Mini-Mental State Research Articles

Dual-Language Use and Cognitive Function Among Mexican Americans Aged 65 and Older.

Better English proficiency and higher frequency of using English among non-native speakers are associated with lower dementia risk. We investigated if Mexican American older adults who use English and Spanish to a more similar degree demonstrate better cognitive function than those who use one language more than the other. We used data from waves one (1992/93) to eight (2012/13) of the Hispanic Established Population for the Epidemiological Study of the Elderly. At baseline, participants were asked what language they usually use across communicative contexts. We based dual language on participants' use of Spanish and English within and across contexts. We categorized participants as low (n = 1,145), medium (n = 717), and high (n = 702) dual-language users. Linear mixed models were used to estimate the association between dual-language use, baseline Mini-Mental State Examination (MMSE) scores, and change in MMSE. Participants in the medium and high dual-language use categories scored 1.91 points and 3.03 points higher at wave one compared to the low dual-language use category. Adjusting for education reduced the association between dual-language use and baseline MMSE (medium B = 0.99 SE = 0.19 p < 0.01; high B = 1.41 SE = 0.21 p < 0.01). The association between dual-language use and decline in the MMSE was not statistically significant. Greater dual-language use was associated with higher MMSE scores but not change in MMSE scores among Mexican Americans aged 65 and older. Future work should characterize bilingualism with greater nuance and use more rigorous cognitive measures to identify the components of the bilingual experience that may benefit the cognitive functioning of older adult bilinguals.

Simplifying Alzheimer's Disease Monitoring: A Novel Machine-Learning Approach to Estimate the Clinical Dementia Rating Sum of Box Changes Using the Mini-Mental State Examination and Functional Activities Questionnaire.

Primary outcome measure in the clinical trials of disease modifying therapy (DMT) drugs for Alzheimer's disease (AD) has often been evaluated by Clinical Dementia Rating sum of boxes (CDRSB). However, CDR testing requires specialized training and 30-50 minutes to complete, not being suitable for daily clinical practice. Herein, we proposed a machine-learning method to estimate CDRSB changes using simpler cognitive/functional batteries (Mini-Mental State Examination [MMSE] and Functional Activities Questionnaire [FAQ]), to replace CDR testing. Baseline data from 944 ADNI and 171 J-ADNI amyloid-positive participants were used to build machine-learning models predicting annualized CDRSB changes between visits, based on MMSE and FAQ scores. Prediction performance was evaluated with mean absolute error (MAE) and R2 comparing predicted to actual rmDeltaCDRSB/rmDeltayear. We further assessed whether decline in cognitive function surpassing particular thresholds could be identified using the predicted rmDeltaCDRSB/rmDeltayear. The models achieved the minimum required prediction errors (MAE < 1.0) and satisfactory prediction accuracy (R2>0.5) for mild cognitive impairment (MCI) patients for changes in CDRSB over periods of 18 months or longer. Predictions of annualized CDRSB progression>0.5, >1.0, or >1.5 demonstrated a consistent performance (i.e., Matthews correlation coefficient>0.5). These results were largely replicated in the J-ADNI case predictions. Our method effectively predicted MCI patient deterioration in the CDRSB based solely on MMSE and FAQ scores. It may aid routine practice for disease-modifying therapy drug efficacy evaluation, without necessitating CDR testing at every visit.

Effects of Type 2 Diabetes on the Neuropsychological Profile in Mild Cognitive Impairment.

Diabetes is one of the main risk factors for developing mild cognitive impairment (MCI) and Alzheimer's disease. Most studies have demonstrated a worse performance in executive function, verbal fluency, and information processing speed in patients with diabetes. To assess the cognitive functioning of persons with type 2 diabetes and amnesic mild cognitive impairment (aMCI-T2DM) compared to persons with aMCI without diabetes and persons without diabetes or aMCI as controls, to understand the role of diabetes in the neuropsychological profile. Cross-sectional study involving a sample of 83 patients, ranging in age from 61 to 85 years and divided into three groups: aMCI-T2DM (27 patients), aMCI (29 patients), Controls (27 individuals). All the participants undertook an exhaustive neuropsychological assessment (auditory-verbal and visual memory, attention, information processing speed, language, executive function, and depression). Both groups of aMCI patients performed significantly worse than the controls in all the neuropsychological tests. A significant linear tendency (p trend < 0.05) was found between groups, with the aMCI-T2DM group presenting worse results in global cognition assessed by the Mini-Mental State Examination and Montreal Cognitive Assessment; Rey-Osterrieth Complex Figure Test; Auditory Verbal Learning Test; Trail Making Test A and B, Verbal Fluency Test, and Hamilton Depression Rating Scale. aMCI patients with or without diabetes showed worse cognitive function compared to persons without diabetes or aMCI. Additionally, aMCI patients without T2DM presented a different cognitive profile than aMCI patients with T2DM, which tended towards presenting worse cognitive functions such as global cognition, memory, attention, executive function, and language.

