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Predicting specific abilities after disabling stroke: Development and validation of prognostic models
BACKGROUND: Predicting specific abilities (e.g. walk and talk) to provide a functional profile six months after disabling stroke could help patients/families prepare for the consequences of stroke and facilitate involvement in treatment decision-making. AIM: To develop new statistical models to pred...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8554496/ https://www.ncbi.nlm.nih.gov/pubmed/33402051 http://dx.doi.org/10.1177/1747493020982873 |
Sumario: | BACKGROUND: Predicting specific abilities (e.g. walk and talk) to provide a functional profile six months after disabling stroke could help patients/families prepare for the consequences of stroke and facilitate involvement in treatment decision-making. AIM: To develop new statistical models to predict specific abilities six months after stroke and test their performance in an independent cohort of patients with disabling stroke. METHODS: We developed models to predict six specific abilities (to be independent, walk, talk, eat normally, live without major anxiety/depression, and to live at home) using data from seven large multicenter stroke trials with multivariable logistic regression. We included 13,117 participants recruited within three days of hospital admission. We assessed model discrimination and derived optimal cut-off values using four statistical methods. We validated the models in an independent single-center cohort of patients (n = 403) with disabling stroke. We assessed model discrimination and calibration and reported the performance of our models at the statistically derived cut-off values. RESULTS: All six models had good discrimination in external validation (AUC 0.78–0.84). Four models (predicting to walk, eat normally, live without major anxiety/depression, live at home) calibrated well. Models had sensitivities between 45.0 and 97.9% and specificities between 21.6 and 96.5%. CONCLUSIONS: We have developed statistical models to predict specific abilities and demonstrated that these models perform reasonably well in an independent cohort of disabling stroke patients. To aid decision-making regarding treatments, further evaluation of our models is required. |
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