Obstructive sleep apnea may be linked to postoperative cognitive decline. We conducted a prospective observational study to determine whether the severity of sleep apnea is associated with postoperative cognitive decline following non-cardiac surgery.
Adult patients undergoing elective non-cardiac surgery were enrolled in the study. A series of cognitive tests, including the verbal fluency test, digit symbol substitution test, and word list recall, were used to compare cognitive function before and after surgery. The Telephone Interview for Cognitive Status assessed long-term cognitive function at 30 and 90 days post-surgery.
In total, 65 patients were included in the analysis, with a mean age of 63.7 years (SD = 7.4). The overall incidence of postoperative cognitive decline within the first 2 days after surgery was 18.5%. Our study found that patients with moderate to severe obstructive sleep apnea did not have a higher risk of postoperative cognitive decline compared to those with no or mild obstructive sleep apnea (p = 0.339). However, a history of depression emerged as an independent risk factor for postoperative cognitive decline (p = 0.045). Furthermore, there was no significant difference in cognitive function between the obstructive sleep apnea groups at 30 and 90 days after surgery.
Our study indicates no clear association between the severity of obstructive sleep apnea and postoperative cognitive decline within 90 days after surgery. Instead, we identified preoperative depression as a significant risk factor for postoperative cognitive decline. Therefore, it is important to exercise caution when managing patients with depression.
Obstructive sleep apnea (OSA), common in geriatric patients, has been associated with neurocognitive memory disorders such as Alzheimer's disease and other related dementias. An unusual pattern of memory testing has been found to be associated with OSA in a retrospective study (Dexter and Ebert, 2019). This atypical pattern is reported when immediate memory performance is lower than delayed memory performance on the repeatable battery for the assessment of neurological status (RBANS). The current study examines this cognitive testing results pattern coupled with snoring for predicting OSA in geriatric memory patients presenting to a university-based memory clinic.
A convenience sample of patients presenting to the University of Wisconsin Hospitals and Clinics geriatric memory clinic from 2016-2020 for cognitive assessments comprised the study population. Patients completed the mini-mental state examination (MMSE) and obtained a score of 25 out of 30 points or greater and the patients were given the RBANS. Patients were referred for a sleep evaluation if they snored and their immediate memory index score was one or more points lower than their delayed memory index score on the RBANS. No other test score requirements were utilized to trigger the referral.
Of the 251 patients (138 men; 113 women) referred based only on these two criteria to the associated sleep clinic, 158 (80%) were found to have OSA.
The prevalence of positive sleep studies suggests that memory clinic patients who snore and present this unusual pattern of results on the RBANS should be referred for a sleep evaluation for possible OSA.
Hypertensive intracerebral hemorrhage (HICH) constitutes a highly lethal form of cerebrovascular disease. A frequent consequence of HICH is cognitive dysfunction, which significantly impacts patients' quality of life. Despite the burgeoning interest in integrated traditional Chinese and Western medicine (ITCWM) for the rehabilitation of cognitive deficits following HICH, the available evidence supporting its efficacy remains limited.
This study seeks to summarize the efficacy and safety of ITCWM in addressing cognitive dysfunction resulting from HICH using meta-analysis.
A literature search was conducted across the China National Knowledge Infrastructure, Wanfang, CQVIP, SinoMed, PubMed, Embase, Cochrane Library, and Web of Science databases. Studies were selected based on criteria. Quality assessment was evaluated through the Cochrane tool. Pooled results for continuous data were analyzed using the standardized mean difference (SMD) with a 95% confidence interval (CI). Binary categorical data were summarily analyzed using risk ratio (RR) and 95% CI.
A total of 13 RCTs involving 1123 patients were included. ITCWM significantly reduced NIHSS score (SMD = −2.36, 95% CI: −4.92, 0.19) and traditional Chinese medicine syndrome (TCMS) scores (SMD = −3.28, 95% CI: −4.02, −2.54), while improving activities of daily living (SMD = 3.67, 95% CI: 2.09, 5.26) and cognitive function scores (SMD = 1.27, 95% CI: 0.41, 2.14). The incidence of adverse events (RR = 0.26, 95% CI: 0.14, 0.46) was significantly lower in the ITCWM group. Subgroup analyses supported these findings, indicating that longer treatment durations (≥ 3 weeks) and multiple TCM therapies were associated with better outcomes.
ITCWM demonstrates both effectiveness and safety in the management of post-HICH cognitive dysfunction, improving neurological function, daily living abilities, and cognitive function while reducing adverse events.
