A nomogram for predicting mild cognitive impairment in older adults with hypertension

BMC Neurology - Tập 23 Số 1
Jingyu Lu1, Wen Ding1, Liping Zhang2, Xiaoling Liu3
1Nursing Department, General Hospital of Ningxia Medical University, Yinchuan, China
2Department of Cardiovascular Medicine, General Hospital of Ningxia Medical University, Yinchuan, China
3Neurology Department, General Hospital of Ningxia Medical University, Yinchuan, China

Tóm tắt

Abstract Background Hyper- and hypotension increase the risk of cognitive dysfunction. As effective control of blood pressure can reduce the risk of mild cognitive impairment (MCI), early risk assessment is necessary to identify MCI in senile hypertension as soon as possible and reduce the risk of developing dementia. No perfect risk-prediction model or nomogram has been developed to evaluate the risk of MCI in older adults with hypertension. We aimed to develop a nomogram model for predicting MCI in older patients with hypertension. Methods We selected 345 older patients with hypertension in Xixiangtang District, Nanning City, as the modeling group and divided into the MCI (n = 197) and non-MCI groups (n = 148). Comparing the general conditions, lifestyle, disease factors, psychosocial and other indicators. Logistic regression was used to analyze risk factors for MCI in older hypertensive patients, and R Programming Language was used to draw the nomogram. We selected 146 older patients with hypertension in Qingxiu District, Nanning City, as the verification group. The effectiveness and discrimination ability of the nomogram was evaluated through internal and external verification. Results Multivariate logistic regression analysis identified 11 factors, including hypertension grade, education level, complicated diabetes, hypertension years, stress history, smoking, physical exercise, reading, social support, sleep disorders, and medication compliance, as risk factors for MCI in older patients with hypertension. To develop a nomogram model, the validity of the prediction model was evaluated by fitting the curve, which revealed a good fit for both the modeling (P = 0.98) and verification groups (P = 0.96). The discrimination of the nomogram model was evaluated in the modeling group using a receiver operating characteristic curve. The area under the curve was 0.795, and the Hosmer–Lemeshow test yielded P = 0.703. In the validation group, the area under the curve was 0.765, and the Hosmer–Lemeshow test yielded P = 0.234. Conclusions We developed a nomogram to help clinicians identify high-risk groups for MCI among older patients with hypertension. This model demonstrated good discrimination and validity, providing a scientific basis for community medical staff to evaluate and identify the risk of MCI in these patients at an early stage.

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BMC Neurology

Tập 23 Số 1

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