Cardiorespiratory Fitness Impact on All-Cause Mortality in Prediabetic Veterans
Bibliographic record
Abstract
Background: The objective of this study was to evaluate the role of cardiorespiratory fitness (CRF) on all-cause mortality in prediabetic veterans. Methods: In this prospective cohort study, CRF was calculated from metabolic equivalents (METs) obtained from routine exercise tolerance testing in a cohort of 1,118 prediabetic veterans. Four fitness categories were established: low-fit ( 8.5 METs; > 75th percentile). Date of death was verified from the Veterans Affairs Beneficiary Identification and Record Locator System File. Results: The mean follow-up period was 7.7 years (8,610 person-years) and there were a total of 251 deaths, averaging 29.1 events per 1,000 person-years. An inverse and graded association between CRF and mortality risk was observed (P = 0.002). For every 1-MET increase in CRF, the adjusted mortality was lowered by 13% (hazard ratios (HR) = 0.87; CI: 0.81 - 0.94, P 8.5 METs) compared to least-fit individuals. With increasing incidence of prediabetes as well as diminished response to preventative lifestyle modifications, enhanced CRF should be advocated in prediabetic individuals. J Endocrinol Metab. 2015;5(3):215-219 doi: http://dx.doi.org/10.14740/jem284w
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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 | 0.001 |
| 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".