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Analysis of influencing factors and construction of nomogram model in elderly patients with hypertension complicated with stroke
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Rui WANG, Hong-ji ZENG, Wen-juan WANG, Ya-hui LIU, Shu-fan WEI, Qing-feng TIAN
Modern Preventive Medicine | 2024, 51(14) : 2620 - 2627
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Modern Preventive Medicine | 2024, 51(14): 2620-2627
Disease Control and Prevention
Analysis of influencing factors and construction of nomogram model in elderly patients with hypertension complicated with stroke
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Rui WANG, Hong-ji ZENG, Wen-juan WANG, Ya-hui LIU, Shu-fan WEI, Qing-feng TIAN
Affiliations
  • Department of Social Medicine and Health Management, School of Public Health,Zhengzhou University, Zhengzhou, Henan 450000, China
Published: 2024-07-25 doi: 10.20043/j.cnki.MPM.202312221
Outline
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Objective

To identify the influencing factors of stroke in elderly patients with hypertension based on community health survey, and establish a nomogram prediction model according to the influencing factors.

Methods

In 2022, the multi-stage sampling method was used to select the residents of Zhengzhou City, Henan province who lived for more than half a year for community health survey, and univariate and multivariate analysis was used to screen the influential factors of elderly hypertension patients complicated with stroke, and a nomogram prediction model was constructed. ROC curve, calibration curve and DCA decision curve are used to verify the accuracy and stability of the nomogram model.

Results

A total of 15 995 elderly patients with hypertension were included in this study. The original data set was randomly divided into a training set and a validation set at 7:3. Model construction: The results of binary logistics analysis of the training set showed that age, gender, waist circumference, blood pressure control, overweight or obesity, exercise, smoking, drinking, balanced diet, dyslipidemia and heart disease were independent influencing factors for stroke. A nomogram model was constructed according to the results of multi-factor analysis. Model validation: the area under the ROC curve of the training set and the verification set is 0.748\0.779 respectively, and the calibration curve is well fitted, indicating that the model has good predictive value.

Conclusion

In this study, we established a nomogram prediction model for elderly hypertensive patients with stroke, including demographic characteristics, health status and lifestyle. The model is accurate and stable, which can help to screen high-risk individuals, provide clinical decision-making and prevention recommendations.

Old people  /  Hypertension  /  Stroke  /  Influencing factors  /  Nomogram
Rui WANG, Hong-ji ZENG, Wen-juan WANG, Ya-hui LIU, Shu-fan WEI, Qing-feng TIAN. Analysis of influencing factors and construction of nomogram model in elderly patients with hypertension complicated with stroke[J]. Modern Preventive Medicine, 2024 , 51 (14) : 2620 -2627 . DOI: 10.20043/j.cnki.MPM.202312221
Year 2024 volume 51 Issue 14
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Article Info
doi: 10.20043/j.cnki.MPM.202312221
  • Receive Date:2023-12-13
  • Online Date:2026-03-18
  • Published:2024-07-25
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  • Received:2023-12-13
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    Department of Social Medicine and Health Management, School of Public Health,Zhengzhou University, Zhengzhou, Henan 450000, China
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表12种不同金属材料的力学参数

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Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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