Lung volume measurement using chest CT in COVID-19 patients: a cohort study in Japan.

OBJECTIVE: This study aimed to investigate the utility of CT quantification of lung volume for predicting critical outcomes in COVID-19 patients. METHODS: This retrospective cohort study included 1200 hospitalised patients with COVID-19 from 4 hospitals. Lung fields were extracted using artificial intelligence-based segmentation, and the percentage of the predicted (%pred) total lung volume (TLC (%pred)) was calculated. The incidence of critical outcomes and posthospitalisation complications was compared between patients with low and high CT lung volumes classified based on the median percentage of predicted TLCct (n=600 for each). Prognostic factors for residual lung volume loss were investigated in 208 patients with COVID-19 via a follow-up CT after 3 months. RESULTS: The incidence of critical outcomes was higher in the low TLCct (%pred) group than in the high TLCct (%pred) group (14.2% vs 3.3%, p<0.0001). Multivariable analysis of previously reported factors (age, sex, body mass index and comorbidities) demonstrated that CT-derived lung volume was significantly associated with critical outcomes. The low TLCct (%pred) group exhibited a higher incidence of bacterial infection, heart failure, thromboembolism, liver dysfunction and renal dysfunction than the high TLCct (%pred) group. TLCct (%pred) at 3 months was similarly divided into two groups at the median (71.8%). Among patients with follow-up CT scans, lung volumes showed a recovery trend from the time of admission to 3 months but remained lower in critical cases at 3 months. CONCLUSION: Lower CT lung volume was associated with critical outcomes, posthospitalisation complications and slower improvement of clinical conditions in COVID-19 patients.

CT-derived vertebral bone mineral density is a useful biomarker to predict COVID-19 outcome.

The low vertebral bone computed tomography (CT) Hounsfield unit values measured on CT scans reflect low bone mineral density (BMD) and are known as diagnostic indicators for osteoporosis. The potential prognostic significance of low BMD defined by vertebral bone CT values for the coronavirus disease 2019 (COVID-19) remains unclear. This study aimed to assess the impact of BMD on the clinical outcome in Japanese patients with COVID-19 and evaluate the association between BMD and critical outcomes, such as high-flow nasal cannula, non-invasive and invasive positive pressure ventilation, extracorporeal membrane oxygenation, or death. We examined the effects of COVID-19 severity on the change of BMD over time. This multicenter retrospective cohort study enrolled 1132 inpatients with COVID-19 from the Japan COVID-19 Task Force database between February 2020 and September 2022. The bone CT values of the 4th, 7th, and 10th thoracic vertebrae were measured from chest CT images. The average of these values was defined as BMD. Furthermore, a comparative analysis was conducted between the BMD on admission and its value 3 months later. The low BMD group had a higher proportion of critical outcomes than did the high BMD group. In a subanalysis stratifying patients by epidemic wave according to onset time, critical outcomes were higher in the low BMD group in the 1st-4th waves. Multivariable logistic analysis of previously reported factors associated with COVID-19 severity revealed that low BMD, chronic kidney disease, and diabetes were independently associated with critical outcomes. At 3 months post-infection, patients with oxygen demand during hospitalization showed markedly decreased BMD than did those on admission. Low BMD in patients with COVID-19 may help predict severe disease after the disease onset. BMD may decrease over time in patients with severe COVID-19, and the impact on sequelae symptoms should be investigated in the future.

Integrated assessment of computed tomography density in pectoralis and erector spinae muscles as a prognostic biomarker for coronavirus disease 2019.

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.

Gastrointestinal symptoms in COVID-19 and disease severity: a Japanese registry-based retrospective cohort study.

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.

Prognostic significance of hypertension history and blood pressure on admission in Japanese patients with coronavirus disease 2019: integrative analysis from the Japan COVID-19 Task Force.

