Significant Predictor Of Cognitive Impairment Research Articles

Association between Trace elements and cognitive function among Elderly Subjects with Osteoporosis: A retrospective study

Background: Cognitive dysfunction and osteoporosis (OP) are common among elderly subjects. Different mechanisms are reported. However the potential role of trace elements is not well studied. The current work aimed to estimate the toenail levels of trace elements in older patients with cognitive function with or without osteoporosis. Methods: In a retrospective manner, we collected data of people older than 60 years of age. We collected data of 165 subjects, with 1:1:1 distribution for studied groups (i.e., 55 subjects in each group). The first group for normal cognition with no OP; the second for cognitive dysfunction with no OP and the third for cognitive dysfunction with OP. The cognitive function was determined by the mini-mental state examination (MMSE), while osteoporosis was diagnosed by the measurement of bone mineral density (BMD) with calculation of T-scores. Toenail samples were collected and prepared to estimate the levels of trace elements. Results: Calcium and zinc were significantly reduced in groups (2 and 3) than the normal group (15.44±1.17 and 13.47±1.81 versus 18.93±1.90 µg/g, respectively; and 88.16±6.10 and 84.07±6.56 versus 104.27±4.79 µg/g, respectively). However, there were significant increase of toenail lead, aluminum and copper in the second and third groups than the first group. But, chromium and selenium were reduced in the second and third groups than the first group. The MMSE and T-scores were proportionately correlated with T-score, body mass index, calcium, zinc, chromium and selenium. But, inversely correlated with lead, aluminum and copper. Finally, calcium, zinc lead, age and BMI were the significant predictors of cognitive impairment and OP. Conclusion: Trace elements are associated with cognitive impairment with or without osteoporosis. Some are protective and others had harmful effects with different mechanism. Thus, monitoring of these trace elements should be considered to avoid further cognitive decline with or without osteoporosis in future.

Predictors of cognitive impairment and its association with mortality in maintenance hemodialysis patients: A prospective follow-up study.

To determine predictors of cognitive impairment (CI) and its association with mortality in maintenance haemodialysis (MHD) patients. This prospective follow up study was conducted at HD Department, Mayo Hospital, Lahore from September, 2021 to November, 2022. All patients undergoing MHD for more than three months and having age between 18-65 years were included while those with dialysis duration less than three months, history of neuropsychiatric illness was excluded. Cognitive function was assessed using British Columbia Cognitive Complaints Inventory (BC-CCI) questionnaire. CI was defined on Likert scale as mild, moderate, and severe. Patients were followed up to one year regarding outcome measures. One hundred and four patients were included in the study. Mean age was 45.86±11.11 years and Diabetes Mellitus (DM) was the most common cause of End Stage Renal Disease (ESRD) in 39(37.5%) patients. CI was found in 86(82.7%) patients in following order of severity: mild 61(58.7%), moderate 19(18.3%) and severe 6(5.9%). Increasing age (≥50 years), gender (female), Diabetes Mellitus (DM), unemployment and education <10th grade were found as significant predictors of CI (p<0.05). Significant positive correlations of CI score with age (r=0.338, p<0.001) and MHD duration (r=0.211, p=0.032) were found. However, the CI was not significantly associated with mortality (p=0.302). CI was common in MHD patients. Factors affecting CI were increasing age, female gender, DM, unemployment and low education level. CI was not associated with mortality in MHD patients.

The impact of education and occupation on cognitive impairment: a cross-sectional study in China.

Education, occupation, and cognitive activity are key indicators of cognitive reserve and are thought to influence cognitive impairment. However, the individual and combined impacts of these factors are not fully understood. This study aims to investigate the roles of education and occupation in cognitive impairment while controlling for brain reserve and cognitive activity. This cross-sectional study involved 369 participants aged 50 years or older from urban outpatient clinics in Jilin Province, China. Cognitive impairment was assessed using neuropsychological scales and brain imaging. Cognitive activity was evaluated with the Cognitive Reserve Scale (CRS). Covariance analysis and logistic regression models were used to analyze the associations, adjusting for age, sex, education, and occupation. Higher education was significantly associated with a lower risk of cognitive impairment (p < 0.001), regardless of occupation. In contrast, occupational complexity and cognitive activity did not show a significant relationship with cognitive impairment (p > 0.05). Education, rather than occupation or cognitive activities, is a significant predictor of cognitive impairment, highlighting the importance of educational attainment in cognitive health.

