Cognitive Impairment In Patients Research Articles

The capacity of cognitive tests to detect generalized anxiety disorder (GAD): A pilot study

Cognitive impairment remains understudied in generalized anxiety disorder (GAD), despite the high prevalence and substantial burden associated with this disorder. We aimed to assess cognitive impairment in patients with GAD and evaluate the ability of cognitive tests to detect this disorder. Because of its high rate of comorbidity, we also examined how other anxiety disorders and current major depressive episodes affected our results. We tested 263 consecutive general practice outpatients. We used the GAD-7 and the Mini International Neuropsychiatric Interview (MINI) to detect anxiety and mood disorders. We assessed cognitive performance with the Stroop test, a facial emotion recognition test, and the trail-making test (TMT). Compared to patients without GAD, patients with GAD were significantly slower to complete the TMT(B-A) and faster to recognize emotions, especially negative ones such as disgust and anger. When controlling for other anxiety disorders and current major depressive episode, GAD retained a significant effect on the TMT(B-A), but not on the emotion recognition test. The TMT(B-A) could detect GAD with good accuracy (area under the curve (AUC) = 0.83, maximal Youden's index = 0.56), which was by no means comparable to the GAD-7 (AUC = 0.97, Youden's index = 0.81). While it is not efficient enough to replace the GAD-7 as a diagnostic tool, the capacity of the TMT(B-A) to detect GAD emphasizes the importance of cognitive flexibility impairment in GAD.

Spontaneous brain activity in the hippocampal regions could characterize cognitive impairment in patients with Parkinson's disease.

This study aimed to investigate whether spontaneous brain activity can be used as a prospective indicator to identify cognitive impairment in patients with Parkinson's disease (PD). Resting-state functional magnetic resonance imaging (RS-fMRI) was performed on PD patients. The cognitive level of patients was assessed by the Montreal Cognitive Assessment (MoCA) scale. The fractional amplitude of low-frequency fluctuation (fALFF) was applied to measure the strength of spontaneous brain activity. Correlation analysis and between-group comparisons of fMRI data were conducted using Rest 1.8. By overlaying cognitively characterized brain regions and defining regions of interest (ROIs) based on their spatial distribution for subsequent cognitive stratification studies. A total of 58 PD patients were enrolled in this study. They were divided into three groups: normal cognition (NC) group (27 patients, average MoCA was 27.96), mild cognitive impairment (MCI) group (21 patients, average MoCA was 23.52), and severe cognitive impairment (SCI) group (10 patients, average MoCA was 17.3). It is noteworthy to mention that those within the SCI group exhibited the most advanced chronological age, with an average of 74.4 years, whereas the MCI group displayed a higher prevalence of male participants at 85.7%. It was found hippocampal regions were a stable representative brain region of cognition according to the correlation analysis between the fALFF of the whole brain and cognition, and the comparison of fALFF between different cognitive groups. The parahippocampal gyrus was the only region with statistically significant differences in fALFF among the three cognitive groups, and it was also the only brain region to identify MCI from NC, with an AUC of 0.673. The paracentral lobule, postcentral gyrus was the region that identified SCI from NC, with an AUC of 0.941. The midbrain, hippocampus, and parahippocampa gyrus was the region that identified SCI from MCI, with an AUC of 0.926. The parahippocampal gyrus was the potential brain region for recognizing cognitive impairment in PD, specifically for identifying MCI. Thus, the fALFF of parahippocampal gyrus is expected to contribute to future study as a multimodal fingerprint for early warning.

A Nomogram Including Total Cerebral Small Vessel Disease Burden Score for Predicting Mild Vascular Cognitive Impairment in Patients with Type 2 Diabetes Mellitus.

