Background: The effectiveness of intravenous tissue plasminogen activator (IV tPA) in patients with large-vessel occlusion (LVO) receiving endovascular treatment (EVT) for acute ischemic stroke (AIS) has been questioned. We investigated IV tPA effectiveness in real-world AIS patients, including those with intracranial LVO receiving EVT. Methods: We identified patients with AIS who presented to hospital with National Institutes of Health Stroke Scale ≥4 within 8 hours of symptom onset from the institutional stroke registry. The association of IV tPA use with effectiveness and safety outcomes was analyzed in overall enrolled AIS patients; LVO patients; and patients treated with EVT. The effect of IV tPA was assessed using multiple logistic regression. Results: Among the 654 patients meeting study entry criteria, 238 (36.4%) received IV tPA and 416 (63.6%) did not. Multiple logistic regression analysis and shift analysis revealed IV tPA was associated with improved outcomes in overall enrolled AIS population, LVO, and EVT-treated subgroups. Among EVT-treated patients, IV tPA was associated with higher likelihood of ambulatory or better outcome (modified Rankin Scale 0–3) with odds ratio of 1.95 (P=0.03). Conclusions In this real-world study, IV tPA use was associated with improved outcomes for patients with AIS, including among LVO patients treated and not treated with EVT, in the contemporary mechanical thrombectomy era.

Stent-assisted coil embolization (SAC) is used for complex wide-necked aneurysms but can expose stent struts to the arterial lumen, leading to thrombosis. Herein, we report two cases of delayed thromboembolic stroke post-SAC. Case 1: A 71-year-old woman had an acute ischemic stroke 2 months after Y-stent SAC for a basilar artery aneurysm, and aspirin was prescribed post-procedure. Diffusion-weighted imaging revealed multiple scattered infarcts of various sizes in the posterior circulation. Case 2: A 72-year-old woman experienced an acute ischemic stroke 3 years post-SAC for a right posterior communicating artery aneurysm. The stroke occurred after discontinuation of antiplatelet therapy. Diffusion-weighted imaging revealed scattered acute infarctions in the right middle and anterior cerebral artery territories. These two cases of delayed thromboembolic stroke after SAC might have been due to stent strut exposure in the arterial lumen and concurrent thrombosis.

Background: Worldwide, sepsis is the leading cause of death in hospitals. If mortality rates in patients with sepsis can be predicted early, medical resources can be allocated efficiently. We constructed machine learning (ML) models to predict the mortality of patients with sepsis in a hospital emergency department. Methods: This study prospectively collected nationwide data from an ongoing multicenter cohort of patients with sepsis identified in the emergency department. Patients were enrolled from 19 hospitals between September 2019 and December 2020. For acquired data from 3,657 survivors and 1,455 deaths, six ML models (logistic regression, support vector machine, random forest, extreme gradient boosting [XGBoost], light gradient boosting machine, and categorical boosting [CatBoost]) were constructed using fivefold cross-validation to predict mortality. Through these models, 44 clinical variables measured on the day of admission were compared with six sequential organ failure assessment (SOFA) components (PaO 2 /FIO 2 [PF], platelets (PLT), bilirubin, cardiovascular, Glasgow Coma Scale score, and creatinine).The confidence interval (CI) was obtained by performing 10,000 repeated measurements via random sampling of the test dataset. All results were explained and interpreted using Shapley’s additive explanations (SHAP). Results: Of the 5,112 participants, CatBoost exhibited the highest area under the curve (AUC) of 0.800 (95% CI, 0.756–0.840) using clinical variables. Using the SOFA components for the same patient, XGBoost exhibited the highest AUC of 0.678 (95% CI, 0.626–0.730). As interpreted by SHAP, albumin, lactate, blood urea nitrogen, and international normalization ratio were determined to significantly affect the results. Additionally, PF and PLTs in the SOFA component significantly influenced the prediction results. Conclusion Newly established ML-based models achieved good prediction of mortality in patients with sepsis. Using several clinical variables acquired at the baseline can provide more accurate results for early predictions than using SOFA components. Additionally, the impact of each variable was identified.

Background: We aimed to analyze the effects of an antimicrobial stewardship program (ASP) on the proportion of antimicrobial-resistant pathogens in bacteremia, antimicrobial use, and mortality in pediatric patients. Methods: A retrospective single-center study was performed on pediatric inpatients under 19 years old who received systemic antimicrobial treatment from 2001 to 2019. A pediatric infectious disease attending physician started ASP in January 2008. The study period was divided into the pre-intervention (2001–2008) and the post-intervention (2009–2019) periods. The amount of antimicrobial use was defined as days of therapy per 1,000 patientdays, and the differences were compared using delta slope (= changes in slopes) between the two study periods by an interrupted time-series analysis. The proportion of resistant pathogens and the 30-day overall mortality rate were analyzed by the χ2 . Results: The proportion of extended-spectrum beta-lactamase (ESBL)-producing Escherichia coli and Klebsiella pneumoniae bacteremia increased from 17% (39 of 235) in the pre-intervention period to 35% (189 of 533) in the post-intervention period (P < 0.001). The total amount of antimicrobial use significantly decreased after the introduction of ASP (delta slope value = −16.5; 95% confidence interval [CI], −30.6 to −2.3; P = 0.049). The 30-day overall mortality rate in patients with bacteremia did not increase, being 10% (55 of 564) in the pre-intervention and 10% (94 of 941) in the post-intervention period (P = 0.881). Conclusion The introduction of ASP for pediatric patients reduced the delta slope of the total antimicrobial use without increasing the mortality rate despite an increased incidence of ESBL-producing gram-negative bacteremia.

Background: It is well known that a large number of patients with diabetes also have dyslipidemia, which significantly increases the risk of cardiovascular disease (CVD). This study aimed to evaluate the efficacy and safety of combination drugs consisting of metformin and atorvastatin, widely used as therapeutic agents for diabetes and dyslipidemia. Methods: This randomized, double-blind, placebo-controlled, parallel-group and phase III multicenter study included adults with glycosylated hemoglobin (HbA1c) levels >7.0% and <10.0%, low-density lipoprotein cholesterol (LDL-C) >100 and <250 mg/dL. One hundred eighty-five eligible subjects were randomized to the combination group (metformin+atorvastatin), metformin group (metformin+atorvastatin placebo), and atorvastatin group (atorvastatin+metformin placebo). The primary efficacy endpoints were the percent changes in HbA1c and LDL-C levels from baseline at the end of the treatment. Results: After 16 weeks of treatment compared to baseline, HbA1c showed a significant difference of 0.94% compared to the atorvastatin group in the combination group (0.35% vs. −0.58%, respectively; P<0.0001), whereas the proportion of patients with increased HbA1c was also 62% and 15%, respectively, showing a significant difference (P<0.001). The combination group also showed a significant decrease in LDL-C levels compared to the metformin group (−55.20% vs. −7.69%, P<0.001) without previously unknown adverse drug events. Conclusion The addition of atorvastatin to metformin improved HbA1c and LDL-C levels to a significant extent compared to metformin or atorvastatin alone in diabetes and dyslipidemia patients. This study also suggested metformin’s preventive effect on the glucose-elevating potential of atorvastatin in patients with type 2 diabetes mellitus and dyslipidemia, insufficiently controlled with exercise and diet. Metformin and atorvastatin combination might be an effective treatment in reducing the CVD risk in patients with both diabetes and dyslipidemia because of its lowering effect on LDL-C and glucose.