Development and validation of the APEX-HBD SCORe: a multivariable prediction model for postoperative complications in patients undergoing shoulder arthroplasty.

Abstract

The incidence of total shoulder arthroplasty (TSA) has risen significantly, driven by expanded indications. This study aims to derive and validate a model for classifying patients based on the risk of short-term complications using logistic regression (LR) and other machine learning (ML) techniques. We analyzed de-identified data from the American College of Surgeons' NSQIP database (2005-2022), identifying 39,028 patients who underwent SA using CPT codes. The dataset was split into derivation (60%) and validation (40%) cohorts. We constructed baseline classifiers for complications using backward stepwise multivariate LR and developed the APEX-HBD SCORe, a point-based system to stratify patients into low (<5%), moderate (5-11%), and high-risk (≥19%) categories. To improve accuracy, we also developed ML models, including Gradient Boosting, AdaBoost, Random Forest, and Extra Randomized Trees, using the same predictors identified in the LR model. The derivation cohort (23,417 patients) reported 1,476 (6.3%) patients with complications. LR identified 11 predictors, including albumin levels, hematocrit, ASA classification, preoperative transfusion, and other relevant factors. LR achieved area under the curves of 72%, 75%, 77%, and 63% for any, medical, serious medical, and surgical complications, respectively, in the derivation cohort, and 70%, 75%, 73%, and 58% in the validation cohort-outperforming the 5-item modified frailty index. Gradient Boosting performed best among ML models, with area under the curves of 73%, 82%, 76%, and 67%. APEX-HBD SCORe risk stratification revealed a progressive increase in complication rates across categories, confirmed in the validation cohort. This 16-year analysis introduces the APEX-HBD SCORe, a validated ML-augmented tool predicting 30-day complications using 11 patient factors. It aids in patient stratification, counseling, preoperative planning, and tailored postoperative management.