Imaging diagnosis of mild cognitive impairment (MCI) has garnered increasing attention due to its critical role in the early detection of Alzheimer's disease (AD) and other dementias. This study presents a bibliometric analysis to elucidate global research trends, key contributors, thematic clusters, and emerging topics within the field of MCI imaging diagnosis.
English-language publications related to MCI imaging were retrieved from the Web of Science Core Collection (WoSCC) from January 1999 to December 2024. Bibliometric analyses were performed using VOSviewer, CiteSpace, and R-bibliometrix to evaluate co-authorship networks, institutional collaborations, journal impact, keyword co-occurrence, and burst trends.
A total of 7,568 articles showed an average annual growth of 22.27%, with output surging after 2007 and peaking in 2024 (n = 762). The United States led in productivity and impact, ahead of China and Italy. Leading institutions were the University of California System, Vrije Universiteit Amsterdam, and the University of London, with key authors including Clifford R. Jack Jr., Ronald C. Petersen, and Philip Scheltens. Core journals were Neurology, Neuroimage, and Brain. Cluster analysis revealed four themes: functional and cognitive networks, biomarkers and pathology, structural imaging and computational diagnostics, and guidelines. Recent trendsc (AI) (e.g., machine learning, deep learning), while citation bursts indicate an evolution from early biomarker and imaging research toward current AI and multimodal imaging for improved diagnosis and risk prediction.
This bibliometric analysis provides a comprehensive overview of the evolving research landscape in MCI imaging diagnosis. The integration of advanced computational methodologies, particularly AI-powered tools, is driving precision diagnostics and personalized medicine. These advancements hold significant potential to improve early detection, stratify risk, and inform therapeutic interventions, ultimately contributing to better outcomes for individuals with MCI.
Few studies have addressed the burden of neurological disorders in Greenland (GL). We aim to estimate nationwide incidences and prevalence of a broad group of neurological disorders in the total Greenlandic population and according to ethnicity (Inuit, Non-Inuit). To explore the importance of ethnic and environmental factors we estimated corresponding rates among Inuit and Non-Inuit living in Denmark (DK).
A long-standing collaboration between the Danish and Greenlandic healthcare system enabled us to follow the Greenlandic and Danish population for dementia, Parkinson's Disease (PD), epilepsy, stroke, and infections of the Central Nervous System using national registries from both countries. Incidence rates (IRs) were calculated using log linear Poisson-regression for the combined period 1987-2014, and stratified according to ethnicity, country of residence and periods. Age-standardized IRs (ASIRs) were based on the WHO 2000–2025 standard population.
The Greenlandic IRs of epilepsy and ischemic stroke were 98.6 (95% CI: 93.8–104) and 118 (95% CI: 113–124) respectively, per 100,000 person-years of risk. IRs for the remaining neurological disorders were below 40 per 100,000. During follow-up we observed an increase in IRs of ischemic stroke and a less pronounced for dementia. Apart from dementia, ASIRs of neurological disorders were generally higher in the Greenlandic population compared with the Danish, most pronounced for subarachnoid hemorrhage (ASIRGL/ASIRDK = 2.36 (2.12–2.62)). Inuit in Greenland were at a lower risk of stroke, PD and especially dementia (ASIRGL/ASIRDK = 0.40 (0.35–0.46)) compared with Inuit in Denmark. The most prevalent neurological disorders in Greenland in 2014 were stroke and epilepsy.
Our study emphasizes that stroke and epilepsy are important causes of morbidity in Greenland and suggests that dementia may become a challenge. Noticeable differences according to ethnicity and country of residence warrants further research.
Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is a type of autoimmune disorder manifesting in neurologic, cognitive, and psychological abnormalities, yet its neurological basis remains obscure. The purpose of our study was to assess the modification of functional brain networks in patients diagnosed with anti-NMDAR encephalitis, aiming to uncover the potential pathogenic mechanisms underlying these changes and thus provide insights for further therapeutic strategies.
The present study enrolled 34 healthy controls (HCs) and 35 patients suffering from anti-NMDAR encephalitis who were subject to functional magnetic resonance imaging (fMRI) and neuropsychological testing. Topological properties and functional connectivity (FC) were analyzed using graph theory to quantify network parameters, based on the brain functional network constructed from fMRI data.
Compared to HCs, patients had decreased functional connectivity between most brain regions and increased connectivity only in the parietal and left frontal lobes. In contrast to the control group, patients had an increase in local efficiency (t = 2.181, p = 0.032) and global efficiency (t = 2.253, p = 0.027), and a decrease in shortest path length (t = −2.310, p = 0.022). In terms of regional lymph nodes, both lymph node efficiency and degree got elevated in the default mode network (DMN), whereas the subcortical network (SCN) showed enhanced efficiency and reduced intermediacy of lymph nodes.
