Left ventricular volume as a predictor of exercise capacity and functional independence in individuals with normal ejection fraction
Bibliographic record
Abstract
AIMS: Low cardiorespiratory fitness (CRF) is associated with functional disability, heart failure and mortality. Left ventricular (LV) end-diastolic volume (LVEDV) has been linked with CRF, but its utility as a diagnostic marker of low CRF has not been tested. METHODS: This multi-center international cohort examined the relationship between LV size on echocardiography and CRF (peak oxygen uptake [peak VO2] from cardiopulmonary exercise testing) in individuals with LV ejection fraction ≥50%. Absolute and BSA-indexed LVEDV (LVEDVi) were tested as predictors of low CRF and functional disability (peak VO2 <1100ml/min or <18 ml/kg/min) and compared against candidate measures of cardiac structure and function. RESULTS: 2876 individuals (309 endurance athletes, 251 healthy non-athletes, 1969 individuals with unexplained dyspnea, 347 individuals with heart failure with preserved ejection fraction) were included. For the entire cohort, LVEDV had the strongest univariable association with peak VO2 (R2 =0.45, standardized [std]β 0.67, p<0.001) and remained the strongest independent predictor of peak VO2 after adjusting for age, sex and BMI (stdβ 0.30, p<0.001). LVEDV was better at identifying low CRF than most established echocardiographic measures (LVEDV AUC 0.72; LVEDVi AUC 0.71), but equivalent to the E/e' ratio. The probability of achieving a peak VO2 below the functional independence threshold was highest for smaller ventricular volumes, with LVEDV and LVEDVi of 88ml and 57ml/m2 providing the optimal cut-points, respectively. CONCLUSIONS: Small resting ventricular size is associated with a higher probability of low CRF and functional disability. LV size is the strongest independent echocardiographic predictor of CRF across the health-disease continuum.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".