Effect of Prophylactic Indomethacin in Extremely Low Birth Weight Infants Based on the Predicted Risk of Severe Intraventricular Hemorrhage
Bibliographic record
Abstract
BACKGROUND: Prophylactic indomethacin reduces the risk of severe intraventricular hemorrhage (IVH) but does not reduce death or neurodevelopmental impairment (NDI) among extremely low birth weight (ELBW) infants. Some investigators have suggested that prophylactic indomethacin may have a greater treatment effect on severe IVH among infants at high risk for severe IVH. OBJECTIVE: To determine whether the relative treatment effects of prophylactic indomethacin on severe IVH and the composite outcome of death or NDI vary based on the risk of severe IVH. METHODS: Post hoc analysis of the Trial of Indomethacin Prophylaxis in Preterms (TIPP). We generated a model to predict the risk for severe IVH based on gestational age, birth weight, antenatal steroids, delivery mode, outborn status, sex, and 5-min Apgar score, and we divided the TIPP participants into risk quartiles. We used logistic regression to determine the adjusted odds ratios (aOR) of severe IVH and death or NDI based on indomethacin treatment for each quartile. RESULTS: The relative treatment effects of prophylactic indomethacin on severe IVH did not vary based on the predicted risk of severe IVH: quartile 1: aOR 0.68 (95% confidence interval [CI] 0.19-2.37); quartile 2: aOR 0.61 (95% CI 0.27-1.42); quartile 3: aOR 0.63 (95% CI 0.31-1.31); quartile 4: aOR 0.58 (95% CI 0.32-1.05). The relative treatment effect of prophylactic indomethacin on death or NDI did not vary significantly between quartiles. CONCLUSIONS: These findings do not support selective prophylactic indomethacin treatment to improve long-term outcomes of ELBW infants at high risk for severe IVH.
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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 | 0.005 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".