Predictors of Lower Urinary Tract Symptoms Following Post-Acute Stroke: Analysis of Multiple Variables.

Abstract

Introduction and hypothesis: Lower urinary tract symptoms (LUTS) are associated with post-stroke recovery, and therefore identifying predictors of LUTS is important. This study was designed to determine predictors of LUTS following post-acute stroke.

Methods: Brunnstrom Recovery Stages (BRS), Modified Ashworth Scale (MAS), Modified Rankin Scale (MRS), Functional Ambulation Scale (FAS), Berg Balance Scale (BBS), Functional Independence Measure (FIM), Core Lower Urinary Tract Symptom Score (CLSS), and Incontinence Quality of Life Scale (I-QOL) were used. The CLSS total and subdimensions were obtained by using multiple linear regression analysis using the stepwise selection method.

Results: This study was completed with 93 participants. The stepwise selection method analysis found the regression model created with the variables age, gender, constipation, FAS, stroke type, and I-QOL total score predicting the CLSS total score to be significant (F_(6;87) = 168.035, p < 0.001). The contribution of the variables age, gender, constipation, FAS, stroke type, and I-QOL total score to the model was found to be statistically significant (p < 0.05). According to standardized regression coefficients, the greatest contribution to the model was made by age (0.961) and I-QOL total score (-0.890) variables. The established model explains 91.5% of the variation (R² = 0.915) in CLSS total score.

Conclusions: This is the first study to examine predictors of LUTS following post-acute stroke in a broad context. Post-acute stroke patients with LUTS should be addressed multi-dimensionally, and the rehabilitation program should be planned to take these parameters into consideration.