ArticleBMC neurology2023
A nomogram for predicting mild cognitive impairment in older adults with hypertension.
Article in BMC neurology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 12 citations in OpenAlex.
- Identification of cognitive impairment in patients with hypertension: a systematic review and critical appraisal of existing models.Frontiers in medicine · 2026Pooled it
- The Cognitive Changes Among Patients over 65 Years of Age in a Rural Area-The Preliminary Report of Protective and Predisposing Factors.Neurology international · 2025Article
- Construction and evaluation of nomogram for risk prediction of cognitive impairment in chronic obstructive pulmonary disease comorbidity.BMC psychology · 2025Article
- Prediction Model for Cognitive Impairment among Disabled Older Adults: A Development and Validation Study.Healthcare (Basel, Switzerland) · 2024Article
- Prevalence of cognitive impairment and its associated factors in type 2 diabetes mellitus patients with hypertension in Hunan, China: a cross-sectional study.Frontiers in psychiatry · 2024Article
- Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database.Frontiers in public health · 2024Article
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundHyper- 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.
methodsWe 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.
resultsMultivariate 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.
conclusionsWe 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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