A High Neutrophil-to-Lymphocyte Ratio Predicts Higher Risk of Poststroke Cognitive Impairment: Development and Validation of a Clinical Prediction Model

ObjectivePoststroke cognitive impairment (PSCI) is a serious complication of stroke. The neutrophil-to-lymphocyte ratio (NLR) is a marker of peripheral inflammation. The relationship between the NLR and PSCI is far from well studied, and the thesis of this study was to assess the predictive value of the NLR in patients with PSCI, and establish and verify the corresponding prediction model based on this relationship.MethodsA total of 367 stroke patients were included in this study. Neutrophils, lymphocytes, and NLRs were measured at baseline, and clinical and neuropsychological assessments were conducted 3 months after stroke. The National Institutes of Health Scale (NIHSS) was used to assess the severity of stroke. A Chinese version of the Mini Mental State Examination (MMSE) was used for the assessment of cognitive function.ResultsAfter three months of follow-up, 87 (23.7%) patients were diagnosed with PSCI. The NLR was significantly higher in PSCI patients than in non-PSCI patients (P < 0.001). Patient age, sex, body mass index, NIHSS scores, and high-density lipoprotein levels also differed in the univariate analysis. In the logistic regression analysis, the NLR was an independent risk factor associated with the patients with PSCI after adjustment for potential confounders (OR = 1.67, 95%CI: 1.21–2.29, P = 0.002). The nomogram based on patient sex, age, NIHSS score, and NLR had good predictive power with an AUC of 0.807. In the validation group, the AUC was 0.816.ConclusionAn increased NLR at admission is associated with PSCI, and the model built with NLR as one of the predictors can increase prognostic information for the early detection of PSCI.

Identification of Serum Biomarkers in Patients with Alzheimer’s Disease by 2D-DIGE Proteomics

<b><i>Aim:</i></b> The aim of this study is to identify potential serum biomarkers of Alzheimer’s disease (AD) for early diagnosis and to evaluate these markers on a large cohort. <b><i>Methods:</i></b> We performed two-dimensional difference gel electrophoresis to compare the serum of AD patients and normal controls. Western blot or enzyme-linked immunosorbent assay (ELISA) was used to identify the expression levels of proteins. <b><i>Results:</i></b> In this study, a total of 13 differentially expressed proteins were identified. Among them, 2 proteins (inter-alpha-trypsin inhibitor heavy chain H4 [ITI-H4], Apolipoprotein A-IV) were validated by Western blot and 4 proteins (Cofilin 2, Tetranectin, Zinc-alpha-2-glycoprotein [AZGP1], Alpha-1-microglobulin/bikunin precursor [AMBP]) were validated by ELISA, respectively. Western blot results showed that the full size of the ITI-H4 protein was increased, while a fragment of ITI-H4 was decreased in AD patients. In contrast, 1 fragment of Apo A-IV was mainly found in control group and rare to be detected in AD patients. On the other hand, ELISA results showed that Cofilin 2, Tetranectin, AZGP1, and AMBP were significantly increased in AD patients, and Cofilin 2 is strongly correlated with the Mini-Mental State Examination scores of the AD patients. Serum Cofilin 2 was unchanged in Parkinson disease patients as compared to the control group, indicating a specific correlation of serum Cofilin 2 with AD. Moreover, Cofilin 2 was increased in both the serum and brain tissue in the APP/PS1 transgenic mice. <b><i>Conclusion:</i></b> Our study identified several potential serum biomarkers of AD, including: ITI-H4, ApoA-IV, Cofilin 2, Tetranectin, AZGP1, and AMBP. Cofilin 2 was upregulated in different AD animal models and might play important roles in AD pathology.

