Impaired myocardial reserve underlies reduced exercise capacity and heart rate recovery in preterm-born young adults
Bibliographic record
Abstract
AIMS: We tested the hypothesis that the known reduction in myocardial functional reserve in preterm-born young adults is an independent predictor of exercise capacity (peak VO2) and heart rate recovery (HRR). METHODS AND RESULTS: We recruited 101 normotensive young adults (n = 47 born preterm; 32.8 ± 3.2 weeks' gestation and n = 54 term-born controls). Peak VO2 was determined by cardiopulmonary exercise testing (CPET), and lung function assessed using spirometry. Percentage predicted values were then calculated. HRR was defined as the decrease from peak HR to 1 min (HRR1) and 2 min of recovery (HRR2). Four-chamber echocardiography views were acquired at rest and exercise at 40% and 60% of CPET peak power. Change in left ventricular ejection fraction from rest to each work intensity was calculated (EFΔ40% and EFΔ60%) to estimate myocardial functional reserve. Peak VO2 and per cent of predicted peak VO2 were lower in preterm-born young adults compared with controls (33.6 ± 8.6 vs. 40.1 ± 9.0 mL/kg/min, P = 0.003 and 94% ± 20% vs. 108% ± 25%, P = 0.001). HRR1 was similar between groups. HRR2 decreased less in preterm-born young adults compared with controls (-36 ± 13 vs. -43 ± 11 b.p.m., P = 0.039). In young adults born preterm, but not in controls, EFΔ40% and EFΔ60% correlated with per cent of predicted peak VO2 (r2 = 0.430, P = 0.015 and r2 = 0.345, P = 0.021). Similarly, EFΔ60% correlated with HRR1 and HRR2 only in those born preterm (r2 = 0.611, P = 0.002 and r2 = 0.663, P = 0.001). CONCLUSIONS: Impaired myocardial functional reserve underlies reductions in peak VO2 and HRR in young adults born moderately preterm. Peak VO2 and HRR may aid risk stratification and treatment monitoring in this population.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".