Joint associations of obesity and estimated GFR with clinical outcomes: a population-based cohort study
Bibliographic record
Abstract
Despite the interrelationships between obesity, eGFR and albuminuria, few large studies examine how obesity modifies the association between these markers of kidney function and adverse clinical outcomes. We examined the joint associations between obesity, eGFR and albuminuria on four clinical outcomes (death, end-stage renal disease [ESRD], myocardial infarction [MI], and placement in a long-term care facility) using a population-based cohort with procedures from Alberta. Obesity was defined by body mass index ≥35 kg/m 2 as defined by a fee modifier applied to an eligible procedure. We studied 1,293,362 participants, of whom 171,650 (13.3%) had documented obesity (BMI ≥ 35 kg/m 2 based on claims data) and 1,121,712 (86.7%) did not. The association between eGFR and death was J-shaped for participants with and without documented obesity. After full adjustment, obesity tended to be associated with slightly lower odds of mortality (OR range 0.71–1.02; p for interaction between obesity and eGFR 0.008). For participants with and without obesity, the adjusted odds of ESRD were lowest for participants with eGFR > 90 mL/min*1.73m 2 and increased with lower eGFR, with no evidence of an interaction with obesity ( p = 0.37). Although albuminuria and obesity were both associated with higher odds of ESRD, the excess risk associated with obesity was substantially attenuated at higher levels of albuminuria (p for interaction 0.0006). The excess risk of MI associated with obesity was observed at eGFR > 60 mL/min*1.73m 2 but not at lower eGFR (p for interaction < 0.0001). Participants with obesity had a higher adjusted likelihood of placement in long-term care than those without, and the likelihood of such placement was higher at lower eGFR for those with and without obesity (p for interaction = 0.57). We found significant interactions between obesity and eGFR and/or albuminuria on the likelihood of adverse outcomes including death and ESRD. Since obesity is common, risk prediction tools for people with CKD might be improved by adding information on BMI or other proxies for body size in addition to eGFR and albuminuria.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".