ArticleFrontiers in aging neuroscience2021
Development and Validation of a Nomogram Based on Motoric Cognitive Risk Syndrome for Cognitive Impairment.
Article in Frontiers in aging neuroscience, 2021. 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.
- Mechanisms of motoric cognitive risk-Hypotheses based on a systematic review and meta-analysis of longitudinal cohort studies of older adults.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2022Pooled it
- The association between sarcopenia, sedentary behavior, and the motor cognitive risk syndrome: A Mendelian randomization study.Medicine · 2026Article
- Evaluation criteria for diagnosing motoric cognitive risk syndrome: a scoping review.Dementia & neuropsychologia · 2025Review
- Associations of sarcopenia, sarcopenia parameters and motoric cognitive risk syndrome in Chinese older adults.Frontiers in aging neuroscience · 2023Article
- Stable Sparse Classifiers predict cognitive impairment from gait patterns.Frontiers in psychology · 2022Article
- Incidence Trends and Risk Prediction Nomogram for Suicidal Attempts in Patients With Major Depressive Disorder.Frontiers in psychiatry · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
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Abstract
objectiveTo develop and validate a prediction nomogram based on motoric cognitive risk syndrome for cognitive impairment in healthy older adults.
methodsUsing two longitudinal cohorts of participants (aged ≥ 60 years) with 4-year follow-up, we developed (
resultsThe individualized prediction nomogram was assessed based on the following: motoric cognitive risk syndrome, education, gender, baseline cognition, and age. The model showed good discrimination [Harrell's concordance index (C-index) of 0.814; 95% confidence interval, 0.782-0.835] and good calibration. Comparable results were also seen in the validation cohort, which includes good discrimination (C-index, 0.772; 95% confidence interval, 0.776-0.818) and good calibration. Decision curve analysis demonstrated that the prediction nomogram was clinically useful.
conclusionThis prediction nomogram provides a practical tool with all necessary predictors, which are accessible to practitioners. It can be used to estimate the risk of cognitive impairment in healthy older adults.
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