Longitudinal sleep instability predicts cognitive decline and is associated with increased MRI‐visible perivascular space burden

AbstractBackgroundAlthough emerging data suggest a direct link between sleep duration, aging, and cognitive performance, the impact of longitudinal sleep patterns have on Alzheimer’s disease‐associated pathology and cognitive decline remains unclear.MethodUtilizing longitudinal data on self‐reported sleep duration collected within the Seattle Longitudinal Study, we used a Cox proportional hazard (CPH) regression to evaluate the relationship between longitudinal sleep factors on the development of cognitive decline. Additional analysis in a sub‐cohort utilized multivariate linear regression prediction analyses to evaluate the predictive value of these longitudinal sleep factors on the incidence of developing cognitive impairment over an interval of 10 years.A cohort within the study received MRI and FLAIR neuroimaging, enabling the assessment of the impact these longitudinal sleep factors have on subcortical white matter MRI‐visible perivascular space burden (PVS). A semi‐automated segmentation algorithm accounted for PVS total burden and volume, as well as average PVS width, length, and median volume across participants, blinded by group.ResultCPH analysis found years of education (HR 1.12, 95% CI 1.02, 1.22), APOE4 status (HR 2.18, 95% CI 1.37, 3.49), higher depression scores (HR 1.08, 95% CI 1.04, 1.13), short sleep phenotype (HR 1.78, 95% CI 1.03, 3.08) and increased sleep variability (HR 3.10, 95% CI 1.66, 5.80) were significantly associated with cognitive impairment. Further, when including these factors into our linear regression prediction analyses, age (p&lt;0.0001), depression (p = 0.01) and sleep variability (p = 0.042) were significant predictors of cognitive impairment over a 10‐year period.Preliminary analysis showed significant association between high sleep variability and increased whole‐brain PVS volume (p = 0.04) and length (p = 0.03), with a significant correlation between sleep variability and median PVS volume (p = 0.04). Follow‐up analysis evaluated PVS features within the wider cohort.ConclusionThese findings suggest that variability in longitudinal self‐reported sleep duration exerts a previously unappreciated influence on downstream cognitive performance and pathological processes, potentially including glymphatic dysfunction. These findings elaborate the link between sleep instability, aging, cognitive decline and neuropathologic disease state. Future studies should evaluate these findings on an independent cohort to assess whether sleep variability of different time scales (weeks, years, decades) exerts similar effects on these outcomes.

Longitudinal sleep instability predicts cognitive decline and is associated with increased MRI‐visible perivascular space burden

AbstractBackgroundAlthough emerging data suggest a direct link between sleep duration, aging, and cognitive performance, the impact of longitudinal sleep patterns have on Alzheimer’s disease‐associated pathology and cognitive decline remains unclear.MethodUtilizing longitudinal data on self‐reported sleep duration collected within the Seattle Longitudinal Study, we used a Cox proportional hazard (CPH) regression to evaluate the relationship between longitudinal sleep factors on the development of cognitive decline. Additional analysis in a sub‐cohort utilized multivariate linear regression prediction analyses to evaluate the predictive value of these longitudinal sleep factors on the incidence of developing cognitive impairment over an interval of 10 years. A cohort within the study received MRI and FLAIR neuroimaging, enabling the assessment of the impact these longitudinal sleep factors have on subcortical white matter MRI‐visible perivascular space burden (PVS). A semi‐automated segmentation algorithm accounted for PVS total burden and volume, as well as average PVS width, length, and median volume across participants, blinded by group.ResultCPH analysis found years of education (HR 1.12, 95% CI 1.02, 1.22), APOE4 status (HR 2.18, 95% CI 1.37, 3.49), higher depression scores (HR 1.08, 95% CI 1.04, 1.13), short sleep phenotype (HR 1.78, 95% CI 1.03, 3.08) and increased sleep variability (HR 3.10, 95% CI 1.66, 5.80) were significantly associated with cognitive impairment. Further, when including these factors into our linear regression prediction analyses, age (p&lt;0.0001), depression (p = 0.01) and sleep variability (p = 0.042) were significant predictors of cognitive impairment over a 10‐year period. Preliminary analysis showed significant association between high sleep variability and increased whole‐brain PVS volume (p = 0.04) and length (p = 0.03), with a significant correlation between sleep variability and median PVS volume (p = 0.04). Follow‐up analysis evaluated PVS features within the wider cohort.ConclusionThese findings suggest that variability in longitudinal self‐reported sleep duration exerts a previously unappreciated influence on downstream cognitive performance and pathological processes, potentially including glymphatic dysfunction. These findings elaborate the link between sleep instability, aging, cognitive decline and neuropathologic disease state. Future studies should evaluate these findings on an independent cohort to assess whether sleep variability of different time scales (weeks, years, decades) exerts similar effects on these outcomes.

