Abstract Objectives To analyse survival predictors including injury patterns, physiological parameters, timing of interventions, and healthcare delivery factors across different age groups in trauma patients. Design Single-centre retrospective cohort study. Participants 8,300 trauma patients stratified by age groups (35, 35-50, 51-75, 75 years). Variables Primary variables included injury patterns across seven body regions, clinical parameters (ISS, GCS, Probability of Survival, shock status), and healthcare delivery metrics (Time to CT, consultant presence, hospital/ICU length of stay). Statistical Methods Age-stratified multivariate logistic regression models with ROC curve analysis for model performance evaluation. Results Multivariate analysis revealed multiple injuries in 98.89% of patients (adjusted OR 1.83, 95% CI 1.42-2.36, p0.001), with significantly higher survival rates (93.75%) compared to single injuries (83.87%). The predominant pattern was three to five injuries (52.91%, χ2=187.3, p0.001), with a decreasing frequency gradient thereafter (β=-0.34, p0.001). Age-stratified survival analysis demonstrated significant decline (log-rank p0.001) from 95.7% (35 years) to 85.6% (75 years), with inflection point at 51 years (HR 1.58, 95% CI 1.36-1.84). Time-to-intervention analysis showed median CT time of 27.0 minutes (IQR 18.5-42.0), with consultant presence (66.9%) significantly impacting survival (adjusted OR 1.92, 95% CI 1.63-2.26, p0.001). ROC analysis of the predictive model showed excellent discrimination (AUC 0.89, 95% CI 0.87-0.91). Conclusions The injury patterns significantly impact outcomes, Age consistently emerged as a crucial modifier across all predictors, while healthcare delivery metrics, particularly timing of interventions, showed age-dependent effects Findings suggest the need for pattern-specific approaches to trauma care, age-adjusted intervention timing, modified scoring systems for elderly patients.
Devkaran et al. (Fri,) studied this question.