論文

Background: Computed tomography (CT) imaging is widely used for diagnosing and determining the severity of coronavirus disease 2019 (COVID-19). Chest CT imaging can be used to calculate the epicardial adipose tissue (EAT) and upper abdominal visceral adipose tissue (Abd-VAT) areas. The EAT is the main source of inflammatory cytokines involved in chest inflammatory diseases; thus, the EAT area might be a more useful severity predictor than the Abd-VAT area for COVID-19. However, to the best of our knowledge, there are no large-scale reports that sufficiently consider this issue. In addition, there are no reports on the characteristics of patients with normal body mass index (BMI) and high adipose tissue. Aim: The purpose of this study was to analyze whether the EAT area, among various adipose tissues, was the most associated factor with COVID-19 severity. Using a multicenter COVID-19 patient database, we analyzed the associations of chest subcutaneous, chest visceral, abdominal subcutaneous, and Abd-VAT areas with COVID-19 outcomes. In addition, the clinical significance of central obesity, commonly disregarded by BMI, was examined. Methods: This retrospective cohort study evaluated patients with COVID-19 aged ≥18 years In Japan. Data including from chest CT images collected between February 2020 and October 2022 in four hospitals of the Japan COVID-19 Task Force were analyzed. Patient characteristics and COVID-19 severity were compared according to the adipose tissue areas (chest and abdominal subcutaneous adipose tissue [Chest-SAT and Abd-SAT], EAT, and Abd-VAT) calculated from chest CT images. Results: We included 1077 patients in the analysis. Patients with risk factors of severe COVID-19 such as old age, male sex, and comorbidities had significantly higher areas of EAT and Abd-VAT. High EAT area but not high Abd-VAT area was significantly associated with COVID-19 severity (adjusted odds ratio (aOR): 2.66, 95 % confidence interval [CI]: 1.19–5.93). There was no strong correlation between BMI and VAT. Patients with high VAT area accounted for 40.7 % of the non-obesity population (BMI < 25 kg/m2). High EAT area was also significantly associated with COVID-19 severity in the non-obesity population (aOR: 2.50, 95 % CI: 1.17–5.34). Conclusions: Our study indicated that VAT is significantly associated with COVID-19 severity and that EAT is the best potential predictor for risk stratification in COVID-19 among adipose tissue areas. Body composition assessment using EAT is an appropriate marker for identifying obesity patients overlooked by BMI. Considering the next pandemic of the global health crisis, our findings open new avenues for implementing appropriate body composition assessments based on CT imaging.

Statistical fine-mapping prioritizes putative causal variants from a large number of candidate variants, and is widely used in expression quantitative loci (eQTLs) studies. In eQTL fine-mapping, the existence of causal variants for gene expression is not guaranteed, since the genetic heritability of gene expression explained by nearby (cis-) variants is limited. Here we introduce a refined fine-mapping algorithm, named Knockoff-Finemap combination (KFc). KFc estimates the probability that the causal variant(s) exist in the cis-window of a gene through construction of knockoff genotypes (i.e. a set of synthetic genotypes that resembles the original genotypes), and uses it to adjust the posterior inclusion probabilities (PIPs). Utilizing simulated gene expression data, we show that KFc results in calibrated PIP distribution with improved precision. When applied to gene expression data of 465 genotyped samples from the Japan COVID-19 Task Force (JCTF), KFc resulted in significant enrichment of a functional score as well as reporter assay hits in the top PIP bins. When combined with functional priors derived from an external fine-mapping study (GTEx), KFc resulted in a significantly higher proportion of hematopoietic trait putative causal variants in the top PIP bins. Our work presents improvements in the precision of a major fine-mapping algorithm.