Predictors of Successful Brain Aging: An Autopsy Study

AbstractBackgroundThe neuropathological hallmarks of Alzheimer’s disease (AD), including amyloid plaques and neurofibrillary tangles, also accumulate in the brains of aging individuals. However, some individuals are able to age successfully without significant degenerative neuropathology or cognitive impairment, a phenomenon referred to as “successful aging”. The predictors of successful “neuropathologic” and “cognitive” aging are not fully understood, creating a critical knowledge gap. Factors such as resistance, resilience, and reserve are believed to play important roles. Furthermore, the relationship between neuropathological changes, such as tau pathology and amyloid pathology, and cognitive impairment in the oldest old population remains unclear, and the concept of amyloid plaques causing tau pathology may not be universally valid. The association between amyloid plaques and dementia also continues to be debated.MethodsIn this study, we utilized a collection of 414 post‐mortem brain tissues (171 female, 241 male) from aged individuals (average age 90, range 80‐108) with neuropathological and clinical data (215 without cognitive impairment and 161 with cognitive impairment) to perform a cross‐sectional analysis. Our cohort included subjects who had cognitive assessments available and included those with no amyloid plaque pathology or mild burden based on neuropathological criteria. Variables (including new traits derived from A.I. based feature extraction) associated with the cognitive measures were determined using multivariable logistic regression.ResultsOur results revealed that age of death and Braak neurofibrillary tangle stage were significant predictors of cognitive impairment (p&lt;0.05), while amyloid positivity was not. These findings suggest that tau pathology may have a stronger association with cognitive impairment in the oldest old population compared to amyloid plaques.ConclusionUnderstanding the neuropathological factors associated with successful brain and cognitive aging will contribute to our knowledge of the underlying mechanisms and may pave the way for the development of interventions to promote successful aging and prevent cognitive decline in old age. Further research in this area is warranted to elucidate the complex relationship between neuropathology, cognitive function, and aging in the oldest old population.

48 Longitudinal Study: Impact of Anxiety on the Evolution of Cognitive Performance and Brain Morphology in Patients with Parkinson’s Disease

