Predicting Mortality in Elderly Spine Trauma Patients

Abstract

Study Design. Retrospective analysis on prospectively collected data. Objective. The aim of this study was to construct a clinical prediction model for 90-day mortality in elderly patients with traumatic spine injuries. Summary of Background Data. Spine trauma in the elderly population is increasing. Comparing elderly spine trauma patients to younger patients with similar injuries proves challenging due to the extensive comorbidities and frailty found in the elderly. There is a paucity of evidence to predict survival of elderly patients following traumatic spinal injuries. Methods. All patients 65+ with spine trauma presenting to a level I trauma center from 2010 to 2019 were reviewed from a prospectively maintained trauma registry. Retrospective chart review was performed to record injury, frailty scores, comorbidities, presence of spinal cord injury, imaging evidence of sarcopenia and osteopenia, mortality, and complications. We preselected 13 variables for our multivariable logistic regression model: hypotension on admission, gender, marital status, age, max Abbreviated Injury Scale, Modified Frailty Index, surgical treatment, hematocrit, white blood count, spinal cord injury, closed head injury, injury level and presence of high energy mechanism. The performance of the prediction model was evaluated using a concordance index and calibration plot. The model was internally validated via bootstrap approach. Results. Over the 9-year period, 1746 patients met inclusion criteria; 359 (20.6%) patients died within 90 days after presenting with spine trauma. The most important predictors for 90-day mortality were age, hypotension, closed head injury, max Abbreviated Injury Scale and hematocrit. There was an optimism-corrected C-index of 0.77. A calculator was created to predict a personalized mortality risk. Conclusion. The incidence of spine trauma in elderly patients continues to increase. Previous publications described preexisting conditions that imply increased mortality, but ours is the first to develop a predictive calculator. Prospective research is planned to externally validate this model to better determine its predictive value and utility in the clinical setting.

Improving translatability of spinal cord injury research by including age as a demographic variable

“…Additionally, animal models of SCI do not include comorbidities commonly found in an aging population such as cardiovascular disease, cancer, etc., which increases the frailty and worsens outcomes of older populations by increasing the frequency of adverse events and length of hospitalization ( Velanovich et al, 2013 ; Banaszek et al, 2020 ; Dicpinigaitis et al, 2022 ). Correspondingly, frailty has been correlated as a predictor of mortality in elderly individuals ( Carlile et al, 2022 ). Evidence from thoracoabdominal aortic aneurysm repair indicates that paraplegia risk may be correlated with frailty [using sarcopenia (core muscle loss) as a marker of frailty], however, the extent to which age and frailty interact to affect SCI outcomes remains understudied.…”