Evidence map›Paper›PMID 33402051›Full record

ArticleInternational journal of stroke : official journal of the International Stroke Society2021

Predicting specific abilities after disabling stroke: Development and validation of prognostic models.

Akila Visvanathan, Catriona Graham, Martin Dennis, Julia Lawton, Fergus Doubal, Gillian Mead, William Whiteley

Abstract readMulticenter Study
In one paragraph

Article in International journal of stroke : official journal of the International Stroke Society, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Akila VisvanathanCentre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK.ORCID 0000-0002-9713-8713
Catriona GrahamEdinburgh Clinical Research Facility, The University of Edinburgh, Edinburgh, UK.
Martin DennisCentre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK.
Julia LawtonUsher Institute, The University of Edinburgh, Edinburgh, UK.
Fergus DoubalCentre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK.
Gillian MeadCentre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK.ORCID 0000-0001-7494-2023
William WhiteleyCentre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK.

Funding

Chief Scientist Office SCAF/17/01
6 · The paper itself

Abstract

backgroundPredicting 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.

aimTo 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.

methodsWe 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 (

resultsAll 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%.

conclusionsWe 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.

Indexed as

StrokeCohort StudiesHumansLogistic ModelsModels, StatisticalPrognosisdecision-makingdisabilitypredictionprognosisPrognostic modelsstroke

Identifiers

PMID33402051
PMCPMC8554496

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.