Objective:Anxiety is very common in Parkinson’s disease (PD) where according to a systematic review, the average prevalence is 31%, surprisingly higher than the average 17% of depressive disorders found in PD. Only a few studies have investigated the impact of anxiety on cognitive performance and brain morphology in PD. They demonstrated anxiety to be a significant predictor of cognitive impairment, where PD patients with anxiety have shown to be twice more likely to have deficits in the memory domain compared to those without anxiety. Furthermore, poorer cognitive performance in all cognitive domains was reported to be a significant risk factor for increased anxiety the following year. Anxiety in PD has also shown reduced volume/thinning in the fronto-cingulate, anterior cingulate cortex, left parietal cortices and the precuneus, despite the scant number of studies on this topic. Hence, the objective of this study aims to determine the evolution of cognitive performance and brain morphology in PD patients with and without anxiety over a three-year span.Participants and Methods:We analyzed the baseline and three-year follow-up Parkinson’s Progression Markers Initiative (PPMI) data of 58 PD patients. MRI 3T was processed with FreeSurfer 7.1.1 on the Compute Canada cluster “Cedar” and we extracted cortical (Desikan-atlas-based volumes, thickness, area, folding index, curvature) and volumes of subcortical structures. Additionally, anxiety subscores from the State-trait anxiety inventory as well as neuropsychological tests were analyzed. PD patients were classified in two groups: PD-no-anxiety (n=46) and PD-anxiety (n=12) (subscore of &gt; 40 on the State anxiety scale). Two-way mixed ANOVA models were established with presence/absence of anxiety as a between-subjects factor, time (baseline and three year) as a within-subjects factor and neuropsychological and MRI data were regarded as dependent variables.Results:Mixed ANOVA revealed that PD-anxiety saw a significantly greater decline in performance on the Montreal Cognitive Assessment test compared to PD-no-anxiety. In addition, PD-anxiety saw their performance decline over time in the Hopkins Verbal Learning test (HVLT) immediate recall, HVLT retention and HVLT delayed recall while PD-no-anxiety saw an increase in performance. In terms of brain morphology, over the three years, PD-anxiety had a greater decrease in the frontal precentral thickness, cingulate isthmus area and thickness, and temporal regions (transverse area and inferior folding) all in the left hemisphere compared to PD-no-anxiety. In subcortical regions, PD-anxiety had a greater decrease in volume of the hippocampal cornu ammonis-1 and pallidum compared to PD-no-anxiety. By contrast, PD-anxiety showed a greater increase in curvature of the frontal middle rostral, frontal pole, parietal supramarginal, and insula cortex as well as in the folding of the parietal superior and occipital pericalcarine of the right hemisphere in comparison to PD-no-anxiety.Conclusions:This study highlights the importance of taking into consideration anxiety symptoms in PD, as they contribute to poorer cognitive performance and frontal, parietal and temporal differences over time. More studies with a larger sample size are needed in order to confirm these results.

Patient-reported outcome measurements in a selective cohort of relapsing-remitting multiple sclerosis patients: relationships with physical disability, cognitive impairment, and MRI-derived metrics.

The added value of patient-reported outcome measures (PROMs) in addition to standard clinical outcome tools in the assessment of relapsing-remitting multiple sclerosis (RRMS) patients' status is increasingly recognized. PROMs facilitate the detection of hidden aspects of MS and help to integrate the patient's subjective experience of health-related quality of life (HRQoL) status and treatment satisfaction in a holistic way. However, the relationship between PROMs and clinical and cognitive status has been scarcely investigated up to now. To investigate the association of PROMs with physical and cognitive disability in a cohort of RRMS patients at initiation of a new disease-modifying treatment. In this cross-sectional bicenter study, 59 consecutive RRMS patients underwent neurological examination with EDSS assessment, comprehensive cognitive tests (BVMT-R, SDMT, CVLT-II) and a set of self-reported questionnaires. Lesion and brain volumes were analyzed and processed by the automated MSmetrix® software (Icometrix®, Leuven, Belgium). Spearman's correlation coefficient was used to evaluate the association of collected variables. A cross-sectional logistic regression analysis was performed to find baseline correlates of cognitive impairment. Of the 59 RRMS patients (mean age 39 ± 9.8years, 79.7% female, median EDSS 2.0), 33 (56%) had cognitive impairment. While almost all dimensions of health, explored by PROMs, were impacted in the overall sample, no significant difference was observed in patients with and without cognitive impairment. All PROMs were significantly associated with EDSS (R = 0.37-0.55; p < 0.05), except for the psychological component of MSIS-29, BDI and DEX-Q scores. No significant correlation was found between PROMs and cognitive performances. The cross-sectional logistic regression analysis included age, gender (female), education, EDSS, hippocampus and FLAIR lesion volumes as significant predictors of cognitive impairment. The data highlight that PROMs provide valuable information on the well-being of PwMS closely paralleling the extent of MS-related disability, as measured by the EDSS. Additional research should determine the relevance of PROMs as longitudinal outcome measures.

