Impact of pretransplant recipient body mass index on post heart transplant mortality: A systematic review and meta‐analysis
Bibliographic record
Abstract
Abstract The ISHLT 's 2016 Guidelines on the selection of heart transplant ( HT ) candidates recommends weight loss prior to listing for persons with body mass (BMI) index greater than 35 kg/m 2 . We conducted a systematic review to assess the impact of BMI on all‐cause mortality. We searched to identify eligible observational studies that followed HT recipients. We used the GRADE system to quantify absolute effects and quality of evidence, and meta‐analyzed survival curves to assess post‐transplant mortality across BMI categories. We found a significantly increased risk of mortality in patients with BMI > 30 kg/m 2 across all age categories, independently of transplant era and study source ( BMI 30‐34.9: HR 1.10, 95% CI 1.04‐1.17; BMI ≥ 35: HR 1.24, 95% CI 1.12‐1.38). We also found an increased risk of death in underweight ( BMI < 18.5 kg/m 2 ) candidates over 39 years of age (Age 40‐65: HR 1.24, 95% CI 1.02‐1.53; Age > 65: HR 1.70, 95% 1.13‐2.57). We found obesity and underweight BMI to be associated with mortality post‐ HT . The similar and overlapping increased risk of mortality in patients with BMI 30‐34.9 and BMI ≥ 35 does not support the recently updated ISHLT guidelines. Future evidence in the form of randomized controlled trials is required to assess effectiveness of interventions targeting obesity‐related comorbidities and weight management.
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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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.015 | 0.010 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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; both teacher heads agree on what is shown here.
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".