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A Metadata Extraction Approach for Clinical Case Reports to Enable Advanced Understanding of Biomedical Concepts
Published on: September 20, 2018
Clinical Manifestations
Madeline R Hale1,2, Deling He3, Rebecca E Langhough4,5,6
1Department of Communication Sciences and Disorders, University of Wisconsin-Madison, Madison, WI, USA.
Individuals with Mild Cognitive Impairment (MCI) exhibit distinct speech patterns, including shorter story recall (SR) duration and increased pauses, compared to cognitively unimpaired (CU) individuals. These acoustic speech features show potential as early biomarkers for Alzheimer's disease (AD).
Area of Science:
- Neurology
- Speech Pathology
- Biomarker Discovery
Background:
- Subtle speech features, such as pauses, are sensitive indicators of Alzheimer's disease (AD) pathology, detectable via PET biomarkers.
- Previous research demonstrated that silent pauses in Cookie Theft (CT) picture descriptions could differentiate cognitively unimpaired (CU) from cognitively impaired individuals, with the latter exhibiting longer speech and pauses.
- This study extends the investigation of automated pause detection methods to the domain of story recall (SR) tasks.
Purpose of the Study:
- To investigate the utility of automated acoustic analysis of silent pauses during story recall (SR) as a potential biomarker for early Alzheimer's disease (AD).
- To compare speech characteristics, specifically pause metrics and duration, between individuals with Mild Cognitive Impairment (MCI) and cognitively unimpaired (CU) controls.
- To assess the correlation of these speech metrics with PET biomarkers (amyloid/tau), neuropsychological test results, and overall cognitive status.
Main Methods:
- Fifty participants (25 MCI, 25 CU), matched for key demographics, were selected from the Wisconsin Registry for Alzheimer's Prevention (WRAP) and Wisconsin Alzheimer's Disease Research Center (WADRC).
- Delayed story recall (SR) audio recordings (Logical Memory for WRAP, Craft Story for WADRC) were processed to extract silent pauses (>80ms) using MATLAB Speech Pause Analysis.
- Statistical analyses included Wilcoxon signed rank tests for group comparisons, Spearman correlations for relationships with clinical/biomarker data, and logistic regression/ROC analyses for diagnostic prediction.
Main Results:
- Cognitively unimpaired (CU) participants showed longer SR duration, while the Mild Cognitive Impairment (MCI) group exhibited longer mean pause duration and a higher percentage of pauses.
- Speech duration in SR was significantly correlated with performance on various neuropsychological tests and with amyloid PET burden.
- Total SR duration emerged as a significant predictor of cognitive status (AUC=0.76), outperforming the Cookie Theft (CT) task in differentiating between cognitive groups.
Conclusions:
- Individuals with MCI demonstrate shorter SR duration and increased pause frequency/duration compared to CU individuals, potentially reflecting episodic memory deficits.
- Shorter speech duration in SR tasks is associated with higher amyloid-beta levels, suggesting a link to AD pathology.
- Automated acoustic analysis of pauses in SR shows promise as a sensitive, non-invasive early marker for AD, meriting further investigation in diverse populations.
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