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Total Hip Arthroplasty in Patients Who Have a Body Mass Index ≥ 40: Outcomes at an Institution Without Cutoffs
Carlos Salazar1, Vishal Shankar1, Aedan Hanna2
1Albert Einstein College of Medicine, Bronx, New York.
Background:
Morbid obesity (body Mass Index [BMI] ≥ 40) has been associated with increased perioperative risk following total hip arthroplasty (THA), leading many institutions to impose strict BMI cutoffs. Our institution does not restrict THA based on BMI.
Methods:
A retrospective review was conducted of 3,577 primary THAs performed between June 2016 and April 2024 at a single academic center. Patients were stratified by BMI less than 40 (n = 3,169) and BMI ≥ 40 (n = 408). Primary outcomes were return to the operating room (OR) and revision surgery. Secondary outcomes included infection and aseptic implant failure. Multivariable Cox and logistic regression analyses were performed, including a sensitivity analysis using three BMI categories (less than 30, 30 to 39.9, and ≥ 40).
Results:
Patients who had a BMI ≥ 40 were younger, and had higher American Society of Anesthesiologists (ASA) classifications (83.1% ASA 3 to 4 versus 42.5%, P < 0.01). Infection (2.9 versus 1.1%, P < 0.01), return to OR (6.4 versus 3.0%, P < 0.01), and revision surgery (4.7 versus 2.2%, P < 0.01) were more common in the BMI ≥ 40 cohort. A body mass index ≥ 40 independently predicted return to OR (HR [hazard ratio] 1.63, P = 0.03) and infection (odds ratio [OR] 2.94, P < 0.01). Sensitivity analyses demonstrated that increased perioperative risk was primarily driven by the BMI ≥ 40 cohort, whereas BMI 30 to 39.9 was not associated with increased risk compared with BMI less than 30.
Conclusions:
Morbid obesity is associated with increased postoperative infection and return to the OR following THA. However, patients who had a BMI ≥ 40 demonstrated substantially greater medical complexity, suggesting that perioperative risk is influenced by both BMI and associated comorbidity burden. These findings support individualized, risk-adjusted patient selection and perioperative optimization.