Total cerebral small vessel disease (CSVD) burden score is an important predictor of vascular cognitive impairment (VCI). However, few predictive models of VCI in type 2 diabetes mellitus (T2DM) patients have included the total CSVD burden score, especially in the early stage of VCI. To develop and validate a nomogram that includes the total CSVD burden score to predict mild VCI in patients with T2DM. A total of 322 eligible participants with T2DM who were divided into mild and normal cognitive groups were enrolled in this retrospective study. Demographic data, laboratory data and imaging markers of CSVD were collected. The total CSVD burden score was calculated by combining the different CSVD markers. Step-backward multivariable logistic regression analysis with the Akaike information criterion was applied to select significant predictors and develop a best-fit predictive nomogram. The performance of the nomogram was assessed in terms of discriminative ability, calibrated ability, and clinical usefulness. The nomogram model consisted of five variables: age, education, hemoglobin A1c level, serum homocysteine level, and total CSVD burden score. A nomogram with these variables showed good discriminative ability (area under the receiver operating characteristic curve was 0.801 in internal verification). In addition, the Hosmer-Lemeshow test (χ2 =9.226, P=0.417) and bootstrap-corrected calibration plot indicated that the nomogram had good calibration. The Brier score of the predictive model was 0.178. Decision curve analysis demonstrated that when the threshold probability ranged between 16% and 98%, the use of the nomogram to predict mild VCI in patients with T2DM provide a greater net benefit. The nomogram, composed of age, education, stroke, HbA1c level, Hcy level, and total CSVD burden score, had good predictive accuracy and may provide clinicians with a practical tool for predicting the risk of mild VCI in T2DM patients.

Correlation of dietary inflammation index and dietary pattern with mild cognitive impairment in patients with type 2 diabetes

ObjectiveWe aimed to determine the dietary patterns associated with mild cognitive impairment (MCI) in type 2 diabetes (T2DM) and the correlation of dietary inflammatory index (DII) with MCI. MethodsThe Montreal Cognitive Assessment (MoCA) was used to assess cognitive function. A semi-quantitative food frequency questionnaire was used to collect dietary data and calculate DII. Dietary patterns were determined by reduced-rank regression (RRR), grouping dietary pattern scores and DII into quartiles, with logistic regression for correlation analysis. Dose–response relationships between dietary pattern scores, DII and diabetic MCI were explored using restricted cubic splines (RCS). A mediation analysis was performed to investigate whether DII mediates the association between dietary patterns and MCI. ResultsIn the “Mediterranean-style dietary pattern”, the multivariable-adjusted odds ratio of having MCI was 0.37 (95% CI: 0.20–0.68; p for trend=0.002) in the highest versus lowest quartiles of the dietary score. In the “high-meat and low-vegetable pattern”, the multivariable-adjusted odds ratio of having MCI was 6.84 (95% CI: 3.58–13.10; p for trend<0.001) in the highest versus lowest quartiles of the dietary score. In the “Western-style dietary pattern”, the multivariable-adjusted odds ratio of having MCI was 2.48 (95% CI: 1.38–4.46; p for trend=0.001). The multivariable-adjusted odds ratio of having MCI was 3.99 (95% CI: 2.14–7.42; p for trend<0.001) in the highest versus lowest quartiles of DII.There is a non-linear dose–response relationship between the “high-meat and low-vegetable pattern” score and the prevalence of MCI, as well as the DII and the prevalence of MCI. The DII partially mediated the impact of the “Mediterranean-style dietary pattern” and the “high-meat and low-vegetable pattern” on MCI. ConclusionIn T2DM patients, greater adherence to the “Mediterranean-style dietary pattern” is associated with a lower probability of having MCI. However, excessive consumption of meat, especially red meat and processed meat, combined with a lack of vegetable intake, is associated with a higher probability of having MCI. Greater adherence to the “Western-style dietary pattern” is associated with a higher probability of having MCI. In addition, a pro-inflammatory diet is associated with a higher probability of having MCI, and DII partially mediates the impact of dietary patterns on MCI.

Benefits of Music Therapy in the Cognitive Impairments of Alzheimer's-Type Dementia: A Systematic Review.

