Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database
Background and aimChanges in cognitive function are commonly associated with aging in patients with cardiovascular diseases. The objective of this research was to construct and validate a nomogram-based predictive model for the identification of cognitive impairment in older people suffering from ca...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Public Health |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fpubh.2024.1447366/full |
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| author | Hui Wang Sensen Wu Dikang Pan Yachan Ning Cong Wang Jianming Guo Yongquan Gu |
| author_facet | Hui Wang Sensen Wu Dikang Pan Yachan Ning Cong Wang Jianming Guo Yongquan Gu |
| author_sort | Hui Wang |
| collection | DOAJ |
| description | Background and aimChanges in cognitive function are commonly associated with aging in patients with cardiovascular diseases. The objective of this research was to construct and validate a nomogram-based predictive model for the identification of cognitive impairment in older people suffering from cardiovascular diseases.Methods and resultsThis retrospective study included 498 participants with cardiovascular diseases aged >60 selected from the NHANES 2011–2014. The study employed the Minor Absolute Shrinkage and Selection Operator (LASSO) regression model, in conjunction with multivariate logistic regression analysis, to identify relevant variables and develop a predictive model. We used statistical techniques as in the Minor Absolute Shrinkage (MAS) and the Selection Operator (LASSO) regression model, in conjunction with multivariate logistic regression analysis, to identify variables that were significantly predictive of the outcome. After which, based on the selected relevant variables, we developed a machine learning model that was predictive of cognitive impairment such as Alzheimer’s diseases in the older people. The effectiveness of the resultant nomogram was evaluated by assessing its discriminative capability, calibration, and conducting decision curve analysis (DCA). The constructed predictive nomogram included age, race, educational attainment, poverty income ratio, and presence of sleep disorder as variables. The model demonstrated robust discriminative capability, achieving an area under the receiver-operating characteristic curve of 0.756, and exhibited precise calibration. Consistent performance was confirmed through 10-fold cross-validation, and DCA deemed the nomogram clinically valuable.ConclusionWe constructed a NHANES cardiovascular-based nomogram predictive model of cognitive impairment. The model exhibited robust discriminative ability and validity, offering a scientific framework for community healthcare providers to assess and detect the risk of cognitive decline in these patients prematurely. |
| format | Article |
| id | doaj-art-933c0a9255154ff1ab6cf3134eb1141a |
| institution | Kabale University |
| issn | 2296-2565 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Public Health |
| spelling | doaj-art-933c0a9255154ff1ab6cf3134eb1141a2025-01-13T05:10:15ZengFrontiers Media S.A.Frontiers in Public Health2296-25652025-01-011210.3389/fpubh.2024.14473661447366Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey databaseHui Wang0Sensen Wu1Dikang Pan2Yachan Ning3Cong Wang4Jianming Guo5Yongquan Gu6Department of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, ChinaDepartment of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, ChinaDepartment of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, ChinaDepartment of Intensive Care Medicine, Xuanwu Hospital, Capital Medical University, Beijing, ChinaDepartment of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, ChinaDepartment of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, ChinaDepartment of Vascular Surgery, Xuanwu Hospital, Capital Medical University, Beijing, ChinaBackground and aimChanges in cognitive function are commonly associated with aging in patients with cardiovascular diseases. The objective of this research was to construct and validate a nomogram-based predictive model for the identification of cognitive impairment in older people suffering from cardiovascular diseases.Methods and resultsThis retrospective study included 498 participants with cardiovascular diseases aged >60 selected from the NHANES 2011–2014. The study employed the Minor Absolute Shrinkage and Selection Operator (LASSO) regression model, in conjunction with multivariate logistic regression analysis, to identify relevant variables and develop a predictive model. We used statistical techniques as in the Minor Absolute Shrinkage (MAS) and the Selection Operator (LASSO) regression model, in conjunction with multivariate logistic regression analysis, to identify variables that were significantly predictive of the outcome. After which, based on the selected relevant variables, we developed a machine learning model that was predictive of cognitive impairment such as Alzheimer’s diseases in the older people. The effectiveness of the resultant nomogram was evaluated by assessing its discriminative capability, calibration, and conducting decision curve analysis (DCA). The constructed predictive nomogram included age, race, educational attainment, poverty income ratio, and presence of sleep disorder as variables. The model demonstrated robust discriminative capability, achieving an area under the receiver-operating characteristic curve of 0.756, and exhibited precise calibration. Consistent performance was confirmed through 10-fold cross-validation, and DCA deemed the nomogram clinically valuable.ConclusionWe constructed a NHANES cardiovascular-based nomogram predictive model of cognitive impairment. The model exhibited robust discriminative ability and validity, offering a scientific framework for community healthcare providers to assess and detect the risk of cognitive decline in these patients prematurely.https://www.frontiersin.org/articles/10.3389/fpubh.2024.1447366/fullcognitive impairmentolder adultsAlzheimer’s diseasenomogramprediction modelNHANES |
| spellingShingle | Hui Wang Sensen Wu Dikang Pan Yachan Ning Cong Wang Jianming Guo Yongquan Gu 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 cognitive impairment older adults Alzheimer’s disease nomogram prediction model NHANES |
| title | Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database |
| title_full | Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database |
| title_fullStr | Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database |
| title_full_unstemmed | Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database |
| title_short | Risk prediction model of cognitive performance in older people with cardiovascular diseases: a study of the National Health and Nutrition Examination Survey database |
| title_sort | risk prediction model of cognitive performance in older people with cardiovascular diseases a study of the national health and nutrition examination survey database |
| topic | cognitive impairment older adults Alzheimer’s disease nomogram prediction model NHANES |
| url | https://www.frontiersin.org/articles/10.3389/fpubh.2024.1447366/full |
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