Quick Mild Cognitive Impairment Screen Research Articles

Screening for Cognitive Impairment in Movement Disorders: Comparison of the Montreal Cognitive Assessment and Quick Mild Cognitive Impairment Screen in Parkinson’s Disease and Lewy Body Dementia

Screening for Cognitive Impairment in Movement Disorders: Comparison of the Montreal Cognitive Assessment and Quick Mild Cognitive Impairment Screen in Parkinson’s Disease and Lewy Body Dementia

Psychometric Evaluation of a Tablet-Based Tool to Detect Mild Cognitive Impairment in Older Adults: Mixed Methods Study.

With the rapid aging of the global population, the prevalence of mild cognitive impairment (MCI) and dementia is anticipated to surge worldwide. MCI serves as an intermediary stage between normal aging and dementia, necessitating more sensitive and effective screening tools for early identification and intervention. The BrainFx SCREEN is a novel digital tool designed to assess cognitive impairment. This study evaluated its efficacy as a screening tool for MCI in primary care settings, particularly in the context of an aging population and the growing integration of digital health solutions. The primary objective was to assess the validity, reliability, and applicability of the BrainFx SCREEN (hereafter, the SCREEN) for MCI screening in a primary care context. We conducted an exploratory study comparing the SCREEN with an established screening tool, the Quick Mild Cognitive Impairment (Qmci) screen. A concurrent mixed methods, prospective study using a quasi-experimental design was conducted with 147 participants from 5 primary care Family Health Teams (FHTs; characterized by multidisciplinary practice and capitated funding) across southwestern Ontario, Canada. Participants included health care practitioners, patients, and FHT administrative executives. Individuals aged ≥55 years with no history of MCI or diagnosis of dementia rostered in a participating FHT were eligible to participate. Participants were screened using both the SCREEN and Qmci. The study also incorporated the Geriatric Anxiety Scale-10 to assess general anxiety levels at each cognitive screening. The SCREEN's scoring was compared against that of the Qmci and the clinical judgment of health care professionals. Statistical analyses included sensitivity, specificity, internal consistency, and test-retest reliability assessments. The study found that the SCREEN's longer administration time and complex scoring algorithm, which is proprietary and unavailable for independent analysis, presented challenges. Its internal consistency, indicated by a Cronbach α of 0.63, was below the acceptable threshold. The test-retest reliability also showed limitations, with moderate intraclass correlation coefficient (0.54) and inadequate κ (0.15) values. Sensitivity and specificity were consistent (63.25% and 74.07%, respectively) between cross-tabulation and discrepant analysis. In addition, the study faced limitations due to its demographic skew (96/147, 65.3% female, well-educated participants), the absence of a comprehensive gold standard for MCI diagnosis, and financial constraints limiting the inclusion of confirmatory neuropsychological testing. The SCREEN, in its current form, does not meet the necessary criteria for an optimal MCI screening tool in primary care settings, primarily due to its longer administration time and lower reliability. As the number of digital health technologies increases and evolves, further testing and refinement of tools such as the SCREEN are essential to ensure their efficacy and reliability in real-world clinical settings. This study advocates for continued research in this rapidly advancing field to better serve the aging population. RR2-10.2196/25520.

Combining working memory and speech data in a digital app for early detection of cognitive impairment in primary care

AbstractBackgroundCognitive screening to detect mild cognitive impairment (MCI) and dementia in primary care settings has proven to be a challenging task. The ideal solution would be a brief, low‐burden assessment tool appropriate for use with individuals from diverse educational and cultural backgrounds that requires limited time and expertise from primary care providers. The purpose of this project was to develop a digital cognitive screening app derived from widely used cognitive and speech tasks using machine learning techniques.MethodParticipants were 104 old adults, 53 who were cognitively normal (CN) and 51 who were cognitively impaired (CI). All participants completed a working memory task (WM), followed by four speech‐language tasks, followed by a second administration of WM (WM2) to investigate the added utility of practice effects. Participants also completed the Quick Mild Cognitive Impairment (Qmci) screen. Bayesian adaptive regression trees were used to test 11 models. All models contained sex, age, education, and marital status. One model contained WM and the WM2‐WM difference. Four models contained 26 acoustic and 34 linguistic variables derived from each of the four speech tasks, and four more models were identical, except with the two WM variables added. For comparison, two models with Qmci were fitted: one with and one without the two WM variables.ResultThree models achieved cross‐validated classification accuracy of c≥0.90: WM by itself (estimated c = 0.91; Figure 1), WM and a personal narrative task (c = 0.94; Figure 2), and WM and a counting backwards task (c = 0.90). Models with picture description and procedural discourse tasks performed the worst. The QMCI‐only model yielded c = 0.91.ConclusionCombining WM, acoustic and linguistic variables involved in recounting personal memories, and the ability to benefit from prior exposure to a task discriminated CN from CI groups with a high degree of accuracy. This unique combination assesses key cognitive abilities known to be affected early in neurodegenerative diseases, executive functioning and memory, and includes both verbal and nonverbal tasks. Importantly, individuals with varying levels of cognitive functioning, including mild dementia, were able to use the app successfully, and the automated nature of the tool required minimal staff time or expertise.

