The Modified Telephone-Administered Minnesota Cognitive Acuity Screen for Mild Cognitive Impairment

2018 ◽  
Vol 31 (3) ◽  
pp. 123-128 ◽  
Author(s):  
Sarah Pillemer ◽  
George D. Papandonatos ◽  
Cara Crook ◽  
Brian R. Ott ◽  
Geoffrey Tremont

Objective: This study aimed to compare the sensitivity and specificity of a modified version of the Minnesota Cognitive Acuity Screen (MCAS-m), by adding learning and recognition memory components, to the original version MCAS to distinguish amnestic mild cognitive impairment (aMCI) from healthy controls (HCs). Methods/Design: A total of 30 individuals with aMCI and 30 HCs underwent neuropsychological testing, neurologic examination, laboratory, and brain imaging tests. Once diagnosis was confirmed, participants completed the MCAS and MCAS-m in counterbalanced order. Results: The average administration time was 12.6 minutes for the MCAS and 13.5 minutes for the MCAS-m. Receiver operating characteristic curve analyses showed that the MCAS-m demonstrated 97% sensitivity and 97% specificity for distinguishing between aMCI and HC versus 97% and 87%, respectively, for the original MCAS in this sample. Conclusions: Both the MCAS and the MCAS-m were highly sensitive when distinguishing between normal cognition and aMCI; however, the MCAS-m demonstrated a 10% increase in specificity compared to the original version. Improved specificity is particularly relevant to screening in larger community samples with lower base rates of MCI than clinic populations. This modified screening measure presents a brief and cost-effective tool for identifying MCI. Given the risk of progression from aMCI to Alzheimer disease dementia (AD), the MCAS-m represents a modest improvement in telephone-administered methods for the early detection of AD.

2013 ◽  
Vol 5 (3) ◽  
pp. 16 ◽  
Author(s):  
Fábio Henrique De Gobbi Porto ◽  
Lívia Spíndola ◽  
Maira Okada De Oliveira ◽  
Patrícia Helena Figuerêdo Do Vale ◽  
Marco Orsini ◽  
...  

It is not easy to differentiate patients with mild cognitive impairment (MCI) from subjective memory complainers (SMC). Assessments with screening cognitive tools are essential, particularly in primary care where most patients are seen. The objective of this study was to evaluate the diagnostic accuracy of screening cognitive tests and to propose a score derived from screening tests. Elderly subjects with memory complaints were evaluated using the Mini Mental State Examination (MMSE) and the Brief Cognitive Battery (BCB). We added two delayed recalls in the MMSE (a delayed recall and a late-delayed recall, LDR), and also a phonemic fluency test of letter P fluency (LPF). A score was created based on these tests. The diagnoses were made on the basis of clinical consensus and neuropsychological testing. Receiver operating characteristic curve analyses were used to determine area under the curve (AUC), the sensitivity and specificity for each test separately and for the final proposed score. MMSE, LDR, LPF and delayed recall of BCB scores reach statistically significant differences between groups (P=0.000, 0.03, 0.001 and 0.01, respectively). Sensitivity, specificity and AUC were MMSE: 64%, 79% and 0.75 (cut off <29); LDR: 56%, 62% and 0.62 (cut off <3); LPF: 71%, 71% and 0.71 (cut off <14); delayed recall of BCB: 56%, 82% and 0.68 (cut off <9). The proposed score reached a sensitivity of 88% and 76% and specificity of 62% and 75% for cut off over 1 and over 2, respectively. AUC were 0.81. In conclusion, a score created from screening tests is capable of discriminating MCI from SMC with moderate to good accurancy.


