Severe Obesity Is Associated With Increased Risk of Early Complications and Extended Length of Stay Following Coronary Artery Bypass Grafting Surgery
Bibliographic record
Abstract
BACKGROUND: Better understanding of the relationship between obesity and postsurgical adverse outcomes is needed to provide quality and efficient care. We examined the relationship of obesity with the incidence of early adverse outcomes and in-hospital length of stay following coronary artery bypass grafting surgery. METHODS AND RESULTS: We analyzed data from 7560 patients who underwent coronary artery bypass grafting. Using body mass index (BMI; in kg/m(2)) of 18.5 to 24.9 as a reference, the associations of 4 BMI categories (25.0-29.9, 30.0-34.9, 35.0-39.9, and ≥40.0) with rates of operative mortality, overall early complications, subgroups of early complications (ie, infection, renal and pulmonary complications), and length of stay were assessed while adjusting for clinical covariates. There was no difference in operative mortality; however, higher risks of overall complications were observed for patients with BMI 35.0 to 39.9 (adjusted odds ratio 1.35, 95% CI 1.11-1.63) and ≥40.0 (adjusted odds ratio 1.56, 95% CI 1.21-2.01). Subgroup analyses identified obesity as an independent risk factor for infection (BMI 30.0-34.9: adjusted odds ratio 1.60, 95% CI 1.24-2.05; BMI 35.0-39.9: adjusted odds ratio 2.34, 95% CI 1.73-3.17; BMI ≥40.0: adjusted odds ratio 3.29, 95% CI 2.30-4.71). Median length of stay was longer with BMI ≥40.0 than with BMI 18.5 to 24.9 (median 7.0 days [interquartile range 5 to 10] versus 6.0 days [interquartile range 5 to 9], P=0.026). CONCLUSIONS: BMI ≥40.0 was an independent risk factor for longer length of stay, and infection was a potentially modifiable risk factor. Greater perioperative attention and intervention to control the risks associated with infection and length of stay in patients with BMI ≥40.0 may improve patient care quality and efficiency.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".