Background/Objective: Alzheimer's disease is a condition that can cause memory, thinking, and behaviour impairments. This type of dementia affects approximately 50 million people globally. Currently, there is no remedy for this disease, but there are different treatment approaches, both pharmacological and non-pharmacological, that try to alleviate the symptoms. The remarkable fact about Alzheimer's response to music is that musical abilities can be preserved even though language could be lost. The objective of this systematic review is to assess the benefits of music therapy on cognitive impairments in older adults with Alzheimer's disease. Methods: This is a systematic review carried out following the PRISMA guidelines. The literature searches were conducted in the following databases: PubMed, SCOPUS, Cochrane Library, and Dialnet. The inclusion criteria established were as follows: randomised controlled studies and clinical trials published in English and Spanish from 2010 to 2024, patients diagnosed with dementia of the Alzheimer's type, aged 65 years or older, who had participated in music interventions and had cognitive changes. Results: Eleven studies were included in this review. They showed that music therapy interventions mainly improved memory, language, and orientation. The results of a methodological quality analysis showed that six of the articles had good methodological quality and four had excellent methodological quality. Conclusions: The results of this review suggest that treatment with music therapy improves cognitive impairments in patients with Alzheimer's disease. In addition, we can be sure that music creates a link between the patient and the specialist.

Statistical Analysis Plan for L-oxiracetam Outcomes in Clinical Assessment of Traumatic Brain Injury Effects Trial (LOCATE trial): A Randomized Controlled Clinical Trial

Background: The L-oxiracetam Outcomes in Clinical Assessment of Traumatic Brain Injury Effects (LOCATE) trial is a national, multicenter, randomized, parallel-group, phase III trial including 74 centers across 51 hospitals from 2019 to 2024. The objective is to evaluate the efficacy and safety of L-oxiracetam in improving memory and cognitive impairment in patients with acute traumatic brain injury (TBI). Methods: A total of 591 patients aged 18-75 years will be enrolled with mild acute TBI. The primary outcome is the change in scores on the Loewenstein Occupational Therapy Cognitive Assessment (LOTCA) at 90 days post-treatment compared to baseline. Secondary outcomes included change from baseline in LOTCA, Glasgow Coma Scale (GCS), Mini-Mental State Examination (MMSE), Montreal Cognitive Assessment (MoCA), Glasgow Outcome Scale-Extended (GOS-E), and Barthel Index of Activities of Daily Living (ADL-BI) assessed at the end of treatment, 30 days, 60 days, and/or 90 days. A sample size of 591 allows 80% power (a=0.05) for the efficacy test in the primary outcome of LOTCA assessed at 90 days. Results: A detailed statistical analysis plan was developed for the LOCATE trial following international guidelines. The plan determined the statistical models for the primary and secondary outcomes and defined the covariates to be controlled and the content of the exploratory analyses. Conclusion: The application of this statistical analysis plan in the upcoming LOCATE trial will support an unbiased analysis of these important clinical data.

AUDITORY AND VERBAL MEMORY DISORDER IN YOUNG SCHOOLCHILDREN WITH CONGENITAL HEART DEFECTS

Highlights The presented literature review points to new questions associated with cognitive impairment in patients with congenital heart defects. We propose that cognitive and behavioral impairments in patients with CHD are common, but their development trajectory and degree of severity depend on the CHD subtype. Aim. To study the features of auditory and verbal memory in young schoolchildren who underwent cardiac surgery.Methods. The study included 104 children from 7 to 10 years old, who underwent on-pump cardiac surgery for congenital heart defects at the Research Institute for Complex Issues of Cardiovascular Diseases in the period from 2019 to 2022. We analyzed anamnesis data, clinical and hemodynamic picture, the risk of mortality from surgery according to the RACHS scale, and assessed the auditory and verbal memory according using methodical manual by T.A. Fotekova and T.V. Akhutina (block 1 series 3, block 2 series 1) during 1-year follow up.Results. All children had presented with stage I chronic heart failure (functional class II) at the time of hospitalization. The outcome of surgery was mostly positive a year after the surgery: children had no heart failure symptoms or hemodynamic disorders, however, 80% of children had auditory and verbal memory impairments.Conclusion. In addition to standard methods of examining children with congenital heart disease, it is necessary to introduce a comprehensive interdisciplinary approach that would include the assessment of neurocognitive status before and after surgery.

