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.
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.
Authors: Akila Visvanathan; Martin Dennis; Gillian Mead; William N Whiteley; Julia Lawton; Fergus Neil Doubal Journal: Int J Stroke Date: 2017-09-12 Impact factor: 5.266
Authors: Peter Sandercock; Joanna M Wardlaw; Richard I Lindley; Martin Dennis; Geoff Cohen; Gordon Murray; Karen Innes; Graham Venables; Anna Czlonkowska; Adam Kobayashi; Stefano Ricci; Veronica Murray; Eivind Berge; Karsten Bruins Slot; Graeme J Hankey; Manuel Correia; Andre Peeters; Karl Matz; Phillippe Lyrer; Gord Gubitz; Stephen J Phillips; Antonio Arauz Journal: Lancet Date: 2012-05-23 Impact factor: 79.321
Authors: Ewout W Steyerberg; Karel G M Moons; Danielle A van der Windt; Jill A Hayden; Pablo Perel; Sara Schroter; Richard D Riley; Harry Hemingway; Douglas G Altman Journal: PLoS Med Date: 2013-02-05 Impact factor: 11.069
Authors: Jennifer K Burton; Jennifer Stewart; Mairi Blair; Sinead Oxley; Amy Wass; Martin Taylor-Rowan; Terence J Quinn Journal: Age Ageing Date: 2022-03-01 Impact factor: 12.782