Combination Of Mini-Mental State Examination Research Articles

Combination of Plasma Neurofilament Light Chain and Mini-Mental State Examination Score Predicts Progression from Mild Cognitive Impairment to Alzheimer's Disease within 5 Years.

Individuals with mild cognitive impairment (MCI) are at high risk of progression to Alzheimer's disease (AD) dementia, but some remain stable. There is a need to identify those at higher risk of progression to improve patient management and outcomes. To evaluate the trajectory of plasma neurofilament light chain (pNFL) prior to progression from MCI to AD dementia, the performance of pNFL, in combination with the Mini-Mental State Examination (MMSE), as a predictor of progression from MCI to AD dementia and to inform clinicians on the use of pNFL as a predictive biomarker. Participants (n = 440) with MCI and longitudinal follow-up (mean = 4.2 years) from the AD Neuroimaging Initiative dataset were included. pNFL as a marker for neurodegeneration and the MMSE as a cognitive measure were investigated as simple/practical predictors of progression. The risk of progressing from MCI to AD dementia associated with pNFL and MMSE scores was assessed using Cox and logistic regression models. The current risk of progression to AD dementia was 37%higher in individuals with high pNFL (> 56 ng/L) compared to those with average pNFL (≤40 ng/L). A combination of baseline pNFL and MMSE could differentiate those who progressed within 5 years (AUC = 0.75) from stable individuals. Including change in MMSE over 6-12 months further improved the model (AUC = 0.84). Our findings reveal that combining pNFL with a simple dementia screener (MMSE) can reliably predict whether a person with MCI is likely to progress to AD dementia within 5 years.

The combination of MMSE with VSRAD and eZIS has greater accuracy for discriminating mild cognitive impairment from early Alzheimer's disease than MMSE alone.

Alzheimer's disease (AD) is assessed by carefully examining a patient's cognitive impairment. However, previous studies reported inadequate diagnostic accuracy for dementia in primary care settings. Many hospitals use the automated quantitative evaluation method known as the Voxel-based Specific Regional Analysis System for Alzheimer's Disease (VSRAD), wherein brain MRI data are used to evaluate brain morphological abnormalities associated with AD. Similarly, an automated quantitative evaluation application called the easy Z-score imaging system (eZIS), which uses brain SPECT data to detect regional cerebral blood flow decreases associated with AD, is widely used. These applications have several indicators, each of which is known to correlate with the degree of AD. However, it is not completely known whether these indicators work better when used in combination in real-world clinical practice. We included 112 participants with mild cognitive impairment (MCI) and 128 participants with early AD in this study. All participants underwent MRI, SPECT, and the Mini-Mental State Examination (MMSE). Demographic and clinical characteristics were assessed by univariate analysis, and logistic regression analysis with a combination of MMSE, VSRAD and eZIS indicators was performed to verify whether the diagnostic accuracy in discriminating between MCI and early AD was improved. The area under the receiver operating characteristic curve (AUC) for the MMSE score alone was 0.835. The AUC was significantly improved to 0.870 by combining the MMSE score with two quantitative indicators from the VSRAD and eZIS that assessed the extent of brain abnormalities. Compared with the MMSE score alone, the combination of the MMSE score with the VSRAD and eZIS indicators significantly improves the accuracy of discrimination between patients with MCI and early AD. Implementing VSRAD and eZIS does not require professional clinical experience in the treatment of dementia. Therefore, the accuracy of dementia diagnosis by physicians may easily be improved in real-world primary care settings.

Cognitive Function Outcomes of Post-operative Mild to Moderate Traumatic Brain Injury using Combination of Mini-mental State Examination, Digit Span, and Constructional Praxis

