Can Patient Selection Explain the Obesity Paradox in Orthopaedic Hip Surgery? An Analysis of the ACS-NSQIP Registry
Bibliographic record
Abstract
BACKGROUND: The "obesity paradox" is a phenomenon described in prior research in which patients who are obese have been shown to have lower postoperative mortality and morbidity compared with normal-weight individuals. The paradox is that clinical experience suggests that obesity is a risk factor for difficult wound healing and adverse cardiovascular outcomes. We suspect that the obesity paradox may reflect selection bias in which only the healthiest patients who are obese are offered surgery, whereas nonobese surgical patients are comprised of both healthy and unhealthy individuals. We questioned whether the obesity paradox (decreased mortality for patients who are obese) would be present in nonurgent hip surgery in which patients can be carefully selected for surgery but absent in urgent hip surgery where patient selection is minimized. QUESTIONS/PURPOSES: (1) What is the association between obesity and postoperative mortality in urgent and nonurgent hip surgery? (2) How is obesity associated with individual postoperative complications in urgent and nonurgent hip surgery? (3) How is underweight status associated with postoperative mortality and complications in urgent and nonurgent hip surgery? METHODS: We used 2011 to 2014 data from the American College of Surgeons National Surgical Quality Improvement Project (ACS-NSQIP) to identify all adults who underwent nonurgent hip surgery (n = 63,148) and urgent hip surgery (n = 29,047). We used logistic regression models, controlling for covariants including age, sex, anesthesia risk, and comorbidities, to examine the relationship between body mass _index (BMI) category (classified as underweight < 18.5 kg/m, normal 18.5-24.9 kg/m, overweight 25-29.9 kg/m, obese 30-39.9 kg/m, and morbidly obese > 40 kg/m) and adverse outcomes including 30-day mortality and surgical complications including wound complications and cardiovascular events. RESULTS: For patients undergoing nonurgent hip surgery, regression models demonstrate that patients who are morbidly obese were less likely to die within 30 days after surgery (odds ratio [OR], 0.12; 95% confidence interval [CI], 0.01-0.57; p = 0.038) compared with patients with normal BMI, consistent with the obesity paradox. For patients undergoing urgent hip surgery, patients who are morbidly obese had similar odds of death within 30 days compared with patients with normal BMI (OR, 1.18; 95% CI, 0.76-1.76; p = 0.54). Patients who are morbidly obese had higher odds of wound complications in both nonurgent (OR, 4.93; 95% CI, 3.68-6.65; p < 0.001) and urgent cohorts (OR, 4.85; 95% CI, 3.27-7.01; p < 0.001) compared with normal-weight patients. Underweight patients were more likely to die within 30 days in both nonurgent (OR, 3.79; 95% CI, 1.10-9.97; p = 0.015) and urgent cohorts (OR, 1.47; 95% CI, 1.23-1.75; p < 0.001) compared with normal-weight patients. CONCLUSIONS: Patients who are morbidly obese appear to have a reduced risk of death in 30 days after nonurgent hip surgery, but not for urgent hip surgery. Our results suggest that the obesity paradox may be an artifact of selection bias introduced by careful selection of the healthiest patients who are obese for elective hip surgery. Surgeons should continue to consider obesity a risk factor for postoperative mortality and complications such as wound infections for both urgent and nonurgent surgery. LEVEL OF EVIDENCE: Level III, therapeutic study.
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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 | 0.018 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".