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

Objectives: To (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.

Design: Retrospective observational cohort study.

Setting: Institution for inpatient neurologic rehabilitation.

Participants: Persons with SCI (N=1294) admitted to a rehabilitation facility between 2005 and 2022.

Interventions: Not applicable.

Main outcome measures: Functional 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.

Results: A 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.

Conclusions: Falls 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.