The Care of Preterm Infants With Birth Weight Below 1250 g
Bibliographic record
Abstract
BACKGROUND: In Germany, controversy currently surrounds the contention that the quality of care for preterm infants weighing less than 1250 g is best assured by requiring that centers treat a minimum of 30 such cases per year. METHODS: A risk-adjusted model was developed on the basis of neonatal data from 7405 preterm infants treated in German centers, and the effect of caseload on risk-adjusted mortality was analyzed. In addition, the discriminative ability of the minimal caseload requirement for quality assessment was studied. The authors designate the quality of care in a particular center as above average if the observed mortality is lower than would have been expected from the risk profile of the preterm infants treated there. RESULTS: Risk-adjusted mortality was found to be significantly higher in smaller centers (those with fewer than 30 cases per year) than in larger ones (odds ratio, 1.34). Even among centers whose caseload exceeded the minimum requirement, there was still marked variability in risk-adjusted mortality (range: 3.5% to 28.6%). Of all the preterm infants treated in larger centers, 56% were treated in centers with above-average quality of care. 44% of the centers with above-average quality of care had caseloads in the range of 14 to 29 cases per year. CONCLUSION: Because of the marked variability in risk-adjusted mortality, even among larger centers, a caseload of 30 or more cases per year is not a suitable indicator of the quality of care. The neonatal data of external quality assurance should be used to develop an instrument for quality-based coordination of care that takes not just morbidity and mortality, but also the treating centers' competence profiles into account.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".