Introduction
Patients undergoing total hip arthroplasty (THA) in tertiary centres often present with complex comorbidities that increase the risk of perioperative adverse events (AE). While fast-track and outpatient protocols are expanding, reliable risk stratification tools tailored to high-risk European populations remain limited. This study aimed to (1) compare comorbidity burden in a high-risk population to national data, (2) determine incidence and risk factors for in-hospital AE and (3) develop a simple, pragmatic score to identify patients at elevated AE risk.
Materials and methods
We retrospectively analyzed 4,101 elective primary THA cases from a German tertiary care centre (2010–2019). Comorbidity burden was quantified using the Elixhauser Comorbidities (EC) and benchmarked against national registry data (EPRD). Independent predictors of in-hospital AE were identified using multivariate logistic regression. These variables were then used to develop a pragmatic preoperative clinical risk score via LASSO regression, internally validated with 10-fold cross-validation and bootstrapping.
Results
Compared to the national registry, our cohort showed significantly higher rates of major comorbidities, including cardiac valvular disease, diabetes, and fluid/electrolyte disorders. The overall in-hospital AE rate was 2.6%. Six comorbidities—including pulmonary circulation disorders (OR 10.7, 95% CI: 3.6–31.8)—were independently associated with AE. The derived LASSO model demonstrated strong discrimination (AUC 0.80; 95% CI: 0.75–0.84) and calibration (Brier score 0.07). A cutoff score ≥ 2 identified patients with an AE rate of > 7%, while scores < 2 corresponded to an NPV of 0.99, supporting its utility in identifying low-risk patients for fast-track pathways.
Conclusions
Patients treated in tertiary centres exhibit elevated comorbidity burden but maintain acceptable perioperative AE rate. A simple, validated clinical score can flag patients at substantially increased risk of in-hospital AE who may benefit from closer in-hospital surveillance and effectively identify low-risk candidates for fast-track THA pathways. Further external validation is warranted.
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