Asthma is characterized by chronic airway inflammation, variable airway narrowing, and sensory nerve irritation, which manifest as wheezing, dyspnea, chest tightness, and cough. Longstanding asthma may result in airway remodeling and become intractable. Despite the increased prevalence of asthma in adults, asthma-associated deaths have decreased in Japan (0.94 per 100,000 people in 2020). The goals of asthma treatment include the control of symptoms and reduction of future risks. A functional partnership between physicians and patients is indispensable for achieving these goals. Long-term management with medications and the elimination of triggers and risk factors are fundamental to asthma treatment. Asthma is managed via four steps of pharmacotherapy (“controllers”), ranging from mild to intensive treatments, depending on disease severity; each step involves daily administration of an inhaled corticosteroid, which varies from low to high dosage. Long-acting β2 agonists, leukotriene receptor antagonists, sustained-release theophylline, and long-acting muscarinic antagonists are recommended as add-on drugs. Allergen immunotherapy is a new option that is employed as a controller treatment. Further, as of 2021, anti-IgE antibody, anti-IL-5 and anti-IL-5 receptor α-chain antibodies, and anti-IL-4 receptor α-chain antibodies are available for the treatment of severe asthma. Bronchial thermoplasty can be performed for asthma treatment, and its long-term efficacy has been reported. Algorithms for their usage have been revised. Comorbidities, such as allergic rhinitis, chronic rhinosinusitis, chronic obstructive pulmonary disease, and aspirin-exacerbated respiratory disease, should also be considered during the treatment of chronic asthma. Depending on the severity of episodes, inhaled short-acting β2 agonists, systemic corticosteroids, short-acting muscarinic antagonists, oxygen therapy, and other approaches are used as needed (“relievers”) during exacerbation.

Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.

Since 2019, a large number of people worldwide have been infected with severe acute respiratory syndrome coronavirus 2. Among those infected, a limited number develop severe coronavirus disease 2019 (COVID-19), which generally has an acute onset. The treatment of patients with severe COVID-19 is challenging. To optimize disease prognosis and effectively utilize medical resources, proactive measures must be adopted for patients at risk of developing severe COVID-19. We analyzed the data of COVID-19 patients from seven medical institutions in Tokyo and used mathematical modeling of patient blood test results to quantify and compare the predictive ability of multiple prognostic indicators for the development of severe COVID-19. A machine learning logistic regression model was used to analyze the blood test results of 300 patients. Due to the limited data set, the size of the training group was constantly adjusted to ensure that the results of machine learning were effective (e.g., recognition rate of disease severity > 80%). Lymphocyte count, hemoglobin, and ferritin levels were the best prognostic indicators of severe COVID-19. The mathematical model developed in this study enables prediction and classification of COVID-19 severity.

The development of molecular targeted therapy has improved clinical outcomes in patients with life-threatening advanced lung cancers with driver oncogenes. However, selective treatment for KRAS-mutant lung cancer remains underdeveloped. We have successfully characterised specific molecular and pathological features of KRAS-mutant lung cancer utilising newly developed cell line models that can elucidate the differences in driver oncogenes among tissues with identical genetic backgrounds. Among these KRAS-mutation-associated specific features, we focused on the IGF2-IGF1R pathway, which has been implicated in the drug resistance mechanisms to AMG 510, a recently developed selective inhibitor of KRAS G12C lung cancer. Experimental data derived from our cell line model can be used as a tool for clinical treatment strategy development through understanding of the biology of lung cancer. The model developed in this paper may help understand the mechanism of anticancer drug resistance in KRAS-mutated lung cancer and help develop new targeted therapies to treat patients with this disease.

Background: Research on whether gastrointestinal symptoms correlate with the severity of Coronavirus Disease 2019 (COVID-19) has been inconclusive. This study aimed to clarify any associations between gastrointestinal symptoms and the prognosis of COVID-19. Methods: We collected data from the Japanese nationwide registry for COVID-19 to conduct a retrospective cohort study. Data from 3498 Japanese COVID-19 patients, diagnosed at 74 facilities between February 2020 and August 2022, were analyzed in this study. Hospitalized patients were followed up until discharge or transfer to another hospital. Outpatients were observed until the end of treatment. Associations between gastrointestinal symptoms and clinical outcomes were investigated using multivariable-adjusted logistic regression models. Results: The prevalence of diarrhea, nausea/vomiting, abdominal pain, and melena were 16.6% (581/3498), 8.9% (311/3498), 3.5% (121/3498), and 0.7% (23/3498), respectively. In the univariable analysis, admission to intensive care unit (ICU) and requirement for mechanical ventilation were less common in patients with diarrhea than those without (ICU, 15.7% vs. 20.6% (p = 0.006); mechanical ventilation, 7.9% vs. 11.4% (p = 0.013)). In the multivariable-adjusted analysis, diarrhea was associated with lower likelihood of ICU admission (adjusted odds ratio (aOR), 0.70; 95% confidence interval (CI), 0.53–0.92) and mechanical ventilation (aOR, 0.61; 95% CI, 0.42–0.89). Similar results were obtained in a sensitivity analysis with another logistic regression model that adjusted for 14 possible covariates with diarrhea (ICU; aOR, 0.70; 95% CI, 0.53–0.93; mechanical ventilation; aOR 0.62; 95% CI, 0.42–0.92). Conclusions: Diarrhea was associated with better clinical outcomes in COVID-19 patients.