Combining working memory and speech data in a digital app for early detection of cognitive impairment in primary care

AbstractBackgroundCognitive screening to detect mild cognitive impairment (MCI) and dementia in primary care settings has proven to be a challenging task. The ideal solution would be a brief, low‐burden assessment tool appropriate for use with individuals from diverse educational and cultural backgrounds that requires limited time and expertise from primary care providers. The purpose of this project was to develop a digital cognitive screening app derived from widely used cognitive and speech tasks using machine learning techniques.MethodParticipants were 104 old adults, 53 who were cognitively normal (CN) and 51 who were cognitively impaired (CI). All participants completed a working memory task (WM), followed by four speech‐language tasks, followed by a second administration of WM (WM2) to investigate the added utility of practice effects. Participants also completed the Quick Mild Cognitive Impairment (Qmci) screen. Bayesian adaptive regression trees were used to test 11 models. All models contained sex, age, education, and marital status. One model contained WM and the WM2‐WM difference. Four models contained 26 acoustic and 34 linguistic variables derived from each of the four speech tasks, and four more models were identical, except with the two WM variables added. For comparison, two models with Qmci were fitted: one with and one without the two WM variables.ResultThree models achieved cross‐validated classification accuracy of c = 0.90: WM by itself (estimated c = 0.91; Figure 1), WM and a personal narrative task (c = 0.94; Figure 2), and WM and a counting backwards task (c = 0.90). Models with picture description and procedural discourse tasks performed the worst. The QMCI‐only model yielded c = 0.91.ConclusionCombining WM, acoustic and linguistic variables involved in recounting personal memories, and the ability to benefit from prior exposure to a task discriminated CN from CI groups with a high degree of accuracy. This unique combination assesses key cognitive abilities known to be affected early in neurodegenerative diseases, executive functioning and memory, and includes both verbal and nonverbal tasks. Importantly, individuals with varying levels of cognitive functioning, including mild dementia, were able to use the app successfully, and the automated nature of the tool required minimal staff time or expertise.

A - 53 A Digital Health Solution for Early Detection of Cognitive Impairment in Primary Care.

To determine which task or combination of tasks provided the most effective way to differentiate cognitively impaired (CI) from cognitively normal (CN) participants in under 5minutes and to ensure that classification accuracy was equal to or better than a traditional brief cognitive screening task, the Quick Mild Cognitive Impairment (Qmci) screen. CN (n = 53) and CI (n = 51) participants completed a risk assessment task, a symbol matching (SM) task, and four speech-language tasks, followed by a second administration of SM to examine utility of practice effects administered on an iPad. Participants also completed the Qmci. Eleven models were tested using Bayesian adaptive regression trees. The top three models all included the two SM variables: the one with SM by itself (estimated c = 0.91), one with SM and features from a personal narrative task (c = 0.94), and one with SM and a counting backwards task (c = 0.90). Models with picture description and procedural discourse tasks performed the worst. For comparison, the QMCI-only model yielded c = 0.91. A combination of working memory/processing speed and acoustic and linguistic variables from recalling a personal story achieved a high level of classification accuracy, slightly exceeding that of a traditional cognitive screening task. The inclusion of both verbal and nonverbal tasks may be an important feature, allowing for cognitive screening of individuals who are not able to do one type of task or the other. Future work is planned to examine this shortened tool in a pragmatic clinical trial in two primary care clinics.