Our research examined the functional brain networks of anti-NMDAR encephalitis patients and gained an understanding of the abnormalities, which underlies further investigation into neuropathophysiological mechanisms.
The combination of transcranial magnetic stimulation (TMS) and electroencephalography (EEG) enables direct interaction with the brain while recording the resulting neural activity, offering a unique opportunity to understand the brain's functional dynamics. In this study, TMS–EEG was employed to examine the effects of TMS on functional network connectivity through graph theory parameters.
A total of 29 healthy controls underAuthor: Please check funding information and confirm its correctness.went a single-pulse TMS–EEG protocol targeting the dorsolateral prefrontal cortex. Three graph theory parameters summarizing functional network properties (i.e., connectivity strength, clustering coefficient, and characteristic path length) were analyzed before and after TMS application.
TMS-single pulse administration over the dorsolateral prefrontal cortex of healthy controls was associated with a significant increase in connectivity strength and clustering coefficient, and a significant decrease in the characteristic path length parameters. These changes are consistent with a shift towards a small-world network organization.
These findings provide insight into the neurophysiological mechanisms underlying TMS-induced changes and could have potential therapeutic implications.
There remains a lack of studies evaluating the risk of respiratory failure in intensive care unit (ICU)-admitted ischemic stroke (IS) patients. We aim to develop a nomogram for the prediction of respiratory failure in those patients and the identification of the patients with high risk of respiratory failure, to facilitate early intervention.
The medical data of IS patients in the Medical Information Mart for Intensive Care (MIMIC)-IV database were extracted. Variables were selected using Cox stepwise regression, and variables with statistical significance were finally included in the nomogram. The marginal structural Cox model (MSCM) was to adjust for baseline and time varying confounding factors. The calibration curve and Receiver operating characteristic curve (ROC) were applied to assess the performance of the model.
External validation using IS patient data from the eICU collaborative ersearch database (eICU-CRD). A total of 3462 eligible patients (2424 in the training set and 1038 in the validation set) were included. The following variables were finally included in the model: infarction location, atrial fibrillation, A alkaline phosphatase (ALP), anion gap (AG), lactic dehydrogenase (LDH), and Na2+ concentration. The direction of the hazard ratios (HR) of the variables in the model is consistent with the MSCM results. The area under the ROC curve (AUC-ROC) of respiratory failure occurring between 1 and 7 days after ICU admission was 0.839 and 0.760 in the training set, 0.839 and 0.769 in the validation set, and 0.687 and 0.733 in the eICU set, respectively. The calibration curve showed acceptable consistency, indicating the model was of satisfactory performance.
We have developed a nomogram model for the prediction of respiratory failure in IS patients admitted to the ICU, validated using external data. The model could perform effective prediction and thus provide more information for clinicians.
The visceral adiposity and inflammation index (VAII) is a composite index that combines the visceral adiposity index (VAI) and high-sensitivity C-reactive protein (hs-CRP), both of which are associated with stroke risk. This study aimed to investigate the association between VAII and stroke risk, with a particular focus on different blood pressure (BP) statuses, sexes, and age groups.
Data from 8883 participants in the China Health and Retirement Longitudinal Study were analyzed. VAII levels were categorized into quartiles, and stroke incidence was assessed. Restricted cubic spline analysis was used to assess the association between VAII and stroke risk on the basis of sex, age, and BP status. Sensitivity analyses, including complete-case analysis, multiple imputation, and calculation of the E-value, were conducted to assess the robustness of the findings.
During a median follow-up of 9 years, 827 participants (9.31%) developed stroke. In fully adjusted models, a 1-SD increase in VAII was associated with higher stroke risk (HR = 1.048, 95% CI: 1.009–1.089). Stroke incidence increases across VAII quartiles, with Q4 showing more than twice the risk of Q1 (HR = 2.138, 95% CI: 1.720–2.658). Associations were evident in elevated BP (Q4 vs. Q1: HR = 2.034) and hypertension groups (Q3: HR = 1.906; Q4: HR = 1.713), but not in normal BP. Stronger associations appeared in women and in adults aged 40–60 years. Restricted cubic splines indicated nonlinear relationships. Sensitivity analyses supported the robustness of these findings.
Our study revealed a significant nonlinear relationship between VAII and the risk of stroke. The association between VAII and stroke was nonlinear in individuals with elevated BP and hypertension. Additionally, a nonlinear relationship was observed between VAII and stroke risk in both males and females, as well as in middle-aged and older adults.
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