Search

Abstract Transcutaneous auricular vagus nerve stimulation (taVNS) has been investigated as a novel neuromodulation tool. Although taVNS is generally considered safe with only mild and transient adverse effects (AEs), those specifically caused by taVNS have not yet been investigated. This systematic review and meta-analysis on taVNS aimed to (1) systematically analyze study characteristics and AE assessment, (2) characterize and analyze possible AEs and their incidence, (3) search for predictable risk factors, (4) analyze the severity of AE, and (5) suggest an evidence-based taVNS adverse events questionnaire for safety monitoring. The articles searched were published through April 7, 2022, in Medline, Embase, Web of Science, Cochrane, and Lilacs databases. In general, we evaluated 177 studies that assessed 6322 subjects. From these, 55.37% of studies did not mention the presence or absence of any AEs; only 24.86% of the studies described that at least one adverse event occurred. In the 35 studies reporting the number of subjects with at least one adverse event, a meta-analytic approach to calculate the risk differences of developing an adverse event between active taVNS and controls was used. The meta-analytic overall adverse events incidence rate was calculated for the total number of adverse events reported on a 100,000 person-minutes-days scale. There were no differences in risk of developing an adverse event between active taVNS and controls. The incidence of AE, in general, was 12.84/100,000 person-minutes-days of stimulation, and the most frequently reported were ear pain, headache, and tingling. Almost half of the studies did not report the presence or absence of any AEs. We attribute this to the absence of AE in those studies. There was no causal relationship between taVNS and severe adverse events. This is the first systematic review and meta-analysis of transcutaneous auricular stimulation safety. Overall, taVNS is a safe and feasible option for clinical intervention.

Abstract In acute ischemic stroke (AIS), the hemodynamics around the lesion are important because they determine the recurrence or prognosis of the disease. This study evaluated the effects of perfusion deficits in multiphase arterial spin labeling (ASL) and related radiological parameters on the occurrence of early recurrent ischemic lesions (ERILs) in AIS. We assessed AIS patients who underwent multiphase ASL within 24 h of symptom onset and follow-up diffusion-weighted imaging within 7 days. ASL perfusion deficit, arterial transit artifact (ATA), and intra-arterial high-intensity signal (IAS) were manually rated as ASL parameters. A total of 134 patients were evaluated. In the multivariable analyses, ASL perfusion deficit [adjusted odds ratio (aOR) = 2.82, 95% confidence interval = 1.27–6.27] was positively associated with ERIL. Furthermore, when ATA was accompanied, the ASL perfusion deficit was not associated with ERIL occurrence. Meanwhile, IAS showed a synergistic effect with ASL perfusion deficit on the occurrence of ERIL. In conclusion, we demonstrated the association between perfusion deficits in multiphase ASL with ERIL in patients with AIS. This close association was attenuated by ATA and was enhanced by IAS. ASL parameters may help identify high-risk patients of ERIL occurrence during the acute period.

Abstract To assess the safety and efficacy of navigation-guided balloon Eustachian tuboplasty (BET) compared to medical management (MM) alone in patients with chronic Eustachian tube dilatory dysfunction (ETD). This is a prospective, multicenter, 1:1 parallel-group, randomized controlled trial (RCT). It aims to assess the efficacy of navigation-guided BET compared to MM alone in patients with chronic ETD. The primary outcome measure was an improvement in the Eustachian tube dysfunction questionnaire (ETDQ)-7 score at the 6-week follow-up compared with baseline. Secondary outcome measures included changes in the signs and symptoms during the follow-up, changes in the score for each subcategory of ETDQ-7, type of tympanometry, pure tone audiometry, and the availability of a positive modified Valsalva maneuver. Navigation-guided BET was safely performed in all patients. A total of 38 ears of 31 patients (19 ears of 16 patients in the BET group and 19 ears of 15 patients in the control group) completed the planned treatment and 6 weeks of follow-up. More patients in the BET group (1.99 ± 0.85) had less symptomatic dysfunction than in the control group (3.40 ± 1.29) at 6 weeks post-procedure (P = 0.001). More patients experienced tympanogram improvement in the BET group at 6 weeks compared to the control group (36.5% vs. 15.8%) with a positive modified Valsalva maneuver (36.6% vs. 15.8%, P = 0.014). Additionally, air–bone gap change was significantly decreased in the BET group compared to the control group at the 6-week follow-up visit (P = 0.037). This prospective, multicenter, RCT study suggests that navigation-guided BET is a safe and superior treatment option compared to MM alone in patients with chronic ETD.

Abstract We aimed to develop a novel prediction model for early neurological deterioration (END) based on an interpretable machine learning (ML) algorithm for atrial fibrillation (AF)-related stroke and to evaluate the prediction accuracy and feature importance of ML models. Data from multicenter prospective stroke registries in South Korea were collected. After stepwise data preprocessing, we utilized logistic regression, support vector machine, extreme gradient boosting, light gradient boosting machine (LightGBM), and multilayer perceptron models. We used the Shapley additive explanation (SHAP) method to evaluate feature importance. Of the 3,213 stroke patients, the 2,363 who had arrived at the hospital within 24 h of symptom onset and had available information regarding END were included. Of these, 318 (13.5%) had END. The LightGBM model showed the highest area under the receiver operating characteristic curve (0.772; 95% confidence interval, 0.715–0.829). The feature importance analysis revealed that fasting glucose level and the National Institute of Health Stroke Scale score were the most influential factors. Among ML algorithms, the LightGBM model was particularly useful for predicting END, as it revealed new and diverse predictors. Additionally, the effects of the features on the predictive power of the model were individualized using the SHAP method.

Abstract Insulin resistance is associated with the occurrence of stroke and atherosclerotic disease. However, the relationship between insulin resistance and the prognosis of acute ischemic stroke in non-diabetic patients is unclear. We hypothesized that insulin resistance might affect short-term functional recovery after acute ischemic stroke in non-diabetic patients. Between May 2014 and December 2016, 1377 consecutive patients with acute ischemic stroke were enrolled from a prospectively maintained stroke registry. After excluding patients with transient ischemic attacks (TIA), pre-stroke disabilities, diabetes mellitus, and patients with incomplete evaluations, 517 patients were included in the study. The homeostasis model assessment of insulin resistance (HOMA-IR) score was used to evaluate the degree of insulin resistance. The patients with the highest quartile of log HOMA-IR index scores were younger and had higher fasting blood glucose, total cholesterol, triglycerides, low-density lipoprotein, and HbA1c levels. Multivariable logistic regression analysis revealed that log HOMA-IR scores were independently associated with poor prognosis after adjusting for age and sex and p