Demographic Risk Factors of Retinopathy of Prematurity: A Systematic Review of Population-Based Studies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
INTRODUCTION: Current national guidelines use gestational age (GA) and birth weight (BW) as their basis for retinopathy of prematurity (ROP) screening. The strength of association of these and other demographic risk factors is inconsistent across studies. This review aims to evaluate the strength of association of documented risk factors for ROP in large sample, population-based studies. METHODS: MEDLINE, EMBASE, and Cochrane Library were searched from January 2010 to May 2020. Original studies reporting the risk of ROP in a region and demographic risk factors were included. RESULTS: Eighteen studies comprising 342,005 infants were included. The overall risk of ROP in preterm infants was 18.8%. For every week decrease in GA, there was a median adjusted odds ratio (aOR) of 1.4 times (range 1.2-1.9) of developing ROP. For every 100-g decrease in BW, the median aOR was 1.8 times (range 1.2-2.7). Higher risk was found in infants with neonatal sepsis and bronchopulmonary dysplasia. The risk of any, severe, and treatment-requiring ROP was highest for 23 weeks GA, which was 66.5, 40.3, and 39.4%, respectively. Regions with higher neonatal mortality rates had the highest mean GA of infants with ROP. CONCLUSION: For every week decrease in GA and every 100-g decrease in BW, there was a median of 1.4 times and 1.8 times the odds of developing ROP, respectively. Further research is required to clarify the role of additional risk factors.
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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 | 0.002 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 it