Risk Factors Related to Falling in Patients after Stroke

Olivera Djurovic; Olgica  Mihaljevic; Snezana  Radovanovic; Smiljana  Kostic; Marjana Vukicevic; Biljana Georgievski  Brkic; Snezana  Stankovic; Danijela  Radulovic; Ivana Simic  Vukomanovic; Svetlana R  Radevic

doi:10.18502/ijph.v50i9.7056

Olivera Djurovic Special Hospital for Cerebrovascular Diseases "Sveti Sava", Belgrade, Serbia
Olgica Mihaljevic Department of Pathophysiology, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia
Snezana Radovanovic Department of Social Medicine, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia
Smiljana Kostic Military Medical Academy, Neurology Clinic, Belgrade, Serbia
Marjana Vukicevic Special Hospital for Cerebrovascular Diseases "Sveti Sava", Belgrade, Serbia
Biljana Georgievski Brkic Special Hospital for Cerebrovascular Diseases "Sveti Sava", Belgrade, Serbia
Snezana Stankovic Special Hospital for Cerebrovascular Diseases "Sveti Sava", Belgrade, Serbia
Danijela Radulovic Primary Health Care and Public Health, Faculty of Medicine, University East Sarajevo, Sarajevo, Republic of Srpska, Bos-nia and Herzegovina
Ivana Simic Vukomanovic Department of Social Medicine, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia
Svetlana R Radevic Department of Social Medicine, Faculty of Medical Sciences, University of Kragujevac, Kragujevac, Serbia

DOI: https://doi.org/10.18502/ijph.v50i9.7056

Keywords: Falls; Stroke patients; Risk factors; Hospitalization

Abstract

Background: The aim of this study was to identify the risk factors associated with falling in post stroke patients.

Methods: This retrospective case-control study included 561 neurology patients hospitalized for a stroke and divided into two groups: falling patients and non-falling patients. They referred to the Special Hospital for Cerebrovascular Diseases "Sveti Sava" in Belgrade, Serbia, from 2018- 2019. Logistic regression analysis was applied to examine socio-economic factors associated with predictors of unmet healthcare needs.

Results: A significant difference was seen in the length of hospitalization of falling patients compared to the non-falling (P<0.001). We established statistically significant differences in mental status (P<0.001), sensibility (P=0.016), depressed mood (P<0.001), early (P=0.001) and medium insomnia (P=0.042), psychomotor slowness (P=0.030), somatic anxiety (P=0.044) and memory (P<0.001).

Conclusion: Cerebrovascular disease distribution and the degree of neurological deficit primarily altered mental status, which could be recognized as one of the more important predictors for falling after stroke. The identification of risk factors may be a first step toward the design of intervention programs for preventing a future fall among hospitalized stroke patients.