Derivation and external validation of a case mix model for the standardized reporting of 30-day stroke mortality rates

2.50
Hdl Handle:
http://hdl.handle.net/11287/593803
Title:
Derivation and external validation of a case mix model for the standardized reporting of 30-day stroke mortality rates
Authors:
Bray, B. D.; Campbell, J.; Cloud, G. C.; Hoffman, A.; James, Martin; Tyrrell, P. J.; Wolfe, C. D.; Rudd, A. G.; Intercollegiate Stroke Working Party, Group
Abstract:
BACKGROUND AND PURPOSE: Case mix adjustment is required to allow valid comparison of outcomes across care providers. However, there is a lack of externally validated models suitable for use in unselected stroke admissions. We therefore aimed to develop and externally validate prediction models to enable comparison of 30-day post-stroke mortality outcomes using routine clinical data. METHODS: Models were derived (n=9000 patients) and internally validated (n=18 169 patients) using data from the Sentinel Stroke National Audit Program, the national register of acute stroke in England and Wales. External validation (n=1470 patients) was performed in the South London Stroke Register, a population-based longitudinal study. Models were fitted using general estimating equations. Discrimination and calibration were assessed using receiver operating characteristic curve analysis and correlation plots. RESULTS: Two final models were derived. Model A included age (<60, 60-69, 70-79, 80-89, and >/=90 years), National Institutes of Health Stroke Severity Score (NIHSS) on admission, presence of atrial fibrillation on admission, and stroke type (ischemic versus primary intracerebral hemorrhage). Model B was similar but included only the consciousness component of the NIHSS in place of the full NIHSS. Both models showed excellent discrimination and calibration in internal and external validation. The c-statistics in external validation were 0.87 (95% confidence interval, 0.84-0.89) and 0.86 (95% confidence interval, 0.83-0.89) for models A and B, respectively. CONCLUSIONS: We have derived and externally validated 2 models to predict mortality in unselected patients with acute stroke using commonly collected clinical variables. In settings where the ability to record the full NIHSS on admission is limited, the level of consciousness component of the NIHSS provides a good approximation of the full NIHSS for mortality prediction.
Citation:
Stroke. 2014 Nov;45(11):3374-80.
Publisher:
Stroke
Journal:
Stroke; a journal of cerebral circulation
Issue Date:
1-Nov-2014
URI:
http://hdl.handle.net/11287/593803
DOI:
10.1161/STROKEAHA.114.006451
PubMed ID:
25293667
Additional Links:
http://stroke.ahajournals.org/cgi/pmidlookup?view=long&pmid=25293667
Note:
This article is available via Open Access. Please click on the 'Additional Link' above to access the full-text.
Type:
Journal Article; Research Support, Non-U.S. Gov't; Validation Studies
Language:
eng
ISSN:
1524-4628
Appears in Collections:
Stroke; 2014 RD&E publications

Full metadata record

DC FieldValue Language
dc.contributor.authorBray, B. D.en
dc.contributor.authorCampbell, J.en
dc.contributor.authorCloud, G. C.en
dc.contributor.authorHoffman, A.en
dc.contributor.authorJames, Martinen
dc.contributor.authorTyrrell, P. J.en
dc.contributor.authorWolfe, C. D.en
dc.contributor.authorRudd, A. G.en
dc.contributor.authorIntercollegiate Stroke Working Party, Groupen
dc.date.accessioned2016-01-19T12:35:06Zen
dc.date.available2016-01-19T12:35:06Zen
dc.date.issued2014-11-01en
dc.identifier.citationStroke. 2014 Nov;45(11):3374-80.en
dc.identifier.issn1524-4628en
dc.identifier.pmid25293667en
dc.identifier.doi10.1161/STROKEAHA.114.006451en
dc.identifier.urihttp://hdl.handle.net/11287/593803en
dc.description.abstractBACKGROUND AND PURPOSE: Case mix adjustment is required to allow valid comparison of outcomes across care providers. However, there is a lack of externally validated models suitable for use in unselected stroke admissions. We therefore aimed to develop and externally validate prediction models to enable comparison of 30-day post-stroke mortality outcomes using routine clinical data. METHODS: Models were derived (n=9000 patients) and internally validated (n=18 169 patients) using data from the Sentinel Stroke National Audit Program, the national register of acute stroke in England and Wales. External validation (n=1470 patients) was performed in the South London Stroke Register, a population-based longitudinal study. Models were fitted using general estimating equations. Discrimination and calibration were assessed using receiver operating characteristic curve analysis and correlation plots. RESULTS: Two final models were derived. Model A included age (<60, 60-69, 70-79, 80-89, and >/=90 years), National Institutes of Health Stroke Severity Score (NIHSS) on admission, presence of atrial fibrillation on admission, and stroke type (ischemic versus primary intracerebral hemorrhage). Model B was similar but included only the consciousness component of the NIHSS in place of the full NIHSS. Both models showed excellent discrimination and calibration in internal and external validation. The c-statistics in external validation were 0.87 (95% confidence interval, 0.84-0.89) and 0.86 (95% confidence interval, 0.83-0.89) for models A and B, respectively. CONCLUSIONS: We have derived and externally validated 2 models to predict mortality in unselected patients with acute stroke using commonly collected clinical variables. In settings where the ability to record the full NIHSS on admission is limited, the level of consciousness component of the NIHSS provides a good approximation of the full NIHSS for mortality prediction.en
dc.language.isoengen
dc.publisherStrokeen
dc.relation.urlhttp://stroke.ahajournals.org/cgi/pmidlookup?view=long&pmid=25293667en
dc.titleDerivation and external validation of a case mix model for the standardized reporting of 30-day stroke mortality ratesen
dc.typeJournal Articleen
dc.typeResearch Support, Non-U.S. Gov'ten
dc.typeValidation Studiesen
dc.identifier.journalStroke; a journal of cerebral circulationen
dc.description.noteThis article is available via Open Access. Please click on the 'Additional Link' above to access the full-text.en

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