Clinical features of cognitive dysfunction in patients with relapsing-remitting type of multiple sclerosis

Background. Cognitive dysfunction in patients with multiple sclerosis is quite common, but attention is not always paid to it, since the decline of cognitive functions is often masked by motor, sensory, and visual disorders. Active patient questioning and neurocognitive screening are needed to identify cognitive impairment in patients with multiple sclerosis, even in the early stages of the disease. The goal of the study is to determine the frequency, severity, and clinical features of cognitive impairment in patients with relapsing-remitting multiple sclerosis, taking into account the duration of the disease and the level of disability of the patients. Materials and Methods. 67 patients with a diagnosis of relapsing-remitting multiple sclerosis were examined. All examined patients underwent a thorough neurological, psychometric, and instrumental examination. Patients were divided into 3 groups depending on the duration of the disease: 1st group up to 5 years (24 patients), 2nd group – from 5 to 10 years (22 patients), 3rd group more than 10 years (21 patients). The Symbol Digit Modalities Test (SDMT) and the Montreal Cognitive Function Assessment Scale (MoCA) were used to assess patients’ neuropsychological status. Results. The conducted correlation analysis showed the presence of a probable inverse relationship between the score on the EDSS scale and the scores on the SDMT and MoSA scales (r = –0.61 (p0.05); r = –0.12 (p&gt;0.05) for scores on SDMT and MoCA scales, respectively). We also obtained a probable directly proportional correlation between the test scores on the MoСA scale and SDMT (in 1st group = 0.63, p&lt;0.05, in 2nd group = 0.89, p&lt;0.05, in the 3rd group r = 0.64, p&lt;0.05) in all studied groups, i.e. for all periods of the disease duration. Conclusions. The obtained data of the correlation analysis indicate a relationship between the severity of cognitive impairment according to the test scores, the degree of disability of the patients, and the duration of the disease.

Differences of individual gray matter networks between MCI patients who converted to AD within 3 Years and nonconverters

ObjectiveHere we aimed to explore the differences in individual gray matter (GM) networks at baseline in mild cognitive impairment patients who converted to Alzheimer's disease (AD) within 3 years (MCI-C) and nonconverters (MCI-NC). Materials and methodsData from 461 MCI patients (180 MCI-C and 281 MCI-NC) were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI). For each subject, a GM network was constructed using 3D-T1 imaging and the Kullback–Leibler divergence method. Gradient and topological analyses of individual GM networks were performed, and partial correlations were calculated to evaluate relationships among network properties, cognitive function, and apolipoprotein E (APOE) €4 alleles. Subsequently, a support vector machine (SVM) model was constructed to discriminate the MCI-C and MCI-NC patients at baseline. ResultsThe gradient analysis revealed that the principal gradient score distribution was more compressed in the MCI-C group than in the MCI-NC group, with scores for the left lingual gyrus, right fusiform gyrus and left middle temporal gyrus being increased in the MCI-C group (p < 0.05, FDR corrected). The topological analysis showed significant differences in nodal efficiency in four nodes between the two groups. Furthermore, the regional gradient scores or nodal efficiency were found to be significantly related to the neuropsychological test scores, and the left middle temporal gyrus gradient scores were positively associated with the number of APOE €4 alleles (r = 0.192, p = 0.002). Ultimately, the SVM model achieved a balanced accuracy of 79.4% in classifying MCI-C and MCI-NC patients (p < 0.001). ConclusionThe whole-brain GM network hierarchy in the MCI-C group was more compressed than that in the MCI-NC group, suggesting more serious cognitive impairments in the MCI-C group. The left middle temporal gyrus gradient scores were related to both cognitive function and APOE €4 alleles, thus serving as potential biomarkers distinguishing MCI-C from MCI-NC at baseline.