Factors associated with adherence to antihypertensive agents in the older adult

Highlights Controlling arterial hypertension through medication is important to avoid complications related to this disease. Identifying the associated factors will help health professionals in promoting treatment success. With the practice of health education, it is possible to improve the adherence to pharmacological treatment. Make hypertensive patients aware of the importance of medication in the indicated dosage and schedule. Introduction: With aging, there is an increased risk of suffering from different chronic diseases, including high blood pressure. Hypertension management must be carried out by health professionals, whether or not treatment involves medication. By controlling drug treatment, especially adherence, serious health problems for older people can be avoided. Objective: To determine the factors associated with adherence to arterial hypertension treatment in older adults who live at home. Materials and Methods: A quantitative and cross-sectional study was conducted in La Libertad Region, Peru, with 342 older adults living at home. For data collection, a sociodemographic profile form, anthropometric measurements, blood pressure measurements, the Mini-mental State Examination (MMSE) test, the Geriatric Depression Scale (GDS), and the Morisky Green Levine (MGL) adherence scale were used. In addition, descriptive and analytical statistics were used. Result: 57.60% of the participants did not adhere to the pharmacological treatment, and, in most of the sociodemographic variables examined, they did not adhere to pharmacological treatment in most cases. Likewise, a relationship between retirement in older adults and the MGL adherence scale score was identified. The study showed evidence linking treatment adherence and age (p=0.01), retirement status (p=0.05), and history of stroke (p=0.004). Discussion: Treatment adherence depends on sociodemographic and health factors for disease control and a healthy lifestyle. Conclusion: Older adults and their caregivers need guidance and education to improve adherence to pharmacological treatments. How to cite this article: Fhon, Jack Roberto Silva; Gómez-Luján, María del Pilar; Caetano, Gideany Maiara; Cáceda-Ñazco, Giovanna Sara; Dos Santos Neto, Alexandre Pereira; Leitón-Espinoza, Zoila Esperanza. Factors associated with adherence to hypertensive pharmacological treatment in the older adult. Revista Cuidarte. 2024;15(1):e3474. https://doi.org/10.15649/cuidarte.3474

Development and validation of a nomogram for predicting cognitive frailty in patients on maintenance haemodialysis.

This study aimed to construct a nomogram for predicting the risk of cognitive frailty in patients on maintenance haemodialysis. An explorative cross-sectional design was adopted. From April 2022 to July 2022, 496 participants were recruited from five haemodialysis centres in Qingdao, Shandong Province, China. Participants with cognitive frailty were screened by Frailty Phenotype scale and Mini-Mental State Examination. Least Absolute Shrinkage and Selection Operator (LASSO) regression and multivariate logistic regression were utilized to determine predictors. The predictive performance of the nomogram was validated by calibration and discrimination. Decision curve analysis was used to assess clinical utility. Internal validation was implemented using 1000 bootstrap samples to mitigate overfitting. The prevalence of cognitive frailty was 17.5% (n = 87). Six risk predictors, namely health empowerment, alexithymia, age, educational level, marital status and dialysis vintage, were screened and used to develop a nomogram model. The nomogram had satisfactory discrimination and calibration, and decision curve analysis revealed considerable clinical utility. A nomogram incorporated with the six risk predictors was developed, and it exhibited excellent prediction performance. The nomogram may strengthen the effective screening of patients at high risk of cognitive frailty. This study established a tool for healthcare staff to predict cognitive frailty probability and identify risk factors in patients on maintenance haemodialysis. The nomogram can meet the needs of personalized care and precision medicine simultaneously. Data were collected from patients on maintenance haemodialysis by using questionnaire survey. STROBE checklist was used.