Comparison of the Six Item Cognitive Impairment Test (6CIT) to Commonly-Used Short Cognitive Screening Instruments in a Memory Clinic Population.

Short cognitive screening instruments (CSI) are required to identify cognitive impairment in busy outpatient clinics. While the Six Item Cognitive Impairment Test (6CIT) is commonly used, its accuracy in those with mild cognitive impairment (MCI) and subjective cognitive decline (SCD) and against more widely-used CSIs is less well established. To examine the diagnostic accuracy of the 6CIT against the Montreal Cognitive Assessment (MoCA) and Quick Mild Cognitive Impairment (Qmci) screen across the cognitive spectrum in a memory clinic population. In total, 142 paired assessments were available (21 with SCD, 32 MCI, and 89 with dementia). Consecutive patients underwent a comprehensive assessment and were screened using the 6CIT, Qmci, and MoCA. Accuracy was determined from the area under receiver operating characteristic curves (AUC). The median age of patients was 76 (±11) years; 68% were female. The median 6CIT score was 10/28 (±14). The 6CIT was strongly, negatively, and statistically significantly correlated with the Qmci (r = -0.84) and MoCA (r = -0.86). The 6CIT had good accuracy for separating cognitive impairment (MCI or dementia) from SCD, (AUC:0.88; 0.82-0.94), similar to the MoCA (AUC:0.92; 0.87-0.97, p = 0.308), but statistically lower than the Qmci (AUC:0.96; 0.94-0.99, p = 0.01). The 6CIT was faster to administer, median time 2.05 minutes versus 4.38 and 9.5 for the Qmci and MoCA, respectively. While the Qmci was more accurate than the 6CIT, the shorter administration time of the 6CIT, suggests it may be useful when assessing or monitoring cognitive impairment in busy memory clinics, though larger samples are required to evaluate.

Screening for Cognitive Impairment with the Quick Memory Check: Validation of a Caregiver Administered Cognitive Screen.

Self or home-administered cognitive screening instruments (CSIs) can reduce barriers to the early detection of mild cognitive impairment (MCI) and dementia. To examine the acceptability and diagnostic accuracy of a caregiver-administered CSI, the Quick Memory Check (QMC). Components of the Quick Mild Cognitive impairment (Qmci) screen (orientation, verbal fluency, and logical memory) were re-weighted to create the QMC, scored out of 100 points. Participants, attending a university hospital memory clinic, were provided administration instructions beforehand. Area under the curve (AUC) scores, adjusted for age and education, were compared with the Qmci screen and Montreal Cognitive Assessment (MoCA). Caregivers or family scored the QMC. In all, 366 participants were recruited; 53 with subjective memory complaints (SMC), 74 with MCI, 193 with dementia, and 46 normal controls. Median QMC scores for controls were 70±13 versus 60±20 for SMC, 52±18 for MCI, and 31±21 for dementia. The QMC had excellent accuracy (AUC 0.97) for cognitive impairment (MCI/dementia from controls), similar to the Qmci screen (AUC 0.98, p = 0.17) and MoCA (AUC 0.95, p = 0.13). At a cut-off of <52/100, the QMC had 83% sensitivity and 100% specificity for cognitive impairment. The QMC had lower accuracy differentiating MCI from SMC (AUC 0.73), albeit similar to the MoCA (AUC 0.70). The QMC, administered by caregivers in advance of clinic, compared favorably to established CSIs scored by trained raters. This caregiver, home-administered CSI is acceptable and can identify cognitive impairment, potentially improving efficiency by reducing testing time and patient stress in busy clinical settings.