Revealing the heterogeneity of plasma protein and cognitive decline trajectory among Mild Cognitive Impairment patients by clustering of brain atrophy features

Alzheimer's disease (AD) is suggested to be a heterogeneous disorder, but limited studies explore the heterogeneity of the Mild Cognitive Impairment (MCI) stage. This study aimed to tackle such problems using the CIMLR (Cancer Integration via Multikernel Learning) algorithm to cluster brain structural features extracted from T1-weighted Magnetic Resonance Images of MCI patients from Alzheimer's Disease Neuroimaging Initiative. The demographic and cognitive results, characteristics of brain structural features, plasma biomarkers, and longitudinal cognitive trajectory were analyzed for each cluster. The CIMLR clustering analysis revealed four distinct clusters. Cluster 1 is the oldest group but has had mild atrophy and moderate progression with elevated Tumor Necrosis Factor Receptor 2 level; and low Brain-Derived Neurotrophic Factor and CD40 Ligand levels. Cluster 2 showed the highest risk for aggressive MCI progression, with abnormal Leptin, Adiponectin, and Creatine kinase-MB values. Cluster 3 exhibited a low level of Monokine Induced by Gamma Interferon and mild atrophy that shared similar patterns with Cluster 1. Cluster 4 represented the healthiest group during longitudinal tracking, with the mildest Parahippocampal atrophy, which was found to be positively correlated with cognitive impairment and amino acid levels. The longitudinal analyses showed the potential of Hepatocyte Growth Factor as a marker for slow cognitive impairment; Cortisol and Neurofilament Light Polypeptide as prognosis markers for aggressive MCI progression. These findings may lay out new suggestions for further research contributing to the accurate diagnosis and precision medicine for dementia and AD.

A comprehensive review for artificial intelligence on neuroimaging in rehabilitation of ischemic stroke.

Stroke is the second leading cause of death worldwide, with ischemic stroke accounting for a significant proportion of morbidity and mortality among stroke patients. Ischemic stroke often causes disability and cognitive impairment in patients, which seriously affects the quality of life of patients. Therefore, how to predict the recovery of patients can provide support for clinical intervention in advance and improve the enthusiasm of patients for rehabilitation treatment. With the popularization of imaging technology, the diagnosis and treatment of ischemic stroke patients are often accompanied by a large number of imaging data. Through machine learning and Deep Learning, information from imaging data can be used more effectively. In this review, we discuss recent advances in neuroimaging, machine learning, and Deep Learning in the rehabilitation of ischemic stroke.

Risk factors and characteristics analysis of cognitive impairment in patients with cerebral infarction during recovery period

Objective To analyze the risk factors and characteristics of cognitive impairment in patients with cerebral infarction during the recovery period. Methods This retrospective case-control study included 183 patients with cerebral infarction in the recovery period. According to the MMSE score, they were divided into a cognitive impairment group of 79 cases and a cognitive normal group of 104 cases. Collect clinical data from all patients, including age, gender, body mass index, laboratory test results, past medical history, National Institute of Health Stroke Scale (NIHSS) score, modified Barthel index, Oxfordshire Community Stroke Project (OCSP) classification, and number of infarcted lesions. Multiple logistic regression analysis was used to identify risk factors related to cognitive impairment in patients with cerebral infarction. Result There were significant differences (p < 0.05) between the cognitive impairment group and the cognitive normal group in terms of age, body mass index, low-density lipoprotein level, NIHSS score, modified Barthel index, and number of infarcted lesions. Multivariate logistic regression analysis showed that age ≥ 65 years, stroke, carotid artery plaques, NIHSS score ≥ 5, anterior circulation infarction type, and multiple infarcted lesions were important risk factors for cognitive impairment. Conclusion Elderly age, presence of carotid artery plaques, high NIHSS score, multiple infarct lesions, and specific infarct types are important risk factors for cognitive dysfunction in patients during the recovery period of cerebral infarction.

Prediction model for mild cognitive impairment in patients with type 2 diabetes using the autonomic function test.