Acupuncture Therapy on Patients with Flaccid Hemiplegia after Stroke: A Systematic Review and Meta-Analysis

Background. Acupuncture is a commonly used complementary treatment for flaccid hemiplegia caused by stroke, but evidences from previous randomized trials were inconclusive. The purpose of this study was to evaluate the efficacy and safety of acupuncture in a comprehensive synthesis. Methods. We searched literature from eight databases from their inception to December 2020. We included randomized controlled trials of acupuncture for the treatment of flaccid hemiplegia following stroke. The meta-analysis was carried out using Review Manager 5.3 and Stata 16.0. The main indicator was the Fugl-Meyer Assessment scale. The modified Barthel Index scale, Quality Of Life Assessment scale, Mini-Mental State Examination scale, Berg Balance Scale, Neurological Deficit Assessment scale, and the treatment effective rate were used to measure the secondary indicators. Adverse events from individual studies were used to determine safety. Results. Our search returned 7624 records, of which 27 studies involving a total of 1,293 patients fulfilled our inclusion criteria. To be noted, our results indicated that significant improvements in the scores of the primary indicator showed better clinical scores among the three groups with acupuncture than without acupuncture: acupuncture compared with rehabilitation, 13.53 (95% CI 11.65–14.41, P < 0.01 ); acupuncture plus rehabilitation compared with rehabilitation, 9.84 (95% CI 6.45–13.24, P < 0.01 , I2 = 98%); and acupuncture plus Western medicine therapy compared with Western medicine, 16.86 (95% CI 15.89–17.84, P < 0.01 , I2 = 38%), and the secondary indicators showed the same tendency. Conclusion. Acupuncture was effective and safe in the patients with flaccid hemiplegia after stroke, although there was high heterogeneity between studies.

Brand new norms for a good old test: Northern Italy normative study of MiniMental State Examination

Aim Mini-Mental State Examination (MMSE) is one of the most used tests for the screening of global cognition in patients with neurological and medical disorders. Norms for the Italian version of the test were published in the 90 s; more recent norms were published in 2020 for Southern Italy only. In the present study, we computed novel adjustment coefficients, equivalent scores and cut-off value for Northern Italy (Lombardia and Veneto) and Italian speaking Switzerland. Methods We recruited 361 healthy young and old (range: 20–95 years) individuals of both sexes (men: 156, women: 205) and from different educational levels (range: 4–22 years). Neuropsychiatric disorders and severe medical conditions were excluded with a questionnaire and cognitive deficits and were ruled out with standardized neuropsychological tests assessing the main cognitive domains. We used a slightly modified version of MMSE: the word ‘fiore’ was replaced with ‘pane’ in verbal recalls to reduce the common interference error ‘casa, cane, gatto’. The effect of socio-demographic features on performance at MMSE was assessed via multiple linear regression, with test raw score as dependent variable and sex, logarithm of 101—age and square root of schooling as predictors. Results Mean raw MMSE score was 28.8 ± 1.7 (range: 23–30). Multiple linear regression showed a significant effect of all socio-demographic variables and reported a value of R2 = 0.26. The new cut off was ≥ 26 /30. Conclusion We provide here updated norms for a putatively more accurate version of Italian MMSE, produced in a Northern population but potentially valid all over Italy.

Simple Quantification of Surface Uptake in F-18 Florapronol PET/CT Imaging for the Validation of Alzheimer’s Disease

We developed a novel quantification method named shape feature using F-18 florapronol positron emission tomography–computed tomography (PET/CT) and evaluated its sensitivity and specificity for discriminating between patients with Alzheimer’s disease (AD) and patients with mild cognitive impairment or other precursors dementia (non-AD). We calculated the cerebral amyloid smoothing score (CASS) and brain atrophy index (BAI) using the surface area and volume of the region of interest in PET images. We calculated gray and white matter from trained CT data, prepared using U-net. Shape feature was calculated by multiplying CASS with BAI scores. We measured region-based standard uptake values (SUVr) and performed receiver operating characteristic (ROC) analysis to compare SUVr, shape feature, CASS, and BAI score. We investigated the relationship between shape feature and neuropsychological tests. Fifty subjects (23 with AD and 27 with non-AD) were evaluated. SUVr, shape feature, CASS, and BAI score were significantly higher in patients with AD than in those with non-AD. There was no statistically significant difference between shape feature and SUVr in ROC analysis. Shape feature correlated well with mini-mental state examination scores. Shape feature can effectively quantify beta-amyloid deposition and atrophic changes in the brain. These results suggest that shape feature is useful in the diagnosis of AD.

