Refining evidence-based retinopathy of prematurity screening guidelines: The SCREENROP study
Bibliographic record
Abstract
PURPOSE: Retinopathy of prematurity (ROP) is a potentially blinding condition affecting premature infants for which less than 10% of babies undergoing screening require treatment. This study assessed and validated predictors of developing clinically significant ROP (type 2 or worse) and ROP requiring treatment. DESIGN: Nationwide retrospective cohort study. METHODS: This study included infants born between January 2014 and June 2016, admitted to level 3 neonatal intensive care units across Canada who underwent ROP screening. Data were derived from the Canadian Neonatal Network database. Predefined ≥ 1% risk for clinically significant retinopathy or prematurity and ROP requiring treatment was set as threshold for screening. Thirty-two potential predictors were analyzed, to identify and validate the most important ones for predicting clinically significant ROP. The predictors were determined on a derivation cohort and tested on a validation cohort. Multivariable logistic regression modeling was used for analysis. RESULTS: Using a sample of 4,888 babies and analyzing 32 potential predictors, capturing babies with ≥1% risk of developing clinically significant ROP equated to screening babies with birth weight (BW) <1,300 g or gestational age (GA) <30 weeks while capturing babies with ≥1% risk of requiring ROP treatment equated to screening babies with BW <1,200 g or GA <29 weeks. CONCLUSIONS: The Canadian ROP screening criteria can be modified to screen babies with BW <1,200 g or GA <30 weeks. Using these criteria, babies requiring treatment would be identified while reducing the number of babies screened unnecessarily.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".