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Abstract
Objective To develop and internally validate a prediction model for 6-year risk of stroke and its primary subtypes in middle-aged and elderly Chinese population.
Design This is a retrospective cohort study from a prospectively collected database.
Participants We included a total 3124 adults aged 45–80 years, free of stroke or myocardial infarction at baseline in the 2009–2015 cohort of China Health and Nutrition Survey.
Primary and secondary outcome measures The outcome of the prediction model was stroke. Investigated predictors were: age, gender, body mass index (BMI), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), total cholesterol (TC), hypertension (HBP), drinking status, smoking status, diabetes and site. Stepwise multiple Cox regression was applied to identify independent predictors. A nomogram was constructed to predict 6-year risk of stroke based on the multiple analysis results. Bootstraps with 1000 resamples were applied to both C-index and calibration curve.
Result The overall incidence of overall stroke was 2.98%. Age, gender, HBP and TC were found as significant risk predictors for overall stroke; age, gender, HBP and LDL-C were found as significant risk predictors for ischaemic stroke; age, gender, HBP, BMI and HDL-C were found as significant risk predictors for haemorrhagic stroke. The nomogram was constructed using significant variables included in the model, with a C-index of 0.74 (95% CI: 0.72 to 0.76), 0.74 (95% CI: 0.71 to 0.77), and 0.81 (95% CI: 0.78 to 0.84) for overall stroke, ischaemic stroke, and haemorrhagic stroke model, respectively. The calibration curves demonstrated the good agreements between predicted and observed 6-year risk probability.
Conclusion Our nomogram could be convenient, easy to use and effective prognoses for predicting 6-year risk of stroke in middle-aged and elderly Chinese population.
- epidemiology
- stroke
- risk management
Data availability statement
Data from China Health and Nutrition Survey was used in this study, which can be downloaded at http://www.cpc.unc.edu/projects/china/data/datasets.
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
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Data availability statement
Data from China Health and Nutrition Survey was used in this study, which can be downloaded at http://www.cpc.unc.edu/projects/china/data/datasets.
Supplementary materials
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Footnotes
Contributors QY conceptualised and designed the study, carried out the initial analyses, drafted the initial manuscript, and reviewed and revised the manuscript. YW, QJ, YC, QL and XL critically reviewed and revised the manuscript. All authors approved the final manuscript for submission.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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