Primary Total Hip Arthroplasty in Patients Who Have a Body Mass Index > 50: Is the Risk Worth the Reward?
Bibliographic record
Abstract
BACKGROUND: The obesity epidemic has given rise to a growing number of patients who have a body mass index (BMI) exceeding 50. As BMI cutoffs are no longer recommended, arthroplasty surgeons continue to push the limits of surgical feasibility in total hip arthroplasty (THA) despite possible risks. METHODS: A retrospective cohort study of patients who underwent primary THA (N = 7,458) was developed, comparing outcomes between patients who had a BMI ≥ 50 (N = 147) and those of other weight classes. We used Cox proportional hazard models to estimate the association between patient BMI and revision risk using overweight patients (BMI 25 to 30) as the reference group. Patients entered the study cohort on their date of surgery and exited on the earliest of the date of revision, date of death, or the end of the study. Patient-reported outcome measures were compared pre- and postoperatively. RESULTS: Increased obesity class led to a gradient of elevated revision risk. In the first year after surgery, THA patients who had a BMI ≥ 50 demonstrated an adjusted hazard ratio (for revision of 11.8 (95% confidence interval [CI] 5.3 to 26.2). This risk was also elevated in patients who had a BMI of 40 to 50 (N = 635, hazard ratio = 3.8, 95% CI = 1.9 to 7.7). Although the patients who had a BMI ≥ 50 had a significantly worse preoperative Oxford-12 Hip score than other overweight patients, at five years, this difference was negligible. CONCLUSIONS: There was an increased risk of early THA revision surgery in patients who had a BMI ≥ 50. This risk plateaued after the first year and was equivalent to other weight classes afterward. Despite worse preoperative function and greater failure rates, this population reports major benefits and high satisfaction with THA. The risk of THA appears to be worth it for most patients who have a BMI ≥ 50.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".