Abstract

Objectives: To demonstrate that 1) models based on small numbers of tests can be statistically developed to identify neuropsychological impairment in a general adult neuropsychology clinic and 2) those models show strong predictive validity on replication in a slightly different sample. Method: Latent Class Analyses (LCA) were used to determine neuropsychological classification in 231 patients referred to general adult neuropsychology services. A clinical rating scale was also used to approximate clinical decision-making. Regression models were constructed in a training sample (n = 127) drawn from an adult neuropsychology clinic using test scores from seven different a priori test battery combinations to predict group membership or clinical rating. The utility of the seven models was assessed in a testing sample (n = 104) from another independent adult neuropsychology clinic. Results: The LCA yielded a two class solution characterized by impaired versus non-impaired performance on neuropsychological tests. A seven test battery provided the best balance of accuracy and length in predicting LCA group with a sensitivity of 84.4% and a specificity of 90%. Sensitivity and specificity were slightly attenuated using the clinical rating scale as the criterion, but the seven test battery still provided good accuracy (AUC=.906). Conclusions: Test protocols based on only five to eight test scores can accurately identify most patients with clinical impairment in a diverse adult neuropsychology clinic. Development of short protocols with adequate sensitivity and specificity will become increasingly important to address long waiting lists in light of the COVID pandemic against the general backdrop of increasing demand for neuropsychological services.

摘要

目的：证明 1) 基于少量测试的模型可以在统计上开发，以识别普通成人神经心理学诊所的神经心理损伤，2) 这些模型在略有不同的样本中显示出很强的预测有效性。方法：使用潜在类别分析 (LCA) 来确定 231 名转至一般成人神经心理学服务的患者的神经心理学分类。还使用临床评级量表来近似临床决策。在从成人神经心理学诊所抽取的训练样本 (n = 127) 中构建回归模型，使用七种不同的先验测试组合组合的测试分数来预测小组成员资格或临床评级。在来自另一家独立成人神经心理学诊所的测试样本（n = 104）中评估了七个模型的实用性。结果： LCA 产生了两类解决方案，其特征是神经心理学测试中的表现受损与未受损。七组测试在预测 LCA 组方面提供了准确性和长度的最佳平衡，灵敏度为 84.4%，特异性为 90%。使用临床评定量表作为标准，敏感性和特异性略有减弱，但七组测试仍然提供良好的准确性（AUC=.906）。结论：仅基于五到八个测试分数的测试方案就可以准确识别不同成人神经心理学诊所中大多数患有临床障碍的患者。鉴于新冠疫情大流行以及对神经心理学服务需求不断增加的总体背景，制定具有足够敏感性和特异性的简短方案对于解决漫长的等待名单将变得越来越重要。