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Article: Prediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus – A population-based retrospective cohort study

TitlePrediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus – A population-based retrospective cohort study
Authors
KeywordsType 2 diabetes mellitus
Prediction
Risk
Mortality
Primary care
Issue Date2017
PublisherElsevier Inc. The Journal's web site is located at http://www.elsevier.com/locate/jdiacomp
Citation
Journal of Diabetes and its Complications, 2017, v. 31 n. 6, p. 939-944 How to Cite?
AbstractAims: This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. Methods: A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5 years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Results: Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell”'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Conclusions: Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models.
Persistent Identifierhttp://hdl.handle.net/10722/245100
ISSN
2017 Impact Factor: 2.792
2015 SCImago Journal Rankings: 1.632
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorWan, YF-
dc.contributor.authorFong, DYT-
dc.contributor.authorFung, SCC-
dc.contributor.authorYu, YTE-
dc.contributor.authorChin, WY-
dc.contributor.authorChan, KC-
dc.contributor.authorLam, CLK-
dc.date.accessioned2017-09-18T02:04:36Z-
dc.date.available2017-09-18T02:04:36Z-
dc.date.issued2017-
dc.identifier.citationJournal of Diabetes and its Complications, 2017, v. 31 n. 6, p. 939-944-
dc.identifier.issn1056-8727-
dc.identifier.urihttp://hdl.handle.net/10722/245100-
dc.description.abstractAims: This study aimed to develop and validate an all-cause mortality risk prediction model for Chinese primary care patients with type 2 diabetes mellitus(T2DM) in Hong Kong. Methods: A population-based retrospective cohort study was conducted on 132,462 Chinese patients who had received public primary care services during 2010. Each gender sample was randomly split on a 2:1 basis into derivation and validation cohorts and was followed-up for a median period of 5 years. Gender-specific mortality risk prediction models showing the interaction effect between predictors and age were derived using Cox proportional hazards regression with forward stepwise approach. Developed models were compared with pre-existing models by Harrell's C-statistic and calibration plot using validation cohort. Results: Common predictors of increased mortality risk in both genders included: age; smoking habit; diabetes duration; use of anti-hypertensive agents, insulin and lipid-lowering drugs; body mass index; hemoglobin A1c; systolic blood pressure(BP); total cholesterol to high-density lipoprotein-cholesterol ratio; urine albumin to creatinine ratio(urine ACR); and estimated glomerular filtration rate(eGFR). Prediction models showed better discrimination with Harrell”'s C-statistics of 0.768(males) and 0.782(females) and calibration power from the plots than previously established models. Conclusions: Our newly developed gender-specific models provide a more accurate predicted 5-year mortality risk for Chinese diabetic patients than other established models.-
dc.languageeng-
dc.publisherElsevier Inc. The Journal's web site is located at http://www.elsevier.com/locate/jdiacomp-
dc.relation.ispartofJournal of Diabetes and its Complications-
dc.subjectType 2 diabetes mellitus-
dc.subjectPrediction-
dc.subjectRisk-
dc.subjectMortality-
dc.subjectPrimary care-
dc.titlePrediction of five-year all-cause mortality in Chinese patients with type 2 diabetes mellitus – A population-based retrospective cohort study-
dc.typeArticle-
dc.identifier.emailWan, YF: yfwan@hku.hk-
dc.identifier.emailFong, DYT: dytfong@hku.hk-
dc.identifier.emailFung, SCC: cfsc@hku.hk-
dc.identifier.emailYu, YTE: ytyu@hku.hk-
dc.identifier.emailChin, WY: chinwy@hku.hk-
dc.identifier.emailChan, KC: kcchanae@hku.hk-
dc.identifier.emailLam, CLK: clklam@hku.hk-
dc.identifier.authorityWan, YF=rp02518-
dc.identifier.authorityFong, DYT=rp00253-
dc.identifier.authorityFung, SCC=rp01330-
dc.identifier.authorityYu, YTE=rp01693-
dc.identifier.authorityChin, WY=rp00290-
dc.identifier.authorityLam, CLK=rp00350-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.jdiacomp.2017.01.017-
dc.identifier.pmid28238555-
dc.identifier.scopuseid_2-s2.0-85013661014-
dc.identifier.hkuros278744-
dc.identifier.volume31-
dc.identifier.issue6-
dc.identifier.spage939-
dc.identifier.epage944-
dc.identifier.isiWOS:000402582900003-
dc.publisher.placeUnited States-

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