Conceptio › Archive › ClinicalTrials.gov
ClinicalTrials.gov public full text Public Domain

Lucerne Fall Risk Prediction Score for Stroke Rehabilitation

Luzerner Kantonsspital · 2019
ClinicalTrials.gov · Datasets · License: Public Domain · 2019
Open Source ↗
stroke
In Switzerland, every year around 16'000 people suffer a stroke. Stroke represents the third most common cause of death in Switzerland and leads to impairments (e.g., motoric, cognitive, sensory) resulting in disability. People with disabilities after stroke should have access to specialised interprofessional rehabilitation settings. During inpatient rehabilitation, 15-36% of the patients experience one or more falls. It is well known that stroke is an important risk factor for falls. On average stroke patients fall 1.77 times more than the age- and gender-matched controls over 13 months. Falling events during inpatient stroke rehabilitation result in an extension of rehabilitation stay of about eleven days. Wong et al. (2016) suspect that a reduction in the activity level due to falls, fear of falling again as well as changes in discharge conditions could be the reason for this extended length of stay. Walsh et al. (2018) demonstrate that patients who fall once within the first year after stroke cause € 8'600 and recurrent fallers € 12'700 higher healthcare costs. Fall risk factors after stroke are well investigated. Campbell \& Matthews (2010) have collected multiple factors for falls in inpatient stroke rehabilitation from 1990 to 2009 in an integrative review. A newer systematic review points out physical function, hemi-attention, and stability as the most important factors for falls in inpatient stroke rehabilitation. However, none of the included studies showed a validated prediction model with acceptable performance. Hence, further investigations regarding the impact of various valid and reliable fall risk assessments at admission in inpatient rehabilitation are needed. The neurorehabilitation team of LUKS systematically assesses the patient's functions and activity to design patient-specific, evidence-based rehabilitation. Therefore, a population-specific fall risk model based on standardized assessments performed in the clinical routine would help to ide
Conceptio Open Archive

Analyze & explore related research in Conceptio

Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.

This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗

Related documents

Record · ID 1213699
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive