Trial of Endovascular Therapy for Acute Ischemic Stroke with Large Infarct.

BACKGROUND: The role of endovascular therapy for acute stroke with a large infarction has not been extensively studied in differing populations. METHODS: We conducted a multicenter, prospective, open-label, randomized trial in China involving patients with acute large-vessel occlusion in the anterior circulation and an Alberta Stroke Program Early Computed Tomography Score of 3 to 5 (range, 0 to 10, with lower values indicating larger infarction) or an infarct-core volume of 70 to 100 ml. Patients were randomly assigned in a 1:1 ratio within 24 hours from the time they were last known to be well to undergo endovascular therapy and receive medical management or to receive medical management alone. The primary outcome was the score on the modified Rankin scale at 90 days (scores range from 0 to 6, with higher scores indicating greater disability), and the primary objective was to determine whether a shift in the distribution of the scores on the modified Rankin scale at 90 days had occurred between the two groups. Secondary outcomes included scores of 0 to 2 and 0 to 3 on the modified Rankin scale. The primary safety outcome was symptomatic intracranial hemorrhage within 48 hours after randomization. RESULTS: A total of 456 patients were enrolled; 231 were assigned to the endovascular-therapy group and 225 to the medical-management group. Approximately 28% of the patients in both groups received intravenous thrombolysis. The trial was stopped early owing to the efficacy of endovascular therapy after the second interim analysis. At 90 days, a shift in the distribution of scores on the modified Rankin scale toward better outcomes was observed in favor of endovascular therapy over medical management alone (generalized odds ratio, 1.37; 95% confidence interval, 1.11 to 1.69; P = 0.004). Symptomatic intracranial hemorrhage occurred in 14 of 230 patients (6.1%) in the endovascular-therapy group and in 6 of 225 patients (2.7%) in the medical-management group; any intracranial hemorrhage occurred in 113 (49.1%) and 39 (17.3%), respectively. Results for the secondary outcomes generally supported those of the primary analysis. CONCLUSIONS: In a trial conducted in China, patients with large cerebral infarctions had better outcomes with endovascular therapy administered within 24 hours than with medical management alone but had more intracranial hemorrhages. (Funded by Covidien Healthcare International Trading [Shanghai] and others; ANGEL-ASPECT ClinicalTrials.gov number, NCT04551664.).

The change in pediatric subject symptoms during the COVID-19 pandemic in China: an increase in cardiac consultation.

BACKGROUND: It is reported that the adverse impact of nonpharmaceutical interventions (NPIs) on the mental health of children and adolescents may lead to psychologically related disorders during the coronavirus disease 2019 (COVID-19) period. Subject symptoms such as chest pain, chest tightness, and palpitation may be related to increased stress and anxiety in children and adolescents. The present research aimed to determine the number of pediatric consults and etiology of subject symptoms during the COVID-19 pandemic period and compared it with the same timelines in 2019 and 2021 to discuss the impact of different periods on the organic disease onset of children with subject symptoms, especially in cardiac involvement. METHODS: Children who visited Qingdao Women and Children's Hospital, Qingdao University between January 23 to April 30, 2019 (pre-COVID-19 period), January 23 to April 30, 2020 (COVID-19 period), and January 23 to April 30, 2021 (post-COVID-19 period) presenting chest pain, chest tightness, and palpitation were recruited. Information to determine gender, age, medical history, department for the initial visit, clinical manifestations, time from the latest onset to the visit, and diagnosis were recorded. RESULT: A total of 891 patients were enrolled in the present study (514 males; median age: 7.72). One hundred twenty-three patients presented during the pre-COVID-19 period while 130 during the COVID-19 period, nevertheless, the number substantially increased during the post-COVID-19 period (n = 638). Cardiac etiology accounted for 1.68% (n = 15) of the patient population, including arrhythmias (n = 10, 1.12%), myocarditis (n = 4, 0.44%), and atrial septal defect (n = 1, 0.11%). There was no significant difference among groups in the distribution of organic etiology. The median time from the latest onset to the visit during the pre-COVID-19 period was 7 days compared to 10 days during the COVID-19 period and 3 days during the post-COVID period. CONCLUSION: During the post-COVID-19 period, the median time from the latest onset to the visit was significantly shorter than that in the pre-COVID-19 period or COVID-19 period. The pediatric consult of children with subject symptoms presented increased substantially during the post-COVID-19 period, while there was no significant difference in the number of patients involving the cardiac disease. Clinicians ought to be more careful to screen heart diseases to prevent missed diagnosis and misdiagnosis during special periods.