Cognitive impairment in epilepsy patients and its correlations

Objective Epilepsy is a severe disease in which seizures play the leading role. Striking clinical manifestations of the attacks take most of the attention of healthcare professionals. Apart from epilepsy itself, it is well known that epilepsy patients may also have psychiatric comorbidities. These disorders, such as anxiety and depression, are mostly thought to be related to epileptic seizures or antiepileptic medications. In clinical practice, cognitive impairment is another disrupted area of interest in epileptic patients. Our study aimed to detect this deterioration and its correlations with mood disorders and epileptic disease features such as seizure frequency and illness duration. Materials and methods After obtaining verbal and written consent, we enrolled 52 epilepsy patients in our study. A short demographic form indicating their gender, epileptic disease features, and medication usage information was completed for each patient. The Quick Mild Cognitive Impairment Screen (QMCI) test, the Hamilton Anxiety Rating Scale (Ham-A), and the Hospital Anxiety and Depression Scale (HADS) were applied by an experienced psychologist. Abnormal brain magnetic resonance imaging findings (e.g., encephalomalacia, large arachnoid cysts, a considerable amount of white matter gliotic lesions, neoplastic or vascular space-occupying lesions, hippocampal malformations), vitamin and electrolyte imbalances, other chronic diseases as well as thyroid dysfunction were considered as exclusion criteria since they might interfere with cognition. We excluded abnormalities to this extent because we wanted to acquire a homogenous sampling population without structural disadvantages. Thus, we could be able to determine slight changes in cognition properly. Results We found decreased cognitive scores directly proportional to lower education level, higher seizure frequency, longer disease duration, generalized tonic-clonic (GTC) type of seizure, and antiepileptic polytherapy. Also, complying with the literature, a high frequency of depression was found in our study group. Interestingly, decreased anxiety levels of the patients were statistically related to higher seizure frequency, which may indicate adaptive mechanisms to frequent seizures. Finally, a multivariate regression analysis revealed a significant negative impact of GTC type of seizure on cognition. Conclusion Epilepsy and epileptic seizures affect cognition negatively. Thus, newly diagnosed epilepsy patients should be assessed for cognitive status as soon as possible. This assessment will allow epileptologists to understand future deteriorations in their patients’ cognition. In our study, it is shown that QMCI is an effective and practical way to assess the cognitive statuses of epilepsy patients.

Differences in Brain Volume by Tooth Loss and Cognitive Function in Older Japanese Adults

BackgroundWe investigated the association between tooth loss and structural brain volume and its mediating effect on the association between tooth loss and cognitive function in older Japanese. MethodsA cross-sectional study was conducted by using the data of 494 randomly sampled community-dwelling individuals aged 65–84 years living in Tokamachi City, Japan. Total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), and hippocampal volume (HV) were measured with magnetic resonance imaging. The association of self-reported number of teeth (≥20, 1–19, and 0) with cognitive function assessed with the Japanese version of the Quick Mild Cognitive Impairment screen and structural brain volume was examined. Causal mediation analysis was performed to evaluate the mediating effect of structural brain volume. Age, sex, socioeconomic status, health behavior, comorbid conditions, and total intracranial volume were adjusted. ResultsRespondents with no teeth showed lower cognitive function (coefficient = −4.01; 95% confidence interval [CI]: −7.19, −0.82), lower TBV (coefficient = −10.34; 95% CI: −22.84, 2.17), and lower GMV (coefficient = −6.92; 95% CI: −14.84, 0.99) than those with ≥20 teeth (P for trends were 0.003, 0.035, and 0.047, respectively). The number of teeth was not significantly associated with WMV or HV. GMV showed a significant mediating effect on the association between the number of teeth and cognitive function (coefficient = −0.38; 95% CI: −1.14, −0.002, corresponding to 9.0% of the total effect), whereas TBV did not. ConclusionsGMV was suggested to mediate the relationship between tooth loss and lower cognitive function.

Comparison of the Greek Version of the Quick Mild Cognitive Impairment Screen and Montreal Cognitive Assessment in Older Adults.

Objective: Cognitive screening instruments (CSIs) are essential for everyday practice. The Quick Mild Cognitive Impairment (Qmci) screen, a short instrument designed to identify mild cognitive impairment, was recently translated into Greek (Qmci-Gr). The present study compared its diagnostic value against the Montreal Cognitive Assessment (MoCA) screen and examined its optimal cutoffs. Method: We recruited consecutive patients aged ≥55 years that presented with cognitive complaints from two outpatient clinics in Greece. The Qmci-Gr and MoCA were completed by all patients. Furthermore, they were assessed independently with a comprehensive flexible neuropsychological battery to establish a diagnostic classification. Results: In the current study, we assessed a total of 145 patients, with a median age of 70 years; 44 were classified as having Subjective Memory Complaints (SMC) but normal cognition, 32 with MCI and 69 with dementia. The Qmci-Gr had a higher accuracy compared to the MoCA in discriminating MCI from dementia, area under the curve (AUC) of 0.81 versus 0.75, respectively; however, this finding was marginally significant (p = 0.08). Its accuracy was marginally higher for distinguishing SMC from dementia, AUC of 0.94 versus 0.89 (p = 0.03). However, Qmci-Gr presented a lower accuracy than MoCa in differentiating SMC from MCI, AUC of 0.76 versus 0.94 (p = 0.006). Conclusions: The Qmci-Gr has comparable diagnostic accuracy to the MoCA regarding MCI and dementia groups. Further research, with larger and more diverse samples, may be necessary to ensure generalizability.