2018 ◽  
Vol 15 (2) ◽  
pp. 104-110 ◽  
Author(s):  
Shohei Kato ◽  
Akira Homma ◽  
Takuto Sakuma

Objective: This study presents a novel approach for early detection of cognitive impairment in the elderly. The approach incorporates the use of speech sound analysis, multivariate statistics, and data-mining techniques. We have developed a speech prosody-based cognitive impairment rating (SPCIR) that can distinguish between cognitively normal controls and elderly people with mild Alzheimer's disease (mAD) or mild cognitive impairment (MCI) using prosodic signals extracted from elderly speech while administering a questionnaire. Two hundred and seventy-three Japanese subjects (73 males and 200 females between the ages of 65 and 96) participated in this study. The authors collected speech sounds from segments of dialogue during a revised Hasegawa's dementia scale (HDS-R) examination and talking about topics related to hometown, childhood, and school. The segments correspond to speech sounds from answers to questions regarding birthdate (T1), the name of the subject's elementary school (T2), time orientation (Q2), and repetition of three-digit numbers backward (Q6). As many prosodic features as possible were extracted from each of the speech sounds, including fundamental frequency, formant, and intensity features and mel-frequency cepstral coefficients. They were refined using principal component analysis and/or feature selection. The authors calculated an SPCIR using multiple linear regression analysis. Conclusion: In addition, this study proposes a binary discrimination model of SPCIR using multivariate logistic regression and model selection with receiver operating characteristic curve analysis and reports on the sensitivity and specificity of SPCIR for diagnosis (control vs. MCI/mAD). The study also reports discriminative performances well, thereby suggesting that the proposed approach might be an effective tool for screening the elderly for mAD and MCI.


Author(s):  
James R. Hall ◽  
Leigh A. Johnson ◽  
Fan Zhang ◽  
Melissa Petersen ◽  
Arthur W. Toga ◽  
...  

<b><i>Introduction:</i></b> Alzheimer’s disease (AD) is the most frequently occurring neurodegenerative disease; however, little work has been conducted examining biomarkers of AD among Mexican Americans. Here, we examined diffusion tensor MRI marker profiles for detecting mild cognitive impairment (MCI) and dementia in a multi-ethnic cohort. <b><i>Methods:</i></b> 3T MRI measures of fractional anisotropy (FA) were examined among 1,636 participants of the ongoing community-based Health &amp; Aging Brain among Latino Elders (HABLE) community-based study (Mexican American <i>n</i> = 851; non-Hispanic white <i>n</i> = 785). <b><i>Results:</i></b> The FA profile was highly accurate in detecting both MCI (area under the receiver operating characteristic curve [AUC] = 0.99) and dementia (AUC = 0.98). However, the FA profile varied significantly not only between diagnostic groups but also between Mexican Americans and non-Hispanic whites. <b><i>Conclusion:</i></b> Findings suggest that diffusion tensor imaging markers may have a role in the neurodiagnostic process for detecting MCI and dementia among diverse populations.


2003 ◽  
Vol 182 (5) ◽  
pp. 449-454 ◽  
Author(s):  
Anja Busse ◽  
Jeannette Bischkopf ◽  
Steffi G. Riedel-Heller ◽  
Matthias C. Angermeyer

BackgroundAlthough mild cognitive impairment is associated with an increased risk of developing dementia, there has been little work on its incidence and prevalence.AimsTo report age-specific prevalence, incidence and predictive validities for four diagnostic concepts of mild cognitive impairment.MethodA community sample of 1045 dementia-free individuals aged 75 years and over was examined by neuropsychological testing in a three-wave longitudinal study.ResultsPrevalence rates ranged from 3% to 20%, depending on the concept applied. The annual incidence rates applying different case definitions varied from 8 to 77 per 1000 person-years. Rates of conversion to dementia over 2.6 years ranged from 23% to 47%.ConclusionsMild cognitive impairment is frequent in older people. Prevalence, incidence and predictive validities are highly dependent on the diagnostic criteria applied.


2018 ◽  
Vol 14 (6) ◽  
pp. 734-742 ◽  
Author(s):  
Beth E. Snitz ◽  
Tianxiu Wang ◽  
Yona Keich Cloonan ◽  
Erin Jacobsen ◽  
Chung-Chou H. Chang ◽  
...  

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