JS-HOPE ASIA-2: BLOOD PRESSURE VARIABILITY AND NEURODEGENERATIVE DISEASES

Alzheimer's disease (AD) and Parkinson's disease (PD) have become more prevalent as populations have aged. The treatment of many neurodegenerative disorders has not yet reached a point where it is possible to modify the disease's progression. Midlife hypertension is a significant predictor of cognitive impairment and neurodegenerative brain diseases in later life. These findings emphasize the importance of preventing and controlling hypertension as a neurodegenerative disease risk factor. In neurodegenerative diseases, autonomic dysfunction, neuropsychiatric, and sleep problems can lead to blood pressure variability (BPV). The BPV itself can exacerbate the disease's course. In light of this, it is crucial to regulate BPV in order to halt the progression of the degenerative process.

Association of sleep duration and physical frailty with cognitive function in older patients with coexisting atrial fibrillation and heart failure.

To investigate the associations of sleep duration and physical frailty with cognitive function in older patients with both atrial fibrillation and heart failure. This study used a cross-sectional, secondary data analysis design. We included outpatients aged ≥ 65 years with coexisting atrial fibrillation and heart failure in South Korea. We used a sample of 176 patients (men=100) with HF among 277 data from the parent study. The data were collected through a self-report, structured questionnaire and electronic medical record. Our main finding showed that long sleep duration and physically frail status were significant predictors of cognitive impairment in older adults with both atrial fibrillation and heart failure. Healthcare providers should be aware of the importance of assessing sleep duration and physical activity in older adults with both atrial fibrillation and heart failure to prevent or delay cognitive impairment.

Longitudinal Relationship Between Frailty and Cognitive Impairment in Chinese Older Adults: A Prospective Study.

We aimed to examine the longitudinal association between frailty and cognitive impairment in the older Chinese population. This prospective cohort study used data from the Chinese Longitudinal Healthy Longevity Study 2011 wave. We calculated the follow-up duration as 3 years from the baseline year. Frailty was measured using the frailty index, and cognitive function was calculated by Mini-Mental State Examination Scale. Participants who were non-frailty and those with normal cognitive function were included in 2011 and followed up in 2014, respectively. Frailty was an independent risk factor for early-onset cognitive impairment. Age, hearing impairment, and a decreased ability to perform daily activities were the main risk factors for cognitive impairment, while affluent economic status was a protective factor. Cognitive impairment was not found to be an independent risk factor for frailty. We concluded that the frailty index is a significant predictor of cognitive impairment among community-dwelling older adults.

The unique contribution of depression to cognitive impairment in Post-Acute Sequelae of SARS-CoV-2 infection

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with significant cognitive impairment and increased risk for mental health comorbidities. This study aimed to identify specific associations between cognitive impairment, self-reported disruptions in memory, and psychiatric symptoms including depression, anxiety, posttraumatic stress disorder (PTSD), and perceived sleep concerns. MethodsData collected from all consecutive patients with Post-Acute Sequelae of SARS-CoV-2 infection (PASC) who presented to a dedicated Post-COVID Clinic were used to evaluate whether certain psychiatric symptoms were more strongly associated with cognitive impairment and self-reported memory disturbances. ResultsUnivariate and multivariable analyses revealed that depression symptom severity was significantly associated with the severity of cognitive impairment among patients with PASC. This association was driven primarily by lower performance on verbal fluency, attention, and delayed recall tasks among patients with higher depression symptoms severity. Perceived sleep concerns were an important predictor of self-reported memory disturbances. Conversely, neither PTSD symptom severity nor anxiety symptom severity were significant predictors of cognitive impairment or self-reported memory disturbances. ConclusionsThese findings have important clinical implications for justifying the need for screening patients with PASC for both depression and cognitive impairment.

