Comparison of validation and application on various cardiovascular disease mortality risk prediction models in Chinese rural population

Sun, Changqing; Xu, Fei; Liu, Xiaotian; Fang, Mingwang; Zhou, Hao; Lian, Yixiao; Xie, Chen; Sun, Ning; Wang, Chongjian

doi:10.1038/srep43227

Cited by 9 publications

(9 citation statements)

References 33 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…These findings may be due to the fact the FRS model was developed from individuals of Caucasian ethnicity. Validation and recalibration should be conducted before this risk assessment tool can be applied in other populations [23]. Existing models mostly included hypertension predictors based on the FRS model [13-20], which was easily available.…”

Section: Discussionmentioning

confidence: 99%

“…This survey is a 6-year population-based prospective cohort study in the rural areas of Henan Province, China (Figure S1 in Online Supplementary Document s howed the position where data was collected). Details of the study design and methods have been described and reported previously [22,23]. Briefly, the baseline survey was conducted from July to August of 2007 and of 2008.…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Development and validation of prediction models for hypertension risks in rural Chinese populations

Xu¹,

Zhu²,

Sun³

et al. 2019

Journal of Global Health

Self Cite

View full text Add to dashboard Cite

BackgroundVarious hypertension predictive models have been developed worldwide; however, there is no existing predictive model for hypertension among Chinese rural populations.MethodsThis is a 6-year population-based prospective cohort in rural areas of China. Data was collected in 2007-2008 (baseline survey) and 2013-2014 (follow-up survey) from 8319 participants ranging in age from 35 to 74 years old. Specified gender hypertension predictive models were established based on multivariate Cox regression, Artificial Neural Network (ANN), Naive Bayes Classifier (NBC), and Classification and Regression Tree (CART) in the training set. External validation was conducted in the testing set. The estimated models were assessed by discrimination and calibration, respectively.ResultsDuring the follow-up period, 432 men and 604 women developed hypertension in the training set. Assessment for established models in men suggested men office-based model (M1) was better than others. C-index of M1 model in the testing set was 0.771 (95% confidence Interval (CI) = 0.750, 0.791), and calibration χ2 = 6.3057 (P = 0.7090). In women, women office-based model (W1) and ANN were better than the other models assessed. The C-indexes for the W1 model and the ANN model in the testing set were 0.765 (95% CI = 0.746, 0.783) and 0.756 (95% CI = 0.737, 0.775) and the calibrations χ2 were 6.7832 (P = 0.1478) and 4.7447 (P = 0.3145), respectively.ConclusionsNot all machine-learning models performed better than the traditional Cox regression models. The W1 and ANN models for women and M1 model for men have better predictive performance which could potentially be recommended for predicting hypertension risk among rural populations.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Development and validation of prediction models for hypertension risks in rural Chinese populations

Xu¹,

Zhu²,

Sun³

et al. 2019

Journal of Global Health

Self Cite

View full text Add to dashboard Cite

show abstract

“…The definition of CVD in the Hong Kong cohort was similar to ours, but the sudden death for unknown reason was also included in the outcome. Previous validation of risk scores developed in populations of European ancestry among Chinese populations have only shown moderate performance, even after recalibration leading to recommendations that ethnic-specific risk scores are developed [ 32 33 34 ].…”

Section: Discussionmentioning

confidence: 99%

Prediction of Five-Year Cardiovascular Disease Risk in People with Type 2 Diabetes Mellitus: Derivation in Nanjing, China and External Validation in Scotland, UK