Rationale Nontuberculous mycobacteria (NTM) are environmental mycobacteria that can cause a chronic progressive lung disease. Although epidemiological data indicate potential genetic predisposition, its nature remains unclear. Objectives We aimed to identify host susceptibility loci for Mycobacterium avium complex (MAC), the most common NTM pathogen. Methods This genome-wide association study (GWAS) was conducted in Japanese patients with pulmonary MAC and healthy controls, followed by genotyping of candidate single-nucleotide polymorphisms (SNPs) in another Japanese cohort. For verification by Korean and European ancestry, we performed SNP genotyping. Results The GWAS discovery set included 475 pulmonary MAC cases and 417 controls. Both GWAS and replication analysis of 591 pulmonary MAC cases and 718 controls revealed the strongest association with chromosome 16p21, particularly with rs109592 (p=1.64×10−13, OR 0.54), which is in an intronic region of the calcineurin-like EF-hand protein 2 (CHP2). Expression quantitative trait loci analysis demonstrated an association with lung CHP2 expression. CHP2 was expressed in the lung tissue in pulmonary MAC disease. This SNP was associated with the nodular bronchiectasis subtype. Additionally, this SNP was significantly associated with the disease in patients of Korean (p=2.18×10−12, OR 0.54) and European (p=5.12×10−03, OR 0.63) ancestry. Conclusions We identified rs109592 in the CHP2 locus as a susceptibility marker for pulmonary MAC disease.

Human lung cancer is a constellation of tumors with various histological and molecular properties. To build a preclinical platform that covers this broad disease spectrum, we obtained lung cancer specimens from multiple sources, including sputum and circulating tumor cells, and generated a living biobank consisting of 43 lines of patient-derived lung cancer organoids. The organoids recapitulated the histological and molecular hallmarks of the original tumors. Phenotypic screening of niche factor dependency revealed that EGFR mutations in lung adenocarcinoma are associated with the independence from Wnt ligands. Gene engineering of alveolar organoids reveals that constitutive activation of EGFR-RAS signaling provides Wnt independence. Loss of the alveolar identity gene NKX2-1 confers Wnt dependency, regardless of EGFR signal mutation. Sensitivity to Wnt-targeting therapy can be stratified by the expression status of NKX2-1. Our results highlight the potential of phenotype-driven organoid screening and engineering for the fabrication of therapeutic strategies to combat cancer.

Background: A health-economic evaluation related to COVID-19 is urgently needed to allocate healthcare resources efficiently; however, relevant medical cost data in Japan concerning COVID-19 are scarce. Methods: This cross-sectional study investigated the healthcare cost for hospitalized COVID-19 patients in 2021 at Keio University Hospital. We calculated the healthcare costs during hospitalization using hospital claims data and investigated the variables significantly related to the healthcare cost with multivariable analysis. Results: The median healthcare cost per patient for the analyzed 330 patients was Japanese yen (JPY) 1,304,431 (US dollars ~ 11,871) (interquartile range: JPY 968,349–1,954,093), and the median length of stay was 10 days. The median healthcare cost was JPY 798,810 for mild cases; JPY 1,113,680 for moderate I cases; JPY 1,643,909 for moderate II cases; and JPY 6,210,607 for severe cases. Healthcare costs increased by 4.0% for each additional day of hospitalization; 1.26 times for moderate I cases, 1.64 times for moderate II cases, and 1.84 times for severe cases compared to mild cases; and 2.05 times for cases involving ICU stay compared to those not staying in ICU. Conclusions: We clarified the healthcare cost for hospitalized COVID-19 patients by severity in a Japanese university hospital. These costs contribute as inputs for forthcoming health economic evaluations for strategies for preventing and treating COVID-19.

