Can We Accurately Predict Which Geriatric and Middle-Aged Hip Fracture Patients Will Experience a Delay to Surgery?

Introduction: This study sought to investigate whether a validated trauma triage risk assessment tool can predict time to surgery and delay to surgery. Materials and Methods: Patients aged 55 and older who were admitted for operative repair or arthroplasty of a hip fracture over a 3-year period at a single academic institution were included. Risk quartiles were constructed using Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) calculations. Negative binomial and multivariable logistic regression were used to evaluate time to surgery and delay to surgery, respectively. Pairwise comparisons were performed to evaluate 30-day mortality rates and demonstrate the effectiveness of the STTGMA tool in triaging mortality risk. Results: Six hundred eleven patients met inclusion criteria with mean age 81.1 ± 10.5 years. Injuries occurred mainly secondary to low-energy mechanisms (97.9%). Median time to surgery (31.9 hours overall) was significantly associated with STTGMA stratification (P = .002). Moderate-risk patients had 33% longer (P = .019) and high-risk patients had 28% longer time to surgery (P = .041) compared to minimal risk patients. Delay to surgery (26.4% overall) was significantly associated with STTGMA stratification (P = .015). Low-risk patients had 2.14× higher odds (P = .009), moderate-risk patients had 2.70× higher odds (P = .001), and high-risk patients had 2.18× higher odds of delay to surgery (P = .009) compared to minimal risk patients. High-risk patients experienced higher 30-day mortality compared to minimal (P < .001), low (P = .046), and moderate-risk patients (P = .046). Discussion: Patients in higher STTGMA quartiles encountered longer time to surgery, greater operative delays, and higher 30-day mortality. Conclusion: Score for Trauma Triage in the Geriatric and Middle-Aged can quickly identify hip fracture patients at risk for a delay to surgery and may allow treatment teams to optimize surgical timing by proactively targeting these patients. Level of Evidence: Prognostic Level III.