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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
Yuthachai Sarutikriangkri1,2, Thanakit Pongpitakmetha1,3,4,5, Akarin Hiransuthikul1,6
1Memory Clinic, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.
Background:
Plasma p-tau217 is emerging as a biomarker for Alzheimer's disease (AD) diagnosis, offering a more accessible alternative to CSF and amyloid-PET. The Montreal Cognitive Assessment - Thai Version (MoCA-Thai) and Mini-Mental State Examination - Thai Version (MMSE-Thai) are widely used to detect cognitive impairment in clinical settings, but their optimal cut-off scores for identifying AD pathology, particularly with plasma p-tau217, remain unclear, especially in lower- and middle-income countries (LMICs). This study evaluates the performance of MoCA-Thai, MoCA-Memory Index Score (MoCA-MIS), and MMSE-Thai for AD diagnosis using plasma p-tau217.
Methods:
We recruited patients with early-stage dementia (CDR ≤ 1) from the INDE cohort at King Chulalongkorn Memorial Hospital, Thailand (NCT06375213). AD pathology was determined using an internally validated plasma p-tau217 cutoff (>7.46 pg/mL). Cognitive assessments and Clinical Dementia Rating (CDR) scoring were conducted by trained clinical psychologists. Receiver operating characteristic (ROC) analysis and Youden's index were used to determine optimal cut-off scores.
Results:
There were no significant differences in age, sex, or education level between AD and non-AD groups (Table 1). However, AD patients had significantly lower scores on MoCA-Thai, MoCA-MIS, and MMSE-Thai (p < 0.001). ROC analysis showed that MoCA-MIS (AUROC = 0.762) had the highest discriminative ability, followed by MoCA-Thai (AUROC = 0.738) and MMSE-Thai (AUROC = 0.725) (Figure 1). Optimal cut-off scores were determined as ≤21 for MoCA-Thai (Sensitivity = 75%, Specificity = 69%) and ≤6 for MoCA-MIS (Sensitivity = 67%, Specificity = 77%) (Table 2).
Conclusion:
In our cohort, a MoCA-Thai cut-off of ≤21 and a MoCA-MIS cut-off of ≤6 provided the best optimal sensitivity and specificity for detecting AD pathology. These findings support the integration of cognitive screening tests with plasma biomarkers to enhance early AD detection in clinical settings in Thailand, where access to advanced diagnostics is limited.
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