Group 2 innate lymphoid cells (ILC2s) are GATA3-expressing type 2 cytokine-producing innate lymphocytes that are present in various organs throughout the body. Basically, ILC2s are tissue-resident cells associated with a variety of pathological conditions in each tissue. Differences in the tissue-specific properties of ILC2s are formed by the post-natal tissue environment; however, diversity exists among ILC2s within each localized tissue due to developmental timing and activation. Diversity between steady-state and activated ILC2s in mice and humans has been gradually clarified with the advancement of single-cell RNA-seq technology. Another layer of complexity is that ILC2s can acquire other ILC-like functions, depending on their tissue environment. Further, ILC2s with immunological memory and exhausted ILC2s are both present in tissues, and the nature of ILC2s varies with senescence. To clarify how ILC2s affect human diseases, research should be conducted with a comprehensive understanding of ILC2s, taking into consideration the diversity of ILC2s rather than a snapshot of a single section. In this review, we summarize the current understanding of the heterogeneity of ILC2s in the lungs and highlight a novel field of immunology.

Background: High-attenuation mucus (HAM) is a specific manifestation of allergic bronchopulmonary mycosis (ABPM) on chest computed tomography (CT). Objectives: To compare the diagnostic accuracy of the two definitions of HAM and to clarify the clinical and radiographic characteristics of HAM-positive and HAM-negative ABPM. Methods: CT images at the diagnosis of ABPM using Asano's criteria were retrospectively analysed. In Study #1, radiographic data obtained using the same CT apparatus in a single institute were analysed to determine the agreement between the two definitions of HAM: a mucus plug that is visually denser than the paraspinal muscles or that with a radiodensity ≥70 Hounsfield units. In Study #2, HAM was diagnosed by comparison with the paraspinal muscles in patients with ABPM reporting to 14 medical institutes in Japan. Results: In Study #1, 93 mucus plugs from 26 patients were analysed. A substantial agreement for HAM diagnosis was observed between the two methods, with a κ coefficient of 0.72. In Study #2, 60 cases of ABPM were analysed; mucus plugs were present in all cases and HAM was diagnosed in 45 (75%) cases. The median A. fumigatus-specific IgE titre was significantly lower in HAM-positive patients than in HAM-negative patients (2.5 vs. 24.3 UA/mL, p =.004). Nodular shadows were observed more frequently in the airways distal to HAM than in those distal to non-HAM mucus plugs (59% vs. 32%, p <.001). Conclusion: In conclusion, agreement between the two methods to diagnose HAM was substantial. HAM was associated with some immunological and radiographic characteristics, including lower levels of sensitization to A. fumigatus and the presence of distal airway lesions.

Increased levels of proteases, such as trypsin, in the distal intestine have been implicated in intestinal pathological conditions1–3. However, the players and mechanisms that underlie protease regulation in the intestinal lumen have remained unclear. Here we show that Paraprevotella strains isolated from the faecal microbiome of healthy human donors are potent trypsin-degrading commensals. Mechanistically, Paraprevotella recruit trypsin to the bacterial surface through type IX secretion system-dependent polysaccharide-anchoring proteins to promote trypsin autolysis. Paraprevotella colonization protects IgA from trypsin degradation and enhances the effectiveness of oral vaccines against Citrobacter rodentium. Moreover, Paraprevotella colonization inhibits lethal infection with murine hepatitis virus-2, a mouse coronavirus that is dependent on trypsin and trypsin-like proteases for entry into host cells4,5. Consistently, carriage of putative genes involved in trypsin degradation in the gut microbiome was associated with reduced severity of diarrhoea in patients with SARS-CoV-2 infection. Thus, trypsin-degrading commensal colonization may contribute to the maintenance of intestinal homeostasis and protection from pathogen infection.

Many variants of SARS-CoV-2 have emerged, and decreased neutralizing antibodies after vaccination and breakthrough infections have become a problem. The importance of monitoring titers of neutralizing antibodies is getting higher. We enrolled 146 COVID-19 patients, who were thought to be infected with Wuhan-hu-1 or D614G strains, and examined the time course of neutralizing titers against six concerning strains (Wuhan-hu-1, Alpha, Beta, Gamma, Kappa, and Delta) using newly developed ELISA. The acquisition of neutralizing titer was positively associated with disease severity. Immune evasions were observed approximately 20 to 30% for Alpha, Kappa, and Delta variant, and 40 to 45% for Beta and Gamma variant. The titers against all strains decreased over time, and interestingly, while titers against Wuhan-hu-1 decreased by 23%, those to Delta variant decreased by 70%. Our simple, cost-effective, and non-hazardous system will be applicable to process numerous samples, such as monitoring titers against prevalent strains after infection or vaccination.