Measuring cognitive function by the SDMT across functional domains: Useful but not sufficient

BackgroundThe Symbol Digit Modalities Test (SDMT) is a common screen of cognitive function for people with Multiple Sclerosis (pwMS) but growing acknowledgement that people with cognitive impairment are a heterogeneous population suggests that a single screen may provide limited information. ObjectiveTo assess the adequacy of the SDMT in capturing impairment across specific cognitive domains as measured by a multi-domain cognitive assessment battery (CAB, NeuroTrax). Methods113 pwMS were assessed with SDMT and the CAB. Cognitive impairment in each CAB domain was defined as ≥1.5 SD below the normalized mean. Logistic regression models were fit for each CAB domain with domain-specific cognitive impairment as the outcome and SDMT as the predictor, and a classifier created by selecting cutpoints using the Youden Index. Model performance was assessed by predicting domain-specific cognitive impairment in an independent data set consisting of 81 pwMS. ResultsSDMT was a significant predictor of cognitive impairment in all outcomes considered (Odds Ratio: 0.885-0.950), but prediction metrics such as area under the receiver operating curve (AUC) were modest (0.623-0.778), and the alignment between observed/predicted impairment was less than optimal. ConclusionThe SDMT is not sufficient to differentiate between impaired and non-impaired pwMS across several cognitive domains.

Cognitive Function and White Matter Lesions in Medication-Overuse Headache.

PurposeThis study was designed to investigate the cognitive function and the white matter lesions (WMLs) and the relationship between them in medication-overuse headache (MOH) patients.MethodsSubjects were enrolled and performed Montreal Cognitive Assessment (MoCA, Chinese-Beijing Version), Hamilton Anxiety Rating Scale (HAMA), Hamilton Depression Rating Scale (HAMD-24), and Pittsburgh Sleep Quality Index (PSQI) to evaluate the general cognitive function, anxiety, depression and sleep quality, and they were divided into three groups according to the MoCA scores: healthy controls, MOH with normal cognition group and MOH with cognitive impairment group. All the participants underwent MRI scans and images were obtained for WML evaluation with Fazekas scale.ResultsOne hundred thirty-four participants were enrolled into this study, 46 of them for healthy controls, and 88 for MOH patients, 40 of the MOH patients for MOH with cognitive impairment group, and 48 for MOH with normal cognition group. MOH patients had significantly lower MoCA scores, including the scores of visuospatial and executive function, attention, and orientation, while they had significantly greater HAMA scores, HAMD-24 scores, PSQI scores, and deep white matter hyperintensity scores compared to healthy controls. And in MOH patients, the age, disease duration, monthly headache days, and periventricular white matter hyperintensity scores in patients with cognitive impairment were greater than those in patients with normal cognition. Moreover, the MoCA scores were negatively related to age, disease duration, monthly headache days, and Fazekas scale scores, and disease duration and monthly headache days were significant predictors of cognitive impairment in MOH patients.ConclusionMOH patients showed cognitive impairment and increased WML burden. And in MOH patients, cognitive function was negatively related to WML burden, and disease duration and monthly headache days were potential predictors of cognitive impairment. Prompt and effective treatment to stop the progression of the disease may alleviate cognitive impairment in MOH patients.

Cognitive dysfunction after out-of-hospital cardiac arrest: Rate of impairment and clinical predictors

BackgroundThe purpose of this study was to evaluate the rate and domains of cognitive impairment in out-of-hospital cardiac arrest (OHCA) survivors, as compared to patients who experienced a myocardial infarction (MI), and to explore mechanisms and predictors of this impairment. Methods and resultsOHCA survivors with “good” neurological recovery (i.e., Cerebral Performance Categories Scale ≤ 2) (n = 79), as well as a control group of MI patients (n = 69), underwent a comprehensive neuropsychological assessment. Forty-three percent of OHCA survivors were cognitively impaired (in the lowest decile on a global measure of cognitive functioning). Rates of impairment were approximately six times higher in the OHCA group than the MI group. Attention, memory, language and executive function were affected. Downtime was a significant predictor of cognitive impairment; the interaction between downtime and immediate intervention was significant such that, at short downtimes, receiving cardiopulmonary resuscitation (CPR) or defibrillation within 1 min of collapse predicted less cognitive impairment. ConclusionsOHCA survivors – even those with seemingly good neurological recovery – are at risk for cognitive impairment. Cognitive rehabilitation may be an important consideration post-OHCA.

