Bariatric Surgery as a Bridge to Heart Transplantation in Morbidly Obese Patients
Bibliographic record
Abstract
Class 2 obesity or greater [body mass index (BMI) >35 kg/m2] is a relative contraindication for heart transplant due to its associated perioperative risks and mortality. Whether bariatric surgery can act as a potential bridging procedure to heart transplantation is unknown. The aim of this systematic review and meta-analysis is to investigate the role of bariatric surgery on improving transplant candidacy in patients with end-stage heart failure (ESHF). MEDLINE, EMBASE, CENTRAL, and PubMed databases were searched up to September 2019 for studies that performed bariatric surgery on patients with severe obesity and ESHF. Outcomes of interest included incidence of patients listed for heart transplantation after bariatric surgery, proportion of patients that successfully received transplant, the change in BMI after bariatric surgery, and 30-day complications. Pooled estimates were calculated using a random-effects meta-analysis of proportions. Eleven studies with 98 patients were included. Mean preoperative BMI was 44.9 (2.1) kg/m2 and BMI after surgery was 33.2 (2.3) kg/m2 with an absolute BMI reduction of 26.1%. After bariatric surgery, 71% [95% confidence interval (CI), 55-86%] of patients with ESHF were listed for transplantation. The mean time from bariatric surgery to receiving a heart transplant was 14.9 (4.0) months. Of the listed patients, 57% (95% CI, 39-74%) successfully received heart transplant. The rate of 30-day mortality after bariatric surgery was 0%, and the 30-day major and minor complications after bariatric surgery was 28% (95% CI, 10-49%). Bariatric surgery can facilitate sustained weight loss in obese patients with ESHF, improving heart transplant candidacy and the incidence of transplantation.
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.019 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".