Use of alpha-adrenergic antagonists for lower urinary tract symptoms is not associated with worsening cognitive function.

Alpha-adrenergic antagonists are widely prescribed for lower urinary tract symptoms (LUTS), however there has been a report that their use is associated with dementia. Our objective was to investigate if new users of alpha-adrenergic antagonists with varying levels of cognitive impairment had an increased risk of cognitive decline compared to non-users. This was a retrospective cohort study, utilizing data from the National Alzheimer's Coordinating Center (NACC) data set. After applying relevant exclusion criteria, 916 people who were newly using alpha-antagonist medications were matched with a propensity score to 916 who were not using these medications. The primary outcome was a clinically relevant cognitive decline measured by the Clinical Dementia Rating (CDR) Dementia Staging Instrument or the mini mental state examination (MMSE). Secondary outcomes included scores from other cognitive assessment tools. The matched cohorts did not differ significantly in baseline characteristics. There were no statistically significant differences in baseline or follow-up cognitive scores between those exposed and nonexposed to alpha-adrenergic antagonists. Clinically significant cognitive decline (as defined by the CDR) occurred in 9.72% of the exposed group and 8.19% of the nonexposed group. There was no observed effect of alpha-adrenergic antagonists on cognitive decline, as measured with the CDR (odds ratio [OR] 1.34, p = 0.14) or the MMSE (OR 0.98, p = 0.92). Stratified analyses by cognitive status and apolipoprotein E genotype interaction assessment also demonstrated no significant associations. Alpha-adrenergic antagonists for LUTS do not appear to increase the risk of cognitive decline, offering reassurance to clinicians and patients.

The Beneficial, Formative Role of Lifetime Exposures across Cognitive Domains in Barbados Using Data from the SABE Study.

This study tested the hypothesis that within older Barbadian adults, sex, education, and occupation type lessen age-related cognitive decline. The analyses used a cross-sectional data set from 1325 people collected in the 2006 SABE Study (Health, Well-being, and Aging). Cognition was assessed as scores in each subdomain of the Mini-Mental State Exam. The loss of a single point in each subdomain was predicted by sex, years of education, job type, and their interactions with age. Results demonstrated that age and protective factors affect each cognitive domain differently. High education combined with mentally complex employment helped maintain cognitive performance in later life. Beneficial lifetime exposures are additive, providing combined benefits. Findings provide insight into public policy aiming to minimize the number of adults with cognitive decline and dementia in Barbados and the Caribbean.

Clinical observation on treatment of Alzheimer's disease with Sun's scalp-abdominal acupuncture combined with donepezil hydrochloride.

To observe the effect of scalp-abdominal acupuncture combined with donepezil hydrochloride on cognition and life ability of patients with Alzheimer's disease (AD), so as to evaluate its clinical efficacy. Sixty AD patients were collected and randomly divided into control group (30 cases) and observation group (30 cases). Patients in the control group were treated with oral donepezil hydrochloride (5 mg, once daily). Patients in the observation group were treated with scalp-abdominal acupuncture at Baihui (GV20), Yintang (GV24+), Sishencong (EX-HN1), "emotional area", Shenting (GV24), "abdominal area 1""abdominal area 8", and bilateral Fengchi (GB20), Taixi (KI3), Xuanzhong (GB39), Zusanli (ST36) on the basis of control group, and electroacupuncture (10 Hz/50 Hz, 0.5 to 5.0 mA) was applied to EX-HN1, "emotional area""abdominal area 1" and "abdominal area 8", once daily, 30 min each time. Four weeks as a course of treatment, both the two groups were treated for two consecutive courses. Before and after treatment, the mini-mental state examination (MMSE), AD assessmennt scale-cognitive subscale (ADAS-Cog) and activity of daily living scale (ADL) were evaluated. The clinical efficacy index was calculated and safety was evaluated. After treatment, the MMSE and ADL scores were higher (P<0.05) and the ADAS-Cog score was lower (P<0.05) than those before treatment in both groups. Compared with the control group, the MMSE and ADL scores were increased (P<0.05) and ADAS-Cog score was decreased (P<0.05) in the observation group. The total effective rate of the observation group (26/30, 86.67%) was higher (P<0.05) than that of the control group (23/30, 76.67%). No adverse reactions occurred in both groups during the treatment. Scalp-abdominal acupuncture combined with donepezil hydrochloride can effectively improve the cognitive ability and daily living ability of AD patients, and the efficacy is better than that of oral donepezil hydrochloride alone.

