A Simple Prediction Rule for All-Cause Mortality in a Cohort Eligible for Bariatric Surgery
Bibliographic record
Abstract
IMPORTANCE: Current eligibility criteria for bariatric surgery use arbitrarily chosen body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) thresholds, an approach that has been criticized as arbitrary and lacking evidence. OBJECTIVES: To verify the importance of BMI as a mortality predictor, to identify other important mortality predictors, and to construct a mortality prediction rule in a population eligible for bariatric surgery. DESIGN: We studied individuals from a population-representative register who met contemporary eligibility criteria for bariatric surgery (BMI, ≥35.0 alone or 30.0-34.9 with an obesity-related comorbidity) from January 1, 1988, through December 31, 1998. We used binary logistic regression to construct a parsimonious model and a clinical prediction rule for 10-year all-cause mortality. SETTING: The United Kingdom General Practice Research Database, a population-representative primary care registry. PARTICIPANTS: Fifteen thousand three hundred ninety-four patients aged 18 to 65 years. EXPOSURE: Bariatric surgery. MAIN OUTCOME AND MEASURE: Ten-year all-cause mortality. RESULTS: Mean (SD) age was 46.9 (11.9) years, BMI was 36.2 (5.5), and 63.2% of the patients were women. All-cause mortality was 2.1%, and mean follow-up duration was 9.9 years. The final model, which included age (odds ratio, 1.09 per year [95% CI, 1.07-1.10]), type 2 diabetes mellitus (2.25 [1.76-2.87]), current smoking (1.62 [1.28-2.06]), and male sex (1.50 [1.20-1.87]), had a C statistic of 0.768. Although BMI significantly predicted mortality (odds ratio, 1.03 per unit [95% CI, 1.01-1.05]), it did not improve model discrimination or calibration. We divided clinical prediction rule scoring into 4 tiers. All-cause mortality was 0.2% in tier 1, 0.9% in tier 2, 2.0% in tier 3, and 5.2% in tier 4. CONCLUSIONS AND RELEVANCE: All-cause 10-year mortality in obese individuals eligible for bariatric surgery can be estimated using a simple 4-variable prediction rule based on age, sex, smoking, and diabetes mellitus. Body mass index was not an important mortality predictor. Further work is needed to define low, moderate, and high absolute risk thresholds and to provide external validation.
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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 | 0.017 | 0.089 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".