Characteristics and Outcome Determinants of Hospitalized Older Patients with Cognitive Dysfunction

Cognitive dysfunction commonly occurs among older patients during admission and is associated with adverse prognosis. This study evaluated clinical characteristics and outcome determinants in hospitalized older patients with cognitive disorders. The main outcomes were length of stay, readmission within 30 days, Barthel index (BI) score at discharge, BI score change (discharge BI score minus BI score), and proportion of positive BI score change to indicate change of activities of daily living (ADL) change during hospitalization. A total of 642 inpatients with a mean age of 79.47 years (76–103 years) were categorized into three groups according to the medical history of dementia, and Mini-Mental State Examination (MMSE) scores at admission. Among them, 74 had dementia diagnosis (DD), 310 had cognitive impairment (CI), and 258 had normal MMSE scores. Patients with DD and CI generally had a higher risk of many geriatric syndromes, such as multimorbidities, polypharmacy, delirium, incontinence, visual and auditory impairment, fall history, physical frailty. They had less BI score, BI score change, and proportion of positive BI score change ADL at discharge. (DD 70.0%, CI 79.0%), suggesting less ADL change during hospitalization compared with those with normal MMSE scores (92.9%; p < 0.001). Using multiple regression analysis, we found that among patients with DD and CI, age (p = 0.008) and walking speed (p = 0.023) were predictors of discharge BI score. In addition, age (p = 0.047) and education level were associated with dichotomized BI score change (positive vs. non-positive) during hospitalization. Furthermore, the number and severity of comorbidities predicted LOS (p < 0.001) and readmission (p = 0.001) in patients with cognitive disorders. It is suggested that appropriate strategies are required to improve clinical outcomes in these patients.

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

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

Deficits in color detection in patients with Alzheimer disease

Deficits in color vision and related retinal changes hold promise as early screening biomarkers in patients with Alzheimer’s disease. This study aimed to determine a cut-off score that can screen for Alzheimer’s dementia using a novel color vision threshold test named the red, green, and blue (RGB) modified color vision plate test (RGB-vision plate). We developed the RGB-vision plate consisting of 30 plates in which the red and green hues of Ishihara Plate No.22 were sequentially adjusted. A total of 108 older people participated in the mini-mental state examination (MMSE), Ishihara plate, and RGB-vision plate. For the analyses, the participants were divided into two groups: Alzheimer’s dementia (n = 42) and healthy controls (n = 38). K-means cluster analysis and ROC curve analysis were performed to identify the most appropriate cut-off score. As a result, the cut-off screening score for Alzheimer’s dementia on the RGB-vision plate was set at 25, with an area under the curve of 0.773 (p<0.001). Moreover, there was a negative correlation between the RGB-vision plate thresholds and MMSE scores (r = -0.36, p = 0.02). In conclusion, patients with Alzheimer’s dementia had a deficit in color vision. The RGB-vision plate is a potential early biomarker that may adequately detect Alzheimer’s dementia.

Assessment of the Risk of Depression in Residents Staying at Long-Term Care Institutions in Poland During the COVID-19 Pandemic Depending on the Quality of Cognitive Functioning

Background: The development of the COVID-19 pandemic has prompted the implementation of many procedures to safeguard against further increases in illness. Unfortunately, this has drastically reduced residents’ contact with their families, which has increased feelings of loneliness and isolation. This is particularly difficult in long-term care facilities, where the risk of developing depression is higher than in the general population.Objectives: The aim of the study was to assess the risk of depression among the residents of long-term care institutions in Poland during the COVID-19 pandemic and to determine the relationship between the risk of depression and the occurrence of cognitive impairment in the study group.Methods: The study included 273 residents from long-term care institutions in Poland. The risk of depression was determined based on an originally designed questionnaire. The cognitive state of the subjects was assessed using the screening test Mini-Mental State Examination (MMSE). Both the depression risk assessment and the MMSE test were conducted twice: in March and December 2020.Results: In March, severe dementia was present in 28.2% of the residents and normal MMSE scores were observed in 16.1% of the subjects; in December, the prevalence of severe dementia increased to 31.1% and that of normal scores decreased to 10.3%. In March, no participant was found to be at high risk of depression and moderate risk was observed in 14.3% of the subjects; in December, 2.6% of the residents had a high risk score and 45.4% had a moderate risk score. Statistical analysis revealed that higher MMSE scores correspond with a higher risk of depression.Conclusion: A higher risk of depression was observed with the development of the pandemic. Residents with cognitive impairment were characterised by a lower risk of depression compared to individuals with normal MMSE scores. During the study, progression of cognitive impairment was observed in the residents.