The long-term impact of very preterm birth on adult bone mineral density
Bibliographic record
Abstract
Introduction Preterm infants are at increased risk of osteopenia of prematurity due to insufficient bone mineral accretion. Data on long term effects of prematurity on bone health are conflicting. This study aimed to compare bone mineral density (BMD) in young adults born very preterm and full-term controls and to examine factors associated with long-term bone health. Methods This observational cross-sectional study enrolled 101 young adults (18–29 years) born <29 weeks of gestation and 95 sex- and age-matched full-term controls. Participants underwent dual-energy X-ray absorptiometry to measure areal BMD and body composition. Generalized estimated equations were used to compare groups adjusting for height Z -score, lean body mass and fat mass. Results Adults born preterm were shorter and lighter than full-term controls. Areal BMD was reduced at the lumbar spine, the femoral neck and whole body in the preterm versus full-term group, but after adjustment, areal BMD Z -score was only significantly lower at the femoral neck by −0.3 unit (95% confidence interval −0.6 to −0.0). Low BMD ( Z -score ≤ −1 standard deviation) at any site was observed in 53% of adults born preterm versus 28% of full-term controls, but this was not statistically significantly different. We did not identify any neonatal factors associated with lower BMD within the preterm group. Conclusions Very preterm birth is associated with lower areal BMD at the femoral neck in young adulthood, even after accounting for body size. Whether this will translate into higher risk of osteoporotic fractures later in life remains unknown.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".