Intelligent prediction of Alzheimer’s disease via improved multifeature squeeze-and-excitation-dilated residual network

This study aimed to address the issue of larger prediction errors existing in intelligent predictive tasks related to Alzheimer’s disease (AD). A cohort of 487 enrolled participants was categorized into three groups: normal control (138 individuals), mild cognitive impairment (238 patients), and AD (111 patients) in this study. An improved multifeature squeeze-and-excitation-dilated residual network (MFSE-DRN) was proposed for two important AD predictions: clinical scores and conversion probability. The model was characterized as three modules: squeeze-and-excitation-dilated residual block (SE-DRB), multifusion pooling (MF-Pool), and multimodal feature fusion. To assess its performance, the proposed model was compared with two other novel models: ranking convolutional neural network (RCNN) and 3D vision geometrical group network (3D-VGGNet). Our method showed the best performance in the two AD predicted tasks. For the clinical scores prediction, the root-mean-square errors (RMSEs) and mean absolute errors (MAEs) of mini-mental state examination (MMSE) and AD assessment scale–cognitive 11-item (ADAS-11) were 1.97, 1.46 and 4.20, 3.19 within 6 months; 2.48, 1.69 and 4.81, 3.44 within 12 months; 2.67, 1.86 and 5.81, 3.83 within 24 months; 3.02, 2.03 and 5.09, 3.43 within 36 months, respectively. At the AD conversion probability prediction, the prediction accuracies within 12, 24, and 36 months reached to 88.0, 85.5, and 88.4%, respectively. The AD predication would play a great role in clinical applications.

Factors influencing physiotherapy decisions between restorative and compensatory gait rehabilitation: an Italian multicenter study

Background and purposeThis study aimed to investigate the factors that influence physiotherapists’ decision in choosing restorative or compensatory rehabilitation during gait training in people with neurological disorders (PwNDs) and the different treatments used in the approaches.MethodsThis cross-sectional analysis used the baseline data from an observational cohort study. We analyzed data from 83 PwNDs (65 people after stroke, 5 with multiple sclerosis, and 13 with Parkinson’s disease) who underwent at least 10 sessions of physiotherapy (PT) focusing on gait function. Performance was quantified using the modified Dynamic Gait Index (MDGI), three impairment domains of Fugl–Meyer Assessment for lower extremity (mFM-LL), Activities-specific Balance Confidence (ABC), modified Barthel Index (mBI), Mini-Mental State Examination (MMSE), and Motivational Index (MI). Forty-three physiotherapists completed a treatment report form categorizing the rehabilitation approach and specifying treatments used (e.g., resistance training and proprioceptive exercises).ResultsFifty-six subjects underwent restorative rehabilitation approach. The univariate predictors of restorative approach were being in the subacute phase with a disease onset of less than 180 days, (odds ratio [95%CI]; 3.27[1.19–9.24]), mFM-LL (1.25[1.11–1.44]), MMSE (0.85[0.67–1.00]), and number of sessions (1.03[1–1.01]). The backward stepwise analysis revealed an association between restorative and subacute phase (36.32[4.11–545.50]), mFM-LL (3.11[1.55–9.73]), mBI (1.79[1.08–3.77]), MMSE (0.46[0.25–0.71]), and the interaction between mFM-LL and mBI (0.99[0.98–1.00]). No statistically significant association between treatments used and approach was found (p = 0.46).Discussion and conclusionThe restorative approach was more commonly used to improve gait. The main variables associated with this approach were: being in the subacute phase of the disease, a low level of impairment, and a high level of functional independence at baseline. However, few differences were found between the treatments used for the restorative or compensatory approaches, as similar PT treatments were used for both.

