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Analysis of stroke risk factors and construction of a nomogram model based on LASSO-Logistic regression in elderly hypertensive patients in the Fanjing Mountain region
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Na WANG1, Feng HONG1, Meng-meng ZHOU2, Si-nian LV2, Wei-zhong WANG2, Biao DAI2, Jun HU1, Yu-jie TIAN1, Da-fei REN1, 2
Modern Preventive Medicine | 2026, 53(4) : 602 - 607
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Modern Preventive Medicine | 2026, 53(4): 602-607
• Epidemiology and Statistical Methods Advances •
Analysis of stroke risk factors and construction of a nomogram model based on LASSO-Logistic regression in elderly hypertensive patients in the Fanjing Mountain region
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Na WANG1, Feng HONG1, Meng-meng ZHOU2, Si-nian LV2, Wei-zhong WANG2, Biao DAI2, Jun HU1, Yu-jie TIAN1, Da-fei REN1, 2
Affiliations
  • School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
Published: 2026-02-25 doi: 10.20043/j.cnki.MPM.202509025
Outline
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Objective

To identify the risk factors of stroke in hypertension patients and construct nomogram based on the survey data of elderly health in Fanjingshan area, and to provide reference for stroke risk prevention and control in this area.

Methods

In 2025, proportional sampling method will be adopted to select elderly residents aged ≥65 years old and living locally for ≥6 months to carry out health survey. LASSO-Logistic regression was used to screen stroke risk factors in elderly hypertensive patients to construct nomograms. Receiver operating characteristic curves (ROC), calibration curves, Brier values, and decision curve analysis (DCA) were used to evaluate the discrimination, calibration, and clinical utility of the model. The robustness of the model was evaluated by repeated ten-fold cross validation.

Results

A total of 1 670 hypertensive patients were enrolled, of whom 245 had stroke. LASSO-Logistic regression analysis showed that impaired instrumental ability of daily living (IADL), waist circumference, average monthly income <3 000 yuan, tea drinking, sleep duration>8 hours, heart disease, self-rated health as average, alcohol abstinence were risk factors for stroke, and age ≥85 years old and alcohol consumption were protective factors. The model discriminated well (AUC=0.735), the Hosmer-Lemeshow test (H-L test) statistic was 8.749 (P=0.364), and the Brier value was 0.112, suggesting that the model was well calibrated; DCA indicated that the model had a clinical net benefit within the specified risk threshold range; repeated 10-fold cross validation results further confirmed its robustness.

Conclusion

The nomogram model can be used as an effective tool to assess stroke risk in elderly hypertensive population and formulate individualized prevention and intervention strategies.

Old people  /  Hypertension  /  Stroke  /  Lasso regression  /  Nomogram
王娜, 洪峰, 周萌萌, 吕思念, 王伟忠, 代彪, 胡君, 田玉洁, 任达飞. 基于LASSO-Logistic回归的梵净山老年高血压患者脑卒中发生风险因素分析及列线图模型构建. 现代预防医学, 2026 , 53 (4) : 602 -607 . DOI: 10.20043/j.cnki.MPM.202509025
Na WANG, Feng HONG, Meng-meng ZHOU, Si-nian LV, Wei-zhong WANG, Biao DAI, Jun HU, Yu-jie TIAN, Da-fei REN. Analysis of stroke risk factors and construction of a nomogram model based on LASSO-Logistic regression in elderly hypertensive patients in the Fanjing Mountain region[J]. Modern Preventive Medicine, 2026 , 53 (4) : 602 -607 . DOI: 10.20043/j.cnki.MPM.202509025
Year 2026 volume 53 Issue 4
29
15
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Article Info
doi: 10.20043/j.cnki.MPM.202509025
  • Receive Date:2025-09-01
  • Online Date:2026-11-02
  • Published:2026-02-25
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  • Received:2025-09-01
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    School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, Guizhou 561113, China
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表12种不同金属材料的力学参数
科
Family
属数
Number of
genus
种数
Number of
species
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Percentage of
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属
Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
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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