Table_1_Development and Validation of a Nomogram Based on Motoric Cognitive Risk Syndrome for Cognitive Impairment.DOCX

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 (n = 1,177) and validated (n = 2,076) a prediction nomogram. LASSO (least absolute shrinkage and selection operator) regression model and multivariable Cox regression analysis were used for variable selection and for developing the prediction model, respectively. The performance of the nomogram was assessed with respect to its calibration, discrimination, and clinical usefulness.
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.

研究目的：开发并验证一种基于运动认知风险综合征（motoric cognitive risk syndrome）的健康老年人认知障碍预测列线图（nomogram）。
研究方法：本研究纳入两项纵向队列研究的受试者（年龄≥60岁），随访时长为4年，分别使用1177例受试者数据开发该预测列线图，2076例受试者数据用于验证模型性能。本研究分别采用LASSO（least absolute shrinkage and selection operator，最小绝对收缩和选择算子）回归模型进行变量筛选，以及多变量Cox回归分析构建预测模型。通过校准度、区分度及临床实用性三个维度，评估该列线图的整体性能。
研究结果：本研究构建的个体化预测列线图纳入的预测因子包括：运动认知风险综合征、受教育程度、性别、基线认知水平及年龄。该模型展现出良好的区分度[Harrell一致性指数（C-index）为0.814；95%置信区间为0.782~0.835]与校准度。验证队列中得到了相似的结果：同样具备良好的区分度（C-index为0.772；95%置信区间为0.776~0.818）与校准度。决策曲线分析结果显示，该预测列线图具有临床实用价值。
研究结论：本研究所构建的预测列线图纳入了所有临床从业者易于获取的必要预测因子，是一款实用的临床预测工具，可用于评估健康老年人的认知障碍发病风险。