Developing a Machine Learning Model to Predict Severe Chronic Obstructive Pulmonary Disease Exacerbations: Retrospective Cohort Study.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) poses a large burden on health care. Severe COPD exacerbations require emergency department visits or inpatient stays, often cause an irreversible decline in lung function and health status, and account for 90.3% of the total medical cost related to COPD. Many severe COPD exacerbations are deemed preventable with appropriate outpatient care. Current models for predicting severe COPD exacerbations lack accuracy, making it difficult to effectively target patients at high risk for preventive care management to reduce severe COPD exacerbations and improve outcomes. OBJECTIVE: The aim of this study is to develop a more accurate model to predict severe COPD exacerbations. METHODS: We examined all patients with COPD who visited the University of Washington Medicine facilities between 2011 and 2019 and identified 278 candidate features. By performing secondary analysis on 43,576 University of Washington Medicine data instances from 2011 to 2019, we created a machine learning model to predict severe COPD exacerbations in the next year for patients with COPD. RESULTS: The final model had an area under the receiver operating characteristic curve of 0.866. When using the top 9.99% (752/7529) of the patients with the largest predicted risk to set the cutoff threshold for binary classification, the model gained an accuracy of 90.33% (6801/7529), a sensitivity of 56.6% (103/182), and a specificity of 91.17% (6698/7347). CONCLUSIONS: Our model provided a more accurate prediction of severe COPD exacerbations in the next year compared with prior published models. After further improvement of its performance measures (eg, by adding features extracted from clinical notes), our model could be used in a decision support tool to guide the identification of patients with COPD and at high risk for care management to improve outcomes. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): RR2-10.2196/13783.

Influence of COVID-19 Lockdowns on the Usage of a Vision Assistance App Among Global Users With Visual Impairment: Big Data Analytics Study.

BACKGROUND: Millions of individuals with visual impairment use vision assistance apps to help with their daily activities. The most widely used vision assistance apps are magnifier apps. It is still largely unknown what the apps are used for. Lack of insight into the visual needs of individuals with visual impairment is a hurdle for the development of more effective assistive technologies. OBJECTIVE: This study aimed to investigate how needs for visual aids may vary with social activities, by observing the changes in the usage of a smartphone magnifier app when many users take breaks from work. METHODS: The number of launches of the SuperVision Magnifier app was determined retrospectively from 2018 to 2020 from among active users worldwide. The fluctuation in app usage was examined by comparing weekday vs weekend periods, Christmas and new year vs nonholiday seasons, and COVID-19 lockdowns vs the easing of restriction during the pandemic. RESULTS: On average, the app was used 262,466 times by 38,237 users each month in 2020 worldwide. There were two major trough points on the timeline of weekly app usage, one aligned with the COVID-19 lockdowns in April 2020 and another aligned with the Christmas and new year week in 2018 and 2019. The app launches declined by 6947 (11% decline; P<.001) during the lockdown and by 5212 (9% decline; P=.001) during the holiday weeks. There was no significant decline during March to May 2019. App usage compensated for seasonal changes was 8.6% less during weekends than during weekdays (P<.001). CONCLUSIONS: The need for vision assistance technology was slightly lower during breaks and lockdowns, probably because the activities at home were different and less visually demanding. Nevertheless, for the entire user population, the needs for visual aids are still substantial.

Research Advance on Qingfei Paidu Decoction in Prescription Principle, Mechanism Analysis and Clinical Application.