Type 2 diabetes mellitus (T2DM) is a risk factor for cognitive impairment, and reduced heart rate variability (HRV) has been correlated with cognitive impairment in elderly individuals. This study investigated risk factors and validated a predictive model for mild cognitive impairment (MCI) in patients with T2DM using an autonomic function test. Patients with T2DM, 50-85years of age, who attended the diabetes clinic at Gyeongsang National University Hospital between March 2018 and December 2019, were included. A total of 201 patients had been screened; we enrolled 124 patients according to the inclusion and exclusion criteria in this study. Cognitive function was assessed using the Montreal Cognitive Assessment-Korean version (MOCA-K); MCI was defined as a total MOCA-K score ≤ 23. Risk factors for MCI in patients with T2DM, including demographic- and diabetes-related factors, and autonomic function test results, were analyzed. Based on multivariate logistic regression, a nomogram was developed as a prediction model for MCI. Thirty-nine of 124 patients were diagnosed with MCI. Age, education, and decreased cardiovagal function were associated with a high risk for MCI, with cardiovagal function exerting the greatest influence. However, diabetes-related factors, such as glycemic control, duration of diabetes, or medications, were not associated with the risk for MCI. The nomogram demonstrated excellent discrimination (area under the curve, 0.832) and was well calibrated. Approximately one-third of patients had MCI; as such, carefully evaluating cognitive function in elderly T2DM patients with reduced HRV is important to prevent progression to dementia.

Cancer-related cognitive impairment and wellbeing in patients with newly diagnosed aggressive lymphoma compared to population norms and healthy controls: an exploratory study

PurposeThere has been little dedicated research on cancer-related cognitive impairment in patients with aggressive lymphoma. We describe and compare patients’ cognitive function with that of healthy controls and patients’ wellbeing and distress with general population values. We also explore associations between patients’ neuropsychological test performance and self-reported cognitive function and distress.MethodsSecondary analysis of data from a feasibility study of 30 patients with newly diagnosed aggressive lymphoma and 72 healthy controls. Patients completed neuropsychological tests and self-report measures before and 6–8 weeks after chemotherapy. Healthy controls completed neuropsychological tests and the FACT-Cog at enrolment and 6 months later. Mixed models were used to analyze neuropsychological test and FACT-Cog scores. One-sample t-tests were used to compare patients’ self-reported wellbeing and distress with population norms. Associations were explored with Kendall’s Tau b.ResultsPatients and healthy controls were well matched on socio-demographics. Differences between neuropsychological test scores were mostly large-sized; on average, patients’ scores on measures of information processing speed, executive function, and learning and memory were worse both before and after chemotherapy (all p ≤ 0.003). The same pattern was observed for impact of perceived cognitive impairment on quality-of-life (both p < 0.001). Patients’ physical and emotional wellbeing scores were lower than population norms both before and after chemotherapy (all p ≤ 0.018). Associations between neuropsychological performance and other measures were mostly trivial (all p > 0.10).ConclusionFor many patients with aggressive lymphoma, impaired neuropsychological test performance and impact of perceived impairments on quality-of-life precede chemotherapy and are sustained after chemotherapy. Findings support the need for large-scale longitudinal studies with this population to better understand targets for interventions to address cognitive impairments.

Construction and validation of a risk-prediction model for chemotherapy-related cognitive impairment in patients with breast cancer.

To identify risk factors of chemotherapy-related cognitive impairment (CRCI) and construct and validate a visual prediction model of such for patients with breast cancer. A multicenter, descriptive, and cross-sectional design was adopted. Data were collected from ten public tertiary hospitals in China. Cognitive function was assessed by using Functional Assessment of Cancer Therapy-cognitive function. Socio-demographic, clinical, psychological, and physical indicators were also assessed. The logistic prediction model was constructed by fivefold cross-validation. Then, a nomogram was utilized to visualize the prediction model, which was also evaluated via discrimination, calibration, and decision curve analysis. A total of 71 breast cancer patients had CRCI with a prevalence of 9.58%. This visual prediction model was constructed based on education background, exercise frequency, chemotherapy times, and fatigue and demonstrated good discrimination, with an area under the receiver operating characteristic curve of 0.882. The calibration curve indicated good agreement between experimental and projected values, and the decision curve proved good clinical applicability. Education background, exercise frequency, chemotherapy times, and fatigue were associated with high incidence of CRCI. The prediction model exhibits superior performance and has promise as a useful instrument for assessing the likelihood of CRCI in breast cancer patients. Our findings could provide breast cancer survivors with risk screening based on CRCI predictors to implement prevention and early intervention, and help patients integrate into society and achieve comprehensive recovery.

