Background: Coronavirus disease 2019 (COVID-19) has spread worldwide rapidly. However, the effects of asthma, asthma medication and asthma severity on the clinical outcomes of COVID-19 have not yet been established. Methods: The study included 7590 de-identified patients, who were confirmed to have COVID-19 using the severe acute respiratory syndrome coronavirus 2 RNA-PCR tests conducted up to May 15, 2020; we used the linked-medical claims data provided by the Health Insurance Review and Assessment Service. Asthma and asthma severity (steps suggested by the Global Initiative for Asthma) were defined using the diagnostic code and history of asthma medication usage. Results: Among 7590 COVID-19 patients, 218 (2.9%) had underlying asthma. The total medical cost associated with COVID-19 patients with underlying asthma was significantly higher than that of other patients. Mortality rate for COVID-19 patients with underlying asthma (7.8%) was significantly higher than that of other patients (2.8%; p<0.001). However, asthma was not an independent risk factor for the clinical outcomes of COVID-19 after adjustment, nor did asthma medication use and asthma severity affect the clinical outcomes of COVID-19. However, use of oral short-acting β ₂ -agonists was an independent factor to increase the total medical cost burden. Patients with step 5 asthma showed significant prolonged duration of admission compared to those with step 1 asthma in both univariate and multivariate analysis. Conclusions: Asthma led to poor outcomes of COVID-19; however, underlying asthma, use of asthma medication and asthma severity were not independent factors for poor clinical outcomes of COVID-19, generally.

Determining the ideal ratio of macronutrients for increasing life expectancy remains a high priority in nutrition research. We aim to investigate the association between carbohydrate, fat, and protein intake and all-cause mortality in Koreans. This cohort study investigated 42,192 participants from the Korea National Health and Nutrition Examination Survey (KNHANES) linked with causes of death data (2007–2015). Hazard ratios (HRs) were calculated using the multivariable Cox proportional regression model after adjusting for confounders. We documented 2110 deaths during the follow-up period. Time to exceed 1% of the all-cause mortality rate was longest in participants with 50–60% carbohydrate, 30–40% fat, and 20–30% protein intake. Adjusted hazard ratio (HR) with 95% confidence intervals (CIs) was 1.313 (1.031–1.672, p = 0.0272) for <50% carbohydrate intake, 1.322 (1.116–1.567, p = 0.0013) for ≥60% carbohydrate intake, 1.439 (1.018–2.035, p = 0.0394) for <30% fat intake, and 3.255 (1.767–5.997, p = 0.0002) for ≥40% fat intake. There was no significant association between protein intake proportion and all-cause mortality. We found a U-shaped association between all-cause mortality and carbohydrate intake as well as fat intake, with minimal risk observed at 50–60% carbohydrate and 30–40% fat intake. Our findings suggest current Korean dietary guidelines should be revised to prolong life expectancy.

This narrative literature review evaluated the effects of movement-based mind-body interventions (MMBIs; yoga, tai chi, and qigong) on low back pain. A search of databases was conducted to identify relevant studies. Thirty-two articles met inclusion criteria and were included for this narrative review. Of the reviewed studies, the highest number focused on yoga intervention (n = 25), 4 focused on qigong, and 3 focused on tai chi in managing back pain. The selected articles showed MMBI to be effective for treatment of low back pain, reporting positive outcomes such as reduction in pain or psychological distress (eg, depression and anxiety), and improved functional ability. However, little is known about the effects of MMBI, in particular qigong and tai chi. More clinical trials are needed to determine how to reduce back pain, improve physical function, and minimize behavioral and psychological symptoms associated with low back pain. Nurse practitioners may introduce such mind-body interventions for managing pain, especially for patients at high risk for adverse effects from pharmacological treatment, and refer them to a yoga therapist, tai-chi instructor, or qigong instructor.

Background: The automatic interpretation of electrocardiography (ECG) data can provide continuous analysis of heart activity, allowing the effective use of wireless devices such as the Holter monitor. Materials and Methods: We propose an intelligent heartbeat monitoring system to detect the possibility of arrhythmia in real time. We detected heartbeats and extracted features such as the QRS complex and P wave from ECG signals using the Pan–Tompkins algorithm, and the heartbeats were then classified into 16 types using a decision tree. Results: We tested the sensitivity, specificity, and accuracy of our system against data from the MIT-BIH Arrhythmia Database. Our system achieved an average accuracy of 97% in heartbeat detection and an average heartbeat classification accuracy of above 96%, which is comparable with the best competing schemes. Conclusions: This work provides a guide to the systematic design of an intelligent classification system for decision support in Holter ECG monitoring.

Kim JW, et al. World J Mens Health. 2021 Jun;39:e39. https://doi.org/10.5534/wjmh.210019

Ha JS, et al. Yonsei Med J. 2022 Oct;63(10):908-914. https://doi.org/10.3349/ymj.2022.0122