OBJECTIVE: To develop and internally validate a simple falls prediction tool for rehabilitation settings. DESIGN: Prospective cohort study. PARTICIPANTS: A total of 533 inpatients. METHODS: Possible predictors of falls were collected from medical records, interview and physical assessment. Falls during inpatient stays were monitored. RESULTS: Fourteen percent of participants fell. A multivariate model to predict falls included: male gender (odds ratio (OR) 2.70, 95% confidence interval (CI) 1.57-4.64), central nervous system medications (OR 2.50, 95% CI 1.47-4.25), a fall in the previous 12 months (OR 2.21, 95% CI 1.07-4.56), frequent toileting (OR 2.14, 95% CI 1.27-3.62) and tandem stance inability (OR 2.00, 95% CI 1.11-3.59). The area under the curve for this model was 0.74 (95% CI 0.68-0.80). The Predict_FIRST tool is a unit weighted adaptation of this model (i.e. 1 point allocated for each predictor) and its area under the curve was 0.73 (95% CI 0.68-0.79). Predicted and actual falls risks corresponded closely. CONCLUSION: This tool provides a simple way to quantify the probability with which an individual patient will fall during a rehabilitation stay.
AD - The George Institute for International Health, Missenden Road, Sydney NSW 2050, Australia. csherrington@george.org.au AN - 20544161 BT - Journal of Rehabilitation Medicine ET - 2010/06/15 LA - eng M1 - 5 N1 - Sherrington, CatherineLord, Stephen RClose, Jacqueline C TBarraclough, ElizabethTaylor, MoragOa Rourke, SandraKurrle, SusanTiedemann, AnneCumming, Robert GHerbert, Robert DResearch Support, Non-U.S. Gov'tSwedenJournal of rehabilitation medicine : official journal of the UEMS European Board of Physical and Rehabilitation MedicineJ Rehabil Med. 2010 May;42(5):482-8. N2 -OBJECTIVE: To develop and internally validate a simple falls prediction tool for rehabilitation settings. DESIGN: Prospective cohort study. PARTICIPANTS: A total of 533 inpatients. METHODS: Possible predictors of falls were collected from medical records, interview and physical assessment. Falls during inpatient stays were monitored. RESULTS: Fourteen percent of participants fell. A multivariate model to predict falls included: male gender (odds ratio (OR) 2.70, 95% confidence interval (CI) 1.57-4.64), central nervous system medications (OR 2.50, 95% CI 1.47-4.25), a fall in the previous 12 months (OR 2.21, 95% CI 1.07-4.56), frequent toileting (OR 2.14, 95% CI 1.27-3.62) and tandem stance inability (OR 2.00, 95% CI 1.11-3.59). The area under the curve for this model was 0.74 (95% CI 0.68-0.80). The Predict_FIRST tool is a unit weighted adaptation of this model (i.e. 1 point allocated for each predictor) and its area under the curve was 0.73 (95% CI 0.68-0.79). Predicted and actual falls risks corresponded closely. CONCLUSION: This tool provides a simple way to quantify the probability with which an individual patient will fall during a rehabilitation stay.
PY - 2010 SN - 1651-2081 (Electronic)1650-1977 (Linking) SP - 482 EP - 8 T2 - Journal of Rehabilitation Medicine TI - Development of a tool for prediction of falls in rehabilitation settings (Predict_FIRST): a prospective cohort study VL - 42 ER -