#1454 Usefulness of the clinical frailty scale in Dutch patients with end-stage kidney disease

Abstract Background and Aims Frailty is common in end-stage kidney disease (ESKD) patients which may benefit from advance care planning. Currently there are multiple frailty screening instruments available, of which the Frailty Index is commonly used to estimate frailty in ESKD patients. The Clinical Frailty Scale is a less time consuming alternative to estimate frailty. We aimed to investigate the performance of the Clinical Frailty Scale as a screening tool for frailty in an ESKD population. Method A cross-sectional observational study was performed at Kidney Centre Apeldoorn. Included patients received haemodialysis, peritoneal dialysis, pre-dialysis care, or conservative treatment. Frailty was assessed with both the Frailty Index and the Clinical Frailty Scale. The Frailty Index consisted of 38 components considering activities of daily living, physical aspects, psychosocial factors, comorbidities, and functional tests. The functional tests included grip strength, walking speed, and cognitive functioning measured by the Mini Mental State Examination. The Frailty Index was calculated by dividing the number of deficits by the total number of components measured. A patient with a Frailty Index ≥0.25 was considered frail. The Clinical Frailty Scale consisted of nine classes varying from very fit to terminally ill. Patients who scored 4 on the Clinical Frailty Scale were considered vulnerable. Patients with a score ≥5 were considered frail. Nephrologists not familiar with the Clinical Frailty Scale were asked to complete the Clinical Frailty Scale after medical consultation. The sensitivity, specificity and area under the curve (AUC) of the Clinical Frailty Scale were determined. The Frailty Index was used as the golden standard. Results In total, 144 patients were included of whom 60 (41.7%) were frail according to the Frailty Index. The mean age was 67.4 years (SD±13.5) and 56 (38.9%) were female. Overall, 72 patients (50.0%) were treated by haemodialysis, 13 (9.0%) by peritoneal dialysis, 6 (4.2%) received conservative treatment, and 53 (36.8%) were pre-dialysis patients. According to the Frailty Index, 55.6% of the haemodialysis patients were frail compared to 20.8% of the pre-dialysis patients. The Clinical Frailty Scale identified 37 (25.7%) patients as frail and 17 (11.8%) patients as vulnerable. The cut-off point of the Clinical Frailty Scale for vulnerable (≥4) had a sensitivity of 63.3%, a specificity of 81.0%, and AUC of 0.72. The cut-off point of the Clinical Frailty Scale for frail (≥5) had a sensitivity of 50.0%, a specificity of 91.7%, and AUC of 0.71. Conclusion Prevalence of frailty was high in patients with ESKD. Although the Clinical Frailty Scale is a quick and easy tool for the identification of frailty in ESKD patients, the sensitivity of the Clinical Frailty Scale was too low to implement it in daily clinical practice. Sensitivity might be increased by training of nephrologists in using the Clinical Frailty Scale.

#372 Cross-sectional association between serum magnesium with cognition in patients undergoing hemodialysis: the Osaka Dialysis Complication Study

Abstract Background and Aims Impaired cognitive performance is common in patients with chronic kidney disease including those undergoing haemodialysis, although the mechanisms are not well understood by which chronic kidney disease affects cognitive function. Phosphate plays an important role in the development of aging phenotypes particularly in patients with chronic kidney disease. Phosphate toxicity is thought to be mediated by calciprotein particles, and a shorter T50 reflects a higher propensity of transformation of primary to secondary calciprotein particles. T50 is known to be affected by phosphate, fetuin-A, magnesium, and others. We examined possible relationship between cognitive function and CKD-MBD-related factors in patients undergoing haemodialysis. Method This was a cross-sectional study in 1207 patients on maintenance haemodialysis selected from the participants of Osaka Dialysis Complication Study (ODCS). Cognitive function was assessed by Modified Mini-Mental State examination (3MS). Associations of serum calcium, phosphate, intact PTH, magnesium, fetuin-A, and T50 with 3MS was examined by multiple regression models adjusted for age, sex, dialysis vintage, diabetic kidney disease, prior stroke, prior non-stroke cardiovascular disease, education level, SBP, DBP, Hb, BMI, serum albumin, and CRP. Results Serum magnesium and phosphate levels were significantly and positively associated with 3MS level independent of the potential confounders, whereas other factors were not. Conclusion We found positive associations of cognitive performance with serum magnesium and phosphate levels in haemodialysis patients, suggesting the roles of CKD-MBD-related factors in impaired cognition in this population.

Is it possible to diagnose therapeutic adherence in mild cognitive impairment and dementia patients in clinical practice?

