appropriate. EOS, early-onset sepsis; LOS, late-onset sepsis; SD, standard deviation.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Laboratory parameters by study group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eEOS (n = 143)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLOS (n = 101)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eJaundice (n = 102)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealthy controls (n = 100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.2 \u0026plusmn; 15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7.2 \u0026plusmn; 13.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.6 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9 \u0026plusmn; 0.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePCT (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.3 \u0026plusmn; 8.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.8 \u0026plusmn; 38.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.01 \u0026plusmn; 0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.04 \u0026plusmn; 0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWBC (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37.9 \u0026plusmn; 204.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12.5 \u0026plusmn; 4.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11.6 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21.0 \u0026plusmn; 104.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePlatelets (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e281.3 \u0026plusmn; 82.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e401.5 \u0026plusmn; 146.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e292.7 \u0026plusmn; 97.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e326.7 \u0026plusmn; 106.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNeutrophils (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8.0 \u0026plusmn; 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.8 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.2 \u0026plusmn; 3.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3.8 \u0026plusmn; 1.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLymphocytes (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.4 \u0026plusmn; 2.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5.5 \u0026plusmn; 2.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.6 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4.9 \u0026plusmn; 1.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74.0 \u0026plusmn; 37.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e122.2 \u0026plusmn; 334.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e69.3 \u0026plusmn; 34.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e72.6 \u0026plusmn; 30.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.133\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2.1 \u0026plusmn; 1.4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.4 \u0026plusmn; 3.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.2 \u0026plusmn; 1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9 \u0026plusmn; 0.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003ep values from Kruskal\u0026ndash;Wallis test; p\u0026lt;0.05 was considered statistically significant. CRP, C-reactive protein; PCT, procalcitonin; WBC, white blood cell count; PLR, platelet-to-lymphocyte ratio; NLR, neutrophil-to-lymphocyte ratio; EOS, early-onset sepsis; LOS, late-onset sepsis.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. ROC analysis of CRP, procalcitonin, WBC, PLR and NLR for predicting neonatal sepsis\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTest variable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAUC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCut-off value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCRP (mg/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.746 (0.700\u0026ndash;0.792)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.9700\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePCT (ng/mL)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.971 (0.958\u0026ndash;0.983)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.1090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e90.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eWBC (\u0026times;10⁹/L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.653 (0.602\u0026ndash;0.703)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13.3400\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e43.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.542 (0.489\u0026ndash;0.596)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71.7675\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.125\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.649 (0.598\u0026ndash;0.700)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.4421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAUC, area under the curve; CI, confidence interval; CRP, C-reactive protein; PCT, procalcitonin; WBC, white blood cell count; PLR, platelet-to-lymphocyte ratio; NLR, neutrophil-to-lymphocyte ratio. Biomarkers were analysed for discriminating sepsis-positive (EOS+LOS) from sepsis-negative (jaundice+healthy) infants.\u003c/em\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"neonatal sepsis, early-onset sepsis, late-onset sepsis, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, procalcitonin, C-reactive protein","lastPublishedDoi":"10.21203/rs.3.rs-8339561/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8339561/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eNeonatal sepsis remains a leading cause of morbidity and mortality worldwide despite advances in perinatal and intensive care. Early and accurate diagnosis is challenging because clinical signs are often nonspecific and no single biomarker has shown perfect sensitivity and specificity. In recent years, complete blood count\u0026ndash;derived indices such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) have been proposed as inexpensive, readily available markers of systemic inflammation. This study aimed to evaluate the diagnostic value of NLR and PLR in early-onset (EOS) and late-onset sepsis (LOS) compared with jaundiced and healthy neonates, and to compare their performance with that of procalcitonin (PCT) and C-reactive protein (CRP).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this retrospective single-centre study, we reviewed the records of neonates hospitalised in a level III neonatal intensive care unit between March 2022 and March 2025. A total of 446 infants were classified into four groups: EOS (first 3 postnatal days), LOS (\u0026ge;\u0026thinsp;4th day), jaundice without sepsis, and healthy controls. Pre-treatment laboratory data, including complete blood count, CRP and PCT, were extracted. NLR and PLR were calculated by dividing absolute neutrophil and platelet counts by lymphocyte counts, respectively. Group comparisons were performed using non-parametric tests. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of each biomarker for differentiating sepsis-positive (EOS\u0026thinsp;+\u0026thinsp;LOS) from sepsis-negative (jaundice\u0026thinsp;+\u0026thinsp;healthy) infants.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 446 neonates, 143 (32.1%) had EOS, 101 (22.6%) had LOS, 102 (22.9%) were in the jaundice group and 100 (22.4%) were healthy controls. Median NLR values were significantly higher in the EOS group than in the LOS, jaundice and healthy groups (1.97 vs 0.71, 0.84 and 0.67, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). PLR values did not differ significantly between the four groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). When EOS and LOS were combined as the sepsis-positive group, median NLR was higher in sepsis-positive than in sepsis-negative infants (1.34 vs 0.79; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). In ROC analysis, PCT showed the highest diagnostic accuracy for sepsis (area under the curve [AUC] 0.97), followed by CRP (AUC 0.75) and NLR (AUC 0.65), whereas PLR had limited discriminative ability (AUC 0.54).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eNLR is moderately useful for predicting neonatal sepsis, particularly in EOS, and may serve as a supportive parameter when interpreted alongside PCT, CRP and clinical findings. In this cohort, PLR did not provide meaningful additional diagnostic value. The combined use of CBC-derived ratios and conventional biomarkers may support early decision-making and help reduce unnecessary antibiotic exposure in neonates.\u003c/p\u003e","manuscriptTitle":"Diagnostic Value Of Neutrophil-To-Lymphocyte And Platelet-To-Lymphocyte Ratios İn Early- And Late-Onset Neonatal Sepsis: A Retrospective Single-Centre Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-05 06:11:59","doi":"10.21203/rs.3.rs-8339561/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-01-05T05:15:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-04T11:54:52+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-03T00:50:53+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T23:15:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-31T20:50:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"311379073605712258144936160992689859810","date":"2025-12-30T06:17:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"268466936006306477892783341061677671269","date":"2025-12-29T03:01:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"64495145732012836239693248945991567513","date":"2025-12-28T23:57:47+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"132486126302303791947591460117441366977","date":"2025-12-28T20:08:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"233885104902103225788634105151055818183","date":"2025-12-28T18:45:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-28T02:54:11+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-15T06:55:50+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-13T11:36:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-13T11:34:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2025-12-11T18:45:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pediatrics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bped","sideBox":"Learn more about [BMC Pediatrics](http://bmcpediatr.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bped/default.aspx","title":"BMC Pediatrics","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"07f7f374-3bcf-4ece-9c75-2026b8d781c6","owner":[],"postedDate":"January 5th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-02-16T15:59:55+00:00","versionOfRecord":{"articleIdentity":"rs-8339561","link":"https://doi.org/10.1186/s12887-026-06617-9","journal":{"identity":"bmc-pediatrics","isVorOnly":false,"title":"BMC Pediatrics"},"publishedOn":"2026-02-13 15:57:04","publishedOnDateReadable":"February 13th, 2026"},"versionCreatedAt":"2026-01-05 06:11:59","video":"","vorDoi":"10.1186/s12887-026-06617-9","vorDoiUrl":"https://doi.org/10.1186/s12887-026-06617-9","workflowStages":[]},"version":"v1","identity":"rs-8339561","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8339561","identity":"rs-8339561","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}