Gestational Age–Dependent Association of HALP Score and Systemic Inflammatory Indices with Retinopathy of Prematurity

Gestational Age–Dependent Association of HALP Score and Systemic Inflammatory Indices with Retinopathy of Prematurity | 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 Gestational Age–Dependent Association of HALP Score and Systemic Inflammatory Indices with Retinopathy of Prematurity Zarife Ekici Gök, Nuriye Aslı Melekoğlu, Şeyma Yaşar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9041551/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract Background To evaluate the temporal profile and clinical relevance of the hemoglobin–albumin–lymphocyte–platelet (HALP) score and complete blood count–derived inflammatory indices for retinopathy of prematurity (ROP) across gestational age strata. Methods 139 preterm infants born at ≤ 32 weeks were stratified into ≤ 30 and 30–32 weeks. Early (postnatal days 2–4) and month-1 complete blood count parameters were analyzed. Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index, aggregate index of systemic inflammation, and HALP score were calculated at both time points. Comparisons were performed according to ROP status and gestational age strata, and discriminative performance was evaluated using receiver operating characteristic analysis. Results ROP developed in 30 infants (21.6%), including 9 requiring treatment. The ≤ 30-week group had higher ROP incidence and severity. Early indices were not associated with ROP. At month 1, infants ≤ 30 weeks with ROP showed lower albumin and higher composite inflammatory indices (AUC 0.73–0.82), whereas associations were weaker in the 30–32-week group. HALP and platelet-to-lymphocyte ratio demonstrated limited discrimination. Conclusions Month-1 systemic inflammatory activation is associated with ROP predominantly in infants ≤ 30 weeks, indicating a gestational age–dependent inflammatory contribution and potential value for risk stratification. Retinopathy of Prematurity Infant Premature Gestational Age Inflammation Hematologic Parameters Biomarkers Introduction Retinopathy of prematurity (ROP) is one of the leading causes of preventable childhood blindness in both developed and developing countries, and its incidence continues to increase in parallel with improving survival of premature infants [ 1 ]. Advances in neonatal intensive care have shifted the epidemiologic landscape of ROP, resulting in a growing population of extremely preterm infants at risk for severe disease. Maternal inflammatory responses and neonatal systemic inflammation have been shown to contribute to ROP development [ 2 , 4 ]. Moreover, systemic inflammation may adversely affect retinal vascularization and increase the risk of ROP independently of gestational age and birth weight [ 5 ]. This observation suggests that inflammatory pathways may represent modifiable contributors to disease progression beyond traditional maturity-based risk factors. Inflammation influences ROP both indirectly, through impairment of retinal perfusion, and directly, through modulation of retinal angiogenesis. Experimental animal studies have demonstrated that neonatal systemic inflammation disrupts retinal vascular development and induces pathological features consistent with ROP [ 6 ]. Pro-inflammatory cytokines and immune-mediated signaling cascades have been implicated in dysregulated vascular endothelial growth factor (VEGF) expression and abnormal angiogenic responses. Fluctuations in oxygen saturation secondary to impaired angiogenesis lead to retinal ischemia [ 7 ] and underlie the two-phase pathogenesis of ROP: hyperoxia-induced vascular arrest followed by hypoxia-driven cytokine-mediated pathological neovascularization [ 8 ]. Elevated levels of proinflammatory cytokines in the vitreous and serum of infants with ROP further support the involvement of both local and systemic inflammation in disease progression [ 9 – 11 ]. Collectively, these findings reinforce the concept that ROP represents not solely an oxygen-mediated disorder but a condition in which systemic inflammatory activation may amplify vascular vulnerability. Although ROP is a multifactorial disease, low birth weight and gestational age remain the strongest risk factors. While screening criteria are primarily based on these two parameters [ 12 ], numerous additional risks related to maternal characteristics, prenatal and postnatal exposures, and prematurity-associated comorbidities have been described. Despite this complexity, risk stratification in clinical practice continues to rely predominantly on gestational age and birth weight, underscoring the need for accessible adjunct biomarkers that may refine early risk assessment. Hematologic parameters assessed during the neonatal period have been linked to immune modulation and oxidative stress, yet findings remain inconsistent [ 13 , 14 ]. Complete blood count–derived inflammatory markers—including the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR)—have been investigated in ROP with variable results [ 15 – 17 ]. These indices have also been widely studied as inflammatory biomarkers in systemic diseases such as malignancies and rheumatologic disorders [ 18 , 19 ], as well as in ophthalmic conditions including age-related macular degeneration, glaucoma, and diabetic retinopathy [ 20 – 22 ]. More recently, composite indices integrating multiple hematologic components—such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI), and the hemoglobin–albumin–lymphocyte–platelet (HALP) score—have been proposed as more comprehensive reflections of the balance between inflammatory activation and immune-nutritional status. The limited and inconsistent evidence regarding CBC-derived inflammatory indices in ROP highlights the need for more robust and temporally structured data. In particular, few studies have examined the evolution of inflammatory indices over time or evaluated their performance across different gestational age strata, despite the well-established maturational variability of neonatal hematologic parameters. Therefore, the present study aimed to compare the HALP score and composite systemic inflammatory indices in preterm infants born at ≤ 30 weeks and 30–32 weeks of gestation and to evaluate their associations with ROP development and treatment requirement. We further sought to determine whether inflammatory indices measured during distinct postnatal time windows demonstrate differential clinical relevance, thereby contributing to more refined risk stratification in very preterm infants. Material & Methods Study design and ethical approval This retrospective observational cohort study included secondary case–control comparisons between infants with and without retinopathy of prematurity (ROP). The study was designed to evaluate temporal changes in systemic inflammatory markers and their associations with ROP development and severity. Medical records of 139 preterm infants followed in the neonatal intensive care unit between May 2022 and December 2025 were reviewed. Clinical, laboratory, and ophthalmologic data were extracted from the institutional electronic medical record system. The study was approved by the Health Sciences Scientific Research Ethics Committee of XXX University (Decision No: 18/2026) and conducted in accordance with the Declaration of Helsinki. Given the retrospective nature of the study and the use of de-identified clinical data, the requirement for written informed consent was waived by the ethics committee. Inclusion and exclusion criteria Preterm infants with gestational age ≤32 weeks, regular ROP screening, and available early postnatal complete blood count (CBC) data obtained within postnatal days 2–4 were included. When available, postnatal month-1 CBC data were also recorded. Infants who received blood product transfusion or systemic steroid therapy before the relevant blood sampling time point were excluded, as these interventions may significantly alter hematologic and inflammatory parameters. Infants with culture-proven sepsis, necrotizing enterocolitis, or severe hematologic disease were also excluded in order to minimize confounding effects of acute systemic inflammatory conditions. Time points and gestational age stratification Early postnatal blood samples were obtained within postnatal days 2–4, and month-1 samples between postnatal days 28–32. Infants were stratified by gestational age into two predefined groups: Group 1: ≤30 weeks Group 2: 30–32 weeks This stratification was performed a priori to account for maturational differences in hematologic parameters and baseline ROP risk across gestational age categories. Ophthalmologic examination and definition of treatment-requiring ROP ROP screening was initiated at postnatal week 4 according to institutional protocol and international screening recommendations. Pupillary dilation was achieved using 0.5% tropicamide (Tropamide, Bilim İlaç, Türkiye) and 2.5% phenylephrine (Mydfrin, Alcon, USA), administered three times at 10-minute intervals, followed by topical anesthesia with 0.5% proparacaine (Alcaine, Alcon, USA) immediately before examination. All examinations were performed by the same experienced ophthalmologist using indirect ophthalmoscopy (Heine Omega 500) with a 28-diopter lens, with scleral depression when necessary. ROP staging, zone classification, and presence of plus disease were determined according to the International Classification of Retinopathy of Prematurity (ICROP). Infants were followed at 1–3-week intervals until retinal vascularization reached the ora serrata. Treatment-requiring ROP was defined based on Early Treatment for Retinopathy of Prematurity (ETROP) criteria as: Any stage with plus disease in Zone I Stage 3 without plus disease in Zone I Stage 2–3 with plus disease in Zone II Eligible infants received intravitreal anti-VEGF therapy and/or laser photocoagulation when clinically indicated. Treatment decisions were made according to standardized institutional protocols. Missing data handling Early postnatal CBC data were available for all infants. Month-1 CBC data were available for all infants in Group 1 and for 18 infants in Group 2. Missing data were not imputed; therefore, month-1 analyses were restricted to infants with complete data and reported as supplementary analyses. Given the incomplete availability of month-1 data in the 30–32-week group, these analyses were interpreted cautiously. This was considered a potential source of selection bias. Hematologic measurements and inflammatory indices Peripheral venous blood samples were collected into EDTA tubes as part of routine clinical care and analyzed using an automated hematology analyzer according to manufacturer specifications. Hemoglobin concentration and leukocyte subtypes were obtained from CBC analysis. Serum albumin levels were obtained from routine biochemical analysis performed at the same sampling time points. Platelet, neutrophil, lymphocyte, and monocyte counts were recorded, and the following indices were calculated: NLR: neutrophil / lymphocyte PLR: platelet / lymphocyte LMR: lymphocyte / monocyte SII: (neutrophil × platelet) / lymphocyte SIRI: (neutrophil × monocyte) / lymphocyte HALP: (hemoglobin × albumin × lymphocyte) / platelet AISI: (neutrophil × monocyte × platelet) / lymphocyte All indices were calculated separately for early postnatal and month-1 measurements to evaluate temporal changes in systemic inflammatory status. Statistical analysis Continuous variables were summarized as mean ± standard deviation for normally distributed data and as median (interquartile range) for non-normally distributed data, while categorical variables were presented as counts and percentages. Normality of distribution was assessed using the Kolmogorov–Smirnov or Shapiro–Wilk tests, as appropriate. Distributional assessment was additionally supported by visual inspection of histograms. For comparisons between independent groups (ROP vs. no ROP), the independent-samples t test was used for normally distributed variables and the Mann–Whitney U test for non-normally distributed variables. Categorical variables were compared using the chi-square test or Fisher’s exact test, as appropriate. For paired comparisons within the same individuals (early postnatal vs. month-1 measurements), the paired t test or Wilcoxon signed-rank test was applied according to distributional assumptions. To evaluate associations between inflammatory indices and ROP development, binary logistic regression analyses were performed. Variables demonstrating clinical relevance or statistical significance in univariable comparisons were entered into regression models to estimate odds ratios (ORs) with 95% confidence intervals (CIs). Given the limited number of treatment-requiring ROP cases, regression analyses for this outcome were interpreted cautiously. