Impact of accumulative smoking exposure and chronic obstructive pulmonary disease on COVID-19 outcomes: report based on findings from the Japan COVID-19 task force

Characteristics and clinical effectiveness of COVID-19 vaccination in hospitalized patients in Omicron-dominated epidemic wave – a nationwide study in Japan

“…We extracted 1414 hospitalized COVID-19 patients, such that 56 patients with insufficient clinical information, 735 patients in fifth (6/21/2021–12/16/2021), 495 patients in sixth (12/17/2021–6/24/2022), and 128 patients in seventh (6/25/2022–9/26/2022) epidemic waves were analyzed. We performed a multivariable analysis adjusted for previously reported factors of age, sex, body mass index (BMI), smoking history, hypertension, diabetes, cardiovascular disease, and chronic kidney disease [ 3 , 4 ] to evaluate the relationship between vaccination and 1) critical outcome, defined as conditions requiring the support of a high-flow oxygen device or invasive mechanical ventilation (IMV) or death, and 2) respiratory outcome, defined as conditions requiring any form of oxygen support. Data were compared using the chi-square test or one-way analysis of variance.…”

Influence of simultaneous comorbidities on COVID-associated acute respiratory distress syndrome mortality in people with diabetes

“…The association between smoking and CARDS is multifaceted, involving increased susceptibility to viral infections, increased ACE-2 receptor expression, and the potential to worsen glycemic homeostasis. 27 , 28 , 29 Given the substantial influence of smoking on CARDS outcomes, smoking cessation interventions should be an integral part of patient treatment, highlighting the need to understand the broad implications of smoking on health and its role in comorbidity-related mortality in individuals with HDD.…”

Sex differences in patients with COVID-19 after bariatric surgery: a multicenter cross-sectional study

“…Therefore, relevant variables were identified based on professional knowledge ( 15 , 16 ), and their associations with the self-reported duration of severe symptoms of COVID-19 were examined as the main outcome. Employing a historical confounding approach, a multivariate regression model incorporated age (years) ( 17 ), BMI group ( 18 ), education level ( 19 ), marital status ( 20 ), smoking status ( 21 ), alcohol consumption ( 22 ), bariatric surgery type (SG, RYGB, and others) ( 23 ), hypertension ( 24 ), and diabetes ( 25 ). Due to the skewed distribution of BMI data, we grouped the values into intervals with uniform spacing of 5, namely (<20, 20–25, 25–30, 30–35, 35–40, 45–50, 50–55, and 55–60 kg/m 2 ).…”