Non-adherence is common and contributes to adverse health outcomes, reduced quality of life, and increased healthcare expenditure. The objective of this study was to assess the diagnostic validity to estimate the prevalence of non-adherence in patients with mild cognitive impairment (MCI) and dementia using two self-reported methods (SRMs) that are useful and easy in clinical practice, considering the pill count as a reference method (RM). The cohort study was nested in a multicenter randomized controlled trial NCT03325699. A total of 387 patients from 8 health centers were selected using a non-probabilistic consecutive sampling method. Inclusion criteria were as follows: a score of 20-28 points on the Mini-Mental State Examination (MMSE); older than 55years; taking prescribed medication; and are in charge of their own medication use. Participants were followed up for 18months after the baseline visit, i.e., 6, 12, and 18months. Variables related with treatment adherences were measured in all visits. The variables included age, sex, treatment, comorbidities, and the MMSE test. Adherences included pill counts and Morisky-Green test (MGT) and Batalla test (BT) as SRMs. Statistical analysis included descriptive analysis and 95% confidence intervals (CIs). The diagnostic validity included the following: 1) open comparison statistical association between SRMs and RMs and 2) hierarchy comparison: the RM as the best method to assess non-adherence, kappa value (k), sensitivity (S), specificity (Sp), and likelihood ratio (PPV/PPN). A total of 387 patients were recruited with an average age of 73.29 years (95% CI, 72.54-74.04), of which 59.5% were female. Comorbidities were 54.4% HTA, 35.9% osteoarticular pathology, and 24.5% DM. The MMSE mean score was 25.57 (95% CI, 25.34-25.8). The treatment adherence for the RM oscillates between 22.5% in the baseline and 26.3%, 14.8%, and 17.9% in the follow-up visits. For SRMs, the treatment adherence oscillates between 43.5% in the baseline and 32.4%, 21.9%, and 20.3% in the follow-up visits. The kappa value was statistically significant in all the comparison in all visits with a score between 0.16 and 035. Regarding the diagnostic validity, for the MGT, the sensibility oscillated between 0.4 and 0.58, and the specificity oscillated between 0.68 and 0.87; for the BT, the sensibility oscillated between 0.4 and 0.7, and the specificity oscillated between 0.66 and 0.9; and when both tests were used together, the sensibility oscillated between 0.22 and 0.4, and the specificity oscillated between 0.85 and 0.96. SRMs classify non-adherent subjects correctly. They are very easy to use and yield quick results in clinical practice, so SRMs would be used for the non-adherence diagnosis in patients with MCI and mild dementia.

Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development

Introduction: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention. Methods: This study included 2,288 participants with normal cognitive function from the Ma’anshan Healthy Aging Cohort Study. Forty-two potential predictors, including demographic characteristics, chronic diseases, lifestyle factors, anthropometric indices, physical function, and baseline cognitive function, were selected based on clinical importance and previous research. The dataset was partitioned into training, validation, and test sets in a proportion of 60% for training, 20% for validation, and 20% for testing, respectively. Recursive feature elimination was used for feature selection, followed by six machine learning algorithms that were employed for model development. The performance of the models was evaluated using area under the curve (AUC), specificity, sensitivity, and accuracy. Moreover, SHapley Additive exPlanations (SHAP) was conducted to access the interpretability of the final selected model and to gain insights into the impact of features on the prediction outcomes. SHAP force plots were established to vividly show the application of the prediction model at the individual level. Results: The final predictive model based on the Naive Bayes algorithm achieved an AUC of 0.820 (95% CI, 0.773–0.887) on the test set, outperforming other algorithms. The top ten influential features in the model included baseline Mini-Mental State Examination (MMSE), education, self-reported economic status, collective or social activities, Pittsburgh sleep quality index (PSQI), body mass index, systolic blood pressure, diastolic blood pressure, instrumental activities of daily living, and age. The model demonstrated the potential to identify individuals at a higher risk of cognitive impairment within 3 years from older adults. Conclusion: The predictive model developed in this study contributes to the early detection of cognitive impairment in older adults by primary healthcare staff in community settings.

