Dataset Information

Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol.

ABSTRACT: INTRODUCTION:Diabetes mellitus (DM) is a major disease burden worldwide because it is associated with disabling and lethal complications. DM complication risk assessment and stratification is key to cost-effective management and tertiary prevention for patients with diabetes in primary care. Existing risk prediction functions were found to be inaccurate in Chinese patients with diabetes in primary care. This study aims to develop 10-year risk prediction models for total cardiovascular diseases (CVD) and all-cause mortality among Chinese patients with DM in primary care. METHODS AND ANALYSIS:A 10-year cohort study on a population-based primary care cohort of Chinese patients with diabetes, who were receiving care in the Hospital Authority General Outpatient Clinic on or before 1 January 2008, were identified from the clinical management system database of the Hospital Authority. All patients with complete baseline risk factors will be included and followed from 1 January 2008 to 31 December 2017 for the development and validation of prediction models. The analyses will be carried out separately for men and women. Two-thirds of subjects will be randomly selected as the training sample for model development. Cox regressions will be used to develop 10-year risk prediction models of total CVD and all-cause mortality. The validity of models will be tested on the remaining one-third of subjects by Harrell's C-statistics and calibration plot. Risk prediction models for diabetic complications specific to Chinese patients in primary care will enable accurate risk stratification, prioritisation of resources and more cost-effective interventions for patients with DM in primary care. ETHICS AND DISSEMINATION:The study was approved by the Institutional Review Board of the University of Hong Kong-the Hospital Authority Hong Kong West Cluster (reference number: UW 15-258). TRIAL REGISTRATION NUMBER:NCT03299010; Pre-results.

SUBMITTER: Wan EYF

PROVIDER: S-EPMC6194459 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol.

Wan Eric Yuk Fai EYF Yu Esther Yee Tak EYT Chin Weng Yee WY Fung Colman Siu Cheung CSC Kwok Ruby Lai Ping RLP Chao David Vai Kiong DVK Chan King Hong KH Hui Eric Ming-Tung EM Tsui Wendy Wing Sze WWS Tan Kathryn Choon Beng KCB Fong Daniel Yee Tak DYT Lam Cindy Lo Kuen CLK

BMJ open 20181015 10

<h4>Introduction</h4>Diabetes mellitus (DM) is a major disease burden worldwide because it is associated with disabling and lethal complications. DM complication risk assessment and stratification is key to cost-effective management and tertiary prevention for patients with diabetes in primary care. Existing risk prediction functions were found to be inaccurate in Chinese patients with diabetes in primary care. This study aims to develop 10-year risk prediction models for total cardiovascular di ...[more]

PMID: 30327405

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Project description:ObjectiveGreen space has been shown to be beneficial for human wellness through multiple pathways. This study aimed to explore the contributions of neighbouring green space to cause-specific mortality.MethodsData from 3544 Chinese men and women (aged ≥65 years at baseline) in a community-based cohort study were analysed. Outcome measures, identified from the death registry, were death from all-cause, respiratory system disease, circulatory system disease. The quantity of green space (%) within a 300 m radius buffer was calculated for each subject from a map created based on the Normalised Difference Vegetation Index. Cox proportional hazard models adjusted for demographics, socioeconomics, lifestyle, health conditions and housing type were used to estimate the HRs and 95% CIs.ResultsDuring a mean of 10.3 years of follow-up, 795 deaths were identified. Our findings showed that a 10% increase in coverage of green space was significantly associated with a reduction in all-cause mortality (HR 0.963, 95% CI 0.930 to 0.998), circulatory system-caused mortality (HR 0.887, 95% CI 0.817 to 0.963) and stroke-caused mortality (HR 0.661, 95% CI 0.524 to 0.835), independent of age, sex, marital status, years lived in Hong Kong, education level, socioeconomic ladder, smoking, alcohol intake, diet quality, self-rated health and housing type. The inverse associations between coverage of green space with all-cause mortality (HR 0.964, 95% CI 0.931 to 0.999) and circulatory system disease-caused mortality (HR 0.888, 95% CI 0.817 to 0.964) were attenuated when the models were further adjusted for physical activity and cognitive function. The effects of green space on all-cause and circulatory system-caused mortality tended to be stronger in females than in males.ConclusionHigher coverage of green space was associated with reduced risks of all-cause mortality, circulatory system-caused mortality and stroke-caused mortality in Chinese older people living in a highly urbanised city.

Dataset Information

Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol.

Publications

Ten-year risk prediction models of complications and mortality of Chinese patients with diabetes mellitus in primary care in Hong Kong: a study protocol.

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