Prevalence and predictors of cognitive impairment among the elderly in Bangladesh

To investigate the prevalence of cognitive impairment and its predictors among the elderly in Bangladesh. We use a cross-sectional survey of 1015 older people (≥60 years) in Bangladesh collected jointly by the Sir William Beveridge Foundation (SWBF) and Aging Support Forum (ASF), Bangladesh. The Mini-Mental State Examination (MMSE) scale, adapted to the Bengali language, was used for assessing cognitive impairment, which was available for 111 participants. Logistic regression analysis was used to identify predictors of cognitive impairment. Multiple imputation under the missing-at-random (MAR) mechanism was used to deal with missing data. Overall, 31 out of 111 (27.9%) participants had mild, moderate or severe cognitive impairment, with a higher proportion among women (33.3%, 17 out of 51) than men (23.3%, 14 out of 60). More precisely, 24 out of 111 (21.6%) and 7 out of 111 (6.3%) had mild/moderate and severe cognitive impairment, respectively, with a higher percentage among women (mild/moderate: 25.5%, severe: 7.8%) than men (mild/moderate: 18.3%, severe: 5.0%). Age (odds ratio, OR = 1.06, p = 0.046, 95% CI: 1.001 to 1.119) and social engagement (OR = 0.25, p = 0.033, 95% CI: 0.072 to 0.898) were found to be statistically significant predictors of cognitive impairment in this group of people. The effect of physical disability fell short of statistical significance at the 5% level but was significant at the 10% level (OR = 2.89, p = 0.099, 90% CI: 0.999 to 8.370). The prevalence of cognitive impairment in Bangladesh is alarming and is comparatively higher among elderly women, which seems to increase with age and the presence of any physical disability. Also, prevalence appears to be lower in people who are more socially engaged or active.

Decreased blood CD4+ T lymphocyte helps predict cognitive impairment in patients with amyotrophic lateral sclerosis

BackgroundALS patients have changed peripheral immunity. It is unknown whether peripheral immunity is related to cognitive dysfunction in ALS patients.ObjectiveTo explore the relationship between the peripheral blood lymphocyte subsets and the cognitive status in ALS patients.MethodsAmong 81 ALS patients, we compared the demographic, clinical, and peripheral levels of total T lymphocyte, CD4+ T lymphocyte, CD8+ T lymphocyte, B lymphocyte, and NK cell between those with cognitive impairment (ALS-ci) and those without (ALS-nci). The cognitive status was evaluated via the Chinese version of the Edinburgh cognitive and behavioral screen (ECAS). Significant predictors of cognitive impairment in univariate logistic regression analysis were further examined using multivariate logistic regression analysis.Results39.5% of all ALS patients had cognitive impairment. The ALS-ci group had shorter education time, older age at both symptom onset and testing, longer disease duration, and lower levels of peripheral total, CD4+, and CD8+ T lymphocyte and B lymphocyte than the ALS-nci group. Frequency of behavioral impairment did not differ between the two groups. While parameters with significant differences identified by group comparison were also significant predictors of cognitive impairment in univariate logistic regression analysis except the level of B lymphocyte, only older age at testing, education time less than 9 years, and lower level of CD4+ T lymphocyte remained significant in multivariate logistic regression analysis. The predictive model combining these three parameters had an area under the receiver operating characteristic curve value of 0.842 with a sensitivity of 90.6% and a specificity of 67.3%.ConclusionIn Chinese ALS patients, blood CD4+ T lymphocyte might help evaluate cognitive impairment along with age and education level.

Cognitive reserve in stroke patients.

At present, a limited amount of information exists on the association between cognitive reserve and cognitive impairment in stroke populations. To determine predictors of cognitive reserve among stroke patients, 80 stroke patients attending the neurological and rehabilitation clinic in two different Malaysian general hospitals participated in this study. The Malay Cognitive Reserve Index questionnaire (CRIq-M), Depression Anxiety and Stress Scales-Short Form (DASS-21), WHO Quality of Life assessment BREF-21 (WHO-QOL BREF-21), Montreal Cognitive Assessment (MoCA), and modified Rankin Scale (mRS) were used as instruments in this study. The study found that cognitive reserve (CRIq-M) is positively correlated with cognitive function (MoCA), r = 0.529, p < .01. Multiregression showed that education was a significant predictor of cognitive impairment whereas cognitive impairment as assessed by the MoCA is a significant predictor for cognitive reserve in people with stroke. Early identification of cognitive impairment among stroke patients is important so that effective individual rehabilitation can be designed to enhance individual cognitive reserve and quality of life.