BACKGROUND: Progress has been made in developing systems of care that strives to minimize traumatic brain injury (TBI)-related morbidity and mortality. As the TBI survivors, one’s might be experienced cognitive function disorders that affect their quality of life.
 AIM: We sought to investigate the changes of cognitive function in patients with mild or moderate TBI.
 METHODS: This was a prospective study on 80 patients with mild and moderate TBI who had undergone surgery; 79 patients included in the study and one patient excluded due to incompletion of cognitive tasks. We assessed the cognitive function using a combination of mini-mental state examination (MMSE), digit span (DS), and constructional praxis (CP) tests. The correlations between clinical variables and neuropsychological tests were analyzed.
 RESULTS: In this study, majority of the patients were male (77.2%) with the mean of age 28.4 years, ranging from 15 to 74 years, predominantly was a young adult (15–20 years, 32.9%). In this series, majority of the patients had moderate TBI (69.6%). Most of the patients (55.7%) had 12 or more education years. MMSE examination revealed that 6.3% and 2.5% of patients had mild- and moderate-cognitive disturbances, respectively, significantly correlated with age (p = 0.049) and educational level (p = 0.008). From DS tests, 13.9% patients had attention disorders and significantly correlated with age (p = 0.015), educational level (p = 0.000), and the severity of TBI (p = 0.018). From CP tests, 24.1% and 5.1% had mild- and moderate-disturbances, respectively, significantly correlated with the severity of TBI (p = 0.025) and the type of intracranial lesion (p = 0.009).
 CONCLUSIONS: We found (using a combination of MMP, DS, and CP test) cognitive impairment more frequently in patients with moderate TBI, older age, and low education level, hence, emphasized the importance of holistic neuropsychological assessments and neurological rehabilitation for adequate management of patients with TBI.

Clock-drawing test in vascular mild cognitive impairment: Validity of quantitative and qualitative analyses

ABSTRACT Introduction The clock-drawing test (CDT) has been used as a screening tool to identify cognitive deficit in patients with dementia. However, it has not been extensively evaluated for categorizing patients with vascular mild cognitive impairment (vMCI). This study aimed to examine the discrimination of vMCI using various CDT scoring methods. Method A total of 120 vMCI patients and 119 normal control (NC) subjects were tested using three CDT quantitative scoring systems: the one from the Montreal Cognitive Assessment (MoCA) (CDT3) and the systems of Rouleau (CDT10) and Babins (CDT18). We used a revised scoring method to evaluate the effectiveness in differentiating vMCI patients from NC subjects, which combined the CDT10 quantitative score and three qualitative errors with a significantly higher prevalence in vMCI group (called hereinafter CDTcomb, including CDTcomb13 and CDTcomb16 based on different weights of the three error types). The sensitivity and specificity of the CDT methods were determined by the receiver operating characteristic (ROC) curve. The results of the scoring systems were compared with those of the Mini-Mental State Examination (MMSE). Results The results of the ROC analyses with the CDT3, CDT10, and CDT18 systems produced a sensitivity of 71.1%, 81.8%, and 60.3%, and a specificity of 66.12%, 58.68%, and 73.55%, respectively, for the diagnosis of vMCI. Compared with the separate MMSE score, the combination of MMSE with the CDT3, CDT10 and CDT18 scores did not increase the sensitivity and specificity. When three qualitative errors were incorporated into the CDT10 quantitative score, CDTcomb13 and CDTcomb16 provided a sensitivity of 87.6% and 86.78%, and a specificity of 74.79% and 80.67%, respectively, in differentiating vMCI patients from the NC group. Conclusion Our findings suggest that the combination of CDT quantitative score with qualitative observations of the clock-drawing errors can provide a better discrimination between vMCI patients and cognitively normal subjects.

A machine learning-based linguistic battery for diagnosing mild cognitive impairment due to Alzheimer's disease.

There is a limited evaluation of an independent linguistic battery for early diagnosis of Mild Cognitive Impairment due to Alzheimer’s disease (MCI-AD). We hypothesized that an independent linguistic battery comprising of only the language components or subtests of popular test batteries could give a better clinical diagnosis for MCI-AD compared to using an exhaustive battery of tests. As such, we combined multiple clinical datasets and performed Exploratory Factor Analysis (EFA) to extract the underlying linguistic constructs from a combination of the Consortium to Establish a Registry for Alzheimer’s disease (CERAD), Wechsler Memory Scale (WMS) Logical Memory (LM) I and II, and the Boston Naming Test. Furthermore, we trained a machine-learning algorithm that validates the clinical relevance of the independent linguistic battery for differentiating between patients with MCI-AD and cognitive healthy control individuals. Our EFA identified ten linguistic variables with distinct underlying linguistic constructs that show Cronbach’s alpha of 0.74 on the MCI-AD group and 0.87 on the healthy control group. Our machine learning evaluation showed a robust AUC of 0.97 when controlled for age, sex, race, and education, and a clinically reliable AUC of 0.88 without controlling for age, sex, race, and education. Overall, the linguistic battery showed a better diagnostic result compared to the Mini-Mental State Examination (MMSE), Clinical Dementia Rating Scale (CDR), and a combination of MMSE and CDR.

