Promising Expectations for Pneumococcal Vaccination during COVID-19.

The emergence of new viral infections has increased over the decades. The novel virus is one such pathogen liable for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, popularly known as coronavirus disease 2019 (COVID-19). Most fatalities during the past century's influenza pandemics have cooperated with bacterial co/secondary infections. Unfortunately, many reports have claimed that bacterial co-infection is also predominant in COVID-19 patients (COVID-19 associated co/secondary infection prevalence is up to 45.0%). In the COVID-19 pandemic, Streptococcus pneumoniae is the most common coinfecting pathogen. Half of the COVID-19 mortality cases showed co-infection, and pneumonia-related COVID-19 mortality in patients >65 years was 23%. The weakening of immune function caused by COVID-19 remains a high-risk factor for pneumococcal disease. Pneumococcal disease and COVID-19 also have similar risk factors. For example, underlying medical conditions on COVID-19 and pneumococcal diseases increase the risk for severe illness at any age; COVID-19 is now considered a primary risk factor for pneumococcal pneumonia and invasive pneumococcal disease. Thus, pneumococcal vaccination during the COVID-19 pandemic has become more critical than ever. This review presents positive studies of pneumococcal vaccination in patients with COVID-19 and other medical conditions and the correlational effects of pneumococcal disease with COVID-19 to prevent morbidity and mortality from co/secondary infections and superinfections. It also reports the importance and role of pneumococcal vaccination during the current COVID-19 pandemic era to strengthen the global health system.

Patterns and predictors of smoking relapse among inpatient smoking intervention participants: a 1-year follow-up study in Korea.

OBJECTIVES: This study aimed to identify relapse patterns in smokers who participated in an inpatient treatment program and to investigate factors related to relapse. METHODS: The participants comprised 463 smokers who participated in an inpatient treatment operated by the Daejeon Tobacco Control Center from 2015 to 2018. Participants received high-intensity smoking cessation intervention for 5 consecutive days, including pharmacotherapy and behavioral support, and continued with follow-up for 1 year to determine whether they maintained smoking cessation after discharge from inpatient treatment. Kaplan-Meier and Cox proportional hazard models were used in the analysis. RESULTS: Participants' relapse rate within 1 year was 72.8%, and 59.8% of participants smoked again within 6 months after participation. A higher number of counseling sessions was significantly associated with a lower risk of relapse (hazard ratio [HR], 0.23; 95% confidence interval [CI], 0.17 to 0.32 for ≥9 vs. ≤5 counseling sessions). Conversely, higher relapse rates were significantly associated with the use of nicotine replacement therapy (NRT) (HR, 1.91; 95% CI, 1.43 to 2.55 for use vs. no use), and higher levels of baseline expired carbon monoxide (CO) (HR, 1.58; 95% CI, 1.21 to 2.06 for expired CO concentrations of 10-19 ppm vs. expired CO concentrations <10 ppm). CONCLUSIONS: High-intensity smoking cessation interventions in hospital settings can be effective for smoking cessation in smokers with high nicotine dependence. In addition, the results suggest that for quitters to maintain long-term abstinence, they should receive regular follow-up counseling for 1 year after completing a high-intensity smoking cessation intervention.

The Development of an IMU Integrated Clothes for Postural Monitoring Using Conductive Yarn and Interconnecting Technology.

Spinal disease is a common yet important condition that occurs because of inappropriate posture. Prevention could be achieved by continuous posture monitoring, but most measurement systems cannot be used in daily life due to factors such as burdensome wires and large sensing modules. To improve upon these weaknesses, we developed comfortable "smart wear" for posture measurement using conductive yarn for circuit patterning and a flexible printed circuit board (FPCB) for interconnections. The conductive yarn was made by twisting polyester yarn and metal filaments, and the resistance per unit length was about 0.05 Ω/cm. An embroidered circuit was made using the conductive yarn, which showed increased yield strength and uniform electrical resistance per unit length. Circuit networks of sensors and FPCBs for interconnection were integrated into clothes using a computer numerical control (CNC) embroidery process. The system was calibrated and verified by comparing the values measured by the smart wear with those measured by a motion capture camera system. Six subjects performed fixed movements and free computer work, and, with this system, we were able to measure the anterior/posterior direction tilt angle with an error of less than 4°. The smart wear does not have excessive wires, and its structure will be optimized for better posture estimation in a later study.