BACKGROUND: accurately identifying individuals with cognitive impairment is difficult. Given the time constraints that many clinicians face, assessment of cognitive status is often not undertaken. The intent of this study is to determine the diagnostic accuracy of the Alzheimer's questionnaire (AQ) in identifying individuals with mild cognitive impairment (MCI) and AD. METHODS: utilising a case-control design, 300 [100 AD, 100 MCI, 100 cognitively normal (CN)] older adults between the ages of 53 and 93 from a neurology practice and a brain donation programme had the AQ administered to an informant. Diagnostic accuracy was assessed through receiver-operating characteristic analysis, which yielded sensitivity, specificity and area under the curve (AUC). RESULTS: the AQ demonstrated high sensitivity and specificity for detecting MCI [89.00 (81.20-94.40)]; [91.00 (83.60-65.80)] and AD [99.00 (94.60-100.00)]; [96.00 (90.10-98.90)]. AUC values also indicated high diagnostic accuracy for both MCI [0.95 (0.91-0.97)] and AD [0.99 (0.96-1.00)]. Internal consistency of the AQ was also high (Cronbach's alpha = 0.89). CONCLUSION: the AQ is a valid informant-based instrument for identifying cognitive impairment, which could be easily implemented in a clinician's practice. It has high sensitivity and specificity in detecting both MCI and AD and allows clinicians to quickly and accurately assess individuals with reported cognitive problems.
BACKGROUND: accurately identifying individuals with cognitive impairment is difficult. Given the time constraints that many clinicians face, assessment of cognitive status is often not undertaken. The intent of this study is to determine the diagnostic accuracy of the Alzheimer's questionnaire (AQ) in identifying individuals with mild cognitive impairment (MCI) and AD. METHODS: utilising a case-control design, 300 [100 AD, 100 MCI, 100 cognitively normal (CN)] older adults between the ages of 53 and 93 from a neurology practice and a brain donation programme had the AQ administered to an informant. Diagnostic accuracy was assessed through receiver-operating characteristic analysis, which yielded sensitivity, specificity and area under the curve (AUC). RESULTS: the AQ demonstrated high sensitivity and specificity for detecting MCI [89.00 (81.20-94.40)]; [91.00 (83.60-65.80)] and AD [99.00 (94.60-100.00)]; [96.00 (90.10-98.90)]. AUC values also indicated high diagnostic accuracy for both MCI [0.95 (0.91-0.97)] and AD [0.99 (0.96-1.00)]. Internal consistency of the AQ was also high (Cronbach's alpha = 0.89). CONCLUSION: the AQ is a valid informant-based instrument for identifying cognitive impairment, which could be easily implemented in a clinician's practice. It has high sensitivity and specificity in detecting both MCI and AD and allows clinicians to quickly and accurately assess individuals with reported cognitive problems.
Authors: Beth E Snitz; Lisa A Morrow; Eric G Rodriguez; Kimberly A Huber; Judith A Saxton Journal: J Int Neuropsychol Soc Date: 2008-11 Impact factor: 2.892
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Authors: Alexander J Rajic; Peter S Pressman; Jonathan H Woodcock; Heidi J Chial; Christopher M Filley Journal: J Neurol Sci Date: 2021-05-31 Impact factor: 4.553
Authors: Giuseppe Bellelli; Alessandro Morandi; Daniel H J Davis; Paolo Mazzola; Renato Turco; Simona Gentile; Tracy Ryan; Helen Cash; Fabio Guerini; Tiziana Torpilliesi; Francesco Del Santo; Marco Trabucchi; Giorgio Annoni; Alasdair M J MacLullich Journal: Age Ageing Date: 2014-03-02 Impact factor: 10.668