scholarly journals Rapid Screening for Cognitive Impairment in Parkinson’s Disease: A Pilot Study

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
YanHong Dong ◽  
Way Inn Koay ◽  
Leonard Leong Litt Yeo ◽  
Christopher Li-Hsian Chen ◽  
Jing Xu ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Discriminant Validity ◽  
Operating Characteristic ◽  
Mini Mental State Examination ◽  
Characteristic Curve ◽  
Rapid Screening ◽  
Cognitive Screening ◽  
Clinical Dementia Rating ◽  
Cognitive Screen ◽  
State Examination

Aim. This study sought to establish the discriminant validity of a rapid cognitive screen, that is, the National Institute of Neurological Disease and Stroke-Canadian Stroke Network (NINDS-CSN) 5-minute protocol, and compare its discriminant validity to the Montreal Cognitive Assessment (MoCA) and Mini Mental State Examination (MMSE) in detecting cognitive impairment (CI) in PD patients.Methods. One hundred and one PD patients were recruited from a movement disorders clinic in Singapore and they received the NINDS-CSN 5-minute protocol, MoCA, and MMSE. No cognitive impairment (NCI) was defined as Clinical Dementia Rating (CDR) = 0 and CI was defined as CDR ≥ 0.5.Results. Area under the receiver operating characteristic curve of NINDS-CSN 5-minute protocol was statistically equivalent to MoCA and larger than MMSE (0.86 versus 0.90,P=0.07; 0.86 versus 0.76,P=0.03). The sensitivity of NINDS-CSN 5-minute protocol (<9) was statistically equivalent to MoCA (<22) (0.77 versus 0.85,P=0.13) and superior to MMSE (<24) (0.77 versus 0.52,P<0.01) in detecting CI, while the specificity of NINDS-CSN 5-minute protocol (<9) was statistically equivalent to MoCA (<22) and MMSE (<24) (0.78 versus 0.88,P=0.34).Conclusion. The NINDS-CSN 5-minute protocol is time expeditious while remaining statistically equivalent to MoCA and superior to MMSE and therefore is suitable for rapid cognitive screening of CI in PD patients.

scholarly journals Random Forest Model in the Diagnosis of Dementia Patients with Normal Mini-Mental State Examination Scores

2022 ◽  
Vol 12 (1) ◽  
pp. 37
Author(s):  
Jie Wang ◽  
Zhuo Wang ◽  
Ning Liu ◽  
Caiyan Liu ◽  
Chenhui Mao ◽  
...  
Keyword(s):  
Machine Learning ◽  
Cognitive Impairment ◽  
Random Forest ◽  
Mental State ◽  
Mini Mental State Examination ◽  
Machine Learning Algorithms ◽  
Assessment Model ◽  
Test Time ◽  
Cognitive Screening ◽  
State Examination

Background: Mini-Mental State Examination (MMSE) is the most widely used tool in cognitive screening. Some individuals with normal MMSE scores have extensive cognitive impairment. Systematic neuropsychological assessment should be performed in these patients. This study aimed to optimize the systematic neuropsychological test battery (NTB) by machine learning and develop new classification models for distinguishing mild cognitive impairment (MCI) and dementia among individuals with MMSE ≥ 26. Methods: 375 participants with MMSE ≥ 26 were assigned a diagnosis of cognitively unimpaired (CU) (n = 67), MCI (n = 174), or dementia (n = 134). We compared the performance of five machine learning algorithms, including logistic regression, decision tree, SVM, XGBoost, and random forest (RF), in identifying MCI and dementia. Results: RF performed best in identifying MCI and dementia. Six neuropsychological subtests with high-importance features were selected to form a simplified NTB, and the test time was cut in half. The AUC of the RF model was 0.89 for distinguishing MCI from CU, and 0.84 for distinguishing dementia from nondementia. Conclusions: This simplified cognitive assessment model can be useful for the diagnosis of MCI and dementia in patients with normal MMSE. It not only optimizes the content of cognitive evaluation, but also improves diagnosis and reduces missed diagnosis.

