Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study
IntroductionMany predictive models for cognitive impairment after mild stroke and transient ischemic attack are based on cognitive scales at a certain timepoint. We aimed to develop two easy-to-use predictive models based on longitudinal cognitive trajectories to facilitate early identification and...
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Frontiers Media S.A.
2025-01-01
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| Series: | Frontiers in Aging Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnagi.2025.1427737/full |
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| author | Panpan Zhao Panpan Zhao Lin Shi Guimei Zhang Chunxiao Wei Weijie Zhai Yanxin Shen Yongchun Wang Zicheng Wang Li Sun |
| author_facet | Panpan Zhao Panpan Zhao Lin Shi Guimei Zhang Chunxiao Wei Weijie Zhai Yanxin Shen Yongchun Wang Zicheng Wang Li Sun |
| author_sort | Panpan Zhao |
| collection | DOAJ |
| description | IntroductionMany predictive models for cognitive impairment after mild stroke and transient ischemic attack are based on cognitive scales at a certain timepoint. We aimed to develop two easy-to-use predictive models based on longitudinal cognitive trajectories to facilitate early identification and treatment.MethodsThis was a prospective cohort study of 556 patients, followed up every 3 months. Patients with at least two cognitive scales within 2.5 years were included in the latent class growth analysis (LCGA). The patients were categorized into two groups based on the LCGA. First, a difference analysis was performed, and further univariate and stepwise backward multifactorial logistic regression was performed. The results were presented as nomograms, and receiver operating characteristic curve analysis, calibration, decision curve analysis, and cross-validation were performed to assess model performance.ResultsThe LCGA eventually included 255 patients, and the “22” group was selected for further subgroup analysis. Among them, 29.8% were included in the cognitive impairment trajectory. Model 1, which incorporated baseline Montreal Cognitive Assessment, ferritin, age, and previous stroke, achieved an area under the curve (AUC) of 0.973, and model 2, which incorporated age, previous stroke, education, and ferritin, with an AUC of 0.771. Decision curve analysis and cross-validation showed excellent clinical applicability.DiscussionHere, we developed two simple and easy-to-use predictive models of post-stroke cognitive trajectories based on a LCGA, which are presented in the form of nomograms suitable for clinical application. These models provide a basis for early detection and prompt treatment. |
| format | Article |
| id | doaj-art-91c3f15d1e294fe2af33b0a6758c9a14 |
| institution | Kabale University |
| issn | 1663-4365 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Aging Neuroscience |
| spelling | doaj-art-91c3f15d1e294fe2af33b0a6758c9a142025-01-29T06:46:06ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652025-01-011710.3389/fnagi.2025.14277371427737Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort studyPanpan Zhao0Panpan Zhao1Lin Shi2Guimei Zhang3Chunxiao Wei4Weijie Zhai5Yanxin Shen6Yongchun Wang7Zicheng Wang8Li Sun9Department of Neurology, The First Affiliated Hospital of Henan University, Henan University, Kaifeng, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaDepartment of Neurology and Neuroscience Center, The First Hospital of Jilin University, Jilin University, Changchun, ChinaIntroductionMany predictive models for cognitive impairment after mild stroke and transient ischemic attack are based on cognitive scales at a certain timepoint. We aimed to develop two easy-to-use predictive models based on longitudinal cognitive trajectories to facilitate early identification and treatment.MethodsThis was a prospective cohort study of 556 patients, followed up every 3 months. Patients with at least two cognitive scales within 2.5 years were included in the latent class growth analysis (LCGA). The patients were categorized into two groups based on the LCGA. First, a difference analysis was performed, and further univariate and stepwise backward multifactorial logistic regression was performed. The results were presented as nomograms, and receiver operating characteristic curve analysis, calibration, decision curve analysis, and cross-validation were performed to assess model performance.ResultsThe LCGA eventually included 255 patients, and the “22” group was selected for further subgroup analysis. Among them, 29.8% were included in the cognitive impairment trajectory. Model 1, which incorporated baseline Montreal Cognitive Assessment, ferritin, age, and previous stroke, achieved an area under the curve (AUC) of 0.973, and model 2, which incorporated age, previous stroke, education, and ferritin, with an AUC of 0.771. Decision curve analysis and cross-validation showed excellent clinical applicability.DiscussionHere, we developed two simple and easy-to-use predictive models of post-stroke cognitive trajectories based on a LCGA, which are presented in the form of nomograms suitable for clinical application. These models provide a basis for early detection and prompt treatment.https://www.frontiersin.org/articles/10.3389/fnagi.2025.1427737/fullcognitive trajectoryferritinmild strokenomogramcognitive impairmentprediction model |
| spellingShingle | Panpan Zhao Panpan Zhao Lin Shi Guimei Zhang Chunxiao Wei Weijie Zhai Yanxin Shen Yongchun Wang Zicheng Wang Li Sun Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study Frontiers in Aging Neuroscience cognitive trajectory ferritin mild stroke nomogram cognitive impairment prediction model |
| title | Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study |
| title_full | Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study |
| title_fullStr | Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study |
| title_full_unstemmed | Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study |
| title_short | Development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories: a prospective cohort study |
| title_sort | development and internal validation of a nomogram for predicting cognitive impairment after mild ischemic stroke and transient ischemic attack based on cognitive trajectories a prospective cohort study |
| topic | cognitive trajectory ferritin mild stroke nomogram cognitive impairment prediction model |
| url | https://www.frontiersin.org/articles/10.3389/fnagi.2025.1427737/full |
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