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the discriminative ability of each biomarker measured in the early postnatal period (postnatal days 2–4) and at postnatal month 1 (postnatal days 28–32) for predicting ROP development (coded as 1 = ROP and 0 = no ROP). ROC curves were generated separately for early postnatal and month-1 measurements, as well as for a combined model based on probabilities derived from binary logistic regression incorporating both time points. Because some biomarkers may be inversely associated with ROP, AUC values <0.5 were interpreted as inverse discrimination. For each ROC curve, the area under the curve (AUC), 95% confidence intervals calculated using the DeLong method, and the statistical significance of AUC compared with the null value of 0.5 were determined. Optimal cutoff values were identified by maximizing the Youden index (sensitivity + specificity − 1), and corresponding sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy were reported. Because repeated measurements originated from the same individuals, pairwise comparisons of AUCs across time points and combined models were performed using DeLong’s test for correlated ROC curves. The combined model was fitted using complete-case data (infants with both early postnatal and month-1 measurements); therefore, combined-model analyses primarily reflect the ≤30-week group and the subset of the 30–32-week group with available month-1 data. Accordingly, combined-model findings were interpreted within this context. A two-sided p value < 0.05 was considered statistically significant. All statistical analyses were conducted using IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA). The sample size consisted of all eligible infants meeting the inclusion criteria during the study period. Because of the retrospective study design, no a priori power calculation was performed. Given the exploratory nature of the study, findings were interpreted in light of the available event numbers. Results Participant characteristics and distribution of ROP A total of 139 preterm infants were included in the study. Of these, 68 (48.9%) were born at ≤30 weeks of gestation and 71 (51.1%) at 30–32 weeks. Female infants predominated in the ≤30-week group (52.9%, n=36), whereas males were more frequent in the 30–32-week group (54.9%, n=39). Overall, ROP developed in 30 infants (21.6%), and 9 cases (6.5% of the total cohort) required treatment according to ETROP criteria. Stage–zone distribution included Zone 3 Stage 1 (n=11), Zone 2 Stage 2 (n=14), Zone 2 Stage 3 (n=4), and Zone 1 Stage 3 (n=1), with plus disease present in 16 infants. Among treatment-requiring cases, 4 infants received intravitreal anti-VEGF alone, and 5 underwent anti-VEGF followed by laser photocoagulation. Infants without treatment indication were followed until complete retinal vascularization. The overall incidence and distribution of disease severity were consistent with a population of very preterm infants undergoing routine screening. Baseline demographic and clinical characteristics are summarized in Table 1. Within-group temporal changes ≤30-week group In the ≤30-week group, comparison between the early postnatal period and postnatal month 1 showed a significant decrease in hemoglobin levels (p<0.001), accompanied by significant increases in albumin, platelet, leukocyte, and monocyte counts (all p≤0.001). Among inflammatory indices, the HALP score decreased significantly (p<0.001), whereas SII, SIRI, and AISI increased (p≤0.035). PLR and LMR increased significantly (p<0.001), while NLR showed no significant change (p=0.557). These findings indicate progressive inflammatory activation during the first postnatal month in infants born at earlier gestational ages. 30–32-week group In the 30–32-week group, hemoglobin and platelet counts increased significantly at month 1 (p<0.001 and p=0.002, respectively). Albumin and HALP score also changed significantly (p=0.046 and p=0.006). In contrast, lymphocyte, neutrophil, leukocyte counts and most inflammatory indices (SII, SIRI, AISI, PLR, NLR, LMR) showed no significant temporal variation. This comparatively stable inflammatory profile suggests a more limited postnatal inflammatory response in infants born at higher gestational ages. Between-group comparisons by gestational age Early postnatal period During the early postnatal period, infants born at ≤30 weeks had lower albumin levels (p<0.001) as well as lower platelet, neutrophil, and leukocyte counts and composite inflammatory indices (SII, SIRI, AISI; p≤0.030) compared with the 30–32-week group. HALP, PLR, NLR, and LMR did not differ significantly between groups. These findings are consistent with maturational differences in hematologic parameters during early neonatal life. Postnatal month 1 At postnatal month 1, the ≤30-week group demonstrated higher platelet counts, SII, AISI, and HALP scores (p≤0.048), whereas albumin levels remained higher in the 30–32-week group (p=0.019; month-1 data: n=68 for ≤30 weeks; n=18 for 30–32 weeks). Other indices showed borderline or nonsignificant differences. The emergence of higher composite inflammatory indices at month 1 among the ≤30-week group supports the presence of a gestational age–dependent inflammatory window. Comparisons according to ROP development in infants ≤30 weeks Early postnatal period During the early postnatal period, no significant differences in hematologic parameters or inflammatory indices were observed between infants who later developed ROP and those who did not (all p>0.05). Early inflammatory status did not discriminate subsequent disease development. Postnatal month 1 At postnatal month 1, infants with ROP exhibited lower albumin levels (p=0.010) and higher neutrophil and monocyte counts (p=0.001 and p<0.001). Likewise, SII, SIRI, AISI, and NLR values were markedly elevated (all p≤0.001), and LMR was also significantly higher (p<0.001). The HALP score showed a borderline decrease (p=0.051). These findings indicate that systemic inflammatory activation becomes more clinically relevant during the first postnatal month in infants who develop ROP. Detailed within-group temporal comparisons according to ROP status are presented in Table 2. Treatment-requiring ROP Infants with treatment-requiring ROP demonstrated lower albumin and HALP scores during the early postnatal period (p=0.012 and p=0.008) and higher SII, AISI, PLR, and NLR values (p≤0.028). These early differences suggest that more severe disease may be preceded by subtle systemic inflammatory imbalance. At postnatal month 1, SIRI and AISI remained significantly elevated in the treated group (p=0.048 and p=0.035). Although other parameters did not reach statistical significance, inflammatory indices generally trended higher. Overall, severe ROP appeared to be associated with both early and sustained systemic inflammatory activation, although the limited number of treated cases warrants cautious interpretation. ROC analyses The discriminative performance of biomarkers at different time points is shown in Table 3. Overall, early postnatal measurements demonstrated low AUC values and were generally not statistically significant. Thus, early inflammatory indices did not provide clinically meaningful discrimination. In contrast, month 1 measurements of SII, SIRI, AISI, NLR, and LMR showed significant discrimination for ROP development (AUC ≈ 0.73–0.82; all p<0.001). HALP showed borderline or nonsignificant discrimination, and PLR showed limited discriminative performance. These findings support the greater clinical relevance of inflammatory assessment during the first postnatal month. Combined models yielded AUC values similar to month 1 measurements and did not provide meaningful incremental improvement. Accordingly, the addition of early measurements did not enhance predictive performance beyond month-1 values alone. Pairwise AUC comparisons using the DeLong test (Table 4) confirmed that month 1 measurements of SIRI, AISI, NLR, and LMR provided significantly higher discriminative performance than early postnatal measurements (all p<0.05). No significant temporal differences were observed for HALP, SII, or PLR. Collectively, these findings indicate that the prognostic value of systemic inflammatory indices for ROP becomes most apparent during the first postnatal month, particularly among infants born at ≤30 weeks’ gestation. Discussion The pathogenesis of retinopathy of prematurity (ROP) is a multifactorial process characterized by disrupted retinal vascular development in premature infants, fluctuating oxygen exposure, and the interaction of prenatal and postnatal inflammatory pathways. Risk factors related to prenatal and postnatal inflammation have been shown to be associated with ROP development [23], and exposure of premature neonates to inflammatory mediators has been suggested to increase ROP risk [4]. Increasingly, ROP is recognized as a disorder in which systemic inflammatory activation may amplify vascular vulnerability in the immature retina. In the present study, systemic inflammation was evaluated using complete blood count (CBC)–derived indices measured in the early postnatal period (postnatal days 2–4) and at postnatal month 1 (postnatal days 28–32), including NLR, PLR, and LMR, together with more integrative inflammatory markers such as SII, SIRI, and AISI, as well as the immune-nutritional indicator HALP. Our findings suggest that an inflammatory response that becomes more pronounced at postnatal month 1—particularly in infants born before 30 weeks’ gestation—may be associated with ROP development. The absence of significant differences in NLR, PLR, and SII during the early postnatal period is consistent with physiological hematologic variability and rapid modulation by clinical or iatrogenic factors. Early neonatal hematologic instability may therefore obscure disease-specific inflammatory signals. In contrast, month-1 measurements may better reflect the period during which ROP becomes clinically manifest and systemic inflammatory burden stabilizes. Consistently, ROC analyses demonstrated limited discriminative ability in the early postnatal period but significantly higher AUC values at month 1 (≈ 0.73–0.82), supporting the temporal relevance of inflammatory activity. These findings highlight the importance of timing when interpreting systemic inflammatory markers in very preterm infants. CBC is a low-cost, widely accessible, and practical tool for assessing systemic inflammation in premature populations. Ratios such as NLR, PLR, and LMR have been extensively investigated as inflammatory biomarkers in cardiovascular disease, malignancy, and rheumatologic disorders [24-26], and have also been reported as indicators of inflammatory response in retinal and other ophthalmic diseases [17,27]. Their routine availability in neonatal intensive care units enhances their potential translational applicability. Within the ROP literature, these ratios are generally evaluated at single time points. Hu et al. [17] and Kurtul et al. [16] reported higher NLR and/or LMR values in infants who developed ROP, whereas PLR showed inconsistent associations. Akdoğan et al. demonstrated elevated NLR and reduced PLR at postnatal month 1 in ROP [28]. Oruz et al. reported that NLR and SII early postnatally and NLR, SII, and LMR at month 1 were associated with ROP, and further identified month-1 PLR and SII as independent predictors of laser treatment requirement [29]. In line with these studies, our results indicate that month-1 NLR, LMR, and composite inflammatory indices possess stronger predictive relevance, whereas PLR and HALP show limited discriminative performance. Our gestational age–stratified approach may partly explain differences from earlier reports that did not account for maturational hematologic variability. Gestational age–stratified comparisons revealed no significant early postnatal differences in HALP, PLR, NLR, or LMR; however, infants born at ≤30 weeks exhibited lower albumin levels as well as reduced platelet, neutrophil, leukocyte, and composite inflammatory index values, suggesting a relatively suppressed inflammatory profile in early life. This early pattern likely reflects developmental immaturity rather than absence of inflammatory activation. By contrast, higher platelet counts, SII, AISI, and HALP scores at month 1 in this group indicate the emergence of a clinically meaningful postnatal inflammatory window. Because most previous studies did not stratify by gestational age, maturational hematologic differences may have confounded earlier findings. Thus, gestational age stratification represents an important methodological strength of the present study. Platelets contribute to angiogenesis through the transport and release of VEGF, PDGF, and IGF-1 [14,30]. Thrombocytopenia may impair physiologic retinal vascularization and promote uncontrolled neovascularization. Jensen et al. associated low platelet counts with severe ROP [30] , while Tao et al. highlighted the role of platelets within the angiogenesis–inflammation axis [31,32]. Nevertheless, physiological postnatal variability in platelet counts necessitates interpretation within the context of gestational and postnatal age. Composite platelet-containing indices may therefore capture both angiogenic and inflammatory components of disease progression. Hematologic parameters in premature infants vary substantially with both gestational and postnatal maturation [33,34]. Analyses that combine different gestational age groups may therefore reflect maturational physiology rather than disease-specific mechanisms. Stratification by gestational age in the present study was intended to reduce this potential bias. This design strengthens internal validity by minimizing confounding related to developmental heterogeneity. HALP integrates hemoglobin, albumin, lymphocyte, and platelet levels and reflects immune-nutritional status [35]. Reduced HALP has been associated with poor prognosis in several diseases [36,37] and has been identified as an independent risk factor for diabetic retinopathy [38]. The tendency toward lower HALP and albumin levels in infants who developed ROP in our cohort suggests a potential contribution of the nutrition–inflammation axis to ROP pathobiology. However, the lack of significant ROC discrimination for HALP and PLR indicates that these markers may function better as contextual or supportive indicators rather than standalone predictors. HALP may reflect systemic vulnerability rather than a direct mechanistic driver of retinal angiogenic dysregulation. Composite inflammatory indices such as SII and SIRI more comprehensively reflect the balance between inflammation and immune response and have demonstrated prognostic value across multiple clinical settings [ 27,39-41]. AISI has likewise been associated with obstetric and neonatal outcomes [42-45] . In our study, elevated SII, SIRI, and AISI at postnatal month 1 were strongly associated with ROP, supporting a central role for postnatal systemic inflammation. DeLong comparisons further confirmed the superior discriminative performance of month-1 measurements, emphasizing the prognostic importance of timing. Temporal inflammatory dynamics constituted a key observation. In infants born before 30 weeks, decreasing HALP alongside increasing SII, SIRI, and AISI from early postnatal life to month 1 suggests progressive inflammatory activation. Among infants requiring treatment, early reductions in albumin and HALP combined with persistently elevated inflammatory indices support an association between sustained systemic inflammation and disease severity. Moreover, the exclusive temporal increase