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Early assessment of high-risk individuals is essential for timely intervention and management. This study aimed to develop a practical nomogram for the assessment of cognitive impairment in community-dwelling elderly populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methodology<\/jats:title>\n                    <jats:p>This cross-sectional study recruited 581 participants between October 23 and November 8, 2023, comprising 465 assigned to the training cohort and 116 to the validation cohort. Demographic information, medical history, lifestyle, and biochemical parameters were collected using structured questionnaires. Cognitive impairment was assessed via the Montreal Cognitive Assessment (MoCA). Independent features were identified using LASSO regression followed by binary logistic regression, and a nomogram was constructed based on these variables. Model performance was evaluated by discrimination, calibration, and clinical utility using Receiver Operating Characteristic (ROC) curves, calibration plots, the Hosmer\u2013Lemeshow test, and Decision Curve Analysis (DCA).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Cognitive impairment prevalence was 38.5% in the training and 32.8% in the validation cohort. Six features\u2014sex, age, systolic blood pressure, homocysteine, fruit consumption, and family history of stroke\u2014were integrated into the nomogram. The model demonstrated good discrimination (AUC 0.816 in training cohort; 0.796 in validation cohort) with satisfactory calibration and clinical applicability.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>The proposed nomogram provides a reliable and convenient tool for the early risk assessment of cognitive impairment in middle-aged and older adults, facilitating targeted prevention and personalized management in clinical and community settings. Its implementation may assist healthcare professionals in identifying high-risk individuals and mitigating progression toward dementia.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1186\/s12883-026-04719-6","type":"journal-article","created":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T03:54:44Z","timestamp":1770782084000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Development of a clinical nomogram to assess the risk of cognitive impairment in community-dwelling middle-aged and older adults"],"prefix":"10.1186","volume":"26","author":[{"given":"Mengchen","family":"Wang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yao","family":"Sun","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxiao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chun","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Guo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yu","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Frankliu","family":"Gao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bensheng","family":"Qiu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,2,11]]},"reference":[{"issue":"1","key":"4719_CR1","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/s13690-024-01489-w","volume":"83","author":"S Zhao","year":"2025","unstructured":"Zhao S, Yang H, Zhao H, Miao M, Wang Q, Wang Y, et al. 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