Comparison of the Mini-Mental State Examination and Computerized Brief Cognitive Screening Test as Cognitive Screening Tools in Patients with Mild Cognitive Impairment

2021 ◽  
Vol 18 ◽  
Author(s):  
Che-Sheng Chu ◽  
I-Chen Lee ◽  
Chuan-Cheng Hung ◽  
I-Ching Lee ◽  
Chi-Fa Hung ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Normal Control ◽  
Internal Consistency ◽  
Mental State ◽  
Screening Test ◽  
Mini Mental State Examination ◽  
Cognitive Screening ◽  
Validity And Reliability ◽  
State Examination

Background: The aim of this study was to establish the validity and reliability of the Computerized Brief Cognitive Screening Test (CBCog) for early detection of cognitive impairment. Method: One hundred and sixty participants, including community-dwelling and out-patient volunteers (both men and women) aged ≥ 65 years, were enrolled in the study. All participants were screened using the CBCog and Mini-Mental State Examination (MMSE). The internal consistency of the CBCog was analyzed using Cronbach’s α test. Areas under the curves (AUCs) of receiver operating characteristic analyses were used to test the predictive accuracy of the CBCog in detecting mild cognitive impairment (MCI) in order to set an appropriate cutoff point. Results: The CBCog scores were positively correlated with the MMSE scores of patients with MCI-related dementia (r = 0.678, P < .001). The internal consistency of the CBCog (Cronbach’s α) was 0.706. It was found that the CBCog with a cutoff point of 19/20 had a sensitivity of 97.5% and a specificity of 53.7% for the diagnosis of MCI with education level ≥ 6 years. The AUC of the CBCog for discriminating the normal control elderly from patients with MCI (AUC = 0.827, P < 0.001) was larger than that of the MMSE for discriminating the normal control elderly from patients with MCI (AUC= 0.819, P < .001). Conclusion: The CBCog demonstrated to have sufficient validity and reliability to evaluate mild cognitive impairment, especially in highly educated elderly people.

Validation of the Cuban Version of Addenbrooke’s Cognitive Examination-Revised for Screening Mild Cognitive Impairment

2017 ◽  
Vol 44 (5-6) ◽  
pp. 320-327 ◽  
Author(s):  
Yunier Broche-Pérez ◽  
Héctor Alejandro López-Pujol
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Operating Characteristic ◽  
Mini Mental State Examination ◽  
Screening Tool ◽  
Roc Curves ◽  
Elderly Subjects ◽  
Psychometric Scales ◽  
State Examination ◽  
Addenbrooke’S Cognitive Examination

Background/Aims: The diagnostic accuracy of the Cuban version of the revised Addenbrooke’s Cognitive Examination (ACE-R) in identifying mild cognitive impairment (MCI) in comparison with the Mini-Mental State Examination (MMSE) was assessed. Methods: The Cuban ACE-R was administered to a group of 129 elderly subjects (92 cognitively healthy and 37 subjects with MCI). The t tests for independent samples were used to compare scores of different psychometric scales between groups, and effect sizes (Cohen’s d) were calculated. Cronbach’s coefficient α was used to evaluate the reliability of psychometric scales. The validity of ACE-R to screen for MCI was assessed by receiver operating characteristic (ROC) curves. Results: The Cuban ACE-R had reliable internal consistency (Cronbach’s coefficient α = 0. 879). The optimal cut-off score for ACE-R for detecting MCI was 84/85. The sensitivity and specificity of ACE-R to screen for MCI was superior to those of MMSE. The area under the ROC curve of the Cuban ACE-R was much larger than that of MMSE (0.93 and 0.63) for detecting MCI. Conclusion: The Cuban ACE-R is a valid screening tool for detecting cognitive impairment. It is more sensitive and accurate in screening for MCI than MMSE.

scholarly journals Comparing measures of decline to dementia in amnestic MCI subjects in the National Alzheimer's Coordinating Center (NACC) Uniform Data Set

2012 ◽  
Vol 24 (10) ◽  
pp. 1553-1560 ◽  
Author(s):  
Sarah E. Monsell ◽  
Danping Liu ◽  
Sandra Weintraub ◽  
Walter A. Kukull
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Neuropsychological Tests ◽  
Mini Mental State Examination ◽  
Clinical Dementia Rating ◽  
Data Set ◽  
Global Test ◽  
Allele Status ◽  
Rate Of Decline ◽  
State Examination

