Department of Clinical Health Psychology, University of Manitoba, Winnipeg, MB, Canada.
Arch Clin Neuropsychol. 2011 Feb;26(1):16-25. doi: 10.1093/arclin/acq089. Epub 2010 Dec 8.
The lack of gold standard diagnostic criteria for cognitive impairment in the absence of dementia has resulted in variable nomenclature, case definitions, outcomes, risk factors, and prognostic utilities. Our objective was to elucidate the clinical correlates of conversion to dementia in a longitudinal population-based sample. Using data from the Canadian Study of Health and Aging, a machine learning algorithm was used to identify symptoms that best differentiated converting from nonconverting cognitively impaired not demented participants. Poor retrieval was the sole predictor of conversion to dementia over 5 years. This finding suggests that patients with impaired retrieval are at greater risk for progression to dementia at follow-up. Employing significant predictors as markers for ongoing monitoring and assessment, rather than as clinical markers of conversion, is recommended given the less than optimal specificity of the predictive algorithms.
由于缺乏痴呆症患者认知障碍的金标准诊断标准，导致了命名法、病例定义、结果、风险因素和预后实用性的多样性。我们的目的是在纵向的基于人群的样本中阐明向痴呆症转化的临床相关性。使用来自加拿大健康老龄化研究的数据，机器学习算法被用来识别能够最好地区分从非认知障碍但认知受损的不痴呆参与者中转化的症状。检索能力差是 5 年内转化为痴呆的唯一预测因素。这一发现表明，在随访中，检索能力受损的患者更有可能发展为痴呆。由于预测算法的特异性较差，建议将显著预测因素作为持续监测和评估的标志物，而不是作为转化的临床标志物。