Objectives: Smoking and chronic obstructive pulmonary disease (COPD) are risk factors for severe COVID-19. However, limited literature exists on the effect of COPD and smoking on COVID-19 outcomes. This study examined the impact of smoking exposure in pack-years (PY) and COPD on COVID-19 outcomes among smokers in Japan. Methods: The study included 1266 smokers enrolled by the Japan COVID-19 task force between February 2020 and December 2021. PY and COPD status was self-reported by patients. Patients were classified into the non-COPD (n = 1151) and COPD (n = 115) groups; the non-COPD group was further classified into <10 PY (n = 293), 10-30 PY (n = 497), and >30 PY (n = 361). The study outcome was the need for invasive mechanical ventilation (IMV). Results: The incidence of IMV increased with increasing PY and was highest in the COPD group (<10 PY = 7.8%, 10-30 PY = 12.3%, >30 PY = 15.2%, COPD = 26.1%; P <0.001). A significant association was found for IMV requirement in the >30 PY and COPD groups through univariate (odds ratio [OR]: >30 PY = 2.11, COPD = 4.14) and multivariate (OR: >30 PY = 2.38; COPD = 7.94) analyses. Increasing PY number was also associated with increased IMV requirement in patients aged <65 years. Conclusion: Cumulative smoking exposure was positively associated with COVID-19 outcomes in smokers.

Background: Although cases of respiratory bacterial infections associated with coronavirus disease 2019 (COVID-19) have often been reported, their impact on the clinical course remains unclear. Herein, we evaluated and analyzed the complication rates of bacterial infections, causative organisms, patient backgrounds, and clinical outcome in Japanese patients with COVID-19. Methods: We performed a retrospective cohort study that included inpatients with COVID-19 from multiple centers participating in the Japan COVID-19 Taskforce (April 2020 to May 2021) and obtained demographic, epidemiological, and microbiological results and the clinical course and analyzed the cases of COVID-19 complicated by respiratory bacterial infections. Results: Of the 1,863 patients with COVID-19 included in the analysis, 140 (7.5%) had respiratory bacterial infections. Community-acquired co-infection at COVID-19 diagnosis was uncommon (55/1,863, 3.0%) and was mainly caused by Staphylococcus aureus, Klebsiella pneumoniae and Streptococcus pneumoniae. Hospital-acquired bacterial secondary infections, mostly caused by Staphylococcus aureus, Pseudomonas aeruginosa, and Stenotrophomonas maltophilia, were diagnosed in 86 patients (4.6%). Severity-associated comorbidities were frequently observed in hospital-acquired secondary infection cases, including hypertension, diabetes, and chronic kidney disease. The study results suggest that the neutrophil–lymphocyte ratio (> 5.28) may be useful in diagnosing complications of respiratory bacterial infections. COVID-19 patients with community-acquired or hospital-acquired secondary infections had significantly increased mortality. Conclusions: Respiratory bacterial co-infections and secondary infections are uncommon in patients with COVID-19 but may worsen outcomes. Assessment of bacterial complications is important in hospitalized patients with COVID-19, and the study findings are meaningful for the appropriate use of antimicrobial agents and management strategies.

Background: Respiratory symptoms are associated with coronavirus disease 2019 (COVID-19) outcomes. However, the impacts of upper and lower respiratory symptoms on COVID-19 outcomes in the same population have not been compared. The objective of this study was to characterize upper and lower respiratory symptoms and compare their impacts on outcomes of hospitalized COVID-19 patients. Methods: This was a multicenter, retrospective cohort study; the database from the Japan COVID-19 Task Force was used. A total of 3314 COVID-19 patients were included in the study, and the data on respiratory symptoms were collected. The participants were classified according to their respiratory symptoms (Group 1: no respiratory symptoms, Group 2: only upper respiratory symptoms, Group 3: only lower respiratory symptoms, and Group 4: both upper and lower respiratory symptoms). The impacts of upper and lower respiratory symptoms on the clinical outcomes were compared. The primary outcome was the percentage of patients with poor clinical outcomes, including the need for oxygen supplementation via high-flow oxygen therapy, mechanical ventilation, and extracorporeal membrane oxygenation or death. Results: Of the 3314 COVID-19 patients, 605, 1331, 1229, and 1149 were classified as Group 1, Group 2, Group 3, and Group 4, respectively. In univariate analysis, patients in Group 2 had the best clinical outcomes among all groups (odds ratio [OR]: 0.21, 95% confidence interval [CI]: 0.11–0.39), while patients in Group 3 had the worst outcomes (OR: 3.27, 95% CI: 2.43–4.40). Group 3 patients had the highest incidence of pneumonia, other complications due to secondary infections, and thrombosis during the clinical course. Conclusions: Upper and lower respiratory tract symptoms had vastly different impacts on the clinical outcomes of COVID-19.

