An international comparison of retinopathy of prematurity grading performance within the Benefits of Oxygen Saturation Targeting II trials
Bibliographic record
Abstract
PurposeTo investigate whether the observed international differences in retinopathy of prematurity (ROP) treatment rates within the Benefits of Oxygen Saturation Targeting (BOOST) II trials might have been caused by international variation in ROP disease grading.MethodsGroups of BOOST II trial ophthalmologists in UK, Australia, and New Zealand (ANZ), and an international reference group (INT) used a web based system to grade a selection of RetCam images of ROP acquired during the BOOST II UK trial. Rates of decisions to treat, plus disease grading, ROP stage grading, ROP zone grading, inter-observer variation within groups and intra-observer variation within groups were measured.ResultsForty-two eye examinations were graded. UK ophthalmologists diagnosed treat-requiring ROP more frequently than ANZ ophthalmologists, 13.9 (3.49) compared to 9.4 (4.46) eye examinations, P=0.038. UK ophthalmologists diagnosed plus disease more frequently than ANZ ophthalmologists, 14.1 (6.23) compared to 8.5 (3.24) eye examinations, P=0.021. ANZ ophthalmologists diagnosed stage 2 ROP more frequently than UK ophthalmologists, 20.2 (5.8) compared to 12.7 (7.1) eye examinations, P=0.026. There were no other significant differences in the grading of ROP stage or zone. Inter-observer variation was higher within the UK group than within the ANZ group. Intra-observer variation was low in both groups.ConclusionsWe have found evidence of international variation in the diagnosis of treatment-requiring ROP. Improved standardisation of the diagnosis of treatment-requiring ROP is required. Measures might include improved training in the grading of ROP, using an international approach, and further development of ROP image analysis software.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.038 | 0.065 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".