Study of the costs and morbidities of late-preterm birth
Bibliographic record
Abstract
OBJECTIVE: To compare late-preterm infants (33-36 weeks) with term infants (≥37 weeks) on incidence of morbidities in the first 3 years of life and healthcare costs during the first 2 years of life and third year of life. METHODS: Administrative health records of live infants born between January 1, 1997, and December 31, 2000 with 3 years follow-up data (N=35733) were linked. First, diagnoses of morbidities were compared between late-preterm and term infants using Cox's proportional hazards models. Healthcare costs expressed as mean total costs and cost ratios, accrued following initial hospital discharge after birth, were also examined. RESULTS: The three most common reasons for hospitalisation in late-preterm and term infants were acute bronchitis, otitis media and pneumonia. The most frequent reasons for physician visits included acute upper respiratory infections, otitis media and bronchiolitis. The highest HR were detected for chronic bronchitis 1.64 (1.13-2.39), hearing loss 1.56 (1.14-2.15) and bacterial diseases 1.28 (1.09-1.49). The mean total cost for late-preterm infants during the first 2 years of life was $2568 CAD compared with $1285 CAD for term infants, cost ratio =1.99 (95% CI 1.90 to 2.09). In the third year of life, the cost ratio reduced to 1.46 (95% CI 1.39 to 1.54). CONCLUSIONS: Late-preterm infants are at higher risk of specific morbidities compared with term infants. Their mean total costs fall from almost double that of term infants during the first 2 years of life, to just 46% greater in the third year of life.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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 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".