of inflammatory indices in the ROP group highlights the potential relevance of dynamic inflammatory trajectories, rather than absolute values alone, in disease pathobiology. Collectively, these findings reinforce the concept that ROP is not solely an oxygen-driven disorder but rather a multidimensional disease closely linked to systemic inflammation and immune dysregulation [4,23] . From a clinical perspective, CBC-derived composite indices are attractive because of their accessibility and low cost. In particular, month-1 elevations in SII, SIRI, and AISI may assist in identifying high-risk premature infants who could benefit from closer surveillance or earlier intervention. Nonetheless, these biomarkers should be interpreted within a comprehensive clinical framework that includes gestational age, birth weight, oxygen exposure, and neonatal comorbidities. Our findings support the clinical relevance of postnatal inflammatory assessment but do not suggest replacement of established screening criteria. The retrospective, single-center design, variability in sampling timing, and potential confounding from infection, steroid exposure, respiratory support, and other neonatal comorbidities represent the principal limitations. Missing month-1 data, particularly in the 30–32-week group, may introduce selection bias and limit generalizability of month-1 findings. Multiple statistical comparisons necessitate cautious interpretation. The relatively small number of treatment-requiring cases limits the precision of severity-related analyses. Prospective, multicenter studies with larger cohorts and comprehensive multivariable modeling are required to validate these findings. In conclusion, systemic inflammatory activation emerging during the first postnatal month is closely associated with both the development and severity of retinopathy of prematurity, particularly among infants born before 30 weeks of gestation. Composite complete blood count–derived inflammatory indices—especially SII, SIRI, and AISI, together with NLR and LMR—demonstrate meaningful time-dependent discriminative performance, whereas HALP and PLR appear to function primarily as supportive rather than standalone markers. Given their low cost, universal availability, and ease of calculation, CBC-derived inflammatory indices may serve as pragmatic adjunct biomarkers for early risk stratification and surveillance in premature infants, particularly when assessed at postnatal month 1. Future prospective multicenter validation studies are required before incorporation into routine clinical decision-making. Abbreviations AISI – Aggregate Index of Systemic Inflammation AUC – Area Under the Curve CBC – Complete Blood Count HALP – Hemoglobin–Albumin–Lymphocyte–Platelet Score LMR – Lymphocyte-to-Monocyte Ratio NLR – Neutrophil-to-Lymphocyte Ratio PLR – Platelet-to-Lymphocyte Ratio ROC – Receiver Operating Characteristic ROP – Retinopathy of Prematurity SII – Systemic Immune-Inflammation Index SIRI – Systemic Inflammation Response Index Declarations Data availability The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request. Acknowledgments The authors thank the staff of the Departments of Ophthalmology and Neonatology at Malatya Turgut Ozal University for their technical assistance and support. Funding This study was supported by the Scientific Research Projects Coordination Unit of Malatya Turgut Özal University Clinical trial number : Not applicable. Authors and Affiliations Department of Ophthalmology, Malatya Turgut Ozal University, Malatya, Turkey Zarife Ekici Gök Department of Neonatology, Malatya Turgut Ozal University, Malatya, Turkey Nuriye Aslı Melekoğlu Department of Biostatistics and Medical Informatics, Inonu University , Malatya,Türkiye Şeyma Yaşar Contributions Concept and design: Z.E.G., N.A.M. Data acquisition: Z.E.G. Data analysis and interpretation: Ş.Y. Manuscript drafting: Z.E.G. Supervision: Z.E.G., N.A.M. Final approval of the manuscript: All authors. Corresponding author Correspondence to Zarife Ekici Gök Ethics declarations Ethical approval was obtained from the Health Sciences Scientific Research Ethics Committee of Malatya Turgut Ozal University (Decision No: 18/2026). All procedures were conducted in accordance with the principles of the Declaration of Helsinki. Competing interests The authors declare no competing interests. References Gergely K, Gerinec A. Retinopathy of prematurity: epidemics, incidence, prevalence, blindness. Bratisl Lek Listy. 2010; 111:514-517. Hellström A, Smith LEH, Dammann O. Retinopathy of prematurity. Lancet. 2013; 382:1445-1457. Cavallaro G, Filippi L, Bagnoli P, et al. The pathophysiology of retinopathy of prematurity: an update of previous and recent knowledge. Acta Ophthalmol. 2014; 92:2-20. Chen J, Stahl A, Hellström A, Smith LEH. Current update on retinopathy of prematurity: screening and treatment. Curr Opin Pediatr. 2011; 23:173-178. Tremblay S, Miloudi K, Chaychi S, et al. 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Bowen RC, Little NAB, Harmer JR, et al. Neutrophil-to-lymphocyte ratio as prognostic indicator in gastrointestinal cancers. Oncotarget. 2017; 8:32171-32189. Bonaventura A, Liberale L, Carbone F, et al. Baseline neutrophil-to-lymphocyte ratio and long-term type 2 diabetes remission. Acta Diabetol. 2019; 56:741-748. Ma M, Yu N, Wu B. High systemic immune-inflammation index predicts poor prognosis in malignant pleural mesothelioma. Cancer Manag Res. 2019; 11:3973-3979. Akdogan M, Ustundag Y, Cevik SG, et al. Systemic immune-inflammation index in retinopathy of prematurity prognosis. Indian J Ophthalmol. 2021; 69:2182-2187. Oruz O, Dervişoğulları MS, Öktem ME, İncekaş C. Predictive role of systemic immune-inflammation index and neutrophil/lymphocyte ratio in infants with retinopathy of prematurity. Graefes Arch Clin Exp Ophthalmol. 2024. Jensen AK, Ying GS, Huang J, et al. Thrombocytopenia and retinopathy of prematurity. J AAPOS. 2011; 15: e3-e4. Tao Y, Dong Y, Lu CW, et al. Mean platelet volume and retinopathy of prematurity. Graefes Arch Clin Exp Ophthalmol. 2015; 253:1791-1794. Yu H, Yuan L, Zou Y, et al. Serum cytokine concentrations in infants with retinopathy of prematurity. APMIS. 2014; 122:818-823. Schmutz N, Henry E, Jopling J, Christensen RD. Neonatal neutrophil reference ranges revisited. J Perinatol. 2008; 28:275-281. Manroe BL, Weinberg AG, Rosenfeld CR, Browne R. Neonatal blood count in health and disease. J Pediatr. 1979; 95:89-98. Xu SS, Li S, Xu HX, et al. Hemoglobin-albumin-lymphocyte-platelet score in pancreatic cancer survival. World J Gastroenterol. 2020; 26:828-838. Solmaz S, Uzun O, Sevindik OG, et al. HALP score in multiple myeloma prognosis. Int J Lab Hematol. 2023; 45:13-19. Wang J, Jiang P, Huang Y, et al. HALP cut-off values in endometrial cancer. Am J Clin Oncol. 2023; 46:107-113. Ding R, Zeng Y, Wei Z, et al. HALP score and diabetic retinopathy risk. Front Endocrinol (Lausanne). 2024; 15:1356929. Dziedzic EA, Gąsior JS, Tuzimek A, et al. Systemic inflammatory indices in coronary artery disease. Int J Mol Sci. 2022; 23:9553. Erdal H, Kilic A, Akbulut Yagci B, Yasar E. Pan-immune inflammation indices in pseudoexfoliation. J Clin Pract Res. 2024. Wang S, Pan X, Jia B, Chen S. Systemic immune-inflammation index and diabetic retinopathy. Diabetes Metab Syndr Obes. 2023; 16:3827-3836. Tokalioglu EO, Tanacan A, Agaoglu MO, et al. Aggregate systemic inflammation index in premature rupture of membranes. Int J Gynecol Obstet. 2025; 168:640-649. Akin MS, Akyol O, Okman E, et al. Systemic inflammatory indices and lung maturation in preterm infants. J Pediatr Intensive Care. 2024. Hrubaru I, Motoc A, Moise ML, et al. Maternal inflammatory biomarkers and preterm birth risk. J Clin Med. 2022; 11:6982. Beser DM, Ozgurluk I, Oluklu D, et al. NLR, dNLR, SII, SIRI, and APRI in pregnancy outcomes. Ann Med Res. 2023; 30:1001-1007. Tables Table 1. Baseline demographic and clinical characteristics by gestational age group Characteristic ≤30 weeks (n=68) 30–32 weeks (n=71) Total (n=139) Sex, n (%) Female 36 (52.9) 32 (47.1) 68 (48.9) Male 32 (47.1) 39 (54.9) 71 (51.1) Gestational age (weeks) Mean ± SD 29 ± 1 32 ± 1 — Median (IQR) 29 (28–30) 32 (31–32) — Birth weight (g) Mean ± SD 1189 ± 271 1643 ± 233 — Median (IQR) 1223 (1000–1343) 1675 (1500–1800) — ROP, n (%) 29 (42.6) 1 (1.4) 30 (21.6) Abbreviations: IQR, interquartile range; ROP, retinopathy of prematurity; SD, standard deviation. Table 2. Within-group changes from early postnatal period to postnatal month 1 in infants ≤30 weeks, stratified by ROP status Variable Time point ROP absent Mean ± SD ROP absent Median (IQR) P* ROP present Mean ± SD ROP present Median (IQR) P* Hemoglobin Early postnatal 17.01 ± 2.62 17.1 (4.4) <0.001 16.64 ± 2.39 16.5 (2.6) <0.001 Month 1 10.57 ± 1.98 10.7 (3.0) 9.80 ± 1.81 10.0 (1.7) Albumin Early postnatal 2.46 ± 0.31 2.5 (0.5) 0.001 2.34 ± 0.31 2.3 (0.5) 0.044 Month 1 2.75 ± 0.30 2.8 (0.3) 2.52 ± 0.39 2.5 (0.5) Lymphocyte Early postnatal 5.62 ± 2.11 5.46 (2.84) 0.061 5.53 ± 3.07 5.18 (3.99) 0.918 Month 1 6.50 ± 2.15 6.04 (2.82) 5.63 ± 2.34 5.52 (2.03) Platelet Early postnatal 231.13 ± 79.94 221 (128) <0.001 201.14 ± 69.72 208 (112) <0.001 Month 1 418.95 ± 114.61 436 (187) 406.38 ± 149.26 376 (224) Neutrophil Early postnatal 3.88 ± 3.25 2.85 (3.52) 0.236 2.69 ± 2.21 2.10 (1.73) 0.001 Month 1 2.96 ± 1.79 2.36 (2.50) 6.04 ± 4.60 4.55 (4.56) Leukocyte Early postnatal 10.70 ± 4.46 9.76 (4.57) 0.074 9.35 ± 4.07 8.32 (3.31) 0.004 Month 1 11.64 ± 3.27 11.27 (5.20) 14.30 ± 6.25 12.82 (6.70) Monocyte Early postnatal 0.99 ± 0.77 0.76 (0.58) 0.014 0.88 ± 0.68 0.78 (0.63) <0.001 Month 1 1.31 ± 0.55 1.13 (0.74) 1.99 ± 0.95 1.86 (0.76) HALP score Early postnatal 1.18 ± 0.79 1.02 (0.65) <0.001 1.19 ± 0.74 1.03 (1.00) <0.001 Month 1 0.48 ± 0.24 0.42 (0.24) 0.39 ± 0.24 0.29 (0.28) SII Early postnatal 187.96 ± 188.72 108.00 (230.38) 0.460 153.23 ± 210.45 79.55 (115.33) <0.001 Month 1 225.27 ± 222.17 149.25 (201.38) 463.22 ± 390.53 306.59 (325.64) SIRI Early postnatal 1.11 ± 1.89 0.46 (0.64) 0.867 0.93 ± 1.61 0.29 (0.58) 0.003 Month 1 0.74 ± 0.76 0.50 (0.75) 2.38 ± 2.19 1.55 (2.30) AISI Early postnatal 248.73 ± 416.34 90.43 (167.80) 0.289 153.50 ± 245.27 53.00 (171.32) <0.001 Month 1 310.39 ± 339.92 159.60 (326.95) 974.60 ± 1016.05 641.09 (716.86) PLR Early postnatal 46.41 ± 23.46 39.89 (34.79) <0.001 50.37 ± 40.65 40.67 (29.15) 0.006 Month 1 72.26 ± 39.70 68.01 (27.39) 82.12 ± 42.22 65.15 (49.03) NLR Early postnatal 0.81 ± 0.80 0.59 (0.80) 0.103 0.90 ± 1.34 0.44 (0.62) 0.030 Month 1 0.54 ± 0.47 0.38 (0.44) 1.12 ± 0.74 0.93 (0.99) LMR Early postnatal 0.21 ± 0.17 0.14 (0.16) 0.252 0.23 ± 0.24 0.17 (0.19) 0.001 Month 1 0.22 ± 0.10 0.23 (0.14) 0.39 ± 0.22 0.33 (0.17) *P values reflect within-group comparisons between early postnatal period and month 1 (paired tests as appropriate). Abbreviations: AISI, aggregate index of systemic inflammation; HALP, hemoglobin–albumin–lymphocyte–platelet score; IQR, interquartile range; LMR, lymphocyte-to-monocyte ratio; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; ROP, retinopathy of prematurity; SD, standard deviation; SII, systemic immune-inflammation index; SIRI, systemic inflammatory response index. Table 3. Discriminative performance of biomarkers for predicting ROP (ROC analysis) Model Best cutoff† AUC (95% CI) P value Sensitivity Specificity PPV NPV Accuracy Youden’s J HALP (early postnatal) 1.442 0.52 (0.37–0.67) 0.774 0.448 0.821 0.650 0.667 0.662 0.269 HALP (month 1) 0.297 0.64 (0.50–0.78) 0.055 0.517 0.846 0.714 0.702 0.706 0.363 HALP (combined) 0.481 0.63 (0.49–0.77) 0.072 0.517 0.846 0.714 0.702 0.706 0.363 SII (early postnatal) 155.021 0.58 (0.44–0.72) 0.272 0.759 0.436 0.500 0.708 0.574 0.195 SII (month 1) 216.976 0.73 (0.61–0.85) <0.001 0.759 0.692 0.647 0.794 0.721 0.451 SII (combined) 0.358 0.74 (0.61–0.86) <0.001 0.759 0.692 0.647 0.794 0.721 0.451 SIRI (early postnatal) 0.166 0.56 (0.42–0.70) 0.419 0.414 0.769 0.571 0.638 0.618 0.183 SIRI (month 1) 0.977 0.82 (0.71–0.92) <0.001 0.759 0.821 0.759 0.821 0.794 0.579 SIRI (combined) 0.392 0.82 (0.72–0.92) <0.001 0.690 0.846 0.769 0.786 0.779 0.536 AISI (early postnatal) 63.658 0.58 (0.44–0.72) 0.281 0.586 0.590 0.515 0.657 0.588 0.176 AISI (month 1) 249.619 0.78 (0.67–0.89) <0.001 0.897 0.641 0.650 0.893 0.750 0.538 AISI (combined) 0.297 0.78 (0.67–0.89) <0.001 0.862 0.590 0.610 0.852 0.706 0.452 PLR (early postnatal) 119.676 0.46 (0.32–0.61) 0.599 0.103 1.000 1.000 0.600 0.618 0.103 PLR (month 1) 41.202 0.43 (0.28–0.58) 0.335 0.207 0.897 0.600 0.603 0.603 0.104 PLR (combined) 0.462 0.59 (0.45–0.74) 0.220 0.379 0.897 0.733 0.660 0.676 0.277 NLR (early postnatal) 0.586 0.57 (0.43–0.71) 0.343 0.690 0.513 0.513 0.690 0.588 0.202 NLR (month 1) 0.579 0.78 (0.66–0.89) <0.001 0.759 0.744 0.688 0.806 0.750 0.502 NLR (combined) 0.355 0.78 (0.66–0.89) <0.001 0.793 0.744 0.697 0.829 0.765 0.537 LMR (early postnatal) 0.171 0.50 (0.36–0.65) 0.967 0.517 0.641 0.517 0.641 0.588 0.158 LMR (month 1) 0.239 0.80 (0.69–0.91) <0.001 0.862 0.641 0.641 0.862 0.735 0.503 LMR (combined) 0.377 0.80 (0.70–0.91) <0.001 0.793 0.744 0.697 0.829 0.765 0.537 †For “combined” models, best cutoff refers to predicted probability from logistic regression including early postnatal and month-1 values. Abbreviations: AISI, aggregate index of systemic inflammation; AUC, area under the curve; CI, confidence interval; HALP, hemoglobin–albumin–lymphocyte–platelet score; LMR, lymphocyte-to-monocyte ratio; NLR, neutrophil-to-lymphocyte ratio; NPV, negative predictive value; PLR, platelet-to-lymphocyte ratio; PPV, positive predictive value; ROP, retinopathy of prematurity; SII, systemic immune-inflammation index; SIRI, systemic inflammation response index. Table 4. Pairwise comparison of AUCs between early and month-1 measurements (DeLong test) Parameter Comparison AUC1 AUC2 AUC difference P value HALP Early postnatal vs month 1 0.522 0.639 0.118 0.244 HALP Combined vs early postnatal 0.522 0.631 0.110 0.269 HALP Combined vs month 1 0.639 0.631 -0.008 0.187 SII Early postnatal vs month 1 0.578 0.732 0.154 0.089 SII Combined vs early postnatal 0.578 0.737 0.158 0.051 SII Combined vs month 1 0.732 0.737 0.004 0.840 SIRI Early postnatal vs month 1 0.559 0.818 0.259 0.006 SIRI Combined vs early postnatal 0.559 0.820 0.261 