Impaired lung function and associated risk factors in children born prematurely: a systematic review and meta-analysis
Bibliographic record
Abstract
Background Immature lung development and respiratory morbidity place preterm-born children at high risk of long-term pulmonary sequelae. This systematic review and meta-analysis aims to quantify lung function in preterm-born children and identify risk factors for a compromised lung function. Methods We searched MEDLINE, Embase, Cochrane Library, Web of Science and Scopus for relevant studies published on preterm cohorts born since 1990. Studies comparing forced expiratory volume in 1 s (FEV 1 ) in preterm-born children aged ≥5 years to term-born controls or normative data were included. Study quality was assessed using the Newcastle–Ottawa Scale for cohort studies. Standardised mean differences in FEV 1 and secondary spirometry outcomes per study were pooled using meta-analysis. The impact of different demographic and neonatal variables on studies’ FEV 1 effect sizes was investigated by meta-regression analyses. Certainty of evidence was assessed using the Grading of Recommendations, Assessment, Development, and Evaluations framework. Results We identified 42 studies with unique cohorts including 4743 preterm children and 9843 controls. Median gestational age in the studies was 28.0 weeks and age at assessment ranged from 6.7 to 16.7 years. Preterm children had lower FEV 1 than controls (−0.58 sd , 95% CI −0.69– −0.47 sd , p<0.001) resulting in a relative risk of 2.9 (95% CI 2.4–3.4) for abnormal outcome, with high certainty of evidence. FEV 1 was significantly associated with gestational age, birthweight, bronchopulmonary dysplasia and invasive mechanical ventilation in univariate meta-regression analyses (R 2 =36–96%). Conclusion This systematic review shows robust evidence of impaired lung function in preterm-born children with a high certainty of evidence.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.024 | 0.045 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".