Demographic Determinants of the Cognitive Status among Older Adults: Neyshabur Longitudinal Study on Aging

Introduction: Cognitive disorders affect the elderly’s personal and social life by causing disturbances in their nervous system, and it is important to identify who is at the highest risk of these disorders; therefore, the present study aims to investigate demographic determinants of the cognitive status in the elderly visiting the Geriatric Cohort Center in Neyshabur. Methods: This cross-sectional study was conducted on 3451 people aged 60 and above (52.5% women and 47.5% men) from 2015 to the end of 2017. The selection of statistical sample was done first by classification method, and then, by random method. Data collection was done using demographic questionnaires, and the questionnaires of Mini Mental State Examination (MMSE)and Montreal Cognitive Assessment (MOCA), and data were analyzed using independent t-test, ANOVA, and hierarchical multiple regression in software. were analyzed by SPSS16 software. Results: With MMSE, one fifth of the participants (20/3%) and with MOCA, almost half of the respondents (49/3%) did not have cognitive disorder. Cognitive disorder became more severe with aging. The severity of cognitive disorder was higher in women (P&lt; 0/05) those who were living alone(P &lt;0/05), the women who only did housework(P &lt; 0/05), and the cases who were illiterate (P&lt; 0/05). Conclusion: Screening of cognitive disorders in the elderly and early interventions including holding educational classes, especially for women with low literacy levels whose husbands have died, can prevent the progression of the disorder and improve their quality of life.

EFFECTIVENESS OF COGNITIVE STIMULATION THERAPY(CST) AMONG PEOPLE WITH DEMENTIA - A NARRATIVE REVIEW

OBJECTIVE: This study explores the effectiveness of cognitive stimulation therapy to improve cognition in people with dementia. SELECTION METHOD: PubMed, Google Scholar, Science Direct, Cochrane from these databases, articles were searched using keywords. SELECTION CRITERIA: The articles were collected based on the inclusion criteria focusing on the cognition in people with dementia. RESULTS: The preliminary results suggested that the tasks like measuring attention, memory, speed processing, executive functions, and speed processing following the cognitive stimulation treatment (CST). Evidence shows that CST promisingly improves people’s cognitive functions as measured by the (MMSE) mini-mental state examination. This test investigates memory, orientation, language, and visuospatial abilities. CST has led to significant improvements in quality of life, along with care givers. Analyses suggests CST is equally effective as many dementia drugs. CONCLUSION: Cognitive stimulation therapy improves cognition in people with dementia and benefits the quality of life. Evidence from several studies indicates that cognitive stimulation therapy along with multiple component interventions improves not only cognition but also the language, behavior, and quality of life of people with dementia. Results from interviews of CST sessions found key themes, including positivity being in the groups, due to a supportive and good environment, improvements in confidence, mood, and concentration. KEY WORDS: Non-Pharmacological intervention, Cognitive stimulation therapy (CST), People with Dementia (PwD), Cognition, Older adults, assessment scales, Quality of life (QoL).

Clinical Significance of the Plasma Biomarker Panels in Amyloid-Negative and Tau PET-Positive Amnestic Patients: Comparisons with Alzheimer's Disease and Unimpaired Cognitive Controls.

The purpose of this study was to investigate whether plasma biomarkers can help to diagnose, differentiate from Alzheimer disease (AD), and stage cognitive performance in patients with positron emission tomography (PET)-confirmed primary age-related tauopathy, termed tau-first cognitive proteinopathy (TCP) in this study. In this multi-center study, we enrolled 285 subjects with young-onset AD (YOAD; n = 55), late-onset AD (LOAD; n = 96), TCP (n = 44), and cognitively unimpaired controls (CTL; n = 90) and analyzed plasma Aβ42/Aβ40, pTau181, neurofilament light (NFL), and total-tau using single-molecule assays. Amyloid and tau centiloids reflected pathological burden, and hippocampal volume reflected structural integrity. Receiver operating characteristic curves and areas under the curves (AUCs) were used to determine the diagnostic accuracy of plasma biomarkers compared to hippocampal volume and amyloid and tau centiloids. The Mini-Mental State Examination score (MMSE) served as the major cognitive outcome. Logistic stepwise regression was used to assess the overall diagnostic accuracy, combining fluid and structural biomarkers and a stepwise linear regression model for the significant variables for MMSE. For TCP, tau centiloid reached the highest AUC for diagnosis (0.79), while pTau181 could differentiate TCP from YOAD (accuracy 0.775) and LOAD (accuracy 0.806). NFL reflected the clinical dementia rating in TCP, while pTau181 (rho = 0.3487, p = 0.03) and Aβ42/Aβ40 (rho = -0.36, p = 0.02) were significantly correlated with tau centiloid. Hippocampal volume (unstandardized β = 4.99, p = 0.01) outperformed all of the fluid biomarkers in predicting MMSE scores in the TCP group. Our results support the superiority of tau PET to diagnose TCP, pTau181 to differentiate TCP from YOAD or LOAD, and NFL for functional staging.

