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Risk Factors Related to Falling in Patients after Stroke
Olivera Djurovic1, Olgica Mihaljevic2, Snezana Radovanovic3
1Special Hospital for Cerebrovascular Diseases "Sveti Sava", Belgrade, Serbia.
Insights
Identifying risk factors for falls in stroke patients is crucial. Altered mental status, mood, and sleep disturbances significantly predict falls after stroke, informing prevention strategies.
Area of Science:
- Neurology
- Gerontology
- Rehabilitation Medicine
Background:
- Falls are a significant concern for post-stroke patients.
- Identifying specific risk factors is essential for fall prevention strategies.
Purpose of the Study:
- To identify risk factors associated with falling in patients hospitalized for stroke.
- To analyze predictors of unmet healthcare needs in post-stroke patients.
Main Methods:
- Retrospective case-control study of 561 neurology patients.
- Comparison between falling and non-falling patient groups.
- Logistic regression analysis to examine socio-economic factors and predictors.
Main Results:
- Falling patients had significantly longer hospitalizations.
- Significant differences observed in mental status, sensibility, mood, insomnia, psychomotor slowness, anxiety, and memory.
- Mental status alterations were strongly associated with falls (P<0.001).
Conclusions:
- Altered mental status, influenced by cerebrovascular disease and neurological deficits, is a key predictor of falls post-stroke.
- Identifying these risk factors is a critical first step for developing fall prevention interventions.
- Targeted interventions can help reduce future falls among hospitalized stroke survivors.
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.
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