Prediction of falling among stroke patients in rehabilitation

Baetens, Tina; Kegel, Alexandra De; Vanderstraeten, Guy; Cambier, Dirk

doi:10.2340/16501977-0873

Cited by 56 publications

(78 citation statements)

References 19 publications

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“…Although it has been previously reported by other authors, factors such as age, gender and polypharmacy, which are often associated with the risk of falls in both healthy elderly and patients with stroke [31][32][33][34][35], were not significant predictors in this study.…”

Section: Discussioncontrasting

confidence: 75%

Association between dual-task performance and balance during gait in community-dwelling elderly people after stroke

2015

Healthy Aging Res

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Section: Discussioncontrasting

confidence: 75%

Association between dual-task performance and balance during gait in community-dwelling elderly people after stroke

2015

Healthy Aging Res

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“…They had been included in an extensive study on risk factors for falling (NZ73). 5 For this gait analysis study, patients had to be able to walk without manual help, with or without walking assistive devices (FAC score !3) and did not have aphasia or dysarthria interfering with verbal tasks (nZ38). Figure 1 illustrates the study design and dropouts.…”

Section: Methods Participantsmentioning

confidence: 99%

“…To avoid (quasi-)empty categories, FAC scores of 4 and 5 were combined in 1 functional category, as previously described. 5 Comparisons between Fs and NFs showed that Fs more frequently used a walking aid (PZ.039) and more frequently were defined as walkers in need of supervision for safety (FAC score of 3) (PZ.044). No significant differences between SFs and MFs were found.…”

Section: Participantsmentioning

confidence: 99%

“…1 Several studies demonstrated that falls in stroke survivors often occur during locomotion [1][2][3][4][5] and gait deficits, for example, problems with obstacle-crossing or need of supervision for safety (Functional Ambulation Category [FAC] 6 score of 3) are retained as an important fall-risk factor. However, different patients, all categorized with an FAC score of 3, can still differ significantly in qualitative performance or in quantitative temporal-spatial gait characteristics.…”

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confidence: 99%

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Gait Analysis With Cognitive-Motor Dual Tasks to Distinguish Fallers From Nonfallers Among Rehabilitating Stroke Patients

Baetens

Kegel

Palmans

et al. 2013

Archives of Physical Medicine and Rehabilitation

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This article appeared in a journal published by Elsevier. The attached copy is furnished to the author for internal non-commercial research and education use, including for instruction at the authors institution and sharing with colleagues.Other uses, including reproduction and distribution, or selling or licensing copies, or posting to personal, institutional or third party websites are prohibited. Abstract Objectives: To evaluate fall risk in stroke patients based on single-and dual-task gait analyses, and to investigate the difference between 2 cognitive tasks in the dual-task paradigm. Design: Prospective cohort study. Setting: Rehabilitation hospitals. Participants: Subacute stroke patients (NZ32), able to walk without physical/manual help with or without walking aids, while performing a verbal task. Interventions: Not applicable. Main Outcome Measures: Functional gait measures were Functional Ambulation Categories (FAC) and use of a walking aid. Gait measures were evaluated by an electronic walkway system under single-and dual-task (DT) conditions. For the single-task, subjects were instructed to walk at their usual speed. One of the DTs was a verbal fluency dual task, whereby subjects had to walk while simultaneously enumerating as many different animals as possible. For the other DT (counting dual task), participants had to walk while performing serial subtractions. After inclusion, participants kept a 6-month falls diary. Results: Eighteen (56.3%) of the 32 included patients fell. Ten (31.3%) were single fallers (SFs), and 8 (25%) were multiple fallers (MFs). Fallers (Fs) more frequently used a walking aid and more frequently needed an observatory person for walking safely (FAC score of 3) than nonfallers (NFs). Two gait decrement parameters in counting dual task could distinguish potential Fs from NFs: decrement in stride length percentage (PZ.043) and nonparetic step length percentage (PZ.047). Regarding the division in 3 groups (NFs, SFs, and MFs), only MFs had a significantly higher percentage of decrement for paretic step length (PZ.023) than SFs. Conclusions: Examining the decrement of spatial gait characteristics (stride length and paretic and nonparetic step length) during a DT addressing working memory can identify fall-prone subacute stroke patients.

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“…A recent systematic review summarised falls-prediction models derived within the first year after stroke [6]. Five studies derived nine models to predict falls in community-dwellers [7][8][9][10][11]. Three of these studies reported sufficient information to allow for model validation [9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Validation of two risk-prediction models for recurrent falls in the first year after stroke: a prospective cohort study

et al. 2017

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Key Points:• Accurate identification of stroke patients at risk of falling is important for planning rehabilitation services on discharge• Two previously derived risk-prediction models for recurrent falls post-stroke have performed poorly in this validation study• A further large prospective cohort study is required to derive a useful falls-risk prediction model for this population• Future derivation studies should conduct internal validation and adhere to TRIPOD guidelines to facilitate external validation 3 AbstractBackground: Several multivariable models have been derived to predict post-stroke falls. These require validation before integration into clinical practice. The aim of this study was to externally validate two prediction models for recurrent falls in the first year post-stroke using an Irish prospective cohort study.Methodology: Stroke patients with planned home-discharges from five hospitals were recruited. Falls were recorded with monthly diaries and interviews six and 12 months post-discharge. Predictors for falls included in two risk-prediction models were assessed at discharge. Participants were classified into risk-groups using these models. Model 1, incorporating inpatient falls-history and balance, had a six-month outcome. Model 2, incorporating inpatient near-falls history and upper limb function, had a twelve-month outcome. Measures of calibration, discrimination (area under the curve (AUC)) and clinical utility (sensitivity/ specificity) were calculated.Results: 128 participants (mean age=68.6 years, SD=13.3) were recruited. The fall status of 117 and 110 participants was available at six and 12 months respectively.Seventeen and 28 participants experienced recurrent falls by these respective time- Conclusions: Both models showed poor discrimination for predicting recurrent falls.A further large prospective cohort study would be required to derive a clinicallyuseful falls-risk prediction model for a similar population.

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Prediction of falling among stroke patients in rehabilitation

Abstract: Several assessments and both prediction models showed acceptable accuracy in identifying fall-prone patients. A purely physical model can be used; however, looking beyond mobility aspects adds value. Further validation of these results is required.

Cited by 56 publications

References 19 publications

Association between dual-task performance and balance during gait in community-dwelling elderly people after stroke

Association between dual-task performance and balance during gait in community-dwelling elderly people after stroke

Gait Analysis With Cognitive-Motor Dual Tasks to Distinguish Fallers From Nonfallers Among Rehabilitating Stroke Patients

Validation of two risk-prediction models for recurrent falls in the first year after stroke: a prospective cohort study

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