Edinburgh Research Explorer Understanding and predicting the longitudinal course of dementia
Edinburgh Research Explorer Understanding and predicting the longitudinal course of dementia
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爱丁堡研究探索者了解和预测痴呆症的纵向病程
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通讯作者：
E. Matalova
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作者：
B. Veselá;Adéla Ševčíková;Katerina Holomkova;A. Ramesova;A. Kratochvílová;Paul T. Sharpe;E. Matalova
在临床护理中传达预后时需要考虑到这一点。随着痴呆症患者在他们的患者旅程中以更多的方式发生变化，异质性疾病进展是疾病和患者特征的结果。预测模型将受益于包括跨多个领域的变量。建议对研究方法的推广和标准化进行国际协调。患者本研究使用来自NACC的PWD纵向数据来研究痴呆多维进展的预测因素。同时研究多个结果（在这种情况下是认知和日常功能）使这项研究有别于该领域的大多数其他研究。此外，显示社会人口特征的影响是相当独特和重要的。这项研究使用了来自NACC的PWD的纵向数据，表明早期识别的生长类艾德可以部分复制。尽管GMM是了解疾病过程异质性的重要技术，但其数据驱动的性质促使人们进行重复研究。这项研究重复了一个未被充分认识的发现，即大多数PWD的下降速度比通常报告的平均下降速度慢。
this needs to be taken into account when communicating prognosis in clinical care. As persons with dementia change in many more ways during their patient journey, heterogeneous disease progressions are the result of disease and patient characteristics. Prognostic models would benefit from including variables across a number of domains. International coordination of replication and standardization of the research approach is recommended. patients. This study used longitudinal data from PWD from NACC to study the predictors of multidimensional progression of dementia. Studying multiple outcomes simulta- neously (in this case cognition and daily functioning) sets out this study from most other studies in the field. Also showing the impact of sociodemographic char- acteristics is both fairly unique and important. This study used longitudinal data from PWD from NACC to show that growth classes identified earlier could be partially replicated. Although an important technique to understand heterogeneity in disease course, the data-driven nature of GMM urges for replication studies. The study replicated the underappreciated finding that the majority of PWD showed a decline slower than typically reported for the average decline.