0.002 SIRI Combined vs month 1 0.818 0.820 0.002 0.918 AISI Early postnatal vs month 1 0.577 0.781 0.203 0.020 AISI Combined vs early postnatal 0.577 0.781 0.203 0.006 AISI Combined vs month 1 0.781 0.781 0.000 1.000 PLR Early postnatal vs month 1 0.462 0.427 -0.034 0.740 PLR Combined vs early postnatal 0.462 0.591 0.129 0.105 PLR Combined vs month 1 0.427 0.591 0.164 0.250 NLR Early postnatal vs month 1 0.569 0.777 0.209 0.030 NLR Combined vs early postnatal 0.569 0.776 0.208 0.042 NLR Combined vs month 1 0.777 0.776 -0.001 0.936 LMR Early postnatal vs month 1 0.503 0.799 0.296 <0.001 LMR Combined vs early postnatal 0.503 0.805 0.302 <0.001 LMR Combined vs month 1 0.799 0.805 0.005 0.542 Footnote: AUCs were compared using DeLong’s test for correlated ROC curves Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9041551","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":618898628,"identity":"17997c87-cc43-4153-b958-47ef8539d810","order_by":0,"name":"Zarife Ekici Gök","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIie3PMQuCQBTA8ScHTkXrhZCfIDACIbBP0mLLNbk3SF0EuhTNLX2MaDw5cDJcG5Og2caW6ilNgbo23B8UD+537wRQqf40MccXJfjx4MVaW4lGknxJtOdAkfBGAiXBh7RLgofU7TbDcybwZr1uSDI5PjmLfihxiu9Mqoi2mVkCbzY0iG5JL2HUTqZIYubxCkKAgXwEMD2QFkgvkNQWSDQuK4neuYOIXrAsyaggaVZPWpQh4eAaBdEKcmmYQilOETEM9mvdirYB6x4vOMWt+Rdzx0gufDBpKm/5M3A6djrLrrnvVJJv75+1W79dpVKpVA19AM3FYeanuKJEAAAAAElFTkSuQmCC","orcid":"","institution":"Malatya Turgut Özal Üniversitesi","correspondingAuthor":true,"prefix":"","firstName":"Zarife","middleName":"Ekici","lastName":"Gök","suffix":""},{"id":618898639,"identity":"fac5fd7f-f936-4c12-9ce2-04fe9e1dfce6","order_by":1,"name":"Nuriye Aslı Melekoğlu","email":"","orcid":"","institution":"Malatya Turgut Özal Üniversitesi","correspondingAuthor":false,"prefix":"","firstName":"Nuriye","middleName":"Aslı","lastName":"Melekoğlu","suffix":""},{"id":618898640,"identity":"ee60f652-1a49-4e7d-9b06-9d7627963d3a","order_by":2,"name":"Şeyma Yaşar","email":"","orcid":"","institution":"Inonu University","correspondingAuthor":false,"prefix":"","firstName":"Şeyma","middleName":"","lastName":"Yaşar","suffix":""}],"badges":[],"createdAt":"2026-03-05 14:55:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9041551/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9041551/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":106993928,"identity":"d1bf890a-289c-4dea-9c2d-67a92d79e974","added_by":"auto","created_at":"2026-04-15 15:00:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1522434,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9041551/v1/b7e9e227-4b1b-45e0-9b53-6d8c68041f67.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Gestational Age–Dependent Association of HALP Score and Systemic Inflammatory Indices with Retinopathy of Prematurity","fulltext":[{"header":"Introduction","content":"\u003cp\u003eRetinopathy of prematurity (ROP) is one of the leading causes of preventable childhood blindness in both developed and developing countries, and its incidence continues to increase in parallel with improving survival of premature infants [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Advances in neonatal intensive care have shifted the epidemiologic landscape of ROP, resulting in a growing population of extremely preterm infants at risk for severe disease. Maternal inflammatory responses and neonatal systemic inflammation have been shown to contribute to ROP development [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Moreover, systemic inflammation may adversely affect retinal vascularization and increase the risk of ROP independently of gestational age and birth weight [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This observation suggests that inflammatory pathways may represent modifiable contributors to disease progression beyond traditional maturity-based risk factors.\u003c/p\u003e \u003cp\u003eInflammation influences ROP both indirectly, through impairment of retinal perfusion, and directly, through modulation of retinal angiogenesis. Experimental animal studies have demonstrated that neonatal systemic inflammation disrupts retinal vascular development and induces pathological features consistent with ROP [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Pro-inflammatory cytokines and immune-mediated signaling cascades have been implicated in dysregulated vascular endothelial growth factor (VEGF) expression and abnormal angiogenic responses.\u003c/p\u003e \u003cp\u003eFluctuations in oxygen saturation secondary to impaired angiogenesis lead to retinal ischemia [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e] and underlie the two-phase pathogenesis of ROP: hyperoxia-induced vascular arrest followed by hypoxia-driven cytokine-mediated pathological neovascularization [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Elevated levels of proinflammatory cytokines in the vitreous and serum of infants with ROP further support the involvement of both local and systemic inflammation in disease progression [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Collectively, these findings reinforce the concept that ROP represents not solely an oxygen-mediated disorder but a condition in which systemic inflammatory activation may amplify vascular vulnerability.\u003c/p\u003e \u003cp\u003eAlthough ROP is a multifactorial disease, low birth weight and gestational age remain the strongest risk factors. While screening criteria are primarily based on these two parameters [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e], numerous additional risks related to maternal characteristics, prenatal and postnatal exposures, and prematurity-associated comorbidities have been described. Despite this complexity, risk stratification in clinical practice continues to rely predominantly on gestational age and birth weight, underscoring the need for accessible adjunct biomarkers that may refine early risk assessment.\u003c/p\u003e \u003cp\u003eHematologic parameters assessed during the neonatal period have been linked to immune modulation and oxidative stress, yet findings remain inconsistent [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Complete blood count\u0026ndash;derived inflammatory markers\u0026mdash;including the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR)\u0026mdash;have been investigated in ROP with variable results [\u003cspan additionalcitationids=\"CR16\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These indices have also been widely studied as inflammatory biomarkers in systemic diseases such as malignancies and rheumatologic disorders [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], as well as in ophthalmic conditions including age-related macular degeneration, glaucoma, and diabetic retinopathy [\u003cspan additionalcitationids=\"CR21\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. More recently, composite indices integrating multiple hematologic components\u0026mdash;such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI), and the hemoglobin\u0026ndash;albumin\u0026ndash;lymphocyte\u0026ndash;platelet (HALP) score\u0026mdash;have been proposed as more comprehensive reflections of the balance between inflammatory activation and immune-nutritional status.\u003c/p\u003e \u003cp\u003eThe limited and inconsistent evidence regarding CBC-derived inflammatory indices in ROP highlights the need for more robust and temporally structured data. In particular, few studies have examined the evolution of inflammatory indices over time or evaluated their performance across different gestational age strata, despite the well-established maturational variability of neonatal hematologic parameters.\u003c/p\u003e \u003cp\u003eTherefore, the present study aimed to compare the HALP score and composite systemic inflammatory indices in preterm infants born at \u0026le;\u0026thinsp;30 weeks and 30\u0026ndash;32 weeks of gestation and to evaluate their associations with ROP development and treatment requirement. We further sought to determine whether inflammatory indices measured during distinct postnatal time windows demonstrate differential clinical relevance, thereby contributing to more refined risk stratification in very preterm infants.\u003c/p\u003e"},{"header":"Material \u0026 Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design and ethical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis retrospective observational cohort study included secondary case\u0026ndash;control comparisons between infants with and without retinopathy of prematurity (ROP). The study was designed to evaluate temporal changes in systemic inflammatory markers and their associations with ROP development and severity. Medical records of 139 preterm infants followed in the neonatal intensive care unit between May 2022 and December 2025 were reviewed. Clinical, laboratory, and ophthalmologic data were extracted from the institutional electronic medical record system.\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Health Sciences Scientific Research Ethics Committee of XXX University (Decision No: 18/2026) and conducted in accordance with the Declaration of Helsinki. Given the retrospective nature of the study and the use of de-identified clinical data, the requirement for written informed consent was waived by the ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion and exclusion criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePreterm infants with gestational age \u0026le;32 weeks, regular ROP screening, and available early postnatal complete blood count (CBC) data obtained within postnatal days 2\u0026ndash;4 were included. When available, postnatal month-1 CBC data were also recorded.\u003c/p\u003e\n\u003cp\u003eInfants who received blood product transfusion or systemic steroid therapy before the relevant blood sampling time point were excluded, as these interventions may significantly alter hematologic and inflammatory parameters. Infants with culture-proven sepsis, necrotizing enterocolitis, or severe hematologic disease were also excluded in order to minimize confounding effects of acute systemic inflammatory conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTime points and gestational age stratification\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEarly postnatal blood samples were obtained within postnatal days 2\u0026ndash;4, and month-1 samples between postnatal days 28\u0026ndash;32.\u003c/p\u003e\n\u003cp\u003eInfants were stratified by gestational age into two predefined groups:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eGroup 1: \u0026le;30 weeks\u003c/li\u003e\n \u003cli\u003eGroup 2: 30\u0026ndash;32 weeks\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eThis stratification was performed a priori to account for maturational differences in hematologic parameters and baseline ROP risk across gestational age categories.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOphthalmologic examination and definition of treatment-requiring ROP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eROP screening was initiated at postnatal week 4 according to institutional protocol and international screening recommendations. Pupillary dilation was achieved using 0.5% tropicamide (Tropamide, Bilim İla\u0026ccedil;, T\u0026uuml;rkiye) and 2.5% phenylephrine (Mydfrin, Alcon, USA), administered three times at 10-minute intervals, followed by topical anesthesia with 0.5% proparacaine (Alcaine, Alcon, USA) immediately before examination.\u003c/p\u003e\n\u003cp\u003eAll examinations were performed by the same experienced ophthalmologist using indirect ophthalmoscopy (Heine Omega 500) with a 28-diopter lens, with scleral depression when necessary. ROP staging, zone classification, and presence of plus disease were determined according to the International Classification of Retinopathy of Prematurity (ICROP). Infants were followed at 1\u0026ndash;3-week intervals until retinal vascularization reached the ora serrata.\u003c/p\u003e\n\u003cp\u003eTreatment-requiring ROP was defined based on Early Treatment for Retinopathy of Prematurity (ETROP) criteria as:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eAny stage with plus disease in Zone I\u003c/li\u003e\n \u003cli\u003eStage 3 without plus disease in Zone I\u003c/li\u003e\n \u003cli\u003eStage 2\u0026ndash;3 with plus disease in Zone II\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eEligible infants received intravitreal anti-VEGF therapy and/or laser photocoagulation when clinically indicated. Treatment decisions were made according to standardized institutional protocols.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMissing data handling\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEarly postnatal CBC data were available for all infants. Month-1 CBC data were available for all infants in Group 1 and for 18 infants in Group 2. Missing data were not imputed; therefore, month-1 analyses were restricted to infants with complete data and reported as supplementary analyses. Given the incomplete availability of month-1 data in the 30\u0026ndash;32-week group, these analyses were interpreted cautiously. This was considered a potential source of selection bias.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHematologic measurements and inflammatory indices\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeripheral venous blood samples were collected into EDTA tubes as part of routine clinical care and analyzed using an automated hematology analyzer according to manufacturer specifications. Hemoglobin concentration and leukocyte subtypes were obtained from CBC analysis. Serum albumin levels were obtained from routine biochemical analysis performed at the same sampling time points.\u003c/p\u003e\n\u003cp\u003ePlatelet, neutrophil, lymphocyte, and monocyte counts were recorded, and the following indices were calculated:\u003c/p\u003e\n\u003cul type=\"disc\"\u003e\n \u003cli\u003eNLR: neutrophil / lymphocyte\u003c/li\u003e\n \u003cli\u003ePLR: platelet / lymphocyte\u003c/li\u003e\n \u003cli\u003eLMR: lymphocyte / monocyte\u003c/li\u003e\n \u003cli\u003eSII: (neutrophil \u0026times; platelet) / lymphocyte\u003c/li\u003e\n \u003cli\u003eSIRI: (neutrophil \u0026times; monocyte) / lymphocyte\u003c/li\u003e\n \u003cli\u003eHALP: (hemoglobin \u0026times; albumin \u0026times; lymphocyte) / platelet\u003c/li\u003e\n \u003cli\u003eAISI: (neutrophil \u0026times; monocyte \u0026times; platelet) / lymphocyte\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003eAll indices were calculated separately for early postnatal and month-1 measurements to evaluate temporal changes in systemic inflammatory status.