Neutrophil-to-Lymphocyte Ratio as a Predictive Biomarker for Retinopathy of Prematurity: A Systematic Review
Bibliographic record
Abstract
Introduction: Retinopathy of prematurity (ROP) remains a leading cause of childhood blindness, with its pathogenesis linked to aberrant vascular development and systemic inflammation. There is a critical need for accessible biomarkers to improve risk stratification beyond current screening standards. This systematic review critically appraises the evidence for the neutrophil-to-lymphocyte ratio (NLR), a widely available inflammatory marker, as a predictor of ROP. Methods: Following PRISMA 2020 guidelines, a systematic search was conducted in PubMed, ScienceDirect, ProQuest, and SpringerLink for observational studies published between January 1st, 2015, and December 31st, 2024. Studies assessing the association between NLR and ROP in preterm infants were included. Two reviewers independently performed study selection, data extraction, and a formal risk-of-bias assessment using the Newcastle-Ottawa Scale (NOS). A narrative synthesis was performed due to significant heterogeneity. Results: The search identified 32 records, with 6 retrospective studies ultimately meeting the inclusion criteria, encompassing a total reported sample of 1,065 infants. The methodological quality of the included studies was low to moderate, with NOS scores ranging from 5 to 7 out of a possible 9. The evidence base was defined by profound methodological heterogeneity, particularly in the timing of blood sample collection, which was unspecified in half of the studies, and inconsistent reporting of core population data. A narrative synthesis of the findings showed that several studies reported a statistical association between an elevated NLR or related inflammatory markers and ROP. However, one study reported no significant association, and the interpretation of others was complicated by a focus on different biomarkers or a lack of statistical significance. Conclusion: The available evidence, derived exclusively from retrospective studies of varying quality, suggests a possible association between elevated NLR and ROP, a link supported by strong biological plausibility. However, the current evidence base is severely limited by methodological flaws and profound heterogeneity, making it insufficient to support the adoption of NLR into clinical practice. NLR is not a standalone diagnostic or predictive tool for ROP. Its potential utility can only be realized through large-scale, methodologically rigorous prospective studies designed to overcome the limitations identified in this review.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".