Wan

Read

et al. 2022

View full text Add to dashboard Cite

Background:To use routinely collected data to develop a five-year cardiovascular disease (CVD) risk prediction model for Chinese adults with type 2 diabetes with validation of its performance in a population of European ancestry.Methods: People with incident type 2 diabetes and no history of CVD at diagnosis of diabetes between 2008 and 2017 were included in derivation and validation cohorts. The derivation cohort was identified from a pseudonymized research extract of data from the First Affiliated Hospital of Nanjing Medical University (NMU). Five-year risk of CVD was estimated using basic and extended Cox proportional hazards regression models including 6 and 11 predictors respectively. The risk prediction models were internally validated and externally validated in a Scottish population-based cohort with CVD events identified from linked hospital records. Discrimination and calibration were assessed using Harrell's C-statistic and calibration plots, respectively.Results: Mean age of the derivation and validation cohorts were 58.4 and 59.2 years, respectively, with 53.5% and 56.9% men. During a median follow-up time of 4. 75 [2.67, 7.42] years, 18,827 (22.25%) of the 84,630 people in the NMU-Diabetes cohort and 8,763 (7.31%) of the Scottish cohort of 119,891 people developed CVD. The extended model had a C-statistic of 0.723 [0.721-0.724] in internal validation and 0.716 [0.713-0.719] in external validation. Conclusions: It is possible to generate a risk prediction model with moderate discriminative power in internal and external validation derived from routinely collected Chinese hospital data. The proposed risk score could be used to improve CVD prevention in people with diabetes.2 Wan et al.

show abstract

“…Additionally, all older patients with hypertension received antihypertensive drugs according to Chinese guidelines for the management of hypertension during follow-up ( Sun et al, 2017 ). In this study, patients with hypertension were divided into two categories: treated but with uncontrolled hypertension and hypertension controlled with medication.…”

Section: Methodsmentioning

confidence: 99%

Associations between abdominal obesity and the risk of stroke in Chinese older patients with obstructive sleep apnea: Is there an obesity paradox?

Yang

et al. 2022

Front. Aging Neurosci.

View full text Add to dashboard Cite

Background and purposeAbdominal obesity (AO) is a well-known independent risk factor for stroke in the general population although it remains unclear in the case of the elderly, especially in Chinese older patients with obstructive sleep apnea (OSA), considering the obesity paradox. This study aimed to investigate the association between AO and stroke among Chinese older patients with OSA.MethodsData were collected from January 2015 to October 2017, and 1,290 older patients (age 60–96 years) with OSA (apnea–hypopnea index ≥ 5 events/h on polysomnography) were consecutively enrolled from sleep centers at six hospitals, evaluated for AO defined as waist circumference (WC) using the standardized criteria for the Chinese population, and followed up prospectively for a median period of 42 months. Logistic regression and Cox regression analyses were used to determine the cross-sectional and longitudinal associations between AO and stroke risk in these participants and different groups of the severity of OSA.ResultsParticipants with AO had a higher prevalence of stroke at baseline. A higher incidence of stroke during a median follow-up period of 42 months in participants with AO than in participants without AO (12.4% vs. 6.8% and 8.3% vs. 2.4%, respectively; both P < 0.05) was predicted. Cross-sectional analysis revealed an association between AO and stroke (odds ratio [OR]1.96, 95% confidence interval [CI] 1.31–2.91), which was stronger among participants with moderate OSA only (OR 2.16, 95%CI 1.05–4.43). Cox regression analysis showed that, compared to participants without AO, participants with AO had a higher cumulative incidence of stroke (hazard ratio [HR] 2.16, 95% CI 1.12–4.04) during a median follow-up of 42 months, and this association was observed in patients with severe OSA only (HR 3.67, 95% CI 1.41–9.87) but not for individuals with mild OSA (HR = 1.84, 95% CI 0.43–6.23) and moderate OSA (HR = 1.98, 95% CI 0.73–6.45).ConclusionThe risk of stroke is associated with AO among Chinese older patients who have OSA, both at baseline and during follow-up, and the strength of the association varied by OSA severity. Active surveillance for early detection of AO could facilitate the implementation of stroke-preventive interventions in the Chinese older OSA population.

show abstract

Comparison of validation and application on various cardiovascular disease mortality risk prediction models in Chinese rural population

Cited by 9 publications

References 33 publications

Development and validation of prediction models for hypertension risks in rural Chinese populations

Development and validation of prediction models for hypertension risks in rural Chinese populations

Prediction of Five-Year Cardiovascular Disease Risk in People with Type 2 Diabetes Mellitus: Derivation in Nanjing, China and External Validation in Scotland, UK

Associations between abdominal obesity and the risk of stroke in Chinese older patients with obstructive sleep apnea: Is there an obesity paradox?

Contact Info

Product

Resources

About