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eContinuous variables were summarized as mean \u0026plusmn; standard deviation for normally distributed data and as median (interquartile range) for non-normally distributed data, while categorical variables were presented as counts and percentages. Normality of distribution was assessed using the Kolmogorov\u0026ndash;Smirnov or Shapiro\u0026ndash;Wilk tests, as appropriate. Distributional assessment was additionally supported by visual inspection of histograms.\u003c/p\u003e\n\u003cp\u003eFor comparisons between independent groups (ROP vs. no ROP), the independent-samples t test was used for normally distributed variables and the Mann\u0026ndash;Whitney U test for non-normally distributed variables. Categorical variables were compared using the chi-square test or Fisher\u0026rsquo;s exact test, as appropriate. For paired comparisons within the same individuals (early postnatal vs. month-1 measurements), the paired t test or Wilcoxon signed-rank test was applied according to distributional assumptions.\u003c/p\u003e\n\u003cp\u003eTo evaluate associations between inflammatory indices and ROP development, binary logistic regression analyses were performed. Variables demonstrating clinical relevance or statistical significance in univariable comparisons were entered into regression models to estimate odds ratios (ORs) with 95% confidence intervals (CIs). Given the limited number of treatment-requiring ROP cases, regression analyses for this outcome were interpreted cautiously.\u003c/p\u003e\n\u003cp\u003eReceiver operating characteristic (ROC) curve analyses were performed to evaluate the discriminative ability of each biomarker measured in the early postnatal period (postnatal days 2\u0026ndash;4) and at postnatal month 1 (postnatal days 28\u0026ndash;32) for predicting ROP development (coded as 1 = ROP and 0 = no ROP). ROC curves were generated separately for early postnatal and month-1 measurements, as well as for a combined model based on probabilities derived from binary logistic regression incorporating both time points. Because some biomarkers may be inversely associated with ROP, AUC values \u0026lt;0.5 were interpreted as inverse discrimination.\u003c/p\u003e\n\u003cp\u003eFor each ROC curve, the area under the curve (AUC), 95% confidence intervals calculated using the DeLong method, and the statistical significance of AUC compared with the null value of 0.5 were determined. Optimal cutoff values were identified by maximizing the Youden index (sensitivity + specificity \u0026minus; 1), and corresponding sensitivity, specificity, positive predictive value, negative predictive value, and overall accuracy were reported.\u003c/p\u003e\n\u003cp\u003eBecause repeated measurements originated from the same individuals, pairwise comparisons of AUCs across time points and combined models were performed using DeLong\u0026rsquo;s test for correlated ROC curves. The combined model was fitted using complete-case data (infants with both early postnatal and month-1 measurements); therefore, combined-model analyses primarily reflect the \u0026le;30-week group and the subset of the 30\u0026ndash;32-week group with available month-1 data. Accordingly, combined-model findings were interpreted within this context.\u003c/p\u003e\n\u003cp\u003eA two-sided p value \u0026lt; 0.05 was considered statistically significant. All statistical analyses were conducted using IBM SPSS Statistics for Windows, Version 26.0 (IBM Corp., Armonk, NY, USA).\u003c/p\u003e\n\u003cp\u003eThe sample size consisted of all eligible infants meeting the inclusion criteria during the study period. Because of the retrospective study design, no a priori power calculation was performed. Given the exploratory nature of the study, findings were interpreted in light of the available event numbers.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eParticipant characteristics and distribution of ROP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 139 preterm infants were included in the study. Of these, 68 (48.9%) were born at \u0026le;30 weeks of gestation and 71 (51.1%) at 30\u0026ndash;32 weeks. Female infants predominated in the \u0026le;30-week group (52.9%, n=36), whereas males were more frequent in the 30\u0026ndash;32-week group (54.9%, n=39).\u003c/p\u003e\n\u003cp\u003eOverall, ROP developed in 30 infants (21.6%), and 9 cases (6.5% of the total cohort) required treatment according to ETROP criteria. Stage\u0026ndash;zone distribution included Zone 3 Stage 1 (n=11), Zone 2 Stage 2 (n=14), Zone 2 Stage 3 (n=4), and Zone 1 Stage 3 (n=1), with plus disease present in 16 infants. Among treatment-requiring cases, 4 infants received intravitreal anti-VEGF alone, and 5 underwent anti-VEGF followed by laser photocoagulation. Infants without treatment indication were followed until complete retinal vascularization. The overall incidence and distribution of disease severity were consistent with a population of very preterm infants undergoing routine screening.\u003c/p\u003e\n\u003cp\u003eBaseline demographic and clinical characteristics are summarized in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eWithin-group temporal changes\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026le;30-week group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the \u0026le;30-week group, comparison between the early postnatal period and postnatal month 1 showed a significant decrease in hemoglobin levels (p\u0026lt;0.001), accompanied by significant increases in albumin, platelet, leukocyte, and monocyte counts (all p\u0026le;0.001). Among inflammatory indices, the HALP score decreased significantly (p\u0026lt;0.001), whereas SII, SIRI, and AISI increased (p\u0026le;0.035). PLR and LMR increased significantly (p\u0026lt;0.001), while NLR showed no significant change (p=0.557). These findings indicate progressive inflammatory activation during the first postnatal month in infants born at earlier gestational ages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e30\u0026ndash;32-week group\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the 30\u0026ndash;32-week group, hemoglobin and platelet counts increased significantly at month 1 (p\u0026lt;0.001 and p=0.002, respectively). Albumin and HALP score also changed significantly (p=0.046 and p=0.006). In contrast, lymphocyte, neutrophil, leukocyte counts and most inflammatory indices (SII, SIRI, AISI, PLR, NLR, LMR) showed no significant temporal variation. This comparatively stable inflammatory profile suggests a more limited postnatal inflammatory response in infants born at higher gestational ages.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBetween-group comparisons by gestational age\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEarly postnatal period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the early postnatal period, infants born at \u0026le;30 weeks had lower albumin levels (p\u0026lt;0.001) as well as lower platelet, neutrophil, and leukocyte counts and composite inflammatory indices (SII, SIRI, AISI; p\u0026le;0.030) compared with the 30\u0026ndash;32-week group. HALP, PLR, NLR, and LMR did not differ significantly between groups. These findings are consistent with maturational differences in hematologic parameters during early neonatal life.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePostnatal month 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt postnatal month 1, the \u0026le;30-week group demonstrated higher platelet counts, SII, AISI, and HALP scores (p\u0026le;0.048), whereas albumin levels remained higher in the 30\u0026ndash;32-week group (p=0.019; month-1 data: n=68 for \u0026le;30 weeks; n=18 for 30\u0026ndash;32 weeks). Other indices showed borderline or nonsignificant differences. The emergence of higher composite inflammatory indices at month 1 among the \u0026le;30-week group supports the presence of a gestational age\u0026ndash;dependent inflammatory window.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparisons according to ROP development in infants \u0026le;30 weeks\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEarly postnatal period\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring the early postnatal period, no significant differences in hematologic parameters or inflammatory indices were observed between infants who later developed ROP and those who did not (all p\u0026gt;0.05). Early inflammatory status did not discriminate subsequent disease development.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePostnatal month 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAt postnatal month 1, infants with ROP exhibited lower albumin levels (p=0.010) and higher neutrophil and monocyte counts (p=0.001 and p\u0026lt;0.001). Likewise, SII, SIRI, AISI, and NLR values were markedly elevated (all p\u0026le;0.001), and LMR was also significantly higher (p\u0026lt;0.001). The HALP score showed a borderline decrease (p=0.051). These findings indicate that systemic inflammatory activation becomes more clinically relevant during the first postnatal month in infants who develop ROP.\u003c/p\u003e\n\u003cp\u003eDetailed within-group temporal comparisons according to ROP status are presented in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTreatment-requiring ROP\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInfants with treatment-requiring ROP demonstrated lower albumin and HALP scores during the early postnatal period (p=0.012 and p=0.008) and higher SII, AISI, PLR, and NLR values (p\u0026le;0.028). These early differences suggest that more severe disease may be preceded by subtle systemic inflammatory imbalance.\u003c/p\u003e\n\u003cp\u003eAt postnatal month 1, SIRI and AISI remained significantly elevated in the treated group (p=0.048 and p=0.035). Although other parameters did not reach statistical significance, inflammatory indices generally trended higher. Overall, severe ROP appeared to be associated with both early and sustained systemic inflammatory activation, although the limited number of treated cases warrants cautious interpretation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eROC analyses\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe discriminative performance of biomarkers at different time points is shown in Table 3. Overall, early postnatal measurements demonstrated low AUC values and were generally not statistically significant. Thus, early inflammatory indices did not provide clinically meaningful discrimination.\u003c/p\u003e\n\u003cp\u003eIn contrast, month 1 measurements of SII, SIRI, AISI, NLR, and LMR showed significant discrimination for ROP development (AUC \u0026asymp; 0.73\u0026ndash;0.82; all p\u0026lt;0.001). HALP showed borderline or nonsignificant discrimination, and PLR showed limited discriminative performance. These findings support the greater clinical relevance of inflammatory assessment during the first postnatal month.\u003c/p\u003e\n\u003cp\u003eCombined models yielded AUC values similar to month 1 measurements and did not provide meaningful incremental improvement. Accordingly, the addition of early measurements did not enhance predictive performance beyond month-1 values alone.\u003c/p\u003e\n\u003cp\u003ePairwise AUC comparisons using the DeLong test (Table 4) confirmed that month 1 measurements of SIRI, AISI, NLR, and LMR provided significantly higher discriminative performance than early postnatal measurements (all p\u0026lt;0.05). No significant temporal differences were observed for HALP, SII, or PLR.\u003c/p\u003e\n\u003cp\u003eCollectively, these findings indicate that the prognostic value of systemic inflammatory indices for ROP becomes most apparent during the first postnatal month, particularly among infants born at \u0026le;30 weeks\u0026rsquo; gestation.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe pathogenesis of retinopathy of prematurity (ROP) is a multifactorial process characterized by disrupted retinal vascular development in premature infants, fluctuating oxygen exposure, and the interaction of prenatal and postnatal inflammatory pathways. Risk factors related to prenatal and postnatal inflammation have been shown to be associated with ROP development [23], and exposure of premature neonates to inflammatory mediators has been suggested to increase ROP risk [4]. Increasingly, ROP is recognized as a disorder in which systemic inflammatory activation may amplify vascular vulnerability in the immature retina.\u003c/p\u003e\n\u003cp\u003eIn the present study, systemic inflammation was evaluated using complete blood count (CBC)\u0026ndash;derived indices measured in the early postnatal period (postnatal days 2\u0026ndash;4) and at postnatal month 1 (postnatal days 28\u0026ndash;32), including NLR, PLR, and LMR, together with more integrative inflammatory markers such as SII, SIRI, and AISI, as well as the immune-nutritional indicator HALP. Our findings suggest that an inflammatory response that becomes more pronounced at postnatal month 1\u0026mdash;particularly in infants born before 30 weeks\u0026rsquo; gestation\u0026mdash;may be associated with ROP development. The absence of significant differences in NLR, PLR, and SII during the early postnatal period is consistent with physiological hematologic variability and rapid modulation by clinical or iatrogenic factors. Early neonatal hematologic instability may therefore obscure disease-specific inflammatory signals.\u003c/p\u003e\n\u003cp\u003eIn contrast, month-1 measurements may better reflect the period during which ROP becomes clinically manifest and systemic inflammatory burden stabilizes. Consistently, ROC analyses demonstrated limited discriminative ability in the early postnatal period but significantly higher AUC values at month 1 (\u0026asymp; 0.73\u0026ndash;0.82), supporting the temporal relevance of inflammatory activity. These findings highlight the importance of timing when interpreting systemic inflammatory markers in very preterm infants.