611 Mild cognitive impairment is associated with subclinical left ventricular dysfunction as assessed by global longitudinal strain in hypertensive patients

Abstract Aims Left ventricular global longitudinal strain (GLS) detects subtle systolic abnormalities in various cardiovascular conditions, which represent significant risk factors for cognitive impairment and stroke. Specifically, GLS has emerged as a more precise myocardial function measure than left ventricular ejection fraction (LVEF). This study investigated the relationship of GLS with mild cognitive impairment (MCI) in hypertensive patients. Methods and results From February 2020 to October 2021 were enrolled hypertensive patients without atrial fibrillation and/or cerebrovascular and/or neurodegenerative diseases. Complete demographic, clinical characteristics, laboratory analyses, conventional echocardiographic parameters were collected. Finally, MCI was defined by accurate the Quick Mild Cognitive Impairment (QMCI) Screen corrected for age and education. This score explores spatial and temporal orientation, registration, delayed recall, clock design, logical memory, and verbal fluency in a brief time (5 min—score 0–100); a compliance questionnaire (Morisky medication adherence scale); a questionnaire on nutritional status (MNA). 81 hypertensive patients [66 ± 7.27 years; 9 (11%) female] were included in the study. Concerning echocardiographic evaluation, LVEF was 50.47 ± 9.95% and mean GLS was −16.00 ± 3.66. Mean QMCI corrected for age and education was 56.45 ± 9.37, and MCI was detected in 21 patients (26%). When comparing the patients with MCI (QMCItot &amp;lt;49.4) and without MCI (QMCItot &amp;gt;49.4), a statistically significant difference of GLS values was detected (no MCI: −16.52 ± 3.66 vs. MCI: −14.18 ± 3.23; P = 0.032); on the other hand, the two groups did not differ in LVEF (no MCI: 50.58 ± 9.70 vs. MCI: 48.86 ± 11.93; P = 0.864). Furthermore, excluding patients with FE ≥ 45% from the analysis, a statistically significant linear regression was observed between QMCI (corrected for age and education) and the GLS (P = 0.014) (Figure 1). Conclusions Compromised GLS, but not LV EF, is related to MCI in hypertensive patients who are free of clinical dementia, stroke, and neurodegenerative disease. Moreover, our study demonstrates for the first time the existence of a significant association between the QMCI and GLS; consequently, GLS could be an additional parameter in clinical practice for early recognition of MCI. However, studies on a larger population will be needed to confirm this association.

The Persian Version of the Quick Mild Cognitive Impairment Screen (Qmci-Pr): Psychometric Properties among Middle-Aged and Older Iranian Adults.

Brief cognitive screening instruments are used to identify patients presenting with cognitive symptoms that warrant further assessment. This study aimed to evaluate the reliability and validity of the Persian version of the Quick Mild Cognitive Impairment (Qmci-Pr) among middle-aged and older Iranian adults. Consecutive patients aged ≥55 years and caregivers attending with them as normal controls (NCs) were recruited from geriatric outpatient clinics and a hospital in Tehran, Iran. All patients completed the Qmci-Pr before completing an independent detailed neuropsychological assessment and staging using the Clinical Dementia Rating (CDR) Scale. NCs underwent the same assessment. In all, 92 participants with a median age of 70 years (±13) were available. Of these, 20 participants were NCs, 24 had subjective memory complaints (SMC), 24 had mild cognitive impairment (MCI), and 24 had Alzheimer’s disease (AD). The Qmci-Pr had good accuracy in differentiating SMC and NC from MCI (area under the curve (AUC): 0.80 (0.69–0.91)) and in identifying cognitive impairment (MCI and mild AD) (AUC: 0.87 (0.80–0.95)) with a sensitivity of 88% and specificity of 80%, at an optimal cut-off of <53/100. The Qmci-Pr is an accurate short cognitive screening impairment for separating NC and patients with SMC from MCI and identifying cognitive impairment. Further research with larger samples and comparison with other widely used instruments such as the Montreal Cognitive Assessment is needed. Given its established brevity, the Qmci-Pr is a useful screen for Iranian adults across the spectrum of cognitive decline.