The effect of preexisting hypertension on coronavirus disease 2019 (COVID-19) prognosis remains controversial. Additionally, no studies have compared the association between blood pressure (BP) indices on admission and COVID-19 outcomes using preexisting hypertension status. Therefore, this study aimed to investigate the association between preexisting hypertension and COVID-19 outcomes in Japanese patients with COVID-19 and assess the impact of BP indices on admission on clinical outcomes in patients with and without preexisting hypertension. Preexisting hypertension presence was confirmed based on the patient's clinical history. Critical outcomes were defined as high-flow oxygen use, non-invasive and invasive positive-pressure ventilation, extracorporeal membrane oxygenation, or death during hospitalization. Preexisting hypertension was observed in 64.6% of the patients. Multivariable logistic regression analysis of severe COVID-19 risk factors indicated that preexisting hypertension was independently associated with critical outcomes [adjusted odds ratio (OR): 1.35; 95% confidence interval (CI): 1.05-1.73]. Low or high BP and high pulse pressure on admission were associated with critical outcomes in patients without preexisting hypertension [OR for systolic BP < 100 mmHg: 2.13, 95% CI: 1.21-3.75; OR for high BP stage 2 (160-179 systolic and/or 100-109 mmHg diastolic BP): 2.13, 95% CI: 1.27-3.58; OR for pulse pressure ≥60 mmHg: 1.68, 95% CI: 1.14-2.48]. Preexisting hypertension is a risk factor for critical outcomes in Japanese patients with COVID-19. BP indices are useful biomarkers for predicting COVID-19 outcomes, particularly in patients without preexisting hypertension. Thus, hypertension history, systolic BP, and pulse pressure should be assessed to predict severe COVID-19 outcomes.

Epicardial adipose tissue measured from analysis of adipose tissue area using chest CT imaging is the best potential predictor of COVID-19 severity.

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.

Characteristics of patients with COVID-19 who have deteriorating chest X-ray findings within 48 h: a retrospective cohort study.

The severity of chest X-ray (CXR) findings is a prognostic factor in patients with coronavirus disease 2019 (COVID-19). We investigated the clinical and genetic characteristics and prognosis of patients with worsening CXR findings during early hospitalization. We retrospectively included 1656 consecutive Japanese patients with COVID-19 recruited through the Japan COVID-19 Task Force. Rapid deterioration of CXR findings was defined as increased pulmonary infiltrates in ≥ 50% of the lung fields within 48 h of admission. Rapid deterioration of CXR findings was an independent risk factor for death, most severe illness, tracheal intubation, and intensive care unit admission. The presence of consolidation on CXR, comorbid cardiovascular and chronic obstructive pulmonary diseases, high body temperature, and increased serum aspartate aminotransferase, potassium, and C-reactive protein levels were independent risk factors for rapid deterioration of CXR findings. Risk variant at the ABO locus (rs529565-C) was associated with rapid deterioration of CXR findings in all patients. This study revealed the clinical features, genetic features, and risk factors associated with rapid deterioration of CXR findings, a poor prognostic factor in patients with COVID-19.

Estimating gene-level false discovery probability improves eQTL statistical fine-mapping precision.

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.

Clinical utilization of artificial intelligence-based COVID-19 pneumonia quantification using chest computed tomography - a multicenter retrospective cohort study in Japan.

BACKGROUND: Computed tomography (CT) imaging and artificial intelligence (AI)-based analyses have aided in the diagnosis and prediction of the severity of COVID-19. However, the potential of AI-based CT quantification of pneumonia in assessing patients with COVID-19 has not yet been fully explored. This study aimed to investigate the potential of AI-based CT quantification of COVID-19 pneumonia to predict the critical outcomes and clinical characteristics of patients with residual lung lesions. METHODS: This retrospective cohort study included 1,200 hospitalized patients with COVID-19 from four hospitals. The incidence of critical outcomes (requiring the support of high-flow oxygen or invasive mechanical ventilation or death) and complications during hospitalization (bacterial infection, renal failure, heart failure, thromboembolism, and liver dysfunction) was compared between the groups of pneumonia with high/low-percentage lung lesions, based on AI-based CT quantification. Additionally, 198 patients underwent CT scans 3 months after admission to analyze prognostic factors for residual lung lesions. RESULTS: The pneumonia group with a high percentage of lung lesions (N = 400) had a higher incidence of critical outcomes and complications during hospitalization than the low percentage group (N = 800). Multivariable analysis demonstrated that AI-based CT quantification of pneumonia was independently associated with critical outcomes (adjusted odds ratio [aOR] 10.5, 95% confidence interval [CI] 5.59-19.7), as well as with oxygen requirement (aOR 6.35, 95% CI 4.60-8.76), IMV requirement (aOR 7.73, 95% CI 2.52-23.7), and mortality rate (aOR 6.46, 95% CI 1.87-22.3). Among patients with follow-up CT scans (N = 198), the multivariable analysis revealed that the pneumonia group with a high percentage of lung lesions on admission (aOR 4.74, 95% CI 2.36-9.52), older age (aOR 2.53, 95% CI 1.16-5.51), female sex (aOR 2.41, 95% CI 1.13-5.11), and medical history of hypertension (aOR 2.22, 95% CI 1.09-4.50) independently predicted persistent residual lung lesions. CONCLUSIONS: AI-based CT quantification of pneumonia provides valuable information beyond qualitative evaluation by physicians, enabling the prediction of critical outcomes and residual lung lesions in patients with COVID-19.

