发表机构
University of Manitoba（曼尼托巴大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究基于112名阿尔茨海默病患者的rTMS试验数据，发现早期ADAS-Cog总分反应比领域特异性反应更能预测长期认知变化，岭回归模型MAE为3.067，可作为早期反应更新工具。
AI 中文摘要
重复经颅磁刺激（rTMS）后的早期认知反应可能预测阿尔茨海默病后期的认知变化，但领域特异性反应的增量价值尚不明确。我们分析了112名随机参与者的数据；101人进入第5周里程碑队列，91人在治疗后第8、16和24周拥有完整的预测因子和结局。嵌套预测因子集比较使用岭回归评估基线信息、试验变量、早期总分反应和领域特异性反应。模型类别比较包括岭回归、多任务弹性网络、受限随机森林和纵向混合效应。验证采用重复治疗部位分层5折交叉验证，重复5次，嵌套超参数调整，以及配对参与者水平自助法比较，重采样10,000次。加入第3周和第5周ADAS-Cog总分反应改善了预测。早期总反应岭回归实现了总体MAE 3.067，RMSE 3.885，$R^2=0.384$。用22个分量水平变化替换两个总反应变量使性能下降（MAE 3.363，RMSE 4.269，$R^2=0.257$）。配对MAE差异为-0.297分（95% CI -0.485至-0.115）。混合效应具有竞争力（MAE 3.162），与总反应岭回归的总体差异不确定。使用绝对未来评分和排除第3周反应的敏感性分析支持主要发现。在本样本中，早期聚合ADAS-Cog反应比高维领域特异性表示更具信息量。该模型是内部验证的早期反应更新工具，而非预处理选择模型或rTMS因果疗效的证据。
英文摘要
Early cognitive response after repetitive transcranial magnetic stimulation (rTMS) may predict later cognitive change in Alzheimer disease, but the incremental value of domain-specific response is unclear. We analyzed data from 112 randomized participants; 101 entered a Week-5 landmark cohort and 91 had complete predictors and outcomes at 8, 16, and 24 weeks post-treatment. Nested predictor-set comparisons used ridge regression to evaluate baseline information, trial variables, early total-score response, and domain-specific response. Model-class comparisons included ridge, multi-task elastic net, restricted random forest, and longitudinal mixed effects. Validation used repeated treatment-site-stratified 5-fold cross-validation with five repetitions, nested hyperparameter tuning, and paired participant-level bootstrap comparisons with 10,000 resamples. Adding Week-3 and Week-5 ADAS-Cog total-score response improved prediction. The early total-response ridge achieved overall MAE 3.067, RMSE 3.885, and $R^2=0.384$. Replacing two total-response variables with 22 component-level changes worsened performance (MAE 3.363, RMSE 4.269, $R^2=0.257$). The paired MAE difference was -0.297 points (95% CI -0.485 to -0.115). Mixed effects was competitive (MAE 3.162), with an uncertain overall difference from total-response ridge. Sensitivity analyses using absolute future scores and excluding Week-3 response supported the main findings. In this sample, early aggregate ADAS-Cog response was more informative than a higher-dimensional domain-specific representation. The model is an internally validated early-response updating tool, not a pretreatment selection model or evidence of causal rTMS efficacy.
