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Article: Prediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus – a population-based retrospective cohort study

TitlePrediction of new onset of end stage renal disease in Chinese patients with type 2 diabetes mellitus – a population-based retrospective cohort study
Authors
KeywordsType 2 diabetes mellitus
Prediction
Risk
End stage renal disease
Primary care
Issue Date2017
PublisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcnephrol/
Citation
BMC Nephrology, 2017, v. 18, article no. 257, p. 1-9 How to Cite?
AbstractBackground: Since diabetes mellitus (DM) is the leading cause of end stage renal disease (ESRD), this study aimed to develop a 5-year ESRD risk prediction model among Chinese patients with Type 2 DM (T2DM) in primary care. Methods: A retrospective cohort study was conducted on 149,333 Chinese adult T2DM primary care patients without ESRD in 2010. Using the derivation cohort over a median of 5 years follow-up, the gender-specific models including the interaction effect between predictors and age were derived using Cox regression with a forward stepwise approach. Harrell’s C-statistic and calibration plot were applied to the validation cohort to assess discrimination and calibration of the models. Results: Prediction models showed better discrimination with Harrell’s C-statistics of 0.866 (males) and 0.862 (females) and calibration power from the plots than other established models. The predictors included age, usages of anti-hypertensive drugs, anti-glucose drugs, and Hemogloblin A1c, blood pressure, urine albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR). Specific predictors for male were smoking and presence of sight threatening diabetic retinopathy while additional predictors for female included longer duration of diabetes and quadratic effect of body mass index. Interaction factors with age showed a greater weighting of insulin and urine ACR in younger males, and eGFR in younger females. Conclusions: Our newly developed gender-specific models provide a more accurate 5-year ESRD risk predictions for Chinese diabetic primary care patients than other existing models. The models included several modifiable risk factors that clinicians can use to counsel patients, and to target at in the delivery of care to patients.
Persistent Identifierhttp://hdl.handle.net/10722/247502
ISSN
2017 Impact Factor: 2.395
2015 SCImago Journal Rankings: 1.113
PubMed Central ID
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.accessioned2017-10-18T08:28:16Z-
dc.date.available2017-10-18T08:28:16Z-
dc.date.issued2017-
dc.identifier.citationBMC Nephrology, 2017, v. 18, article no. 257, p. 1-9-
dc.identifier.issn1471-2369-
dc.identifier.urihttp://hdl.handle.net/10722/247502-
dc.description.abstractBackground: Since diabetes mellitus (DM) is the leading cause of end stage renal disease (ESRD), this study aimed to develop a 5-year ESRD risk prediction model among Chinese patients with Type 2 DM (T2DM) in primary care. Methods: A retrospective cohort study was conducted on 149,333 Chinese adult T2DM primary care patients without ESRD in 2010. Using the derivation cohort over a median of 5 years follow-up, the gender-specific models including the interaction effect between predictors and age were derived using Cox regression with a forward stepwise approach. Harrell’s C-statistic and calibration plot were applied to the validation cohort to assess discrimination and calibration of the models. Results: Prediction models showed better discrimination with Harrell’s C-statistics of 0.866 (males) and 0.862 (females) and calibration power from the plots than other established models. The predictors included age, usages of anti-hypertensive drugs, anti-glucose drugs, and Hemogloblin A1c, blood pressure, urine albumin/creatinine ratio (ACR) and estimated glomerular filtration rate (eGFR). Specific predictors for male were smoking and presence of sight threatening diabetic retinopathy while additional predictors for female included longer duration of diabetes and quadratic effect of body mass index. Interaction factors with age showed a greater weighting of insulin and urine ACR in younger males, and eGFR in younger females. Conclusions: Our newly developed gender-specific models provide a more accurate 5-year ESRD risk predictions for Chinese diabetic primary care patients than other existing models. The models included several modifiable risk factors that clinicians can use to counsel patients, and to target at in the delivery of care to patients.-
dc.languageeng-
dc.publisherBioMed Central Ltd. The Journal's web site is located at http://www.biomedcentral.com/bmcnephrol/-
dc.relation.ispartofBMC Nephrology-
dc.rightsBMC Nephrology. Copyright © BioMed Central Ltd.-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectType 2 diabetes mellitus-
dc.subjectPrediction-
dc.subjectRisk-
dc.subjectEnd stage renal disease-
dc.subjectPrimary care-
dc.titlePrediction of new onset of end stage renal disease 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.naturepublished_or_final_version-
dc.identifier.doi10.1186/s12882-017-0671-x-
dc.identifier.pmid28764641-
dc.identifier.pmcidPMC5539616-
dc.identifier.scopuseid_2-s2.0-85026500159-
dc.identifier.hkuros281359-
dc.identifier.volume18-
dc.identifier.spagearticle no. 257, p. 1-
dc.identifier.epagearticle no. 257, p. 9-
dc.identifier.isiWOS:000406869400002-
dc.publisher.placeUnited Kingdom-

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