\u003c/p\u003e\n\u003cp\u003eCBC is a low-cost, widely accessible, and practical tool for assessing systemic inflammation in premature populations. Ratios such as NLR, PLR, and LMR have been extensively investigated as inflammatory biomarkers in cardiovascular disease, malignancy, and rheumatologic disorders [24-26], and have also been reported as indicators of inflammatory response in retinal and other ophthalmic diseases [17,27]. Their routine availability in neonatal intensive care units enhances their potential translational applicability.\u003c/p\u003e\n\u003cp\u003eWithin the ROP literature, these ratios are generally evaluated at single time points. Hu et al. [17] and Kurtul et al. [16] reported higher NLR and/or LMR values in infants who developed ROP, whereas PLR showed inconsistent associations. Akdoğan et al. demonstrated elevated NLR and reduced PLR at postnatal month 1 in ROP [28]. Oruz et al. reported that NLR and SII early postnatally and NLR, SII, and LMR at month 1 were associated with ROP, and further identified month-1 PLR and SII as independent predictors of laser treatment requirement [29]. In line with these studies, our results indicate that month-1 NLR, LMR, and composite inflammatory indices possess stronger predictive relevance, whereas PLR and HALP show limited discriminative performance. Our gestational age\u0026ndash;stratified approach may partly explain differences from earlier reports that did not account for maturational hematologic variability.\u003c/p\u003e\n\u003cp\u003eGestational age\u0026ndash;stratified comparisons revealed no significant early postnatal differences in HALP, PLR, NLR, or LMR; however, infants born at \u0026le;30 weeks exhibited lower albumin levels as well as reduced platelet, neutrophil, leukocyte, and composite inflammatory index values, suggesting a relatively suppressed inflammatory profile in early life. This early pattern likely reflects developmental immaturity rather than absence of inflammatory activation. By contrast, higher platelet counts, SII, AISI, and HALP scores at month 1 in this group indicate the emergence of a clinically meaningful postnatal inflammatory window. Because most previous studies did not stratify by gestational age, maturational hematologic differences may have confounded earlier findings. Thus, gestational age stratification represents an important methodological strength of the present study.\u003c/p\u003e\n\u003cp\u003ePlatelets contribute to angiogenesis through the transport and release of VEGF, PDGF, and IGF-1 [14,30]. Thrombocytopenia may impair physiologic retinal vascularization and promote uncontrolled neovascularization. Jensen et al. associated low platelet counts with severe ROP [30] , while Tao et al. highlighted the role of platelets within the angiogenesis\u0026ndash;inflammation axis [31,32]. Nevertheless, physiological postnatal variability in platelet counts necessitates interpretation within the context of gestational and postnatal age. Composite platelet-containing indices may therefore capture both angiogenic and inflammatory components of disease progression.\u003c/p\u003e\n\u003cp\u003eHematologic parameters in premature infants vary substantially with both gestational and postnatal maturation [33,34]. Analyses that combine different gestational age groups may therefore reflect maturational physiology rather than disease-specific mechanisms. Stratification by gestational age in the present study was intended to reduce this potential bias. This design strengthens internal validity by minimizing confounding related to developmental heterogeneity.\u003c/p\u003e\n\u003cp\u003eHALP integrates hemoglobin, albumin, lymphocyte, and platelet levels and reflects immune-nutritional status [35]. Reduced HALP has been associated with poor prognosis in several diseases [36,37] and has been identified as an independent risk factor for diabetic retinopathy [38]. The tendency toward lower HALP and albumin levels in infants who developed ROP in our cohort suggests a potential contribution of the nutrition\u0026ndash;inflammation axis to ROP pathobiology. However, the lack of significant ROC discrimination for HALP and PLR indicates that these markers may function better as contextual or supportive indicators rather than standalone predictors. HALP may reflect systemic vulnerability rather than a direct mechanistic driver of retinal angiogenic dysregulation.\u003c/p\u003e\n\u003cp\u003eComposite inflammatory indices such as SII and SIRI more comprehensively reflect the balance between inflammation and immune response and have demonstrated prognostic value across multiple clinical settings [ 27,39-41]. AISI has likewise been associated with obstetric and neonatal outcomes [42-45] . In our study, elevated SII, SIRI, and AISI at postnatal month 1 were strongly associated with ROP, supporting a central role for postnatal systemic inflammation. DeLong comparisons further confirmed the superior discriminative performance of month-1 measurements, emphasizing the prognostic importance of timing.\u003c/p\u003e\n\u003cp\u003eTemporal inflammatory dynamics constituted a key observation. In infants born before 30 weeks, decreasing HALP alongside increasing SII, SIRI, and AISI from early postnatal life to month 1 suggests progressive inflammatory activation. Among infants requiring treatment, early reductions in albumin and HALP combined with persistently elevated inflammatory indices support an association between sustained systemic inflammation and disease severity. Moreover, the exclusive temporal increase of inflammatory indices in the ROP group highlights the potential relevance of dynamic inflammatory trajectories, rather than absolute values alone, in disease pathobiology.\u003c/p\u003e\n\u003cp\u003eCollectively, these findings reinforce the concept that ROP is not solely an oxygen-driven disorder but rather a multidimensional disease closely linked to systemic inflammation and immune dysregulation [4,23] . From a clinical perspective, CBC-derived composite indices are attractive because of their accessibility and low cost. In particular, month-1 elevations in SII, SIRI, and AISI may assist in identifying high-risk premature infants who could benefit from closer surveillance or earlier intervention. Nonetheless, these biomarkers should be interpreted within a comprehensive clinical framework that includes gestational age, birth weight, oxygen exposure, and neonatal comorbidities. Our findings support the clinical relevance of postnatal inflammatory assessment but do not suggest replacement of established screening criteria.\u003c/p\u003e\n\u003cp\u003eThe retrospective, single-center design, variability in sampling timing, and potential confounding from infection, steroid exposure, respiratory support, and other neonatal comorbidities represent the principal limitations. Missing month-1 data, particularly in the 30\u0026ndash;32-week group, may introduce selection bias and limit generalizability of month-1 findings. Multiple statistical comparisons necessitate cautious interpretation. The relatively small number of treatment-requiring cases limits the precision of severity-related analyses. Prospective, multicenter studies with larger cohorts and comprehensive multivariable modeling are required to validate these findings.\u003c/p\u003e\n\u003cp\u003eIn conclusion, systemic inflammatory activation emerging during the first postnatal month is closely associated with both the development and severity of retinopathy of prematurity, particularly among infants born before 30 weeks of gestation. Composite complete blood count\u0026ndash;derived inflammatory indices\u0026mdash;especially SII, SIRI, and AISI, together with NLR and LMR\u0026mdash;demonstrate meaningful time-dependent discriminative performance, whereas HALP and PLR appear to function primarily as supportive rather than standalone markers.\u003c/p\u003e\n\u003cp\u003eGiven their low cost, universal availability, and ease of calculation, CBC-derived inflammatory indices may serve as pragmatic adjunct biomarkers for early risk stratification and surveillance in premature infants, particularly when assessed at postnatal month 1. Future prospective multicenter validation studies are required before incorporation into routine clinical decision-making.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAISI \u0026ndash; Aggregate Index of Systemic Inflammation\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;AUC \u0026ndash; Area Under the Curve\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;CBC \u0026ndash; Complete Blood Count\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;HALP \u0026ndash; Hemoglobin\u0026ndash;Albumin\u0026ndash;Lymphocyte\u0026ndash;Platelet Score\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;LMR \u0026ndash; Lymphocyte-to-Monocyte Ratio\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;NLR \u0026ndash; Neutrophil-to-Lymphocyte Ratio\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;PLR \u0026ndash; Platelet-to-Lymphocyte Ratio\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;ROC \u0026ndash; Receiver Operating Characteristic\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;ROP \u0026ndash; Retinopathy of Prematurity\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;SII \u0026ndash; Systemic Immune-Inflammation Index\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;SIRI \u0026ndash; Systemic Inflammation Response Index\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the staff of the Departments of Ophthalmology and Neonatology at Malatya Turgut Ozal University for their technical assistance and support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Scientific Research Projects Coordination Unit of Malatya Turgut \u0026Ouml;zal University\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e: Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Ophthalmology, Malatya Turgut Ozal University, Malatya, Turkey\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZarife Ekici G\u0026ouml;k\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Neonatology, Malatya Turgut Ozal University, Malatya, Turkey\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNuriye Aslı Melekoğlu\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDepartment of Biostatistics and Medical Informatics, Inonu University ,\u0026nbsp;Malatya,T\u0026uuml;rkiye\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eŞeyma Yaşar\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConcept and design: Z.E.G., N.A.M. Data acquisition: Z.E.G. Data analysis and interpretation: Ş.Y. \u0026nbsp;Manuscript drafting: Z.E.G. Supervision: Z.E.G., N.A.M. Final approval of the manuscript: All authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Zarife Ekici G\u0026ouml;k\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Health Sciences Scientific Research Ethics Committee of Malatya Turgut Ozal University (Decision No: 18/2026). All procedures were conducted in accordance with the principles of the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGergely K, Gerinec A. Retinopathy of prematurity: epidemics, incidence, prevalence, blindness. Bratisl Lek Listy. 2010; 111:514-517.\u003c/li\u003e\n \u003cli\u003eHellstr\u0026ouml;m A, Smith LEH, Dammann O. Retinopathy of prematurity. Lancet. 2013; 382:1445-1457.\u003c/li\u003e\n \u003cli\u003eCavallaro G, Filippi L, Bagnoli P, et al. The pathophysiology of retinopathy of prematurity: an update of previous and recent knowledge. Acta Ophthalmol. 2014; 92:2-20.\u003c/li\u003e\n \u003cli\u003eChen J, Stahl A, Hellstr\u0026ouml;m A, Smith LEH. Current update on retinopathy of prematurity: screening and treatment. Curr Opin Pediatr. 2011; 23:173-178.\u003c/li\u003e\n \u003cli\u003eTremblay S, Miloudi K, Chaychi S, et al. Systemic inflammation perturbs developmental retinal angiogenesis and neuroretinal function. Invest Ophthalmol Vis Sci. 2013; 54:8125-8139.\u003c/li\u003e\n \u003cli\u003eRivera JC, Holm M, Austeng D, et al. Retinopathy of prematurity: inflammation, choroidal degeneration, and novel promising therapeutic strategies. J Neuroinflammation. 2017; 14:165.\u003c/li\u003e\n \u003cli\u003eDammann O, Brinkhaus MJ, Bartels DB, et al. Immaturity, perinatal inflammation, and retinopathy of prematurity: a multi-hit hypothesis. Early Hum Dev. 2009; 85:325-329.\u003c/li\u003e\n \u003cli\u003eChen J, Smith LEH. Retinopathy of prematurity. Angiogenesis. 2007; 10:133-140.\u003c/li\u003e\n \u003cli\u003eSehgal P, Narang S, Chawla D, et al. Systemic biomarkers of retinopathy of prematurity in preterm babies. Int Ophthalmol. 2023; 43:1751-1759.\u003c/li\u003e\n \u003cli\u003eWu PY, Fu YK, Lien RI, et al. Systemic cytokines in retinopathy of prematurity. J Pers Med. 2023; 13:291.\u003c/li\u003e\n \u003cli\u003eSato T, Kusaka S, Shimojo H, Fujikado T. Simultaneous analyses of vitreous levels of 27 cytokines in eyes with retinopathy of prematurity. Ophthalmology. 2009; 116:2165-2169.\u003c/li\u003e\n \u003cli\u003eInternational Committee for the Classification of Retinopathy of Prematurity. The international classification of retinopathy of prematurity revisited. Arch Ophthalmol. 2005; 123:991-999.\u003c/li\u003e\n \u003cli\u003ePheng E, Lim ZDI, Tai LM, et al. Haemoglobin levels in early life among infants with and without retinopathy of prematurity. Int J Environ Res Public Health. 2021; 18:7054.\u003c/li\u003e\n \u003cli\u003eŞahinoğlu Keşkek N, G\u0026uuml;lcan H, Yılmaz G, Akkoyun İ. Impact of platelet count in retinopathy of prematurity. Turk J Ophthalmol. 2020; 50:351-355.\u003c/li\u003e\n \u003cli\u003eOzturk T, Durmaz Engin C, Kaya M, Yaman A. Complete blood count parameters to predict retinopathy of prematurity. Int Ophthalmol. 2021; 41:2009-2018.\u003c/li\u003e\n \u003cli\u003eKurtul BE, Kabataş EU, Zenciroğlu A, et al. Serum neutrophil-to-lymphocyte ratio in retinopathy of prematurity. 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Association of neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios with diabetic retinopathy. Diabetol Metab Syndr. 2020; 12:55.