Literature DB >> 27523508

Psychometric Properties of Alzheimer's Disease Assessment Scale-Cognitive Subscale for Mild Cognitive Impairment and Mild Alzheimer's Disease Patients in an Asian Context.

Nur Hani Zainal1, Eveline Silva, Linda Lh Lim, Nagaendran Kandiah.   

Abstract

INTRODUCTION: The purpose of the current study is to assess the psychometric properties of Alzheimer's Disease Assessment Scale-Cognitive subscale (ADAS-Cog) on patients with mild cognitive impairment (MCI) and mild Alzheimer's disease (AD) in a multicultural Asian context.
MATERIALS AND METHODS: Sixty-four mild AD patients (mean age ± SD; 72.24 ± 7.88 years), 80 MCI patients (66.44 ± 7.45 years) and 125 healthy controls (HCs) (61.81 ± 6.96 years) participated in the study. Participants underwent a clinical interview and serial neuropsychological testing. ADAS-Cog total and subtest scores were compared across the 3 groups. Receiver operating characteristics (ROC) analysis were performed and sensitivity, specificity, positive predictive values (PPVs) and negative predictive values (NPVs) were calculated.
RESULTS: Patients with MCI attained significantly worse neuropsychological test scores than healthy controls but significantly better results than patients with mild AD on ADAS-Cog total score, subtest items, and the delayed recall item (P <0.001). The best cutoff score to differentiate between MCI and HC was ≥4 (sensitivity = 0.73, specificity = 0.69, PPV = 0.90, NPV = 0.40), while the best cutoff score to distinguish between MCI and mild AD was ≥12 (sensitivity = 0.86, specificity = 0.89, PPV = 0.99, NPV = 0.32). Evidence of internal consistency of the ADAS-Cog (Cronbach α = 0.85) as well as convergent validity with the Mini-Mental State Examination (MMSE) (ρ = -0.75) and Montreal Cognitive Assessment (MoCA) (ρ = -0.81) (both P <0.001) was also found.
CONCLUSION: The ADAS-Cog which is widely used in clinical trials is applicable to the Asian cohort. It is useful in the detection of MCI and mild AD as well as in distinguishing these 2 conditions.

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Year:  2016        PMID: 27523508

Source DB:  PubMed          Journal:  Ann Acad Med Singapore        ISSN: 0304-4602            Impact factor:   2.473


  5 in total

1.  Cultural adaptation of Alzheimer's disease assessment scale-cognitive subscale for use in India and validation of the Tamil version for South Indian population.

Authors:  Monisha Lakshminarayanan; Sridhar Vaitheswaran; Nivedhitha Srinivasan; Gayathri Nagarajan; Ahalya Ganesh; Kunnukatil S Shaji; Mina Chandra; Murali Krishna; Aimee Spector
Journal:  Aging Ment Health       Date:  2021-01-25       Impact factor: 3.514

2.  Altered Domain Functional Network Connectivity Strength and Randomness in Schizophrenia.

Authors:  Victor M Vergara; Eswar Damaraju; Jessica A Turner; Godfrey Pearlson; Aysenil Belger; Daniel H Mathalon; Steven G Potkin; Adrian Preda; Jatin G Vaidya; Theo G M van Erp; Sarah McEwen; Vince D Calhoun
Journal:  Front Psychiatry       Date:  2019-07-23       Impact factor: 4.157

3.  Visual Abnormalities Associate With Hippocampus in Mild Cognitive Impairment and Early Alzheimer's Disease.

Authors:  Aonan Zhao; Fang Fang; Binyin Li; Yan Chen; Yinghui Qiu; Yanli Wu; Wei Xu; Yulei Deng
Journal:  Front Aging Neurosci       Date:  2021-01-22       Impact factor: 5.750

Review 4.  Evaluation of Available Cognitive Tools Used to Measure Mild Cognitive Decline: A Scoping Review.

Authors:  Chian Thong Chun; Kirsty Seward; Amanda Patterson; Alice Melton; Lesley MacDonald-Wicks
Journal:  Nutrients       Date:  2021-11-08       Impact factor: 5.717

5.  Cognitive Assessment of Patients With Alzheimer's Disease by Telemedicine: Pilot Study.

Authors:  Anna Carotenuto; Raffaele Rea; Enea Traini; Giovanna Ricci; Angiola Maria Fasanaro; Francesco Amenta
Journal:  JMIR Ment Health       Date:  2018-05-11
  5 in total

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