Clinical characteristics of patients with COVID-19 harboring detectable intracellular SARS-CoV-2 RNA in peripheral blood cells.

OBJECTIVES: Although SARS-CoV-2 RNAemia has been reported to strongly impact patients with severe COVID-19, the clinical characteristics of patients with COVID-19 harboring detectable intracellular SARS-CoV-2 RNA remain unknown. METHODS: We included adult patients who had developed COVID-19 between February and September 2020. Total white blood cells derived from the buffy coat of peripheral whole blood were used to detect SARS-CoV-2 RNA using the Illumina COVIDSeq test. We compared the clinical characteristics between patients with and without detected viral RNA (detected and undetected groups). RESULTS: Among the 390 patients included, 17 harbored SARS-CoV-2 RNA in peripheral white blood cells. All 17 patients required oxygen support during the disease course and had higher intensive care unit admission (52.9% vs 28.9%, P = 0.035), mortality (17.7% vs 3.5%, P = 0.004), kidney dysfunction (severe, 23.5% vs 6.4%, P = 0.029), and corticosteroid treatment rates (76.5% vs 46.5%, P = 0.016) than those of patients in the undetected group. CONCLUSION: We propose that patients with circulating intracellular SARS-CoV-2 RNA in the peripheral blood exhibited the most severe disease course.

Association between ABO blood group/genotype and COVID-19 in a Japanese population.

An association between coronavirus disease 2019 (COVID-19) and the ABO blood group has been reported. However, such an association has not been studied in the Japanese population on a large scale. Little is known about the association between COVID-19 and ABO genotype. This study investigated the association between COVID-19 and ABO blood group/genotype in a large Japanese population. All Japanese patients diagnosed with COVID-19 were recruited through the Japan COVID-19 Task Force between February 2020 and October 2021. We conducted a retrospective cohort study involving 1790 Japanese COVID-19 patients whose DNA was used for a genome-wide association study. We compared the ABO blood group/genotype in a healthy population (n = 611, control) and COVID-19 patients and then analyzed their associations and clinical outcomes. Blood group A was significantly more prevalent (41.6% vs. 36.8%; P = 0.038), and group O was significantly less prevalent (26.2% vs. 30.8%; P = 0.028) in the COVID-19 group than in the control group. Moreover, genotype OO was significantly less common in the COVID-19 group. Furthermore, blood group AB was identified as an independent risk factor for most severe diseases compared with blood group O [aOR (95% CI) = 1.84 (1.00-3.37)]. In ABO genotype analysis, only genotype AB was an independent risk factor for most severe diseases compared with genotype OO. Blood group O is protective, whereas group A is associated with the risk of infection. Moreover, blood group AB is associated with the risk of the "most" severe disease.

Serum KL-6 levels predict clinical outcomes and are associated with MUC1 polymorphism in Japanese patients with COVID-19.

BACKGROUND: Krebs von den Lungen-6 (KL-6) is a known biomarker for diagnosis and monitoring of interstitial lung diseases. However, the role of serum KL-6 and the mucin 1 (MUC1) variant (rs4072037) in COVID-19 outcomes remains to be elucidated. We aimed to evaluate the relationships among serum KL-6 levels, critical outcomes and the MUC1 variant in Japanese patients with COVID-19. METHODS: This is a secondary analysis of a multicentre retrospective study using data from the Japan COVID-19 Task Force collected from February 2020 to November 2021, including 2226 patients with COVID-19 whose serum KL-6 levels were measured. An optimal serum KL-6 level cut-off to predict critical outcomes was determined and used for multivariable logistic regression analysis. Furthermore, the relationship among the allele dosage of the MUC1 variant, calculated from single nucleotide polymorphism typing data of genome-wide association studies using the imputation method, serum KL-6 levels and COVID-19 critical outcomes was evaluated. RESULTS: Serum KL-6 levels were significantly higher in patients with COVID-19 with critical outcomes (511±442 U/mL) than those without (279±204 U/mL) (p<0.001). Serum KL-6 levels ≥304 U/mL independently predicted critical outcomes (adjusted OR (aOR) 3.47, 95% CI 2.44 to 4.95). Moreover, multivariable logistic regression analysis with age and sex indicated that the MUC1 variant was independently associated with increased serum KL-6 levels (aOR 0.24, 95% CI 0.28 to 0.32) but not significantly associated with critical outcomes (aOR 1.11, 95% CI 0.80 to 1.54). CONCLUSION: Serum KL-6 levels predicted critical outcomes in Japanese patients with COVID-19 and were associated with the MUC1 variant. Therefore, serum KL-6 level is a potentially useful biomarker of critical COVID-19 outcomes.