A simple and clinically relevant combination of neuroimaging and functional indexes for the identification of those at highest risk of Alzheimer's disease.

The current challenge in clinical practice is to identify those with mild cognitive impairment (MCI), who are at greater risk of Alzheimer's disease (AD) conversion in the near future. The aim of this study was to assess a clinically practical new hippocampal index-hippocampal volume normalized by cerebellar volume (hippocampus to cerebellum volume ratio) used alone or in combination with scores on the Mini-Mental State Examination, as a predictor of conversion from MCI to AD. The predictive value of the HCCR was also contrasted to that of the hippocampal volume to intracranial volume ratio. The findings revealed that the performance of the combination of measures was significantly better than that of each measure used individually. The combination of Mini-Mental State Examination and hippocampal volume, normalized by the cerebellum or by intracranial volume, accurately discriminated individuals with MCI who progress to AD within 5 years from other MCI types (stable, reverters) and those with intact cognition (area under receiver operating curve of 0.88 and 0.89, respectively). Normalization by cerebellar volume was as accurate as normalization by intracranial volume with the advantage of being more practical, particularly for serial assessments.

Cognitive and functional impairment in an older community population from Brazil: The intriguing association with frequent pain

ObjectiveThis cross-sectional community-based epidemiologic survey aimed to investigate the prevalence of cognitive and functional impairment (CFI) and its distribution in relation to socio-demographic and clinical factors in an older community sample in Florianópolis, Brazil. Materials and methodsThe population was a representative sample aged 60 and older; the cluster sample strategy was performed. CFI, a syndromic category that does not exclude dementia, was defined according to the combination of low MMSE (Mini-Mental State Examination) score and moderate/severe dependence in a scale that measured activities of daily living. The data were submitted to multiple regression analysis using the Poisson regression method. ResultsA sample of 1705 subjects was interviewed; the mean age was 70.6 years (60–104 years; SD: 8.0); 63.9% were female and 43.7% had up to 4 years of schooling. CFI was detected in 325 subjects, resulting in a raw prevalence of 19.2% (95% CI: 17.3–21.0). Older age, presence of diabetes, heart disease, stroke, urinary incontinence, arthritis, frequent pain and depression were significantly associated with CFI (p<0.05). ConclusionIn addition to the diversity of factors associated with CFI, the present study indicated the need to investigate the role of frequent pain in the development and progression of cognitive impairment and dementia.

Three screening methods for cognitive dysfunction using the Mini-Mental State Examination and Korean Dementia Screening Questionnaire.

To screen for and determine cognitive dysfunction, cognitive tests and/or informant reports are commonly used. However, these cognitive tests and informant reports are not always available. The present study investigated three screening methods using the Mini-Mental State Examination (MMSE) as the cognitive test, and the Korean dementia screening questionnaire (KDSQ) as the informant report. Participants were recruited from the Korea Clinical Research Center for Dementia of South Korea, and included 2861 patients with Alzheimer's disease (dementia), 3519 patients with mild cognitive impairment and 1375 controls with no cognitive dysfunction. Three screening methods were tested: (i) MMSE alone (MMSE(cut-off) ); (ii) a conventional combination of MMSE and KDSQ (MMSE+KDSQ(cut-off) ); and (iii) a decision tree with MMSE and KDSQ (MMSE+KDSQ(decision tree) ). For discriminating any cognitive dysfunction from controls, MMSE+KDSQ(cut-off) had the highest area under the receiver operating characteristic curve (0.784). For discriminating dementia from controls, MMSE+KDSQ(cut-off) had the highest area under the receiver operating characteristic curve (0.899). For discriminating mild cognitive impairment from controls, MMSE(cut-off) had the highest area under the receiver operating characteristic curve (0.683). MMSE+KDSQ(decision tree) showed the highest sensitivity for all discriminations. For overall classification accuracy, MMSE+KDSQ(decision tree) had the highest value (70.0%). These three methods had different advantageous properties for screening and staging cognitive dysfunction. As there might be different availability across clinical settings, these three methods can be selected and used according to situational needs.

