Predictive Model for Complications in Total Hip Arthroplasty: Development of a Clinical Tool

To develop a predictive model to estimate complications up to 30 days after total hip arthroplasty (THA), based on clinical and functional variables, aiming at the creation of a practical tool for clinical use.

Prospective cohort study conducted in a public referral hospital, with patients undergoing primary and elective THA between November 2021 and April 2022. The sample included 122 patients (mean age: 56 years, 59.8% men). Clinical, sociodemographic, and functional capacity variables were evaluated and estimated by the Duke Activity Status Index (DASI). Outcomes included clinical complications, early readmission, prolonged hospitalization (> 6 days), and intensive care unit (ICU) stay for more than one day. A logistic regression model was used, with performance evaluated by the C-statistic (area under the curve, AUC), and the model was incorporated into an online tool.

The most prevalent comorbidities were hypertension (61%), diabetes (23%), and dyslipidemia (15%). Complications within 30 days occurred in 13.1% of patients, with surgical wound infection and anemia being the most common events. Dyslipidemia (odds ratio [OR]: 4.70; p  = 0.010), sedentary lifestyle (OR: 4.71; p  = 0.026), high ASA classification (OR: 3.67; p  = 0.035), and functional capacity < 4 metabolic equivalents of task (METs) (OR: 4.08; p  = 0.040) were significant risk factors. The tool is available at https://upneuro.shinyapps.io/atq-pred .

Dyslipidemia, sedentary lifestyle, low functional capacity, and high ASA classification were associated with a higher risk of post-THA complications. The preoperative evaluation should include functional and cardiovascular aspects. The model showed good accuracy, and further studies are needed to validate its clinical application.

This is a prospective cohort study without a control group aimed at identifying prognostic factors for complications after total hip arthroplasty.