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

OBJECTIVES: COVID-19 was severe in the Delta variant-dominated epidemic wave (fifth wave) in Japan. The clinical characteristics and effectiveness of COVID-19 vaccination are not fully understood in the Omicron variant-dominated wave (sixth and seventh waves), especially in hospitalized patients. We investigated the relationship between vaccination and disease severity in the Omicron-dominated wave and compared these variant-dominated waves. METHODS: The nationwide COVID-19 database (Japan COVID-19 Task Force) was used to compare clinical characteristics and critical outcomes in patients hospitalized with Delta (fifth, N = 735) vs Omicron-dominated waves (sixth, N = 495; seventh, N = 128). RESULTS: Patients in the sixth and seventh waves had a lower incidence of critical outcomes and respiratory outcomes, and a higher incidence of bacterial infection, although the mortality rate did not differ significantly between waves. In the sixth and seventh waves, 138 (27.9%) and 29 (22.7%) patients with COVID-19 were unvaccinated, respectively. Multivariable analysis adjusted with previously reported factors revealed that the proportion of (1) critical outcomes and (2) respiratory outcomes decreased in a frequency-dependent manner. Thus, (1) (the number of vaccinations): 1-2 times: adjusted odds ratio (aOR) 0.37 (95% confidence interval [CI]; 0.20-0.69); 3-4 times: aOR 0.25 (95% CI; 0.11-0.58); and (2) 1-2 times: aOR 0.43 (95% CI; 0.27-0.66); 3-4 times: aOR 0.36 (95% CI; 0.21-0.60). CONCLUSIONS: Patients hospitalized with COVID-19 with Omicron infections showed a lower incidence of critical outcomes than those with Delta infections, and COVID-19 vaccination may contribute to preventing respiratory failure.

Use of the neutrophil-to-lymphocyte ratio and an oxygen requirement to predict disease severity in patients with COVID-19.

We investigated the association between complete blood count, including neutrophil-to-lymphocyte ratio (NLR) in combination with patient characteristics, and coronavirus disease (COVID-19) outcomes to identify the best prognostic indicator. We analyzed data of patients with confirmed COVID-19 from the nationwide database of the Japan COVID-19 Task Force between February 2020 and November 2021. A composite outcome was defined as the most severe condition, including noninvasive positive-pressure ventilation, high-flow nasal cannula, invasive mechanical ventilation, extracorporeal membrane oxygenation, or death. Of 2425 patients in the analysis, 472 (19.5%) experienced a composite outcome. NLR was the best predictor of composite outcomes, with an area under the curve (AUC) of 0.81, and a sensitivity and specificity of 72.3% and 75.7%, respectively, using a cut-off value of 5.04. The combination of NLR and an oxygen requirement on admission had the highest AUC (0.88). This simple combination may help identify patients at risk of progression to severe disease.

Viral load of SARS-CoV-2 Omicron BA.5 is lower than that of BA.2 despite the higher infectivity of BA.5.

BACKGROUND: Sublineage BA.5 of the SARS-CoV-2 Omicron variant rapidly spread and replaced BA.2 in July 2022 in Tokyo. A high viral load can be a possible cause of high transmissibility. METHODS AND RESULTS: The copy numbers of SARS-CoV-2 in nasopharyngeal swab samples obtained from all patients visiting the hospital where this research was conducted were measured using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Viral genotypes were determined using PCR-based melting curve analysis. Next, whole-genome sequencing was performed using approximately one fifth of the samples to verify the viral genotypes determined using PCR. Then, the copy numbers of the BA.1, BA.2, and BA.5 cases were compared. Contrary to expectations, the copy numbers of the BA.5 cases (median 4.7 × 104 copies/µL, n = 291) were significantly (p = .001) lower than those of BA.2 cases (median 1.1 × 105 copies/µL, n = 184). There was no significant difference (p = .44) between the BA.5 and BA.1 cases (median, 3.3 × 104 copies/µL; n = 215). CONCLUSION: The results presented here suggest that the increased infectivity of BA.5 is not caused by higher viral loads, but presumably by other factors such as increased affinity to human cell receptors or immune escape due to its L452R mutation.

