Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026
Clinical validation of a voice-based AI tool for screening cognitive impairment: a prospective multicenter study.
СтатьяМногоцентровое исследованиеВалидационное исследованиеНазвание и аннотация: Перевод пока не подготовлен
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Yoon Bora, Lee Hyuk-Je, Kim Woojun, Shim Yong Soo, Lim Eun Ye, Cho A-Hyun, Song In Wook, Hong Yun Jeong, Shin Hye Eun, Ku Bon D, Cho Soo Hyun, Ku Hyejin, Shin Dong-Hoon, Yang Dong Won
Аннотация
BACKGROUND: Early, scalable screening for cognitive impairment is needed beyond traditional paper-and-pencil tools.
OBJECTIVE: To evaluate the diagnostic accuracy and usability of SPICK, a Korean-language, voice-based cognitive screener.
METHODS: In a prospective multicenter validation study (ITT N = 399), the reference diagnosis cognitively impaired (mild cognitive impairment [MCI] or Alzheimer's dementia [AD]) or cognitively unimpaired (CU) was determined independently by board-certified neurologists; SPICK provided the index test result. The primary endpoint was SPICK sensitivity and specificity versus prespecified thresholds (≥ 80% and ≥ 59%). Secondary endpoints included subgroup performance (MCI vs CU; AD vs CU), accuracy, area under the receiver operating characteristic (ROC) curve [AUC], and System Usability Scale (SUS).
RESULTS: For cognitive impairment detection, SPICK achieved sensitivity 85.71% (95% confidence interval [CI] 81.46-89.31%) and specificity 74.29% (62.44-83.99%), meeting thresholds; AUC 0.800 and accuracy 83.71%. Subgroup analyses showed MCI sensitivity 79.64% (72.73-85.47%) and specificity 74.29% (62.44-83.99%), and AD sensitivity 91.98% (86.67-95.66%) and specificity 74.29% (62.44-83.99%). Among 395 participants with usability data, mean SUS was 67.32 (SD 19.10; median 70.0).
CONCLUSION: SPICK demonstrated clinically meaningful accuracy with acceptable usability, supporting its potential as an automated, voice-based screening tool for diverse clinical settings.
OBJECTIVE: To evaluate the diagnostic accuracy and usability of SPICK, a Korean-language, voice-based cognitive screener.
METHODS: In a prospective multicenter validation study (ITT N = 399), the reference diagnosis cognitively impaired (mild cognitive impairment [MCI] or Alzheimer's dementia [AD]) or cognitively unimpaired (CU) was determined independently by board-certified neurologists; SPICK provided the index test result. The primary endpoint was SPICK sensitivity and specificity versus prespecified thresholds (≥ 80% and ≥ 59%). Secondary endpoints included subgroup performance (MCI vs CU; AD vs CU), accuracy, area under the receiver operating characteristic (ROC) curve [AUC], and System Usability Scale (SUS).
RESULTS: For cognitive impairment detection, SPICK achieved sensitivity 85.71% (95% confidence interval [CI] 81.46-89.31%) and specificity 74.29% (62.44-83.99%), meeting thresholds; AUC 0.800 and accuracy 83.71%. Subgroup analyses showed MCI sensitivity 79.64% (72.73-85.47%) and specificity 74.29% (62.44-83.99%), and AD sensitivity 91.98% (86.67-95.66%) and specificity 74.29% (62.44-83.99%). Among 395 participants with usability data, mean SUS was 67.32 (SD 19.10; median 70.0).
CONCLUSION: SPICK demonstrated clinically meaningful accuracy with acceptable usability, supporting its potential as an automated, voice-based screening tool for diverse clinical settings.