A Lung Ultrasound Severity Score Predicts Chronic Lung Disease in Preterm Infants
Why this work is in the frame
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Bibliographic record
Abstract
Objective To test the hypothesis that a lung ultrasound severity score (LUSsc) can predict the development of chronic lung disease (CLD) in preterm neonates. Study Design Preterm infants <30 weeks' gestational age were enrolled in this study. Lung ultrasound (LUS) was performed between 1 and 9 postnatal weeks. All ultrasound studies were done assessing three lung zones on each lung. Each zone was given a score between 0 and 3. A receiver operating characteristic curve was constructed to assess the ability of LUSsc to predict CLD. Results We studied 27 infants at a median (interquartile range [IQR]) gestational age and birth weight of 26 weeks (25–29) and 780 g (530–1,045), respectively. Median (IQR) postnatal age at the time of LUS studies was 5 (2–8) weeks. Fourteen infants who developed CLD underwent 34 studies. Thirteen infants without CLD underwent 30 studies. Those who developed CLD had a higher LUSsc than those who did not (median [IQR] of scores: 9 [6–12] vs. 3 [1–4], p < 0.0001). An LUSsc cutoff of 6 has a sensitivity and specificity of 76 and 97% and positive and negative predictive values of 95 and 82%, respectively. Adding gestational age < 27 weeks improved sensitivity and specificity to 86 and 98% and positive and negative predictive values to 97 and 88%. Conclusion LUSsc between 2 and 8 weeks can predict development of CLD in preterm neonates.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it