\u003c/li\u003e\n \u003cli\u003eGoldstein GP, Leonard SA, Kan P, et al. Prenatal and postnatal inflammation-related risk factors for retinopathy of prematurity. J Perinatol. 2019; 39:964-973.\u003c/li\u003e\n \u003cli\u003eWang X, Zhang G, Jiang X, et al. Neutrophil-to-lymphocyte ratio and mortality risk: meta-analysis. Atherosclerosis. 2014; 234:206-213.\u003c/li\u003e\n \u003cli\u003eBowen RC, Little NAB, Harmer JR, et al. Neutrophil-to-lymphocyte ratio as prognostic indicator in gastrointestinal cancers. Oncotarget. 2017; 8:32171-32189.\u003c/li\u003e\n \u003cli\u003eBonaventura A, Liberale L, Carbone F, et al. Baseline neutrophil-to-lymphocyte ratio and long-term type 2 diabetes remission. Acta Diabetol. 2019; 56:741-748.\u003c/li\u003e\n \u003cli\u003eMa M, Yu N, Wu B. High systemic immune-inflammation index predicts poor prognosis in malignant pleural mesothelioma. Cancer Manag Res. 2019; 11:3973-3979.\u003c/li\u003e\n \u003cli\u003eAkdogan M, Ustundag Y, Cevik SG, et al. Systemic immune-inflammation index in retinopathy of prematurity prognosis. Indian J Ophthalmol. 2021; 69:2182-2187.\u003c/li\u003e\n \u003cli\u003eOruz O, Dervişoğulları MS, \u0026Ouml;ktem ME, İncekaş C. Predictive role of systemic immune-inflammation index and neutrophil/lymphocyte ratio in infants with retinopathy of prematurity. Graefes Arch Clin Exp Ophthalmol. 2024.\u003c/li\u003e\n \u003cli\u003eJensen AK, Ying GS, Huang J, et al. Thrombocytopenia and retinopathy of prematurity. J AAPOS. 2011; 15: e3-e4.\u003c/li\u003e\n \u003cli\u003eTao Y, Dong Y, Lu CW, et al. Mean platelet volume and retinopathy of prematurity. Graefes Arch Clin Exp Ophthalmol. 2015; 253:1791-1794.\u003c/li\u003e\n \u003cli\u003eYu H, Yuan L, Zou Y, et al. Serum cytokine concentrations in infants with retinopathy of prematurity. APMIS. 2014; 122:818-823.\u003c/li\u003e\n \u003cli\u003eSchmutz N, Henry E, Jopling J, Christensen RD. Neonatal neutrophil reference ranges revisited. J Perinatol. 2008; 28:275-281.\u003c/li\u003e\n \u003cli\u003eManroe BL, Weinberg AG, Rosenfeld CR, Browne R. Neonatal blood count in health and disease. J Pediatr. 1979; 95:89-98.\u003c/li\u003e\n \u003cli\u003eXu SS, Li S, Xu HX, et al. Hemoglobin-albumin-lymphocyte-platelet score in pancreatic cancer survival. World J Gastroenterol. 2020; 26:828-838.\u003c/li\u003e\n \u003cli\u003eSolmaz S, Uzun O, Sevindik OG, et al. HALP score in multiple myeloma prognosis. Int J Lab Hematol. 2023; 45:13-19.\u003c/li\u003e\n \u003cli\u003eWang J, Jiang P, Huang Y, et al. HALP cut-off values in endometrial cancer. Am J Clin Oncol. 2023; 46:107-113.\u003c/li\u003e\n \u003cli\u003eDing R, Zeng Y, Wei Z, et al. HALP score and diabetic retinopathy risk. Front Endocrinol (Lausanne). 2024; 15:1356929.\u003c/li\u003e\n \u003cli\u003eDziedzic EA, Gąsior JS, Tuzimek A, et al. Systemic inflammatory indices in coronary artery disease. Int J Mol Sci. 2022; 23:9553.\u003c/li\u003e\n \u003cli\u003eErdal H, Kilic A, Akbulut Yagci B, Yasar E. Pan-immune inflammation indices in pseudoexfoliation. J Clin Pract Res. 2024.\u003c/li\u003e\n \u003cli\u003eWang S, Pan X, Jia B, Chen S. Systemic immune-inflammation index and diabetic retinopathy. Diabetes Metab Syndr Obes. 2023; 16:3827-3836.\u003c/li\u003e\n \u003cli\u003eTokalioglu EO, Tanacan A, Agaoglu MO, et al. Aggregate systemic inflammation index in premature rupture of membranes. Int J Gynecol Obstet. 2025; 168:640-649.\u003c/li\u003e\n \u003cli\u003eAkin MS, Akyol O, Okman E, et al. Systemic inflammatory indices and lung maturation in preterm infants. J Pediatr Intensive Care. 2024.\u003c/li\u003e\n \u003cli\u003eHrubaru I, Motoc A, Moise ML, et al. Maternal inflammatory biomarkers and preterm birth risk. J Clin Med. 2022; 11:6982.\u003c/li\u003e\n \u003cli\u003eBeser DM, Ozgurluk I, Oluklu D, et al. NLR, dNLR, SII, SIRI, and APRI in pregnancy outcomes. Ann Med Res. 2023; 30:1001-1007.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1. Baseline demographic and clinical characteristics by gestational age group\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;30 weeks (n=68)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e30\u0026ndash;32 weeks (n=71)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTotal (n=139)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSex, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e36 (52.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68 (48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 (47.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39 (54.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e71 (51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eGestational age (weeks)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29 \u0026plusmn; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 \u0026plusmn; 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29 (28\u0026ndash;30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e32 (31\u0026ndash;32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBirth weight (g)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1189 \u0026plusmn; 271\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1643 \u0026plusmn; 233\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedian (IQR)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1223 (1000\u0026ndash;1343)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1675 (1500\u0026ndash;1800)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026mdash;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eROP, n (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e29 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1 (1.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e30 (21.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: IQR, interquartile range; ROP, retinopathy of prematurity; SD, standard deviation.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Within-group changes from early postnatal period to postnatal month 1 in infants \u0026le;30 weeks, stratified by ROP status\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eTime point\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eROP absent Mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eROP absent Median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eROP present Mean \u0026plusmn; SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eROP present Median (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHemoglobin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.01 \u0026plusmn; 2.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.1 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.64 \u0026plusmn; 2.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e16.5 (2.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.57 \u0026plusmn; 1.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.7 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.80 \u0026plusmn; 1.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.0 (1.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAlbumin\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.46 \u0026plusmn; 0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.34 \u0026plusmn; 0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.3 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.75 \u0026plusmn; 0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.8 (0.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.52 \u0026plusmn; 0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.5 (0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLymphocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.62 \u0026plusmn; 2.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.46 (2.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.53 \u0026plusmn; 3.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.18 (3.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.50 \u0026plusmn; 2.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.04 (2.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.63 \u0026plusmn; 2.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e5.52 (2.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePlatelet\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e231.13 \u0026plusmn; 79.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e221 (128)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e201.14 \u0026plusmn; 69.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e208 (112)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e418.95 \u0026plusmn; 114.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e436 (187)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e406.38 \u0026plusmn; 149.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e376 (224)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNeutrophil\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e3.88 \u0026plusmn; 3.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.85 (3.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.69 \u0026plusmn; 2.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.10 (1.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.96 \u0026plusmn; 1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.36 (2.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e6.04 \u0026plusmn; 4.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e4.55 (4.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLeukocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e10.70 \u0026plusmn; 4.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.76 (4.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.35 \u0026plusmn; 4.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e8.32 (3.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.64 \u0026plusmn; 3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e11.27 (5.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e14.30 \u0026plusmn; 6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e12.82 (6.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMonocyte\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.99 \u0026plusmn; 0.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.76 (0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88 \u0026plusmn; 0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78 (0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.31 \u0026plusmn; 0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.13 (0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.99 \u0026plusmn; 0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.86 (0.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP score\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.18 \u0026plusmn; 0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02 (0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.19 \u0026plusmn; 0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.03 (1.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.48 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.42 (0.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.39 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.29 (0.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e187.96 \u0026plusmn; 188.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e108.00 (230.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.460\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e153.23 \u0026plusmn; 210.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e79.55 (115.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e225.27 \u0026plusmn; 222.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e149.25 (201.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e463.22 \u0026plusmn; 390.53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e306.59 (325.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.11 \u0026plusmn; 1.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.46 (0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.867\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93 \u0026plusmn; 1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.29 (0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.74 \u0026plusmn; 0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50 (0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.38 \u0026plusmn; 2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.55 (2.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e248.73 \u0026plusmn; 416.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e90.43 (167.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.289\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e153.50 \u0026plusmn; 245.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e53.00 (171.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e310.39 \u0026plusmn; 339.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e159.60 (326.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e974.60 \u0026plusmn; 1016.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e641.09 (716.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e46.41 \u0026plusmn; 23.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e39.89 (34.79)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.37 \u0026plusmn; 40.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e40.67 (29.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e72.26 \u0026plusmn; 39.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.01 (27.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e82.12 \u0026plusmn; 42.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65.15 (49.03)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.81 \u0026plusmn; 0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.59 (0.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.90 \u0026plusmn; 1.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.44 (0.62)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.54 \u0026plusmn; 0.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.38 (0.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.12 \u0026plusmn; 0.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.93 (0.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21 \u0026plusmn; 0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.14 (0.16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.252\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.23 \u0026plusmn; 0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.17 (0.