(1) Background: The role of uric acid in stroke outcomes remains inconclusive. (2) Methods: We retrospectively enrolled 3370 patients with acute ischemic stroke. (3) Results: Uric acid level was higher in men than in women. Univariate analyses revealed that the rates of hyperuricemia were higher in all patients and in women for unfavorable outcomes. For death, the hyperuricemia rates were higher in all patients including men and women, and the uric acid levels were also higher in all patients and in women. A J-shaped curve was observed between uric acid and the discharge-modified Rankin Scale score. Patients within Quartiles 1 (6.5 mg/dL) of uric acid had higher rates of unfavorable outcomes and death than patients within Quartiles 2 (4.1–5.1 mg/dL) and 3 (5.1–6.2 mg/dL). Multivariable analyses for unfavorable outcomes revealed that Quartile 1 of uric acid was a significant factor in all patients and in men. In men, a significant factor for death was being in Quartile 1 of uric acid. In women, higher levels of uric acid or hyperuricemia (>6.6 mg/dL) were significant factors for death. (4) Conclusions: Lower uric acid levels are a predictor for unfavorable outcomes and death in men, and higher uric acid levels are a predictor for death in women.

Carotid atherosclerosis is associated with cardiovascular and cerebrovascular events. We explored an appropriate method for selecting participants without ischemic cerebrovascular disease but with various comorbidities eligible for a carotid ultrasound. This was a retrospective subgroup analysis of the carotid plaque burden from a previous study involving a vascular and cognitive survey of 956 elderly recycling volunteers (778 women and 178 men; mean age: 70.8 years). We used carotid ultrasound to detect the carotid plaque and computed the carotid plaque score (CPS). A moderate or high degree of carotid atherosclerosis (MHCA) was defined as CPS > 5 and was observed in 22% of the participants. The CPS had positive linear correlations with age, systolic blood pressure, and fasting glucose. We stratified the participants into four age groups: 60–69, 70–74, 75–79, and ≥80 years. Multivariable analysis revealed that significant predictors for MHCA were age, male sex, hypertension, diabetes mellitus, hyperlipidemia, coronary artery disease, and a nonvegetarian diet. Coronary artery disease and advanced age were the two strongest predictors. We chose the aforementioned seven significant predictors to establish a nomogram for MHCA prediction. The area under the receiver operating characteristic curve in internal validation with 10-fold cross-validation and the classification accuracy of the nomogram were 0.785 and 0.797, respectively. We presumed people who have a ≥50% probability of MHCA warranted a carotid ultrasound. A flowchart table derived from the nomogram addressing the probabilities of all models of combinations of comorbidities was established to identify participants who had a probability of MHCA ≥ 50% (corresponding to a total nomogram score of ≥15 points). We further established a carotid risk score range from 0 to 17 comprising the seven predictors. A carotid risk score ≥ 7 was the most optimal cutoff value associated with a probability of MHCA ≥ 50%. Both total nomogram score ≥ 15 points and carotid risk score ≥ 7 can help in the rapid identification of individuals without stroke but who have a ≥50% probability of MHCA—these individuals should schedule a carotid ultrasound.

We investigated the seasonal variations in stroke in 4040 retrospectively enrolled patients with acute ischemic stroke (AIS) admitted between January 2011 and December 2022, particularly those with cardioembolic (CE) stroke, and compared predictors of unfavorable outcomes between AIS patients and CE stroke patients. The classification of stroke subtypes was based on the Trial of ORG 10172 in Acute Stroke Treatment. Stroke occurrence was stratified by seasons and weekdays or holidays. Of all AIS cases, 18% were of CE stroke. Of all five ischemic stroke subtypes, CE stroke patients were the oldest; received the most thrombolysis and thrombectomy; had the highest initial National Institutes of Stroke Scale (NIHSS) and discharge modified Rankin Scale (mRS) scores; and had the highest rate of in-hospital complications, unfavorable outcomes (mRS > 2), and mortality. The highest CE stroke prevalence was noted in patients aged ≥ 85 years (30.9%); moreover, CE stroke prevalence increased from 14.9% in summer to 23.0% in winter. The main predictors of death in patients with CE stroke were age > 86 years, heart rate > 79 beats/min, initial NIHSS score > 16, neutrophil-to-lymphocyte ratio (NLR) > 6.4, glucose > 159 mg/dL, cancer history, in-hospital complications, and neurological deterioration (ND). The three most dominant factors influencing death, noted in not only patients with AIS but also those with CE stroke, are high initial NIHSS score, ND, and high NLR. We selected the most significant factors to establish nomograms for predicting fatal outcomes. Effective heart rhythm monitoring, particularly in older patients and during winter, may help develop stroke prevention strategies and facilitate early AF detection.

