Breathlessness shares aging mechanisms of frailty and sarcopenia. Are frailty and sarcopenia associated with breathlessness itself? We analyzed data from a population-based, prospective cohort study of 780 community-dwelling older adults. Breathlessness was defined using the modified Medical Research Council Dyspnea Scale (≥2 points) and the Chronic Obstructive Pulmonary Disease Assessment Test (≥10 points). Frailty was defined by frailty index (FI), frailty phenotype, and FRAIL questionnaire. Sarcopenia was defined by the Asian Working Group for Sarcopenia 2019. Sarcopenia phenotype score quantifies the number of criteria met. The associations of frailty and sarcopenia with breathlessness was evaluated by logistic regression analyses. Adjusted odds ratio (aOR) were calculated, accounting for age, sex, chronic airway disease, smoking status, body mass index, lung functions, socioeconomic status (living alone, income, education), comorbid conditions (hypertension, diabetes, malignancy, myocardial infarction, heart failure), and other geriatric contributors (cognitive dysfunction, depression, malnutrition, polypharmacy, fall history in the past year). Institutionalization-free survival was compared by log-rank test. The prevalence of frailty is higher in the breathlessness group compared to non-breathlessness group (42.6% vs. 10.5% by FI, 26.1% vs. 8.9% by frailty phenotype, and 23.0% vs. 4.2% by FRAIL) and sarcopenia (38.3% vs. 26.9%), with P < 0.01 for all comparisons. The multivariable logistic regression analyses showed that frailty (FI [aOR: 9.29], FRAIL questionnaire [aOR: 5.21], and frailty phenotype [aOR: 3.09]) and sarcopenia phenotype score (score 2 [aOR: 2.00] and score 3 [aOR: 2.04] compared to score 0) were associated with breathlessness. The cumulative incidence of institutionalization-free survival was higher in the breathlessness group than counterparts (P = 0.02). The findings suggest that frailty and sarcopenia strongly contribute to breathlessness in community-dwelling older adults. Measuring sarcopenia and frailty in older adults may offer opportunities to prevent age-related breathlessness.

Background: Drug-induced liver injury (DILI) may lead to the discontinuation of antituberculosis (anti-TB) treatment (ATT). Some studies have suggested that metabolic disorders increase the risk of DILI during ATT. This study aimed to identify risk factors for DILI, particularly metabolic disorders, during ATT. Methods: A multicenter prospective observational cohort study to evaluate adverse events during ATT was conducted in Korea from 2019 to 2021. Drug-susceptible patients with TB who had been treated with standard ATT for 6 months were included. The patients were divided into 2 groups depending on the presence of 1 or more metabolic conditions, such as insulin resistance, hypertension, obesity, and dyslipidemia. We monitored ATT-related adverse events, including DILI, and treatment outcomes. The incidence of DILI was compared between individuals with and without metabolic disorders, and related factors were evaluated. Results: Of 684 patients, 52 (7.6%) experienced DILI, and 92.9% of them had metabolic disorders. In the multivariable analyses, underlying metabolic disorders (adjusted hazard ratio [aHR], 2.85; 95% CI, 1.01–8.07) and serum albumin <3.5 g/dL (aHR, 2.26; 95% CI, 1.29–3.96) were risk factors for DILI during ATT. In the 1-month landmark analyses, metabolic disorders were linked to an elevated risk of DILI, especially significant alanine aminotransferase elevation. The treatment outcome was not affected by the presence of metabolic disorders. Conclusions: Patients with metabolic disorders have an increased risk of ATT-induced liver injury compared with controls. The presence of metabolic disorders and hypoalbuminemia adversely affects the liver in patients with ATT.

We evaluated whether the pathogens identified during acute exacerbation of chronic obstructive pulmonary disease (AE-COPD) are associated with the COPD medications used in the 6 months before AE-COPD. We collected the medical records of patients diagnosed with AE-COPD at 28 hospitals between January 2008 and December 2019 and retrospectively analyzed them. Microorganisms identified at the time of AE-COPD were analyzed according to the use of inhaled corticosteroid (ICS) and systemic steroid after adjusting for COPD severity. We evaluated 1177 patients with AE-COPD and available medication history. The mean age of the patients was 73.9 ± 9.2 years, and 83% were males. The most frequently identified bacteria during AE-COPD were Pseudomonas aeruginosa (10%), followed by Mycoplasma pneumoniae (9.4%), and Streptococcus pneumoniae (5.1%), whereas the most commonly identified viruses were rhinovirus (11%) and influenza A (11%). During AE-COPD, bacteria were more frequently identified in the ICS than non-ICS group (p = 0.009), and in the systemic steroid than non-systemic steroid group (p < 0.001). In patients who used systemic steroids before AE-COPD, the risk of detecting Pseudomonas aeruginosa was significantly higher during AE-COPD (OR 1.619, CI 1.007–2.603, p = 0.047), but ICS use did not increase the risk of Pseudomonas detection. The risk of respiratory syncytial virus (RSV) detection was low when ICS was used (OR 0.492, CI 0.244–0.988, p = 0.045). COPD patients who used ICS had a lower rate of RSV infection and similar rate of P. aeruginosa infection during AE-COPD compared to patients who did not use ICS. However, COPD patients who used systemic steroids within 6 months before AE-COPD had an increased risk of P. aeruginosa infection. Therefore, anti-pseudomonal antibiotics should be considered in patients with AE-COPD who have used systemic steroids.

An TJ, et al. Tuberc Respir Dis. 2018 Jan;81(1):80-87. https://doi.org/10.4046/trd.2017.0108

Background: Evaluating the diaphragm muscle in chronic obstructive pulmonary disease (COPD) is important. However, the role of diaphragm ultrasound (DUS) in distinguishing the exacerbation status of COPD (AECOPD) is not fully understood. We set this study to evaluate the role of DUS as a biomarker for distinguishing the AECOPD. Methods: COPD patients who underwent DUS were enrolled between March 2020 and November 2020. The diaphragm thickening fraction (TF_max) and diaphragm excursion (DE_max) during maximal deep breathing were measured. Patients were divided into exacerbation and stable groups. Demographics, lung function, and DUS findings were compared between the two groups. Receiver operating characteristic curve and univariate/multivariate logistic regression analyses were performed. Results: Fifty-five patients were enrolled. The exacerbation group had a lower body mass index (BMI) (20.9 vs 24.2, p = 0.003), lower TF_max (94.8 ± 8.2% vs 158.4 ± 83.5%, p = 0.010), and lower DE_max (30.8 ± 11.1 mm vs 40.5 ± 12.5 mm, p = 0.007) compared to stable group. The areas under the TF_max (0.745) and DE_max (0.721) curves indicated fair results for distinguishing AECOPD. The patients were divided into low and high TF_max and DE_max groups based on calculated cut-off values. Low TF_max (odds ratio [OR] 8.40; 95% confidence interval [CI] 1.55– 45.56) and low DE_max (OR 11.51; 95% CI 1.15– 115.56) were associated with AECOPD after adjusting for age, sex, BMI, and lung functions. Conclusion: DUS showed the possibility of an imaging biomarker distinguishing AECOPD from stable status.