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Article: A Cox Regression Analysis of Covariates for Asthma Hospital Readmissions

TitleA Cox Regression Analysis of Covariates for Asthma Hospital Readmissions
Authors
KeywordsAsthma
Covariate
Cox regression
Hospital readmission
Issue Date2003
PublisherInforma Healthcare. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/02770903.asp
Citation
Journal Of Asthma, 2003, v. 40 n. 6, p. 645-652 How to Cite?
AbstractBackground. Asthma hospital admissions and readmissions are unacceptably high, thus, a method to identify those at greatest risk could be helpful. Methods. An observational retrospective study using a Cox regression to determine the relationship between the time interval between admissions and possible covariates of a readmission. The covariates were age, sex, ethnicity, smoking habit, history of allergy or eczema/hay fever, age of onset, Townsend index (TI), Jarman score (JS), and drugs on discharge. Those with p < 0.2, together with interacting covariates, from the preliminary analysis were eligible for the multivariate Cox regression analysis. Results. Of the 523 patients admitted between 1994 and 1998 because of their asthma, complete data were available for 440. Of these, 112 were readmitted. Eligible covariates for the multivariate Cox regression analysis were sex, allergy status, history of eczema/hay fever, the JS and TI together with interactions between JS and TI, JS and allergy, and allergy with eczema/hay fever. There were 278 subjects (71 with a readmission) with complete data for these eligible covariates. The multivariate analysis revealed that female sex (odds ratio [OR] = 2.65, 95% confidence interval [CI] 1.42, 4.92), high JS (OR = 2.03, 95% CI 1.13-3.65), and history of allergy (OR= 1.88, 95% CI 1.06-3.32) formed the final model as significant predictors of readmission. Conclusion. Females with a history of allergy that were registered at a practice with a high workload (JS) had a higher risk of readmission. The analysis method used highlights how those at risk of readmission can be identified so that they can be targeted post discharge.
Persistent Identifierhttp://hdl.handle.net/10722/132903
ISSN
2015 Impact Factor: 1.854
2015 SCImago Journal Rankings: 0.762
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorSalamzadeh, Jen_HK
dc.contributor.authorWong, ICKen_HK
dc.contributor.authorHosker, HSRen_HK
dc.contributor.authorChrystyn, Hen_HK
dc.date.accessioned2011-04-04T07:57:53Z-
dc.date.available2011-04-04T07:57:53Z-
dc.date.issued2003en_HK
dc.identifier.citationJournal Of Asthma, 2003, v. 40 n. 6, p. 645-652en_HK
dc.identifier.issn0277-0903en_HK
dc.identifier.urihttp://hdl.handle.net/10722/132903-
dc.description.abstractBackground. Asthma hospital admissions and readmissions are unacceptably high, thus, a method to identify those at greatest risk could be helpful. Methods. An observational retrospective study using a Cox regression to determine the relationship between the time interval between admissions and possible covariates of a readmission. The covariates were age, sex, ethnicity, smoking habit, history of allergy or eczema/hay fever, age of onset, Townsend index (TI), Jarman score (JS), and drugs on discharge. Those with p < 0.2, together with interacting covariates, from the preliminary analysis were eligible for the multivariate Cox regression analysis. Results. Of the 523 patients admitted between 1994 and 1998 because of their asthma, complete data were available for 440. Of these, 112 were readmitted. Eligible covariates for the multivariate Cox regression analysis were sex, allergy status, history of eczema/hay fever, the JS and TI together with interactions between JS and TI, JS and allergy, and allergy with eczema/hay fever. There were 278 subjects (71 with a readmission) with complete data for these eligible covariates. The multivariate analysis revealed that female sex (odds ratio [OR] = 2.65, 95% confidence interval [CI] 1.42, 4.92), high JS (OR = 2.03, 95% CI 1.13-3.65), and history of allergy (OR= 1.88, 95% CI 1.06-3.32) formed the final model as significant predictors of readmission. Conclusion. Females with a history of allergy that were registered at a practice with a high workload (JS) had a higher risk of readmission. The analysis method used highlights how those at risk of readmission can be identified so that they can be targeted post discharge.en_HK
dc.languageengen_US
dc.publisherInforma Healthcare. The Journal's web site is located at http://www.tandf.co.uk/journals/titles/02770903.aspen_HK
dc.relation.ispartofJournal of Asthmaen_HK
dc.subjectAsthmaen_HK
dc.subjectCovariateen_HK
dc.subjectCox regressionen_HK
dc.subjectHospital readmissionen_HK
dc.titleA Cox Regression Analysis of Covariates for Asthma Hospital Readmissionsen_HK
dc.typeArticleen_HK
dc.identifier.emailWong, ICK: wongick@hku.hken_HK
dc.identifier.authorityWong, ICK=rp01480en_HK
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1081/JAS-120019035en_HK
dc.identifier.pmid14579995-
dc.identifier.scopuseid_2-s2.0-0142021837en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-0142021837&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume40en_HK
dc.identifier.issue6en_HK
dc.identifier.spage645en_HK
dc.identifier.epage652en_HK
dc.identifier.isiWOS:000185995800006-
dc.publisher.placeUnited Statesen_HK
dc.identifier.scopusauthoridSalamzadeh, J=25636288500en_HK
dc.identifier.scopusauthoridWong, ICK=7102513915en_HK
dc.identifier.scopusauthoridHosker, HSR=6701774618en_HK
dc.identifier.scopusauthoridChrystyn, H=7005136151en_HK

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