Volume 24 Issue 6
Jun.  2026
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Article Navigation >  Chinese Journal of General Practice  > 2026  >  24(6): 1006-1009
WU Xuan, WEI Wenjie, CHEN Lin, ZHU Mingyao, HAN Weiwei, HUANG Qing, FANG Jiamin. Construction of a risk prediction model for cerebral infarction complicated with hypertension based on clinical laboratory indicators[J]. Chinese Journal of General Practice, 2026, 24(6): 1006-1009. doi: 10.16766/j.cnki.issn.1674-4152.004541
Citation: WU Xuan, WEI Wenjie, CHEN Lin, ZHU Mingyao, HAN Weiwei, HUANG Qing, FANG Jiamin. Construction of a risk prediction model for cerebral infarction complicated with hypertension based on clinical laboratory indicators[J]. Chinese Journal of General Practice, 2026, 24(6): 1006-1009. doi: 10.16766/j.cnki.issn.1674-4152.004541
shu

Construction of a risk prediction model for cerebral infarction complicated with hypertension based on clinical laboratory indicators

doi: 10.16766/j.cnki.issn.1674-4152.004541
  • 1.

    Department of Clinical Laboratory, the Second Affiliated Hospital of Bengbu Medical University, Bengbu, Anhui 233080, China

Funds:

 2023AH051915

 2026HX0301012

  • Received Date: 2025-12-30
    Available Online: 2026-11-10
    Abstract
  •   Objective  To establish a prediction model for evaluating the occurrence risk of cerebral infarction combined with hypertension based on Lasso-logistic regression through clinical indicators, and to evaluate the diagnostic value of the model.  Methods  A total of 127 confirmed patients of cerebral infarction admitted to the Second Affiliated Hospital of Bengbu Medical University from January 2022 to December 2024 were included. Based on the presence or absence of a history of hypertension, patients were assigned to two groups: the cerebral infarction group (CI) and the cerebral infarction complicated with hypertension group (CIHT). Clinical data and laboratory indicators were compared, and multivariate logistic regression was utilized to analyze the risk factors associated with cerebral infarction accompanied by hypertension, and the Nomogram model was established. The ROC curve was drawn to analyze its predictive value.  Results  The National Institute of Health stroke scale (NIHSS) scores, BMI, CRP, D-dimer, and neutrophil-lymphocyte ratio (NLR) in the CI group were significantly lower than those in the CIHT group (P < 0.05). The results of the multivariate logistic regression revealed that BMI, CRP, D-dimer, NLR, and NIHSS were all risk factors for cerebral infarction complicated with hypertension. Based on these five independent influencing factors, the Nomogram model was constructed, and the ROC curve was drawn. The AUC was 0.885, the sensitivity was 77.8%, the specificity was 88.9%, and the Youden's index was 0.667, reflecting the excellent discriminatory ability of the established model. The calibration curve results showed that the mean absolute error (MAE) was 0.021, and the calibration curve was highly consistent with the ideal curve, demonstrating a satisfactory calibration of the model.  Conclusion  BMI, CRP, D-dimer, NLR, and NIHSS scores were identified as risk factors for cerebral infarction complicated with hypertension. The constructed Nomogram prediction model has a good calibration and clinical practicality.

     

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