Killer cell immunoglobulin-like receptor three domains long cytoplasmic tail 1 gene *007 may modulate disease progression of human immunodeficiency virus-1 infection in the Japanese population.

One of the KIR allele, KIR3DL1*007, was associated with the progression to acquired immunodeficiency syndrome and not with the susceptibility to HIV-1 infection in the Japanese and Indian populations, implying that KIR3DL1*007-positive NK cells might eliminate HIV-infected cells less effectively than NK cells bearing the other KIR3DL1 alleles or KIR3DS1 alleles.

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.

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.

Clinical significance of prediabetes, undiagnosed diabetes and diagnosed diabetes on critical outcomes in COVID-19: Integrative analysis from the Japan COVID-19 task force.

AIM: Diabetes mellitus (DM) is a known risk factor for severe coronavirus disease 2019 (COVID-19), but the clinical impact of undiagnosed diabetes and prediabetes in COVID-19 are unclear particularly in Japan. We clarify the difference in clinical characteristics, including age, sex, body mass index and co-morbidities, laboratory findings and critical outcomes, in a large Japanese COVID-19 cohort without diabetes, with prediabetes, undiagnosed diabetes and diagnosed diabetes, and to identify associated risk factors. MATERIALS AND METHODS: This multicentre, retrospective cohort study used the Japan COVID-19 Task Force database, which included data on 2430 hospitalized COVID-19 patients from over 70 hospitals from February 2020 to October 2021. The prevalence of prediabetes, undiagnosed diabetes and diagnosed diabetes were estimated based on HbA1c levels or a clinical diabetes history. Critical outcomes were defined as the use of high-flow oxygen, invasive positive-pressure ventilation or extracorporeal membrane oxygenation, or death during hospitalization. RESULTS: Prediabetes, undiagnosed diabetes and diagnosed diabetes were observed in 40.9%, 10.0% and 23.0%, respectively. Similar to diagnosed diabetes, prediabetes and undiagnosed diabetes were risk factors for critical COVID-19 outcomes (adjusted odds ratio [aOR] [95% CI]: 2.13 [1.31-3.48] and 4.00 [2.19-7.28], respectively). HbA1c was associated with COVID-19 severity in prediabetes patients (aOR [95% CI]: 11.2 [3.49-36.3]), but not other groups. CONCLUSIONS: We documented the clinical characteristics and outcomes of Japanese COVID-19 patients according to HbA1c levels or diabetes co-morbidity. As well as undiagnosed and diagnosed diabetes, physicians should be aware of prediabetes related to COVID-19 severity.

Characteristics of hospitalized patients with COVID-19 during the first to fifth waves of infection: a report from the Japan COVID-19 Task Force.

BACKGROUND: We aimed to elucidate differences in the characteristics of patients with coronavirus disease 2019 (COVID-19) requiring hospitalization in Japan, by COVID-19 waves, from conventional strains to the Delta variant. METHODS: We used secondary data from a database and performed a retrospective cohort study that included 3261 patients aged ≥ 18 years enrolled from 78 hospitals that participated in the Japan COVID-19 Task Force between February 2020 and September 2021. RESULTS: Patients hospitalized during the second (mean age, 53.2 years [standard deviation {SD}, ± 18.9]) and fifth (mean age, 50.7 years [SD ± 13.9]) COVID-19 waves had a lower mean age than those hospitalized during the other COVID-19 waves. Patients hospitalized during the first COVID-19 wave had a longer hospital stay (mean, 30.3 days [SD ± 21.5], p < 0.0001), and post-hospitalization complications, such as bacterial infections (21.3%, p < 0.0001), were also noticeable. In addition, there was an increase in the use of drugs such as remdesivir/baricitinib/tocilizumab/steroids during the latter COVID-19 waves. In the fifth COVID-19 wave, patients exhibited a greater number of presenting symptoms, and a higher percentage of patients required oxygen therapy at the time of admission. However, the percentage of patients requiring invasive mechanical ventilation was the highest in the first COVID-19 wave and the mortality rate was the highest in the third COVID-19 wave. CONCLUSIONS: We identified differences in clinical characteristics of hospitalized patients with COVID-19 in each COVID-19 wave up to the fifth COVID-19 wave in Japan. The fifth COVID-19 wave was associated with greater disease severity on admission, the third COVID-19 wave had the highest mortality rate, and the first COVID-19 wave had the highest percentage of patients requiring mechanical ventilation.

Impact of upper and lower respiratory symptoms on COVID-19 outcomes: a multicenter retrospective cohort study.

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.