A Combined Index Using the Mini-Mental State Examination and Lawton Index to Discriminate Between Clinical Dementia Rating Scores of 0.5 and 1

A Combined Index Using the Mini-Mental State Examination and Lawton Index to Discriminate Between Clinical Dementia Rating Scores of 0.5 and 1

Distinctive subgingival microbial signatures in older adults with different levels of cognitive function.

To examine association between subgingival microbial signatures and levels of cognitive impairment in older adults. We analysed subgingival plaque samples and 16S ribosomal RNA sequences for microbiota among 165 participants (normal controls [NCs]: 40, subjective cognitive decline [SCD]: 40, mild cognitive impairment [MCI]: 49 and dementia: 36). The bacterial richness was lower among individuals with worse cognitive function, and subgingival microbial communities differed significantly among the four groups. Declining cognitive function was associated with decreasing relative abundance of genera Capnocytophaga, Saccharibacteria_genera_incertae_sedis, Lautropia and Granulicatella, and increasing abundance of genus Porphyromonas. Moreover, there were differentially abundant genera among the groups. Random forest model based on subgingival microbiota could distinguish between cognitive impairment and NC (AUC = 0.933, 95% confidence interval 0.873-0.992). Significant correlations were observed between oral microbiota and sex, Montreal Cognitive Assessment (MoCA) score and Mini-Mental State Examination score. Partial correlation analysis showed that Leptotrichia and Burkholderia were closely negatively associated with the MoCA score after adjusting for multiple covariates. Gene function was not significantly different between SCD and NC groups, whereas three homozygous genes were altered in MCI patients and two in dementia patients. This is the first study to demonstrate an association between the composition, function and metabolic pathways of subgingival microbiota and different levels of cognitive function among older individuals. Future cohort studies should assess its diagnostic usefulness for cognitive impairment.

Differences in insomnia-related self-reported outcomes among elderly hospitalized patients.

Insomnia is among the most common sleep disorders worldwide. Insomnia in older adults is a social and public health problem. Insomnia affects the physical and mental health of elderly hospitalized patients and can aggravate or induce physical illnesses. Understanding subjective feelings and providing reasonable and standardized care for elderly hospitalized patients with insomnia are urgent issues. To explore the differences in self-reported outcomes associated with insomnia among elderly hospitalized patients. One hundred patients admitted to the geriatric unit of our hospital between June 2021 and December 2021 were included in this study. Self-reported symptoms were assessed using the Athens Insomnia Scale (AIS), Generalized Anxiety Disorder Scale-7 (GAD-7), Geriatric Depression Scale-15 (GDS-15), Memorial University of Newfoundland Scale of Happiness (MUNSH), Barthel Index Evaluation (BI), Morse Fall Scale (MFS), Mini-Mental State Examination, and the Short Form 36 Health Survey Questionnaire (SF-36). Correlation coefficients were used to analyze the correlation between sleep quality and self-reported symptoms. Effects of insomnia was analyzed using Logistic regression analysis. Nineteen patients with AIS ≥ 6 were included in the insomnia group, and the incidence of insomnia was 19% (19/100). The remaining 81 patients were assigned to the non-insomnia group. There were significant differences between the two groups in the GDA-7, GDS-15, MUNSH, BI, MFS, and SF-36 items (P < 0.05). Patients in the insomnia group were more likely to experience anxiety, depression, and other mental illnesses, as well as difficulties with everyday tasks and a greater risk of falling (P < 0.05). Subjective well-being and quality of life were poorer in the insomnia group than in the control group. The AIS scores positively correlated with the GAD-7, GDS-15, and MFS scores in elderly hospitalized patients with insomnia (P < 0.05). Logistic regression analysis showed that GDS-15 ≥ 5 was an independent risk factor for insomnia in elderly hospitalized patients (P < 0.05). The number of self-reported symptoms was higher among elderly hospitalized patients with insomnia. Therefore, we should focus on the main complaints of patients to meet their care needs.