ABSTRACTBackground: Many studies have investigated factors associated with the rate of decline and evolution from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia in elderly patients. In this analysis, we compared the rates of decline to dementia estimated from three common global measures of cognition: Mini-Mental State Examination (MMSE) score, Clinical Dementia Rating sum of boxes (CDR-SB) score, and a neuropsychological tests composite score (CS).Methods: A total of 2,899 subjects in the National Alzheimer's Coordinating Center Uniform Data Set aged 65+ years diagnosed with amnestic mild cognitive impairment (aMCI) were included in this analysis. Population-averaged decline to dementia rates was estimated and compared for standardized MMSE, CDR-SB, and CS using Generalized Estimating Equations (GEE). Associations between rate of decline and several potential correlates of decline were also calculated and compared across measures.Results: The CDR-SB had the steepest estimated slope, with a decline of 0.49 standard deviations (SD) per year, followed by the MMSE with 0.22 SD per year, and finally the CS with 0.07 SD per year. The rate of decline of the three measures differed significantly in a global test for differences (p < 0.0001). Age at visit, body mass index (BMI) at visit, Apolipoprotein E (APOE) ɛ4 allele status, and race (black vs. white) had significantly different relationships with rate of decline in a global test for difference among the three measures.Conclusions: These results suggest that both the rate of decline and the effects of AD risk factors on decline to dementia can vary depending on the evaluative measure used.

The NUCOG: Construction and Piloting of a Cognitive Screening Instrument in a Neuropsychiatric Unit

2003 ◽  
Vol 11 (3) ◽  
pp. 325-329 ◽  
Author(s):  
Mark Walterfang ◽  
Dennis Velakoulis ◽  
Andrew Gibbs ◽  
John Lloyd
Keyword(s):  
Mental State ◽  
Mini Mental State Examination ◽  
Screening Instrument ◽  
Face Validity ◽  
Diverse Population ◽  
Screening Instruments ◽  
Cognitive Screening ◽  
Cognitive Screen ◽  
High Degree ◽  
State Examination

Objective: To develop a cognitive screening instrument suitable for a neuropsychiatric inpatient, outpatient and consultation—liaison population. Methods: A number of cognitive screening instruments used clinically and published in the literature were reviewed. A new tool, the Neuropsychiatry Unit Cognitive Screen (NUCOG), was developed on the basis of this review, and piloted in a diverse population of patients in the unit. Conclusions: The NUCOG demonstrated a high degree of face validity, correlation with the Mini-Mental State Examination, and significant scoring differences between demented and non-demented patients.

Comparison of the Montreal Cognitive Assessment and the Mini-Mental State Examination in detecting multi-domain mild cognitive impairment in a Chinese sub-sample drawn from a population-based study

2013 ◽  
Vol 25 (11) ◽  
pp. 1831-1838 ◽  
Author(s):  
YanHong Dong ◽  
Wah Yean Lee ◽  
Saima Hilal ◽  
Monica Saini ◽  
Tien Yin Wong ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Mental State ◽  
Cognitive Assessment ◽  
Discriminant Validity ◽  
Mini Mental State Examination ◽  
Population Based ◽  
Montreal Cognitive Assessment ◽  
Population Based Study ◽  
State Examination

ABSTRACTBackground:We examined the discriminant validity of the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) in detecting multiple-domain mild cognitive impairment (md-MCI) in a Chinese sub-sample drawn from elderly population-based study.Methods:This study included Chinese participants from the Epidemiology of Dementia in Singapore (EDIS) study aged ≥ 60 years who underwent cognitive screening with the Abbreviated Mental Test and Progressive Forgetfulness Questionnaire. Screen-positive participants subsequently underwent MoCA, MMSE, and a comprehensive formal neuropsychological battery. MCI was defined by Petersen's criteria and further classified into single-domain MCI (sd-MCI) and md-MCI. Area under the receiver operating characteristic curve (AUC) with 95% confidence intervals (CIs) was computed for the MoCA and the MMSE in detecting md-MCI.Results:A total of 300 participants were recruited: 128 (42.7%) were diagnosed with no cognitive impairment (NCI), 47 (15.7%) with sd-MCI, and 83 (28.0%) with md-MCI. Forty-one participants were excluded, 7 (2.3%) had dementia, and 34 (11.3%) had only objective cognitive impairment without subjective complaints. Although the MoCA had a significantly larger AUC than the MMSE (0.94 (95% CI = 0.91–0.97) vs. 0.91 (95% CI = 0.86–0.95), p= 0.04), at optimal cut-off points, the MoCA (19/20) was equivalent to the MMSE (25/26) in detecting md-MCI (sensitivity: 0.80 vs. 0.87, specificity: 0.92 vs. 0.80).Conclusion:Both screening tests had good discriminant validity and can be used in detecting md-MCI in a sub-sample of Chinese drawn from a population-based study.