Comparison of regional gray matter atrophy, white matter alteration, and glucose metabolism as a predictor of the conversion to Alzheimer's disease in mild cognitive impairment.

We compared the predictive ability of the various neuroimaging tools and determined the most cost-effective, non-invasive Alzheimer's disease (AD) prediction model in mild cognitive impairment (MCI) individuals. Thirty-two MCI subjects were evaluated at baseline with [(18)F]-fluorodeoxyglucose positron emission tomography (FDG-PET), MRI, diffusion tensor imaging (DTI), and neuropsychological tests, and then followed up for 2 yr. After a follow up period, 12 MCI subjects converted to AD (MCIc) and 20 did not (MCInc). Of the voxel-based statistical comparisons of baseline neuroimaging data, the MCIc showed reduced cerebral glucose metabolism (CMgl) in the temporo-parietal, posterior cingulate, precuneus, and frontal regions, and gray matter (GM) density in multiple cortical areas including the frontal, temporal and parietal regions compared to the MCInc, whereas regional fractional anisotropy derived from DTI were not significantly different between the two groups. The MCIc also had lower Mini-Mental State Examination (MMSE) score than the MCInc. Through a series of model selection steps, the MMSE combined with CMgl model was selected as a final model (classification accuracy 93.8%). In conclusion, the combination of MMSE with regional CMgl measurement based on FDG-PET is probably the most efficient, non-invasive method to predict AD in MCI individuals after a two-year follow-up period.

A Quick Test of Cognitive Speed (AQT): Usefulness in dementia evaluations in primary care

Objective. To validate A Quick Test of Cognitive Speed (AQT) as an instrument in diagnostic dementia evaluations against final clinical diagnosis and compare AQT with the Mini-Mental State Examination (MMSE) and Clock Drawing Test (CDT) in primary care. Design. Primary health care cohort survey. Setting. Four primary health care centres and a geriatric memory clinic in Sweden. Patients. 81 patients (age 65 and above) were included: 52 with cognitive symptoms and 29 presumed cognitively healthy. None of the patients had a previous documented dementia diagnosis. All patients performed MMSE, CDT, and AQT at the primary health care clinic and were referred for extensive neuropsychological testing at a memory clinic. AQT was validated against final clinical diagnosis determined by a geriatric specialist and a neuropsychologist. Main outcome measures. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), likelihood ratios, correlation data, and receiver operating characteristic (ROC). Results. For MMSE, sensitivity and specificity was 0.587 and 0.909; CDT 0.261 and 0.879; and AQT 0.783 and 0.667, respectively. For the combination of MMSE and CDT, sensitivity and specificity was 0.696 and 0.788, for MMSE and AQT 0.913 and 0.636. The ROC curve for AQT showed an area under curve (AUC) of 0.773. Conclusion. Our results suggest AQT is a usable test for dementia assessments in primary care. Sensitivity for AQT is superior to CDT, equivalent to MMSE, and comparable to the combination MMSE and CDT. MMSE in combination with AQT improves sensitivity. Because AQT is user-friendly and quickly administered, it could be applicable for primary care settings.

Diagnostic performance of a combination of Mini-Mental State Examination and Clock Drawing Test in detecting Alzheimer&amp;rsquo;s disease

