The global coronavirus disease 2019 (COVID-19) pandemic has necessitated the establishment of new medical care systems worldwide. Medical staff treating COVID-19 patients perform their care duties in highly challenging and psychologically demanding situations, raising concerns about their impact on patient safety. Therefore, this study aimed to investigate and characterize incident reports related to COVID-19 patients to clarify the impact of COVID-19 on patient safety. The study included data from 557 patients admitted to the Critical Care Center of a tertiary-care teaching hospital in Osaka, Japan, from April 2020 to March 2021. The patients were divided into two groups: COVID-19 (n = 106) and non-COVID-19 (n = 451) and compared based on various characteristics, incident reporting rates, and the content of incident reports. The findings indicated a significantly higher rate of patients with incident reports in the COVID-19 group compared to the non-COVID-19 group (49.1% vs. 24.4%, P < 0.001). In addition, quantitative text analysis revealed that the topic ratio, consisting of “respiration,” “circuit,” “settings,” “connection,” “nursing,” “ventilator,” “control,” “tape,” “Oxylog^®,” and “artificial nose” was significantly higher in the incident reports of the COVID-19 group (P = 0.003). In conclusion, COVID-19 patients are more susceptible to adverse incidents and may face a higher risk of patient safety issues. The characteristic topics in incident reports involving COVID-19 patients primarily revolved around ventilator-related issues. In the future, the methodology used in the current study may be utilized to identify incident characteristics and implement appropriate countermeasures in the event of unknown patient safety issues.

Our previous study revealed oxidized-low density lipoprotein (oxLDL)-stimulated macrophages delivered exosomes to exacerbate vascular smooth muscle cell (VSMC) viability and invasion; and microRNA-320b was enriched in exosomes from oxLDL-stimulated macrophages. This study aimed to further explore molecular mechanisms of exosomal microRNA-320b from oxLDL-stimulated macrophages on cellular functions of VSMCs. Exosomes from oxLDL-stimulated macrophages with microRNA-320b mimic/inhibitor transfection were used to treat VSMCs. Next, microRNA-320b mimic/inhibitor, and microRNA-320b mimic with or without peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A) overexpression vector were transfected into VSMCs. Viability, invasion, apoptosis, contractile/synthetic phenotype markers, and MEK/ERK pathway were detected in VSMCs. Exosomes from microRNA-320b mimic-treated macrophages promoted viability, invasion, and synthetic phenotype marker osteopontin, while suppressed apoptosis and contractile phenotype marker α-smooth muscle actin in VSMCs. Importantly, direct microRNA-320b mimic treatment aggravated viability, invasion, and synthetic phenotype transition in VSMCs. However, microRNA-320b inhibitor showed the opposite effects as microRNA-320b mimic. Next, luciferase reporter gene assay showed that microRNA-320b directly bound to PPARGC1A; microRNA-320b also inversely regulated PPARGC1A in VSMCs. Moreover, the effect of microRNA-320b mimic on cellular functions of VSMCs was hampered by PPARGC1A overexpression vector (all P < 0.05). Additionally, microRNA-320b activated MEK/ERKT pathway, which was also suppressed by PPARGC1A overexpression vector (all P < 0.05). OxLDL-stimulated macrophages deliver exosomal microRNA-320b to exacerbate viability, invasion, and synthetic phenotype transition in VSMCs via modulating PPARGC1A-mediated MEK/ERK pathway, thus participating in the progression of atherosclerosis.

Hereditary angioedema is a rare, potentially life-threatening disease. There is a lack of data describing the clinical course of hereditary angioedema (HAE) in children. We aimed to evaluate the clinical characteristics of pediatric patients with hereditary angioedema: The age of disease onset, age at diagnosis, the frequency of angioedema attacks, the total number of attacks before diagnosis, the regions where angioedema attacks were observed, accompanying abdominal pain, and serum levels of C4 and C1 esterase inhibitor were obtained and recorded. In addition, the results of SERPING1 (C1INH) gene sequence analysis of the patients in this group were also collected from medical records and recorded. While none of the patients reported a skin rash as a symptom of attack, there was formication observed in the region of angioedema in 46.9% (n = 15) of the patients and pruritus in 6.2% (n = 2) of the patients. At disease onset, the complaints of the patients regarding location of edema were on the hands of 32.3% (n = 10), on the feet of 9.7% (n = 3), on the faces of 25.7% (n = 8), and abdominal attacks in 32.3% of the patients (n = 10). Four different variants, one of which was novel, were detected in the SERPING1 gene in eight different families. The results of this study suggest that hereditary angioedema is diagnosed only when the patient requests examination following recurrent angioedema. Severe laryngeal edema attacks in patients without a diagnosis of HAE are fatal at a higher rate than attacks in patients with a diagnosis. Thus, awareness of the symptoms of HAE is necessary, and correct diagnosis is essential to proper treatment.

