Document Type : Original Article
Authors
1 Department of Biostatistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran
2 Department of Surgery, School of Medicine, Ardabil University of Medical Sciences, Ardabil, Iran
3 Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
Abstract
Objective: Elderly people live longer and are more active nowadays; however, their bodily conditions make them more susceptible to injuries. An appropriate prognostic tool tailored for the needs and conditions of the elderly who sustain injuries has not been well elaborated in trauma research. To fill a gap in existing general models, this study has developed a modified model based on injury severity in order to predict trauma-related mortality in older people.
Methods: Data belonging to 643 older patients aged 55 and above who were admitted due to trauma to Fatemi University Hospital in Ardabil between 2019 and 2022 were analyzed. A convenience sampling approach was used, where all eligible patients were included. The study used regression modeling to examine the association between predictor variables and death. A geriatric injury prognostic scale (GIPS) was constructed and evaluated for its efficacy in distinguishing mortality statuses using binary logistic regression. The adjusted odds ratios (ORs), area under the ROC curve (AUC), and Hosmer-Lemeshow test results were reported. The statistical analyses were conducted utilizing the STATA statistical software package, version 17.
Results: The study enrolled 643 trauma patients aged between 55 and 95 years, 62.36% of whom were male. The mean pulse rate (PR) of the patients assessed in the emergency department was 81.7 (SD = 8.2), and 5% had Glasgow Coma Scale (GCS) scores below 13. The mean Injury Severity Score (ISS) for 636 patients was 8 (SD = 8.5), and the in-hospital case fatality proportion was 6.2%. A comprehensive multivariate model was developed using PR per minute, GCS, and ISS that effectively predicted 83.2% (P value < 0.001) of trauma-related mortality in the study population. The model’s area under the ROC curve was 0.995 for GIPS.
Conclusion: The GIPS accurately predicts death probability in the older population, aiding in decision-making for appropriate treatment approaches in the geriatric-specific population.
Keywords
Main Subjects
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