ArticleClinical medicine (London, England)2021
Pre-stroke disability and stroke severity as predictors of discharge destination from an acute stroke ward.
Article in Clinical medicine (London, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.
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Who cites it
10 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Risk prediction models for discharge disposition in patients with stroke: a systematic review and meta-analysis.Frontiers in neurology · 2025Pooled it
- Risk prediction models for frailty in stroke patients: a systematic review and meta-analysis.Frontiers in neurologyPooled it
- Associations of pre-stroke function disability and post-stroke cognitive impairment among older adults in China.Scientific reports · 2026Article
- Impact of Severe Prestroke Disability on Outcomes After Mechanical Thrombectomy: A Multicenter Analysis.Stroke (Hoboken, N.J.) · 2026Article
- Prolonged venous transit is associated with worse neurological recovery in successfully reperfused large vessel strokes.Annals of clinical and translational neurology · 2025Article
- Impact of possible sarcopenia on functional prognosis in patients with acute stroke with premorbid disability.Geriatrics & gerontology international · 2024Article
- Improving multidisciplinary hospital care for acute cerebral circulation disorders in Kazakhstan.Heliyon · 2023Article
- Predictors of Discharge Destination After Stroke.Neurorehabilitation and neural repair · 2023Observational
- The cost of ischaemic stroke in Croatia.European stroke journal · 2023Article
- Assisting clinical decision making: tools, rules and teams.Clinical medicine (London, England) · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
background and rationaleReliable prediction of discharge destination in acute stroke informs discharge planning and can determine the expectations of patients and carers. There is no existing model that does this using routinely collected indices of pre-morbid disability and stroke severity.
methodsAge, gender, pre-morbid modified Rankin Scale (mRS) and National Institutes of Health Stroke Scale (NIHSS) were gathered prospectively on an acute stroke unit from 1,142 consecutive patients. A multiclass random forest classifier was used to train and validate a model to predict discharge destination.
resultsUsed alone, the mRS is the strongest predictor of discharge destination. The NIHSS is only predictive when combined with our other variables. The accuracy of the final model was 70.4% overall with a positive predictive value (PPV) and sensitivity of 0.88 and 0.78 for home as the destination, 0.68 and 0.88 for continued inpatient care, 0.7 and 0.53 for community hospital, and 0.5 and 0.18 for death, respectively.
conclusionPre-stroke disability rather than stroke severity is the strongest predictor of discharge destination, but in combination with other routinely collected data, both can be used as an adjunct by the multidisciplinary team to predict discharge destination in patients with acute stroke.
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