The Montreal Cognitive Assessment is superior to the Mini–Mental State Examination in detecting patients at higher risk of dementia

2012 ◽  
Vol 24 (11) ◽  
pp. 1749-1755 ◽  
Author(s):  
YanHong Dong ◽  
Wah Yean Lee ◽  
Nur Adilah Basri ◽  
Simon Lowes Collinson ◽  
Reshma A. Merchant ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mental State ◽  
Cognitive Assessment ◽  
Discriminant Validity ◽  
Mini Mental State Examination ◽  
Montreal Cognitive Assessment ◽  
Memory Clinic ◽  
Clinic Setting ◽  
Incident Dementia ◽  
State Examination

ABSTRACTBackground: To examine the discriminant validity of the Montreal Cognitive Assessment (MoCA) and the Mini-Mental State Examination (MMSE) in detecting patients with cognitive impairment at higher risk for dementia at a memory clinic setting.Methods: Memory clinic patients were administered the MoCA, MMSE, and a comprehensive formal neuropsychological battery. Mild cognitive impairment (MCI) subtypes were dichotomized into two groups: single domain–MCI (sd–MCI) and multiple domain-MCI (md–MCI). Area under the receiver operating characteristic curve (ROC) analysis was used to compare the discriminatory ability of the MoCA and the MMSE.Results: Two hundred thirty patients were recruited, of which 136 (59.1%) were diagnosed with dementia, 61 (26.5%) with MCI, and 33 (14.3%) with no cognitive impairment (NCI). The majority of MCI patients had md–MCI (n = 36, 59%). The MoCA had significantly larger AUCs than the MMSE in discriminating md–MCI from the lower risk group for incident dementia (NCI and sd–MCI) [MoCA 0.92 (95% CI, 0.86–0.98) vs. MMSE 0.84 (95% CI, 0.75–0.92), p = 0.02). At their optimal cut-off points, the MoCA (19/20) remained superior to the MMSE (23/24) in detecting md–MCI [sensitivity: 0.83 vs. 0.72; specificity: 0.86 vs. 0.83; PPV: 0.79 vs. 0.72; NPV: 0.89 vs. 0.83; correctly classified: 85.1% vs. 78.7%].Conclusion: The MoCA is superior to the MMSE in the detection of patients with cognitive impairment at higher risk for incident dementia at a memory clinic setting.

scholarly journals Validity of the Japanese Version of the Quick Mild Cognitive Impairment Screen

2019 ◽  
Vol 16 (6) ◽  
pp. 917 ◽  
Author(s):  
Ayako Morita ◽  
Rónán O’Caoimh ◽  
Hiroshi Murayama ◽  
D. Molloy ◽  
Shigeru Inoue ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Predictive Value ◽  
Mini Mental State Examination ◽  
Japanese Version ◽  
Community Dwelling ◽  
Cognitive Screening ◽  
State Examination ◽  
Normal Cognition ◽  
Moderate Positive Correlation

Early detection of dementia provides opportunities for interventions that could delay or prevent its progression. We developed the Japanese version of the Quick Mild Cognitive Impairment (Qmci-J) screen, which is a performance-based, easy-to-use, valid and reliable short cognitive screening instrument, and then we examined its validity. Community-dwelling adults aged 65–84 in Niigata prefecture, Japan, were concurrently administered the Qmci-J and the Japanese version of the standardized Mini-Mental State Examination (sMMSE-J). Mild cognitive impairment (MCI) and dementia were categorized using established and age-adjusted sMMSE-J cut-offs. The sample (n = 526) included 52 (9.9%) participants with suspected dementia, 123 (23.4%) with suspected MCI and 351 with likely normal cognition. The Qmci-J showed moderate positive correlation with the sMMSE-J (r = 0.49, p < 0.001) and moderate discrimination for predicting suspected cognitive impairment (MCI/dementia) based on sMMSE-J cut-offs, area under curve: 0.74, (95%CI: 0.70–0.79), improving to 0.76 (95%CI: 0.72 to 0.81) after adjusting for age. At a cut-off of 60/61/100, the Qmci-J had a 73% sensitivity, 68% specificity, 53% positive predictive value, and 83% negative predictive value for cognitive impairment. Normative data are presented, excluding those with any sMMSE-J < 27. Though further research is required, the Qmci-J screen may be a useful screening tool to identify older adults at risk of cognitive impairment.

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