Corrigendum to: Comparison of the Greek Version of the Quick Mild Cognitive Impairment Screen and Standardised Mini-Mental State Examination

Corrigendum to: Comparison of the Greek Version of the Quick Mild Cognitive Impairment Screen and Standardised Mini-Mental State Examination

Insomnia and falls in older adults: are they linked to executive dysfunction?

Insomnia increases the incidence of falls and impairs executive function. Moreover, falls are associated with executive function impairment. The relationship between falls and executive function in patients with insomnia is not clear. The aim of this study was to evaluate relationship between falls and executive function in individuals with insomnia and a control group. This study involved 122 patients (47 insomnia, 75 controls). The Mini-Mental State Examination, Quick Mild Cognitive Impairment Screen, Trail Making Test A, clock-drawing test, and digit span test were used to measure executive function. Semantic and working memory dual task was also performed. Fall history was recorded and the Falls Efficacy Scale - International administered. The median age of the patients was 71 years (range: 65-89 years), and 60.7% were women. The insomnia group scored lower on the three-word recall than the control group (P = 0.005), but there was no difference between the groups on cognitive tests. Fall history and fear of falling were more frequent in the insomnia group (P = 0.003, P < 0.001). Semantic and working memory dual tasks were correlated with clock-drawing test only in the insomnia group (r = -0.316, P = 0.031; r = -0.319, P = 0.029). Depression (odds ratio (OR) = 9.65, P = 0.001) and Trail Making Test A (OR = 1.025, P = 0.07) were independently associated with insomnia. Four-metre walking speed (OR = 2.342, P = 0.025), insomnia (OR = 3.453; P = 0.028), and the semantic memory dual task (OR = 1.589; P = 0.025) were also independently associated with falls. Our study showed that dual tasking and executive function are related to falls in patients with insomnia. Managing insomnia and assessment of executive dysfunction may have beneficial effects on preventing falls.

Screening for Cognitive Impairment After Stroke: Validation of the Chinese Version of the Quick Mild Cognitive Impairment Screen.

Background: Screening for post-stroke cognitive impairment (PSCI) is necessary because stroke increases the incidence of and accelerates premorbid cognitive decline. The Quick Mild Cognitive Impairment (Qmci) screen is a short, reliable and accurate cognitive screening instrument but is not yet validated in PSCI. We compared the diagnostic accuracy of a Chinese version of the Qmci screen (Qmci-CN) compared with the widely-used Chinese versions of the Montreal Cognitive Assessment (MoCA-CN) and Mini-Mental State Examination (MMSE-CN).Methods: We recruited 34 patients who had recovered from a stroke in rehabilitation unit clinics in 2 university hospitals in China: 11 with post-stroke dementia (PSD), 15 with post-stroke cognitive impairment no dementia (PSCIND), and 8 with normal cognition (NC). Classification was made based on clinician assessment supported by a neuropsychological battery, independent of the screening test scores. The Qmci-CN, MoCA-CN, and MMSE-CN screens were administered randomly by a trained rater, blind to the diagnosis.Results: The mean age of the sample was 63 ± 13 years and 61.8% were male. The Qmci-CN had statistically similar diagnostic accuracy in differentiating PSD from NC, an area under the curve (AUC) of 0.94 compared to 0.99 for the MoCA-CN (p = 0.237) and 0.99 for the MMSE-CN (p = 0.293). The Qmci-CN (AUC 0.91), MoCA-CN (AUC 0.94), and MMSE-CN (AUC 0.79) also had statistically similar accuracy in separating PSD from PSCIND. The MoCA-CN more accurately distinguished between PSCIND and normal cognition than the Qmci-CN (p = 0.015). Compared to the MoCA-CN, the administration times of the Qmci-CN (329s vs. 611s, respectively, p < 0.0001) and MMSE-CN (280 vs. 611s, respectively, p < 0.0001) were significantly shorter.Conclusion: The Qmci-CN is accurate in identifying PSD and separating PSD from PSCIND in patients post-stroke following rehabilitation and is comparable to the widely-used MoCA-CN, albeit with a significantly shorter administration time. The Qmci-CN had relatively poor accuracy in identifying PSCIND from NC and hence may lack accuracy for certain subgroups. However, given the small sample size, the study is under-powered to show superiority of one instrument over another. Further study is needed to confirm these findings in a larger sample size and in other settings (countries and languages).

