Impact of bariatric surgery on patients with chronic kidney disease and severe obesity: multiple-linked population-based cohort study
Bibliographic record
Abstract
BACKGROUND: Chronic kidney disease (CKD) is prevalent among patients with obesity, contributing to increased morbidity and mortality. Metabolic bariatric surgery (MBS) may improve kidney outcomes, but its long-term effects remain unclear. The aim of this study was to examine the association between bariatric surgery and mortality and major adverse kidney events (MAKE) in patients with a diagnosis of CKD and severe obesity. METHODS: Patients with a diagnosis of CKD (stage ≥3 and estimated glomerular filtration rate (eGFR) ≤60 ml per min per 1.73 m2) and BMI ≥35 kg/m2 or who underwent bariatric surgery from 2010 to 2016 in Ontario, Canada, were included. Non-surgical controls were identified from a primary care database. Multiple-linked administrative databases were used to define confounders, including age, BMI, sex, co-morbidities, socio-economic status, psychiatric history, healthcare utilization, substance misuse, and cancer screening. The primary outcomes were all-cause mortality and MAKE (a composite outcome of mortality, 50% decline in eGFR, dialysis initiation, and hospital admission for heart failure, myocardial infarction, and acute kidney injury). A multivariable Cox proportional hazards model was used for analysis. RESULTS: Among 1538 patients (563 surgical and 975 non-surgical) followed for a median of 7.7 years, there were 285 deaths (207 (21.2%) non-surgical and 78 (13.9%) surgical). MBS was associated with 52% lower hazards of mortality (HR 0.48 (95% c.i. 0.34 to 0.67)) and 53% lower hazards of MAKE (HR 0.47 (95% c.i. 0.39 to 0.57)). Benefits were greater in females, patients aged >55 years, and those with a BMI >40 kg/m2. CONCLUSION: MBS was associated with reduced mortality and improved kidney outcomes in CKD patients, particularly in older individuals, females, and those with a higher BMI, highlighting its potential role in high-risk patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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; a candidate call from one teacher head, 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".