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMonth 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.22 \u0026plusmn; 0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.23 (0.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.39 \u0026plusmn; 0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.33 (0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*P values reflect within-group comparisons between early postnatal period and month 1 (paired tests as appropriate).\u003cbr\u003e\u0026nbsp;Abbreviations: AISI, aggregate index of systemic inflammation; HALP, hemoglobin\u0026ndash;albumin\u0026ndash;lymphocyte\u0026ndash;platelet score; IQR, interquartile range; LMR, lymphocyte-to-monocyte ratio; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; ROP, retinopathy of prematurity; SD, standard deviation; SII, systemic immune-inflammation index; SIRI, systemic inflammatory response index.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Discriminative performance of biomarkers for predicting ROP (ROC analysis)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eModel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eBest cutoff\u0026dagger;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAUC (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSensitivity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eSpecificity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003ePPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eNPV\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAccuracy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eYouden\u0026rsquo;s J\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.52 (0.37\u0026ndash;0.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.774\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.448\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.662\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.64 (0.50\u0026ndash;0.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.481\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.63 (0.49\u0026ndash;0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.714\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.702\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.363\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e155.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.58 (0.44\u0026ndash;0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.272\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.436\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.500\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.574\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e216.976\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.73 (0.61\u0026ndash;0.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.358\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.74 (0.61\u0026ndash;0.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.647\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.721\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.451\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.56 (0.42\u0026ndash;0.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.419\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.638\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.183\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.977\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.82 (0.71\u0026ndash;0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.82 (0.72\u0026ndash;0.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.846\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.769\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.786\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.779\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e63.658\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.58 (0.44\u0026ndash;0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.515\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.657\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.176\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e249.619\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78 (0.67\u0026ndash;0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.650\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.893\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.538\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.297\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78 (0.67\u0026ndash;0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.590\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.610\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.852\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.706\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.452\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e119.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.46 (0.32\u0026ndash;0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.599\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.618\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.103\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.202\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.43 (0.28\u0026ndash;0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.335\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.207\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.600\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.603\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.59 (0.45\u0026ndash;0.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.220\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.676\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.277\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.586\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.57 (0.43\u0026ndash;0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.513\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.690\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.579\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78 (0.66\u0026ndash;0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.759\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.688\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.502\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.355\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78 (0.66\u0026ndash;0.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR (early postnatal)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50 (0.36\u0026ndash;0.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.967\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.517\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.588\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR (month 1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.80 (0.69\u0026ndash;0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.641\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.862\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.735\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR (combined)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.80 (0.70\u0026ndash;0.91)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.793\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.744\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.697\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.829\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.765\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.537\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026dagger;For \u0026ldquo;combined\u0026rdquo; models, best cutoff refers to predicted probability from logistic regression including early postnatal and month-1 values.\u003c/p\u003e\n\u003cp\u003eAbbreviations: AISI, aggregate index of systemic inflammation; AUC, area under the curve; CI, confidence interval; HALP, hemoglobin\u0026ndash;albumin\u0026ndash;lymphocyte\u0026ndash;platelet score; LMR, lymphocyte-to-monocyte ratio; NLR, neutrophil-to-lymphocyte ratio; NPV, negative predictive value; PLR, platelet-to-lymphocyte ratio; PPV, positive predictive value; ROP, retinopathy of prematurity; SII, systemic immune-inflammation index; SIRI, systemic inflammation response index.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Pairwise comparison of AUCs between early and month-1 measurements (DeLong test)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"3\" cellpadding=\"0\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eComparison\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAUC1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAUC2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAUC difference\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.244\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.269\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eHALP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.631\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.187\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.578\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.051\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.737\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.840\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSIRI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.818\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.820\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.918\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.203\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAISI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.740\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.462\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.129\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.427\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.164\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.777\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.936\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eEarly postnatal vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.296\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs early postnatal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.503\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eCombined vs month 1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.799\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.805\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.542\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eFootnote: AUCs were compared using DeLong\u0026rsquo;s test for correlated ROC curves\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"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":"Retinopathy of Prematurity, Infant, Premature, Gestational Age, Inflammation, Hematologic Parameters, Biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-9041551/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9041551/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo evaluate the temporal profile and clinical relevance of the hemoglobin\u0026ndash;albumin\u0026ndash;lymphocyte\u0026ndash;platelet (HALP) score and complete blood count\u0026ndash;derived inflammatory indices for retinopathy of prematurity (ROP) across gestational age strata.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e139 preterm infants born at \u0026le;\u0026thinsp;32 weeks were stratified into \u0026le;\u0026thinsp;30 and 30\u0026ndash;32 weeks. Early (postnatal days 2\u0026ndash;4) and month-1 complete blood count parameters were analyzed. Neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index, aggregate index of systemic inflammation, and HALP score were calculated at both time points. Comparisons were performed according to ROP status and gestational age strata, and discriminative performance was evaluated using receiver operating characteristic analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eROP developed in 30 infants (21.6%), including 9 requiring treatment. The \u0026le;\u0026thinsp;30-week group had higher ROP incidence and severity. Early indices were not associated with ROP. At month 1, infants\u0026thinsp;\u0026le;\u0026thinsp;30 weeks with ROP showed lower albumin and higher composite inflammatory indices (AUC 0.73\u0026ndash;0.82), whereas associations were weaker in the 30\u0026ndash;32-week group. HALP and platelet-to-lymphocyte ratio demonstrated limited discrimination.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eMonth-1 systemic inflammatory activation is associated with ROP predominantly in infants\u0026thinsp;\u0026le;\u0026thinsp;30 weeks, indicating a gestational age\u0026ndash;dependent inflammatory contribution and potential value for risk stratification.\u003c/p\u003e","manuscriptTitle":"Gestational Age–Dependent Association of HALP Score and Systemic Inflammatory Indices with Retinopathy of Prematurity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-08 13:48:27","doi":"10.21203/rs.3.rs-9041551/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-04-15T19:38:51+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-15T17:38:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-10T07:02:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"105794188687157922151215319413826699107","date":"2026-04-10T05:15:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"50477136232276891310640964941319987271","date":"2026-04-09T14:48:30+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"163485488577339071361878326919509993680","date":"2026-04-02T10:20:04+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-02T08:38:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-31T10:03:08+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-10T03:04:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-10T00:06:53+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pediatrics","date":"2026-03-09T19:54:03+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":"dfb4e7da-f4fb-4dea-b799-8d6dc6588916","owner":[],"postedDate":"April 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-08T13:48:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-08 13:48:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9041551","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9041551","identity":"rs-9041551","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}