Association between positive grandparental involvement during childhood and generativity in late life among community-dwelling, cognitively intact, older adults in Japan.

Generativity is increasingly being recognized as a key element of healthy aging. The present study investigated whether children who received more positive grandparental involvement would show higher generativity in late life. In 2017, 173 older adults living in Wakuya City (Miyagi Prefecture, Japan), and who showed normal cognition based on the Quick Mild Cognitive Impairment Screen, participated in a self-report life course survey (age range: 65-88 years). The association between positive grandparental involvement in childhood and generativity (measured by the Loyola Generativity Scale) was investigated using multiple linear regression adjusted for potential confounders. Compared with older adults without or had low positive grandparental involvement in childhood, a higher level of generativity was observed among those with medium (β = 1.93, 95% confidence interval [CI]: 0.24-3.62) and high positive grandparental involvement (β = 2.09, 95% CI: 0.32-3.87), adjusting for age, gender, memory performance, depressive symptoms, childhood socio-economic status and parental involvement. The significant dose-response association remained even after further adjusting for education and current grandparental experiences. Greater positive grandparental involvement in childhood was associated with a higher level of generativity among community-dwelling, cognitively intact, Japanese older adults. Geriatr Gerontol Int ••; ••: ••-•• Geriatr Gerontol Int 2021; ••: ••-••.

Comparison of the Greek Version of the Quick Mild Cognitive Impairment Screen and Standardised Mini-Mental State Examination.

Short cognitive screening instruments (CSIs) are widely used to stratify patients presenting with cognitive symptoms. The Quick Mild Cognitive Impairment (Qmci) screen is a new, brief (<5mins) CSI designed to identify mild cognitive impairment (MCI), which can be used across the spectrum of cognitive decline. Here we present the translation of the Qmci into Greek (Qmci-Gr) and its validation against the widely-used Standardised Mini-Mental State Examination (SMMSE). Consecutive patients aged ≥55years presenting with cognitive complaints were recruited from two outpatient clinics in Greece. All patients completed the Qmci-Gr and SMMSE and underwent an independent detailed neuropsychological assessment to determine a diagnostic classification. In total, 140 patients, median age 75years, were included; 30 with mild dementia (median SMMSE 23/30), 76 with MCI and 34 with subjective memory complaints (SMC) but normal cognition. The Qmci-Gr had similar accuracy in differentiating SMC from cognitive impairment (MCI & mild dementia) compared with SMMSE, area under the curve (AUC) of 0.84 versus 0.79, respectively; while accuracy was higher for the Qmci-Gr, this finding was not significantly different, (p=.19). Similarly, the Qmci-Gr had similar accuracy in separating SMC from MCI, AUC of 0.79 versus 0.73 (p=.23). The Qmci-Gr compared favorably with the SMMSE. Further research with larger samples and comparison with other instruments such as the Montreal Cognitive Assessment is needed to confirm these findings but given its established brevity, it may be a better choice in busy clinical practice in Greece.

Screening for Cognitive Frailty Using Short Cognitive Screening Instruments: Comparison of the Chinese Versions of the MoCA and Qmci Screen.