Since the sudden epidemic of coronavirus disease 2019 (COVID-19), the State Administration of Traditional Chinese Medicine immediately organized experts to formulate and screen the effective prescriptions of traditional Chinese medicine according to the characteristics of the novel coronavirus infection. Qingfei Paidu decoction (QFPDD) has been proven to be effective in multi-provincial clinical trials, and has been selected as a general prescription for the treatment of COVID-19 in different stages that was later promoted to be used nationwide. This review highlights the latest advances of QFPDD, focusing on the TCM theory, mechanism analysis, clinical application of QFPDD and its future perspectives. Moreover, an in-depth discussion of some valuable issues and possible development for future research on QFPDD is also discussed, aiming to provide a novel guide to combat the global epidemic COVID-19.

Research progress of traditional Chinese medicine against COVID-19.

BACKGROUND: Currently, the number of confirmed cases and deaths of COVID-19 worldwide continues to rise, receiving great concern from the international community. However, there is no specific and widely accepted effective vaccines. The experience in controlling the outbreak in China has proven the effectiveness of traditional Chinese medicine (TCM). OBJECTIVES: This review aims to evaluate the role of TCM in COVID-19 treatment, hoping to provide references for prevention and control of global pandemic. DATA SOURCES: China National Knowledge Infrastructure, Web of Science, Baidu Scholar, ScienceDirect, Elsevier and PubMed were used to search literatures published from December 2019 to December 2020 by entering the keywords "Traditional Chinese medicine", "COVID-19″, "Severe acute respiratory syndrome coronavirus 2″, "Pathogenesis", "Syndrome differentiation", "Prescriptions" and their combinations. Hence, we have performed an extensive review of research articles, reviews and primary scientific studies to identify TCM against COVID-19. RESULTS: Among clinical treatments of COVID-19, several TCM prescriptions and characteristic therapies have been effectively suggested, the underlying mechanisms of which are mainly involved in antiviral, anti-inflammatory, immunomodulatory and organ-protective effects of multi-components acting on multi-targets at multi-pathways. CONCLUSIONS: This review may provide meaningful and feasible information that can be considered for the treatment of COVID-19 pandemic globally.

Inpatient Virtual Vision Clinic Improves Access to Vision Rehabilitation Before and During the COVID-19 Pandemic.

OBJECTIVE: To describe and evaluate a secure video call system combined with a suite of iPad vision testing apps to improve access to vision rehabilitation assessment for inpatients. DESIGN: Retrospective. SETTING: Two acute care inpatient rehabilitation hospitals and 1 long-term acute care (LTAC) hospital. PARTICIPANTS: Records of inpatients seen by the vision service. INTERVENTIONS: Records from a 1-year telemedicine pilot performed at acute rehabilitation (AR) hospital 1 and then expanded to AR hospital 2 and LTAC hospital during coronavirus disease 2019 (COVID-19) were reviewed. In the virtual visits, an occupational therapist measured the patients' vision with the iPad applications and forwarded results to the off-site Doctor of Optometry (OD) for review prior to a video visit. The OD provided diagnosis and education, press-on prism application supervision, strategies and modifications, and follow-up recommendations. Providers completed the telehealth usability questionnaire (10-point scale). MAIN OUTCOME MEASURES: Vision examinations per month at AR hospital 1 before and with telemedicine. RESULTS: With telemedicine at AR hospital 1, mean visits per month significantly increased from 10.7±5 to 14.9±5 (P=.002). Prism was trialed in 40% of cases of which 83% were successful, similar to previously reported in-person success rates. COVID-19 caused only a marginal decrease in visits per month (P=.08) at AR1, whereas the site without an established program (AR hospital 2) had a 3-4 week gap in care while the program was initiated. Cases at the LTAC hospital tended to be more complex and difficult to manage virtually. The telehealth usability questionnaire median category scores were 7 for Ease of Use, 8 for Interface Quality, 6 for Reliability, and 9 for Satisfaction and Future Use. CONCLUSIONS: The virtual vision clinic process improved inpatient access to eye and visual neurorehabilitation assessment before and during the COVID-19 quarantine and was well accepted by providers and patients.