Exercise Tolerance can Explain the Obesity Paradox in Patients with Systolic Heart Failure: Data from the MECKI Score Research Group
Bibliographic record
Abstract
AIMS: Obesity has been found to be protective in heart failure (HF), a finding leading to the concept of an obesity paradox. We hypothesized that a preserved cardiorespiratory fitness in obese HF patients may affect the relationship between survival and body mass index (BMI) and explain the obesity paradox in HF. METHODS AND RESULTS: A total of 4623 systolic HF patients (LVEF 31.5 ± 9.5%, BMI 26.2 ± 3.6 kg/m(2) ) were recruited and prospectively followed in 24 Italian HF centres belonging to the MECKI Score Research Group. Besides full clinical examination, patients underwent maximal cardiopulmonary exercise test at study enrolment. Median follow-up was 1113 (553-1803) days. The study population was divided according to BMI (<25, 25-30, >30 to ≤35 kg/m(2) ) and predicted peak oxygen consumption (peak VO2 , <50%, 50-80%, >80%). Study endpoints were all-cause and cardiovascular deaths including urgent cardiac transplant. All-cause and cardiovascular deaths occurred in 951 (28.6%, 57.4 per person-years) and 802 cases (17.4%, 48.4 per 1000 person-years), respectively. In the high BMI groups, several prognostic parameters presented better values [LVEF, peak VO2 , ventilation/carbon dioxide slope, renal function, and haemoglobin (P < 0.01)] compared with the lower BMI groups. Both BMI and peak VO2 were significant positive predictors of longer survival: both higher BMI and peak VO2 groups showed lower mortality (P < 0.001). At multivariable analysis and using a matching procedure (age, gender, LVEF, and peak VO2 ), the protective role of BMI disappeared. CONCLUSION: Exercise tolerance affects the relationship between BMI and survival. Cardiorespiratory fitness mitigates the obesity paradox observed in HF patients.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".