BackgroundCognitive frailty describes cognitive impairment associated with physical decline. Few studies have explored whether short cognitive screens identify frailty. We examined the diagnostic accuracy of the Chinese versions of the Quick Mild Cognitive Impairment (Qmci-CN) screen and Montreal Cognitive Assessment (MoCA-CN) in identifying cognitive frailty.MethodsNinety-five participants with cognitive symptoms [47 with mild cognitive impairment (MCI), 34 with subjective cognitive disorder, and 14 with dementia] were included from two outpatient rehabilitation clinics. Energy (work intensity) and physical activity levels were recorded. Cognitive frailty was diagnosed by an interdisciplinary team using the IANA/IAGG consensus criteria, stratified on the Clinical Frailty Scale (CFS). Instruments were administered sequentially and randomly by trained assessors, blind to the diagnosis.ResultsThe mean age of the sample was 62.6 ± 10.2 years; median CFS score was 4 ± 1 and 36 (38%) were cognitively frail. The Qmci-CN had similar accuracy in differentiating the non-frail from cognitively frail compared to the MoCA-CN, AUC 0.82 versus 0.74, respectively (p = 0.19). At its optimal cut-off (≤55/100), the Qmci-CN provided a sensitivity of 83% and specificity of 67% versus 91% and 51%, respectively, for the MoCA-CN (≤23/30). Neither was accurate in separating MCI from cognitive frailty but both accurately separated cognitive frailty from dementia.ConclusionEstablished short cognitive screens may be useful in identifying cognitive frailty in Chinese adults with cognitive complaints but not in separating MCI from cognitive frailty. The Qmci-CN had similar accuracy to the MoCA-CN and a shorter administration time in this small and under-powered study, necessitating the need for adequately powered studies in different healthcare settings.

Is the Quick Mild Cognitive Impairment Screen (QMCI) more accurate at detecting mild cognitive impairment than existing short cognitive screening tests? A systematic review of the current literature.

Differentiating normal cognition, mild cognitive impairment (MCI), and dementia is important, as these conditions differ in terms of their prognosis and treatment. Existing short cognitive screening tests vary widely in their accuracy, sensitivity, and specificity at detecting MCI and dementia. The Quick Mild Cognitive Impairment Screen (QMCI) was developed in 2012 as a fast and accurate "MCI specific" screening test. The aim of the current study was to conduct a literature review to compare the accuracy, sensitivity, and specificity of the QMCI at differentiating normal cognition, MCI, and dementia to existing short cognitive screening tests at their optimal cut-off scores. A search of the electronic journal databases EBSCO, Psych info, and Science Direct was undertaken using the keywords "Quick Mild Cognitive Impairment Screen," "QMCI," "accuracy," "sensitivity," and "specificity." Results of individual studies were examined, and 2 × 2 tables were drawn up to obtain the overall accuracy, sensitivity, and specificity of each test across the studies included. Results from individual studies show that the QMCI has higher accuracy at detecting MCI and dementia than these cognitive screens. Pooled analysis shows that it also has greater sensitivity and specificity at optimal cut-off points for each test. Based in the current review, the QMCI represents a more accurate, sensitive, and specific screening test for MCI and dementia than the SMMSE or the MoCA. This has important implications in screening for cognitive impairment.

Comparing the Diagnostic Accuracy of Two Cognitive Screening Instruments in Different Dementia Subtypes and Clinical Depression.

Short but accurate cognitive screening instruments are required in busy clinical practice. Although widely-used, the diagnostic accuracy of the standardised Mini-Mental State Examination (SMMSE) in different dementia subtypes remains poorly characterised. We compared the SMMSE to the Quick Mild Cognitive Impairment (Qmci) screen in patients (n = 3020) pooled from three memory clinic databases in Canada including those with mild cognitive impairment (MCI) and Alzheimer’s, vascular, mixed, frontotemporal, Lewy Body and Parkinson’s dementia, with and without co-morbid depression. Caregivers (n = 875) without cognitive symptoms were included as normal controls. The median age of patients was 77 (Interquartile = ±9) years. Both instruments accurately differentiated cognitive impairment (MCI or dementia) from controls. The SMMSE most accurately differentiated Alzheimer’s (AUC 0.94) and Lewy Body dementia (AUC 0.94) and least accurately identified MCI (AUC 0.73), vascular (AUC 0.74), and Parkinson’s dementia (AUC 0.81). The Qmci had statistically similar or greater accuracy in distinguishing all dementia subtypes but particularly MCI (AUC 0.85). Co-morbid depression affected accuracy in those with MCI. The SMMSE and Qmci have good-excellent accuracy in established dementia. The SMMSE is less suitable in MCI, vascular and Parkinson’s dementia, where alternatives including the Qmci screen may be used. The influence of co-morbid depression on scores merits further investigation.