Cognitive Impairment Among Older Adults With Diabetes Mellitus in Puducherry: A Community-Based Cross-Sectional Study.

BackgroundCognitive impairment is a global public health problem in the elderly population. There is increasing evidence that diabetes mellitus predisposes to cognitive impairment. Early diagnosis and management of cognitive impairment can delay the onset of dementia, thereby improving self-care and quality of life of diabetic patients. This study intends to assess cognitive impairment, and the factors influencing cognitive impairment among older adults with diabetes mellitus in Puducherry.MethodsA community-based cross-sectional study was conducted in field practice areas of a Government Medical College in Puducherry between April and June 2019. After obtaining ethical approval, 240 registered diabetic patients aged 55 years and above were randomly selected. Data on demographic profile and clinical variables were collected using a semi-structured questionnaire. Cognitive function was assessed using the Hindi Mental State Examination (HMSE) tool, and participants who scored below 26 were considered to have cognitive impairment.ResultsAmong 240 participants, 67.9% were aged 60 years and above, 62.5% were females, and 83.8% were unemployed. The proportion of cognitive impairment among older adults with diabetes was 30.0% (95% confidence interval (CI): 24.5-36.03). The mean ± standard deviation of the HMSE Score was 26.13 ± 3.8, and the median score was 27. Female gender (P= 0.02, adjusted prevalence ratio (aPR) = 5.31, 95% CI: 1.34-21), widowhood status (P= 0.005, aPR= 2.71, 95% CI: 1.34-5.46), illiteracy (P<0.001, aPR= 3.55, 95% CI: 1.78-7.07), and presence of probable symptomatic hypoglycemia (P=0.02, aPR= 2.18, 95% CI: 1.13-4.20) were significant predictors of cognitive impairment in the study population by multivariate analysis.ConclusionAlmost one-third of older adults with diabetes were found to be at risk of cognitive impairment. Older diabetic patients with identified risk factors may be prioritized for a screening of cognitive impairment at the primary care level.

Biopsychosocial Predictors of Cognitive Impairment in the Elderly: A Case-control Study

Background: Cognitive impairment is one of the most common diseases in the elderly. Several studies have already been conducted to identify related factors, but few have explored all the factors involved in the development of cognitive problems. Objective: The present study aimed to identify significant biopsychosocial predictors of cognitive impairment. Methods:: This case-control study was conducted on 535 elderly people referred to Shafa Clinic in the city of Tehran in 2017. The biological factors including serum cholesterol, fasting blood sugar, systolic and diastolic blood pressure, vitamin D, vitamin B12, serum folate, serum homocysteine, height, and weight were measured. The psychological variable in this study was a history of depression that was extracted from the medical records. Social network and social support were measured by LSNS-6 and MOS-SSS questionnaires. The SPSS version 25 was used to analyze the data. Results: The mean age of the control group was 68.4 years (SD = 5.89) and of the case group was 71.5 years (SD = 7.37). The results of multiple logistic regression analysis showed age (AOR=1.05; CI:1.089-1.016, p≤0.05,), Secondary education (AOR=0.51; CI:0.266-0.990, p&lt;0.05,), Tertiary education (AOR=0.41; CI:0.212-0.810, p&lt;0.01,), hypertension (AOR=2.16; CI:3.671-1.266, p&lt;0.01) homocysteine level (AOR=1.09; CI:1.147-1.045, p&lt;0.001,), Hypothyroidism (AOR=0.43; CI: 0.226 0.820, p&lt;0.001,), and depression (AOR=4.5; CI:7.163-2.822, p&lt;0.001) to be significant predictors of cognitive impairment. Conclusion: Results of this study showed that low education level, high blood pressure, high level of homocysteine and depression likely increase the risk of cognitive impairment; also, it was implied that timely screening can identify people at risk. The novelty of the present study is that it used a combination of the biopsychosocial factors to predict unique predictors of cognitive impairment.