Johannes Tröger, Ebru Baykara, Jian Zhao, Daphne Ter Huurne, Nina Possemis, Elisa Mallick, Simona Schäfer, Louisa Schwed, Mario Mina, Nicklas Linz, Inez Ramakers, Craig Ritchie
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We present the evaluation of a novel digital speech biomarker for cognition (SB-C) following the Digital Medicine Society's V3 framework: verification, analytical validation, and clinical validation.</p><p><strong>Methods: </strong>Evaluation was done in two independent clinical samples: the Dutch DeepSpA (<i>N</i> = 69 subjective cognitive impairment [SCI], <i>N</i> = 52 mild cognitive impairment [MCI], and <i>N</i> = 13 dementia) and the Scottish SPeAk datasets (<i>N</i> = 25, healthy controls). 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引用次数: 4
摘要
进行性认知能力下降是阿尔茨海默病等大多数痴呆性疾病的主要行为症状。虽然大多数公认的认知测量方法可能不适合未来分散的远程临床试验,但数字认知评估将变得越来越重要。我们根据数字医学协会的V3框架对一种新的认知数字语音生物标志物(SB-C)进行了评估:验证、分析验证和临床验证。方法:在两个独立的临床样本中进行评估:荷兰DeepSpA (N = 69主观认知障碍[SCI], N = 52轻度认知障碍[MCI], N = 13痴呆)和苏格兰SPeAk数据集(N = 25健康对照)。为了验证,使用了两个锚点评分:迷你精神状态检查(MMSE)和临床痴呆评分(CDR)量表。结果:验证:使用自动语音处理管道可以可靠地提取两种语言的SB-C。分析验证:在两种语言中,SB-C与MMSE得分密切相关。临床验证:SB-C在临床组间(包括MCI和痴呆)差异显著,与CDR强相关,可追踪临床有意义的下降。结论:我们的研究结果表明,ki:e SB-C是一种客观、可扩展和可靠的认知能力下降指标,适合作为临床早期痴呆试验的远程评估。
Validation of the Remote Automated ki:e Speech Biomarker for Cognition in Mild Cognitive Impairment: Verification and Validation following DiME V3 Framework.
Introduction: Progressive cognitive decline is the cardinal behavioral symptom in most dementia-causing diseases such as Alzheimer's disease. While most well-established measures for cognition might not fit tomorrow's decentralized remote clinical trials, digital cognitive assessments will gain importance. We present the evaluation of a novel digital speech biomarker for cognition (SB-C) following the Digital Medicine Society's V3 framework: verification, analytical validation, and clinical validation.
Methods: Evaluation was done in two independent clinical samples: the Dutch DeepSpA (N = 69 subjective cognitive impairment [SCI], N = 52 mild cognitive impairment [MCI], and N = 13 dementia) and the Scottish SPeAk datasets (N = 25, healthy controls). For validation, two anchor scores were used: the Mini-Mental State Examination (MMSE) and the Clinical Dementia Rating (CDR) scale.
Results: Verification: The SB-C could be reliably extracted for both languages using an automatic speech processing pipeline. Analytical Validation: In both languages, the SB-C was strongly correlated with MMSE scores. Clinical Validation: The SB-C significantly differed between clinical groups (including MCI and dementia), was strongly correlated with the CDR, and could track the clinically meaningful decline.
Conclusion: Our results suggest that the ki:e SB-C is an objective, scalable, and reliable indicator of cognitive decline, fit for purpose as a remote assessment in clinical early dementia trials.