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P2-205 Heterogeneity in functional recovery after stroke: an exploratory study using longitudinal latent class analysis
IntroductionPrediction models for functional recovery after stroke can be improved by adjusting for the heterogeneity in functional recovery patterns. This study explored the heterogeneity in functional recovery after stroke using longitudinal latent class analysis and characterised the patients in...
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Published in: | Journal of epidemiology and community health (1979) 2011-08, Vol.65 (Suppl 1), p.A278-A278 |
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description | IntroductionPrediction models for functional recovery after stroke can be improved by adjusting for the heterogeneity in functional recovery patterns. This study explored the heterogeneity in functional recovery after stroke using longitudinal latent class analysis and characterised the patients in the different latent classes.MethodsThe analyses were performed on a data set from a cohort of 448 stroke survivors participating in a study of outcomes at 1 year. Heterogeneity in functional recovery after stroke was investigated using Longitudinal Latent class analysis of total Barthel scores measured at 1, 6 and 12 months after stroke. Identification of the optimal number of classes was based on BIC, AIC, and Lo-Mendell-Rubin Adjusted Likelihood ratio test. The second analysis characterised the latent classes.ResultsA four latent class structure was preferred. All the four latent classes showed a non linear pattern of recovery over time. Persons in the very poor functional recovery group had the largest median length of initial hospital stay 99 (13–257 days), mean age 75±9.27 years and greatest probability of being urinary and bladder incontinence. The group with best functional recovery had the least initial hospital stay 14 (2–147 days), least proportion of people with previous stroke, least proportion of people with urinary and bladder incontinence, the mean age at admission was 68.76±11.72 years.ConclusionThe study showed that there is heterogeneity in functional recovery patterns after stroke. Latent class analysis is a useful method for identifying subgroups of functional recovery after stroke. |
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This study explored the heterogeneity in functional recovery after stroke using longitudinal latent class analysis and characterised the patients in the different latent classes.MethodsThe analyses were performed on a data set from a cohort of 448 stroke survivors participating in a study of outcomes at 1 year. Heterogeneity in functional recovery after stroke was investigated using Longitudinal Latent class analysis of total Barthel scores measured at 1, 6 and 12 months after stroke. Identification of the optimal number of classes was based on BIC, AIC, and Lo-Mendell-Rubin Adjusted Likelihood ratio test. The second analysis characterised the latent classes.ResultsA four latent class structure was preferred. All the four latent classes showed a non linear pattern of recovery over time. Persons in the very poor functional recovery group had the largest median length of initial hospital stay 99 (13–257 days), mean age 75±9.27 years and greatest probability of being urinary and bladder incontinence. The group with best functional recovery had the least initial hospital stay 14 (2–147 days), least proportion of people with previous stroke, least proportion of people with urinary and bladder incontinence, the mean age at admission was 68.76±11.72 years.ConclusionThe study showed that there is heterogeneity in functional recovery patterns after stroke. Latent class analysis is a useful method for identifying subgroups of functional recovery after stroke.</description><identifier>ISSN: 0143-005X</identifier><identifier>EISSN: 1470-2738</identifier><identifier>DOI: 10.1136/jech.2011.142976j.38</identifier><identifier>CODEN: JECHDR</identifier><language>eng</language><publisher>London: BMJ Publishing Group Ltd</publisher><subject>Heterogeneity ; Prediction models</subject><ispartof>Journal of epidemiology and community health (1979), 2011-08, Vol.65 (Suppl 1), p.A278-A278</ispartof><rights>2011, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.</rights><rights>Copyright: 2011 (c) 2011, Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-b2488-441ca236f68319ac11d7556d99175ff44c03a020281862639341c299f41bf7453</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://jech.bmj.com/content/65/Suppl_1/A278.1.full.pdf$$EPDF$$P50$$Gbmj$$H</linktopdf><linktohtml>$$Uhttps://jech.bmj.com/content/65/Suppl_1/A278.1.full$$EHTML$$P50$$Gbmj$$H</linktohtml><link.rule.ids>112,113,314,780,784,3194,27924,27925,77594,77595</link.rule.ids></links><search><creatorcontrib>Munyombwe, T</creatorcontrib><creatorcontrib>West, R</creatorcontrib><creatorcontrib>Hill, K</creatorcontrib><creatorcontrib>Tu, Y-K</creatorcontrib><creatorcontrib>Knapp, P</creatorcontrib><title>P2-205 Heterogeneity in functional recovery after stroke: an exploratory study using longitudinal latent class analysis</title><title>Journal of epidemiology and community health (1979)</title><addtitle>J Epidemiol Community Health</addtitle><description>IntroductionPrediction models for functional recovery after stroke can be improved by adjusting for the heterogeneity in functional recovery patterns. This study explored the heterogeneity in functional recovery after stroke using longitudinal latent class analysis and characterised the patients in the different latent classes.MethodsThe analyses were performed on a data set from a cohort of 448 stroke survivors participating in a study of outcomes at 1 year. Heterogeneity in functional recovery after stroke was investigated using Longitudinal Latent class analysis of total Barthel scores measured at 1, 6 and 12 months after stroke. Identification of the optimal number of classes was based on BIC, AIC, and Lo-Mendell-Rubin Adjusted Likelihood ratio test. The second analysis characterised the latent classes.ResultsA four latent class structure was preferred. All the four latent classes showed a non linear pattern of recovery over time. Persons in the very poor functional recovery group had the largest median length of initial hospital stay 99 (13–257 days), mean age 75±9.27 years and greatest probability of being urinary and bladder incontinence. The group with best functional recovery had the least initial hospital stay 14 (2–147 days), least proportion of people with previous stroke, least proportion of people with urinary and bladder incontinence, the mean age at admission was 68.76±11.72 years.ConclusionThe study showed that there is heterogeneity in functional recovery patterns after stroke. Latent class analysis is a useful method for identifying subgroups of functional recovery after stroke.