Co-ultraPEALut in Subjective Cognitive Impairment Following SARS-CoV-2 Infection: An Exploratory Retrospective Study.

Neurological involvement following coronavirus disease 19 (COVID-19) is thought to have a neuroinflammatory etiology. Co-ultraPEALut (an anti-inflammatory molecule) and luteolin (an anti-oxidant) have shown promising results as neuroinflammation antagonists. The aim of this study was to describe cognitive impairment in patients with post-COVID-19 treated with co-ultraPEALut. The Montreal Cognitive Assessment (MoCA), the Prospective-Retrospective Memory Questionnaire (PRMQ), the Fatigue Severity Scale (FSS), and a subjective assessment were administered at baseline and after 10 months. Patients treated with co-ultraPEALut were retrospectively compared with controls. Twenty-six patients treated with co-ultraPEALut showed a significant improvement in PRMQ (T0: 51.94 ± 10.55, T1: 39.67 ± 13.02, p < 0.00001) and MoCA raw score (T0: 25.76 ± 2.3, T1: 27.2 ± 2, p 0.0260); the MoCA-adjusted score and the FSS questionnaires also showed an improvement, even though it was not statistically significant; and 80.77% of patients reported a subjective improvement. In the control subjects (n = 15), the improvement was not as pronounced (PRMQ T0: 45.77 ± 13.47, T1: 42.33 ± 16.86, p 0.2051; FSS T0: 4.95 ± 1.57, T1: 4.06 ± 1.47, p 0.1352). Patients treated with co-ultraPEALut and corticosteroids were not statistically different from those treated with co-ultraPEALut alone. Neuro-post-COVID-19 patients treated with co-ultraPEALut scored better than controls in MoCA and PRMQ questionnaires after 10 months: this may support the importance of neuroinflammation modulation for neuro-long-COVID-19.

Retracted: A Predictive Model for the Risk of Cognitive Impairment in Patients with Gallstones.

[This retracts the article DOI: 10.1155/2021/3792407.].

Altered Dynamics of Brain Spontaneous Activity and Functional Networks Associated With Cognitive Impairment in Patients With Type 2 Diabetes.

Cognitive impairment is increasingly recognized as an important comorbidity and complication of type 2 diabetes (T2D), affecting patients' quality of life and diabetes management. Dynamic brain activity indicators can reflect changes in key neural activity patterns of cognition and behavior. To investigate dynamic functional connectivity (DFC) changes and spontaneous brain activity based on resting-state functional magnetic resonance imaging (rs-fMRI) in patients with T2D, exploring their correlations with clinical features. Retrospective. Forty-five healthy controls (HCs) (22 males and 23 females) and 102 patients with T2D (57 males and 45 females). 3.0 T/T1-weighted imaging and rs-fMRI with gradient-echo planar imaging sequence. Functional networks were created using independent component analysis. DFC states were determined using sliding window approach and k-means clustering. Spontaneous brain activity was assessed using dynamic regional homogeneity (dReHo) variability. One-way analysis of variance and post hoc analysis were used to compare the essential information including demographics, clinical data, and features of DFC and dReHo among groups. Diagnostic performance was assessed using receiver operating characteristic (ROC) curve. P-values <0.05 were taken to indicate statistical significance. T2D group had significantly decreased mean dwell time and fractional windows in state 4 compared to HC. T2D with mild cognitive impairment showed significantly increased dReHo variability in left superior occipital gyrus compared to T2D with normal cognition. Mean dwell time and number of fractional windows of state 4 both showed significant positive correlations with the Montreal cognitive assessment scores (r = 0.309; r = 0.308, respectively) and the coefficient of variation of dReHo was significantly positively correlated with high-density lipoprotein cholesterol (r = 0.266). The integrated index had an area under the curve of 0.693 (95% confidence interval = 0.592-0.794). Differences in DFC and dynamic characteristic of spontaneous brain activity associated with T2D-related functional impairment may serve as indicators for predicting symptom progression and assessing cognitive dysfunction. 2 TECHNICAL EFFICACY: Stage 2.

