Prediction of Falls in Subjects Suffering From Parkinson Disease, Multiple Sclerosis, and Stroke

Arch Phys Med Rehabil. 2018 Apr;99(4):641-651. doi: 10.1016/j.apmr.2017.10.009. Epub 2018 Feb 1.

Abstract

Objective: To compare the risk of falls and fall predictors in patients with Parkinson disease (PD), multiple sclerosis (MS), and stroke using the same study design.

Design: Multicenter prospective cohort study.

Setting: Institutions for physical therapy and rehabilitation.

Participants: Patients (N=299) with PD (n=94), MS (n=111), and stroke (n=94) seen for rehabilitation.

Interventions: Not applicable.

Main outcome measures: Functional scales were applied to investigate balance, disability, daily performance, self-confidence with balance, and social integration. Patients were followed for 6 months. Telephone interviews were organized at 2, 4, and 6 months to record falls and fall-related injuries. Incidence ratios, Kaplan-Meier survival curves, and Cox proportional hazards models were used.

Results: Of the 299 patients enrolled, 259 had complete follow-up. One hundred and twenty-two patients (47.1%) fell at least once; 82 (31.7%) were recurrent fallers and 44 (17.0%) suffered injuries; and 16%, 32%, and 40% fell at 2, 4, and 6 months. Risk of falls was associated with disease type (PD, MS, and stroke in decreasing order) and confidence with balance (Activities-specific Balance Confidence [ABC] scale). Recurrent fallers were 7%, 15%, and 24% at 2, 4, and 6 months. The risk of recurrent falls was associated with disease type, high educational level, and ABC score. Injured fallers were 3%, 8%, and 12% at 2, 4, and 6 months. The only predictor of falls with injuries was disease type (PD).

Conclusions: PD, MS, and stroke carry a high risk of falls. Other predictors include perceived balance confidence and high educational level.

Keywords: Falls; Multiple sclerosis; Parkinson disease; Rehabilitation; Risk factors; Stroke.

Publication types

  • Comparative Study
  • Multicenter Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidental Falls / statistics & numerical data*
  • Aged
  • Educational Status
  • Female
  • Humans
  • Incidence
  • Kaplan-Meier Estimate
  • Male
  • Middle Aged
  • Multiple Sclerosis / complications*
  • Multiple Sclerosis / physiopathology
  • Parkinson Disease / complications*
  • Parkinson Disease / physiopathology
  • Postural Balance
  • Proportional Hazards Models
  • Prospective Studies
  • Risk Assessment / methods
  • Risk Assessment / statistics & numerical data
  • Risk Factors
  • Stroke / complications*
  • Stroke / physiopathology