Impact of clinical subtypes of preterm birth on child health and development
Bibliographic record
Abstract
IntroductionPreterm birth (birth <37 weeks of gestation) is common. While the clinical conditions leading to preterm birth are heterogeneous, most studies examining the short- and long-term consequences of preterm birth on child health and development, only consider the gestational age at delivery, and not the underlying mechanism of preterm birth. Objectives and ApproachMaternal hospitalization and perinatal data for deliveries occurring in Alberta, Canada in 2004, 2009, and 2014 were linked to identify underlying mechanisms for delivery (i.e., infection/inflammation (I/I), placental dysfunction (PD), both, or neither). Linked hospitalization, emergency department, and physician claims data were used to assess child health outcomes up to age 10. Chi-square tests were used to assess differences in the absolute rate of each outcome stratified by gestational age at delivery and underlying mechanism for delivery. Logistic regression was used to assess relative differences following adjustment for confounders compared to term infants without exposure to I/I or PD. ResultsA total of 134,424 children were included in the analysis. For preterm births occurring <32 weeks of gestation, no differences were observed in child health outcomes based on the underlying mechanism of preterm birth. However, infants born at 32-33 weeks following PD compared to I/I had significantly higher odds (PD:69.1%, OR=29.7, 95% CI:25.7-34.2 vs. I/I:47.2%, OR=18.7, 95% CI:16.8-20.9) of neonatal morbidity; while those born at 34-36 weeks had increased odds of neonatal morbidity (PD:21.1%, OR=5.1, 95% CI: 4.7-5.5 vs. I/I:16.2%, OR=3.7, 95% CI:3.4-3.9) and developmental disabilities (PD:3.3%, OR=2.2, 95% CI:1.8-2.6 vs. I/I:1.6%, OR=1.7, 95% CI:1.4-2.0). No differences were observed in mortality by sub-type of preterm birth; however, as expected perinatal mortality rates were significantly more common in preterm than term births. Conclusion/ImplicationsBoth the short- and long-term outcomes of preterm birth differ by the underlying mechanism leading to preterm delivery. Having a clearer prognosis for infants born preterm may promote the use of clinical interventions earlier for children at increased risk, leading to improved child health and development.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".