Seizures should be diagnosed and treated to ensure optimal health outcomes in critically ill patients admitted in the medical intensive care unit (MICU). Continuous electroencephalography is still infrequently used in the MICU. We investigated the effectiveness of routine EEG (rEEG) in detecting seizures in the MICU. A total of 560 patients admitted to the MICU between October 2018 and March 2023 and who underwent rEEG were reviewed. Seizure-related rEEG constituted 47% of all rEEG studies. Totally, 39% of the patients experienced clinical seizures during hospitalization; among them, 48% experienced the seizure, and 13% experienced their first seizure after undergoing an rEEG study. Seventy-seven percent of the patients had unfavorable short-term outcomes. Patients with cardiovascular diseases were the most likely to have the suppression/burst suppression (SBS) EEG pattern and the highest mortality rate. The rhythmic and periodic patterns (RPPs) and electrographic seizure (ESz) EEG pattern were associated with seizures within 24 h after rEEG, which was also related to unfavorable outcomes. Significant predictors of death were age > 59 years, the male gender, the presence of cardiovascular disease, a Glasgow Coma Scale score ≤ 5, and the SBS EEG pattern, with a predictive performance of 0.737 for death. rEEG can help identify patients at higher risk of seizures. We recommend repeated rEEG in patients with ESz or RPP EEG patterns to enable a more effective monitoring of seizure activities.

Background: We investigated the clinical signs to establish a method for rapid identification of patients with the National Institute of Health Stroke Scale (NIHSS) score ≥ 8 eligible for direct brain CTA study; Methods: We retrospectively enrolled 2895 in patients with acute ischemic stroke (AIS). Four items in the NIHSS were selected as the main clinical signs of stroke; Results: A total of 922 (31.8%) patients had an initial NIHSS score of ≥8. The average door-to-CT time and door-to-CTA time were 13.4 ± 1.8 and 75.5 ± 44.5 min, respectively. Among 658 patients who had the priority signs, namely dense hemiplegia (D), aphasia with right arm drop (AR), and eyeball forced deviation (E), 634 patients (96.4%) with an NIHSS score ≥ 8 were identified. By using a classification and regression tree analysis, 153 patients with an NIHSS ≥ 8 were identified among 175 patients (87.4%) who had the secondary signs, namely hemiparesis with limb falls (P), aphasia (A), drowsy or worse consciousness (C), and eyeball limitation (E). The sensitivity, specificity, and accuracy were 85.4%, 97.7%, and 95.3%, respectively. Conclusions: The DARE-PACE assessment involving a checkbox list provides excellent accuracy for rapid identification of AIS patients with an NIHSS score ≥ 8 for direct CTA study to reduce the time delay for endovascular thrombectomy.

This study evaluated the utility of the 2HELPS2B score in predicting seizures from routine electroencephalographs (rEEGs). In total, 670 rEEGs obtained in a medical intensive care unit (MICU) between October 2018 and March 2023 were analyzed. More than 75% of these rEEGs were requested due to seizures and unexplained altered consciousness. Seizures occurred most frequently in patients with rEEGs characterized by brief, potentially ictal rhythmic discharges and electrographic seizures. A history of seizures was the most prevalent risk factor identified by the 2HELPS2B score. Seizures occurred in 28% of the cohort who experienced a seizure within 24 h of the rEEG and in 38% of the cohort who experienced a seizure before MICU discharge. Among the patients with suspected altered consciousness, the seizure incidence before MICU discharge (9.2%) was twice that within 24 h of the initial rEEG (4.7%). The seizure rate also increased from 12% for a 2HELPS2B score of 1 to 100% for scores ≥ 4. A score ≥ 2 was the optimal cutoff for predicting post-rEEG seizures and guiding antiseizure medication (ASM) treatment. Seizures occurred most frequently in patients whose ASMs were supplemented with new medications, and most new prescriptions for antiseizure medication were issued to patients with altered consciousness. These results demonstrate that the 2HELPS2B score can effectively predict seizures on the basis of rEEG results.