Falls During Inpatient Rehabilitation After Spinal Cord Injury: Characterization, Clock-Hour Visualization, and Time to Event Predictors

Abstract

ObjectivesTo (1) determine fall characteristics (eg, cause, location, witnesses) of inpatients with spinal cord injury (SCI) and whether they were different for ambulatory persons vs wheelchair users; (2) visualize the total number of daily falls per clock-hour for different inpatients’ features (eg, cause of injury, age); (3) compare clinical and demographic characteristics of inpatients who experienced a first fall event vs inpatients who did not experience such event; and (4) identify first fall event predictors. DesignRetrospective observational cohort study. SettingInstitution for inpatient neurologic rehabilitation. ParticipantsPersons with SCI (N=1294) admitted to a rehabilitation facility between 2005 and 2022. InterventionsNot applicable. Main Outcome MeasuresFunctional independence measure (FIM), Hospital Anxiety and Depression Scale (HADS), American Spinal Injury Association Impairment Scale (AIS), and Spinal Cord Independence Measure (SCIM) at admission. Kaplan-Meier survival curves and Cox proportional hazards models were used. ResultsA total of 502 fall events were experienced by 369 ambulatory inpatients (19.8%) and wheelchair users (80.2%) in 63.9% of cases being alone, with cause, situation, and location significantly different in both groups. Clock-hour visualizations revealed an absolute peak at 12 AM (complete or incomplete injuries, with paraplegia or tetraplegia) but a relative peak at 9 AM mainly including incomplete patients with paraplegia. Of the (n=1294) included patients, 16.8% experienced at least 1 fall. Fallen patients reported higher levels of HADS depression, lower total SCIM, and longer time since injury to admission, with no differences in age, sex, educational level, FIM (quasi-significant), and AIS grade. Multivariable Cox proportional hazards identified time since injury to admission and AIS grade D as significant predictors of first fall event. ConclusionsFalls identification, characterization, and clock-hour visualization can support decisions for mitigation strategies specifically addressed to inpatients with SCI. Fall predictors were identified as a first step for future research.