The pandemic of COVID-19 is still ongoing, and many studies on serum antibodies have been reported, however, there are few studies about asymptomatic and mild patients. In this study, we enrolled 44 COVID-19 patients with relatively mild disease and 48 pre-pandemic controls. We measured serum antibodies against extracellular domain, S1 domain, and receptor-binding domain of Spike and N protein, examined neutralization titers by authentic virus neutralization assay and newly-developed bead/cell-based Spike-ACE2 inhibition assay, and compared them with clinical features. Most of these antibodies, including neutralizing titers, were mutually correlated, and the production of antibodies were associated with low Ct values of PCR test, disease severity, symptoms especially pneumonia, lymphopenia, and serological test including CRP, LD, D-dimer, and procalcitonin. Notably, 87.5% of asymptomatic and 23.5% of mild patients did not have antibody against SARS-CoV-2. Our results revealed the inadequate acquisition of humoral immunity in patients with asymptomatic and mild COVID-19 patients.

Background ＆ aims: Muscle quantification using chest computed tomography (CT) is a useful prognostic biomarker for coronavirus disease 2019 (COVID-19). However, no studies have evaluated the clinical course through comprehensive assessment of the pectoralis and erector spinae muscles. Therefore, we compared the impact of the areas and densities of these muscles on COVID-19 infection outcome. Methods: This multicenter retrospective cohort study was conducted by the COVID-19 Task Force. A total of 1410 patients with COVID-19 were included, and data on the area and density of the pectoralis and erector spinae muscles on chest CT were collected. The impact of each muscle parameter on the clinical outcome of COVID-19 was stratified according to sex. The primary outcome was the percentage of patients with severe disease, including those requiring oxygen supplementation and those who died. Additionally, 167 patients were followed up for changes in muscle parameters at three months and for the clinical characteristics in case of reduced CT density. Results: For both muscles, low density rather than muscle area was associated with COVID-19 severity. Regardless of sex, lower erector spinae muscle density was associated with more severe disease than pectoralis muscle density. The muscles were divided into two groups using the receiver operating characteristic curve of CT density, and the population was classified into four (Group A: high CT density for both muscles, Group B: low CT density for pectoralis and high for erector spinae muscle. Group C: high CT density for pectoralis and low for erector spinae muscle, Group D: low CT density for both muscles). In univariate analysis, Group D patients exhibited worse outcomes than Group A (OR: 2.96, 95% CI: 2.03–4.34 in men; OR: 3.02, 95% CI: 2.66–10.4 in women). Multivariate analysis revealed that men in Group D had a significantly more severe prognosis than those in Group A (OR: 1.82, 95% CI: 1.16–2.87). Moreover, Group D patients tended to have the highest incidence of other complications due to secondary infections and acute kidney injury during the clinical course. Longitudinal analysis of both muscle densities over three months revealed that patients with decreased muscle density over time were more likely to have severe cases than those who did not. Conclusions: Muscle density, rather than muscle area, predicts the clinical outcomes of COVID-19. Integrated assessment of pectoralis and erector spinae muscle densities demonstrated higher accuracy in predicting the clinical course of COVID-19 than individual assessments.

This cross-sectional study of 136 patients with chronic obstructive pulmonary disease (COPD) investigated the mechanism underlying overlap syndrome, defined as coexisting COPD and obstructive sleep apnea (OSA). OSA was defined as a respiratory event index (REI) ≥ 5 events/h, determined using type-3 portable monitors. The mean REI was 12.8 events/h. Most participants (60.1%) had mild OSA (REI: 5–15 events/h). The REI was positively correlated with forced expiratory volume in one second (%FEV1) (r = 0.33, p < 0.001), body mass index (BMI) (r = 0.24, p = 0.005), and fat-free mass index (r = 0.31, p = 0.005), and negatively correlated with residual volume divided by total lung capacity (r = −0.27, p = 0.003). Receiver-operating characteristic curve analysis revealed an optimal BMI cutoff of 21.96 kg/m2 for predicting moderate/severe OSA. A BMI ≥ 21.96 kg/m2 was associated with OSA among participants with %FEV1 ≥ 50%, but not those with %FEV1 < 50%. This study revealed an interaction between airflow limitation and hyperinflation, nutritional status, and OSA.