Juvenile myasthenia gravis (JMG) exhibits a more favorable response to glucocorticoids and has a better prognosis than adult myasthenia gravis. However, no established treatment exists for refractory JMG. Although thymectomy has been performed in several patients with refractory systemic JMG, there are few detailed clinical descriptions of patients who underwent thymectomy. Here, we present the case of a 10-year-old boy with refractory systemic JMG who was successfully treated with thymectomy. The patient developed symptoms, including dysphagia, malaise, diurnal ptosis, and weakness in the trunk muscles, and he was diagnosed with generalized JMG. Despite undergoing various treatments, including steroids, tacrolimus, steroid pulse therapy, intravenous immunoglobulin, azathioprine (AZT), and rituximab, his symptoms did not improve. Therefore, he underwent a thoracoscopic thymectomy 24 months after disease onset. Thymectomy led to remission, as demonstrated by a significant reduction in the quantitative myasthenia gravis score and anti-acetylcholine receptor antibody levels, which persisted for 43 months after surgery. Our case demonstrates the effectiveness of thymectomy in systemic JMG patients with positive anti-acetylcholine receptor antibodies, despite therapeutic failure with AZT and rituximab, within 2 years of disease onset.

As evidence of risk factors for severe cases of coronavirus disease 2019 (COVID-19) was uncertain in early phases of the pandemic, the development of an efficient predictive model for severe cases to triage high-risk individuals represented an urgent yet challenging issue. It is crucial to select appropriate statistical models when available data and evidence are limited. This study was conducted to assess the accuracy of different statistical models in predicting severe cases using demographic data from patients with COVID-19 prior to the emergence of consequential variants. We analyzed data from 929 consecutive patients diagnosed with COVID-19 prior to March 2021, including their age, sex, body mass index, and past medical histories, and compared areas under the receiver operating characteristic curve (ROC AUC) between different statistical models. The random forest (RF) model, deep learning (DL) models with not too many neurons, and naïve Bayes model exhibited AUC measures of > 0.70 with the validation datasets. The naïve Bayes model performed the best with the AUC measures of > 0.80. The accuracies in RF were more robust with narrower distribution of AUC measures compared to those in DL. The benefit of performing feature selection with a training dataset before building models was seen in some models, but not in all models. In summary, the naïve Bayes and RF models exhibited ideal predictive performance even with limited available data. The benefit of performing feature selection before building models with limited data resources depended on machine learning methods and parameters.

A moment magnitude (Mw) 7.5 earthquake (the Global IDentifire (GLIDE) number: # Q-2024-000001-JPN) struck the Noto Peninsula of Ishikawa Prefecture on 1 January 2024 at 16:10 (Japan Standard Time). The reversed fault, 150 km in length and subducting beneath the peninsula, resulted in maximum seismic intensity 7 shaking, triggered the tsunami, destroyed over 43 thousand buildings, and disrupted roads and lifelines. The disaster claimed 236 deaths, including 15 indirect disaster deaths as of Jan. 28, 2024. There were Disaster Base Hospitals (DBHs) in the region, which survived structurally but suffered from impaired functions and the surge of medical needs of affected people. The disaster medical system of Japan immediately responded and coordinated the hundreds of emergency medical teams (EMTs), i.e., the Japan Disaster Medical Assistance Team (DMAT), from all over the country. Tohoku University Hospital, which had the experience of the 2011 Great East Japan Earthquake (GEJE), joined the coordinated response, dispatching a chain of DMATs, which helped the medical and public health coordination in Wajima City. The medical and public health needs included injuries, non-communicable diseases, infectious diseases, mental health issues, and maternal and child health issues, which were similar in the affected communities in GEJE. Although the actual damage far exceeded expectations, the structural retrofitting and business continuity plans of DBHs and the coordinated response of the national disaster medical system enhanced the effectiveness of medical and public health response.