Caregivers' Role in In-Home Video Telehealth: National Survey of Occupational Therapy Practitioners.

Older adults face barriers to specialty care, such as occupational therapy (OT), and these challenges are worse for rural older adults. While in-home video telehealth may increase access to OT, older adults' health- and technology-related challenges may necessitate caregiver assistance. This study examines caregiver assistance with in-home OT video telehealth visits from the perspectives of OT practitioners at Veterans Health Administration (VHA). A web-based national survey of VHA OT practitioners about caregivers' role in video telehealth was conducted between January and February 2022. Survey items were developed with input from subject matter experts in geriatrics and OT and identified patient factors that necessitate caregiver participation; the extent to which caregivers assist with different types of tasks (technological and clinical tasks); and the perceived facilitators of, benefits of, and barriers to caregiver involvement. Of approximately 1787 eligible VHA OT practitioners, 286 (16% response rate) participated. Not all survey items required completion, resulting in different denominators. Most respondents were female (183/226, 81%), White (163/225, 72.4%), and occupational therapists (275/286, 96.2%). Respondents were from 87 VHA medical centers, the catchment areas of which served a patient population that was 34% rural, on average (SD 0.22). Most participants (162/232, 69.8%) had >10 years of OT experience serving a patient cohort mostly aged ≥65 years (189/232, 81.5%) in primarily outpatient rehabilitation (132/232, 56.9%). The top patient factors necessitating caregiver involvement were lack of technical skills, cognitive impairment, and advanced patient age, with health-related impairments (eg, hearing or vision loss) less frequent. Technological tasks that caregivers most frequently assisted with were holding, angling, moving, repositioning, or operating the camera (136/250, 54.4%) and enabling and operating the microphone and setting the volume (126/248, 50.8%). Clinical tasks that caregivers most frequently assisted with were providing patient history (143/239, 59.8%) and assisting with patient communication (124/240, 51.7%). The top facilitator of caregiver participation was clinician-delivered caregiver education about what to expect from video telehealth (152/275, 55.3%), whereas the top barrier was poor connectivity (80/235, 34%). Increased access to video telehealth (212/235, 90.2%) was the top-rated benefit of caregiver participation. Most respondents (164/232, 70.7%) indicated that caregivers were at least sometimes unavailable or unable to assist with video telehealth, in which case the appointment often shifted to phone. Caregivers routinely assist VHA patients with in-home OT video visits, which is invaluable to patients who are older and have complex medical needs. Barriers to caregiver involvement include caregivers' challenges with video telehealth or inability to assist, or lack of available caregivers. By elucidating the caregiver support role in video visits, this study provides clinicians with strategies to effectively partner with caregivers to enhance older patients' access to video visits.

Correlation between frailty and reduction in cortical thickness in patients with chronic obstructive pulmonary disease

Physical inactivity and cognitive impairment in patients with chronic obstructive pulmonary disease (COPD) can lead to frailty and poor prognoses. However, little is known regarding the association between frailty and the human brain. We hypothesized that the brain structure could change according to frailty in patients with COPD and focused on cortical thickness. Cortical thickness measured by magnetic resonance imaging and frailty scores using the Kihon Checklist (KCL) were assessed in 40 patients with stable COPD and 20 healthy controls. Among the 34 regions assessed, multiple regions were thinner in patients with COPD than in healthy individuals (p < 0.05). We found significant negative correlations between the eight regions and the KCL scores only in patients with COPD. After adjusting for age and cognitive impairment, the association between the left and six right regions remained statistically significant. The correlation coefficient was the strongest in the bilateral superior frontal gyrus (left: ρ = − 0.5319, p = 0.0006) (right: ρ = − 0.5361, p = 0.0005). Interestingly, among the KCL scores, the daily activity domain showed the strongest correlation (sensitivity, 90%; specificity, 73%) with the bottom quartile of the reduction in the superior frontal gyrus. Frailty in patients with COPD is associated with a thickness reduction in the cortical regions, reflecting social vulnerability.