</description><subject>Heterogeneity</subject><subject>Prediction models</subject><issn>0143-005X</issn><issn>1470-2738</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><recordid>eNqNkM9O3DAQxq2qldgCb8DBEucsHtuJY27VqpT_IBUQN8ubtbcOId7aDiI3Ln3RPkkdLeLc08xovt98ow-hAyBzAFYdtab5NacEYA6cSlG1c1Z_QjPgghRUsPozmhHgrCCkfNxBX2NsSW4FlTM03tKCkvLv259Tk0zwa9Mbl0bsemyHvknO97rDwTT-xYQRa5tFOKbgn8wx1j02r5vOB518XsY0rEY8RNevcef7tcuzm_BOJ9Mn3HQ6xgzpbowu7qEvVnfR7L_XXXR_8v1ucVpc3vw4W3y7LJaU13XBOTSasspWNQOpG4CVKMtqJSWI0lrOG8I0oYTWUFe0YpJlgEppOSyt4CXbRYfbu5vgfw8mJtX6IeQnogIhJBVUVCKr-FbVBB9jMFZtgnvWYVRA1BSymkJWU8jqPWTF6owVW8zFZF4_GB2eVD4qSnX9sFBXPy9uF1cP52qyOdrql8_t_zn8A3GkkCE</recordid><startdate>201108</startdate><enddate>201108</enddate><creator>Munyombwe, T</creator><creator>West, R</creator><creator>Hill, K</creator><creator>Tu, Y-K</creator><creator>Knapp, P</creator><general>BMJ Publishing Group Ltd</general><general>BMJ Publishing Group LTD</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>88I</scope><scope>8AF</scope><scope>8C1</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AN0</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BTHHO</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PSYQQ</scope><scope>Q9U</scope></search><sort><creationdate>201108</creationdate><title>P2-205 Heterogeneity in functional recovery after stroke: an exploratory study using longitudinal latent class analysis</title><author>Munyombwe, T ; West, R ; Hill, K ; Tu, Y-K ; Knapp, P</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-b2488-441ca236f68319ac11d7556d99175ff44c03a020281862639341c299f41bf7453</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>Heterogeneity</topic><topic>Prediction models</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Munyombwe, T</creatorcontrib><creatorcontrib>West, R</creatorcontrib><creatorcontrib>Hill, K</creatorcontrib><creatorcontrib>Tu, Y-K</creatorcontrib><creatorcontrib>Knapp, P</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Proquest Nursing & Allied Health Source</collection><collection>ProQuest_Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Science Database (Alumni Edition)</collection><collection>STEM Database</collection><collection>Public Health Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>British Nursing Database</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>BMJ Journals</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection (Proquest) (PQ_SDU_P3)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database (ProQuest)</collection><collection>ProQuest Science Journals</collection><collection>Biological Science Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><jtitle>Journal of epidemiology and community health (1979)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Munyombwe, T</au><au>West, R</au><au>Hill, K</au><au>Tu, Y-K</au><au>Knapp, P</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>P2-205 Heterogeneity in functional recovery after stroke: an exploratory study using longitudinal latent class analysis</atitle><jtitle>Journal of epidemiology and community health (1979)</jtitle><addtitle>J Epidemiol Community Health</addtitle><date>2011-08</date><risdate>2011</risdate><volume>65</volume><issue>Suppl 1</issue><spage>A278</spage><epage>A278</epage><pages>A278-A278</pages><issn>0143-005X</issn><eissn>1470-2738</eissn><coden>JECHDR</coden><abstract>IntroductionPrediction models for functional recovery after stroke can be improved by adjusting for the heterogeneity in functional recovery patterns. This study explored the heterogeneity in functional recovery after stroke using longitudinal latent class analysis and characterised the patients in the different latent classes.MethodsThe analyses were performed on a data set from a cohort of 448 stroke survivors participating in a study of outcomes at 1 year. Heterogeneity in functional recovery after stroke was investigated using Longitudinal Latent class analysis of total Barthel scores measured at 1, 6 and 12 months after stroke. Identification of the optimal number of classes was based on BIC, AIC, and Lo-Mendell-Rubin Adjusted Likelihood ratio test. The second analysis characterised the latent classes.ResultsA four latent class structure was preferred. All the four latent classes showed a non linear pattern of recovery over time. Persons in the very poor functional recovery group had the largest median length of initial hospital stay 99 (13–257 days), mean age 75±9.27 years and greatest probability of being urinary and bladder incontinence. The group with best functional recovery had the least initial hospital stay 14 (2–147 days), least proportion of people with previous stroke, least proportion of people with urinary and bladder incontinence, the mean age at admission was 68.76±11.72 years.ConclusionThe study showed that there is heterogeneity in functional recovery patterns after stroke. Latent class analysis is a useful method for identifying subgroups of functional recovery after stroke.</abstract><cop>London</cop><pub>BMJ Publishing Group Ltd</pub><doi>10.1136/jech.2011.142976j.38</doi><oa>free_for_read</oa></addata></record> |
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title | P2-205 Heterogeneity in functional recovery after stroke: an exploratory study using longitudinal latent class analysis |
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