ASA Physical Status Classification Improves Predictive Ability of a Validated Trauma Risk Score

Konda, Sanjit R.; Parola, Rown; Perskin, Cody; Egol, Kenneth A.

INTRODUCTION: The Score for Trauma Triage in the Geriatric and Middle-Aged (STTGMA) is a validated mortality risk score that evaluates 4 major physiologic criteria: age, comorbidities, vital signs, and anatomic injuries. The aim of this study was to investigate whether the addition of ASA physical status classification system to the STTGMA tool would improve risk stratification of a middle-aged and elderly trauma population. METHODS: A total of 1332 patients aged 55 years and older who sustained a hip fracture through a low-energy mechanism between October 2014 and February 2020 were included. The STTGMA and STTGMAASA mortality risk scores were calculated. The ability of the models to predict inpatient mortality was compared using area under the receiver operating characteristic curves (AUROCs) by DeLong’s test. Patients were stratified into minimal, low, moderate, and high risk cohorts based on their risk scores. Comparative analyses between risk score stratification distribution of mortality, complications, length of stay, ICU admission, and readmission were performed using Fisher’s exact test. Total cost of admission was fitted by univariate linear regression with STTGMA and STTGMAASA. RESULTS: There were 27 inpatient mortalities (2.0%). When STTGMA was used, the AUROC was 0.742. When STTGMAASA was used, the AUROC was 0.823. DeLong’s test resulted in significant difference in predictive capacity for inpatient mortality between STTGMA and STTGMAASA (p = 0.04). Risk score stratification yielded significantly different distribution of all outcomes between risk cohorts (p < 0.01). STTGMAASA stratification produced a larger percentage of all negative outcomes with increasing risk cohort. Total hospital cost was statistically correlated with both STTGMAASA (p < 0.01) and STTGMA (p = 0.02). CONCLUSION: Including ASA physical status as a variable in STTGMA improves the model’s ability to predict inpatient mortality and risk stratify middle-aged and geriatric hip fracture patients.