The Third Epidemic of Blindness: Early ROP Screening vs. KIDROP Conventional Screening of Retinopathy of Prematurity in Neonates- A Prospective Cohort Study
Bibliographic record
Abstract
Aim: To assess the benefits of initiating early Retinopathy of Prematurity (ROP) screening compared to conventional KIDROP screening and study the incidence, severity, and risk factors of ROP. Methods: Preterm neonates born with weight < 2000 g and/or < 36 weeks of gestation admitted to the Level III-A neonatal intensive care unit (NICU), BLDE (Deemed to be University), Shri B. M. Patil Medical College, Hospital and Research Centre, were enrolled in the study. The in-house retina specialist performed Early ROP screening at 10-14 days of life, depending on the gestational age at birth. Subsequently, KIDROP conventional screening was done at 3 to 6 weeks of life by the Karnataka Internet Assisted Diagnosis for Retinopathy of Prematurity (KIDROP) team once weekly. ROP findings were recorded as per the standard ICROP norms. The data was analyzed for gestational age, birth weight, and systemic factors predisposing to ROP. Results: The incidence of Early ROP was 14% (7/50). Of the neonates diagnosed with ROP, 43% had a gestational age of < 30 weeks, and 86% had birth weight in the group 1000- 1500 g. The incidence of type 1 ROP is 28.5% (2/7). The significant predictors of the increased risk of ROP were birth weight, gestational age, prolonged oxygen therapy, synchronized intermittent mandatory ventilation (SIMV), sepsis, patent ductus arteriosus (PDA), and nutrition, including MOM & Parenteral Nutrition. Conclusion: Early enrolment of neonates for ROP screening in the NICU itself ensures early diagnosis and timely intervention and also ensures compliance and routine follow-up of these neonates. 14% had early ROP, which suggests the need to redefine the ROP screening criteria.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 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".