ObjectiveBecause of the growing need for quick cognitive screening tests to distinguish Alzheimer’s disease (AD) from mild cognitive impairment (MCI), we compare the diagnostic performance of a combination of the Mini-Mental State Examination (MMSE) and a Clock Drawing Test (CDT) to the Japanese version of the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-J cog) in differentiating between patients with AD, patients with MCI, and healthy controls (HC).MethodsData from 146 subjects with AD and 60 subjects with MCI, as well as 49 HC, was retrospectively analyzed. We used logistic regression analysis with diagnosis as dependent variables and scores of the MMSE, the CDT-command, and the CDT-copy as independent variables, and receiver operating characteristic analysis to distinguish patients with AD from patients with MCI or HC.ResultsWhen patients with AD were compared to HC, the independent predictors of AD were scores on the MMSE and the CDT-command. This combination was more sensitive than the MMSE alone and has nearly the same sensitivity and specificity as the ADAS-J cog. When patients with AD were compared to patients with MCI, the independent predictors were the MMSE and the CDT-copy. This combination was more sensitive and specific than the MMSE alone and was almost as sensitive and specific as the ADAS-J cog.ConclusionThe combination of the MMSE and the CDT could be a powerful screening tool for differentiating between patients with AD, patients with MCI, and HC. Its sensitivity and specificity are comparable to ADAS-J cog, which takes more time.

Screening of Cognitive Impairment in Chronic Obstructive Pulmonary Disease

Cognitive dysfunction is common and clinically important in severe chronic obstructive pulmonary disease (COPD). We investigated the diagnostic accuracy of the Mini Mental State Examination (MMSE) and Instrumental Activities of Daily Living (IADL) scale in screening severe cognitive dysfunction in 149 patients with COPD, mean age 69.3 ± 8.5 years, forced expiratory volume in 1 s = 36.6 ± 17.8% of the predicted. Patients underwent the MMSE and an in-depth neuropsychological assessment based upon the Mental Deterioration Battery (MDB). The 5-item IADL scale was assessed. The sample was randomly divided into a training (n = 73) and a testing (n = 76) population. The diagnostic accuracy of MMSE, IADL scale or both versus cognitive dysfunction corresponding to abnormal performance in 3 or more MDB tests was assessed in the training population and the model obtained was tested in the testing population. The combination of MMSE <24 and dependence in at least 1 IADL had better diagnostic accuracy than either MMSE or IADL, with sensitivity = 52.4, specificity = 82.7, positive predictive value = 55.0% and negative predictive value = 81.1% in the testing population. MMSE and the 5-item IADL scale can be used to exclude, but not to detect cognitive dysfunction in COPD patients. A confirmatory cognitive test should be administered to patients with an MMSE score of <24 and who are dependent in at least 1 IADL.

The combination of cognitive testing and an informant questionnaire in screening for dementia.

A cognitive test and an informant report questionnaire were used together to investigate whether their combined use could improve the accuracy of detecting dementia in a memory clinic, compared with either test used alone. The subjects were 323 patients assessed at a memory clinic. The Mini-Mental State Examination and the short form of the Informant Questionnaire on Cognitive Decline in the Elderly were used. A method of combining the test scores developed by Mackinnon and Mulligan [Am J Psychiatry 1998; 155: 1529-35] was used. Dementia was diagnosed according to Diagnostic and Statistical Manual of Mental Disorders, Third Edition-Revised criteria. Logistic regression analysis showed that the combination of the Mini-Mental State Examination and the Informant Questionnaire on Cognitive Decline in the Elderly produced a slightly more accurate prediction of dementia caseness than either test used alone. Using receiver operating characteristic analysis the performance of the combination of the tests according to a weighted sum rule was compared with the performance of either test used alone. This way of combining the tests resulted in a more accurate screening for dementia than when the Informant Questionnaire on Cognitive Decline in the Elderly was used alone. The area under the receiver operating characteristic curve for the Mini-Mental State Examination combined with the Informant Questionnaire on Cognitive Decline in the Elderly was 0.89 compared with 0.82 for the Informant Questionnaire on Cognitive Decline in the Elderly alone (chi-square = 10.63; P = 0.0011). However, there was no improvement in screening performance when the combination of Mini-Mental State Examination and Informant Questionnaire on Cognitive Decline in the Elderly was compared with the Mini-Mental State Examination used alone (area under the receiver operating characteristic curve = 0.89 versus 0.86; chi-square = 3.54; P = 0.060). The combination of cognitive testing and an informant report according to a weighted sum rule in this population did not result in any advantage over the use of the Mini-Mental State Examination alone. The mixed results of this study contrast with those of Mackinnon and Mulligan.