Association of domain-specific physical activity with albuminuria among prediabetes and diabetes: a large cross-sectional study.

BACKGROUND: Albuminuria, the presence of excess of protein in urine, is a well-known risk factor for early kidney damage among diabetic/prediabetic patients. There is a complex interaction between physical activity (PA) and albuminuria. However, the relationship of specific-domain PA and albuminuria remained obscure. METHODS: Albuminuria was defined as urinary albumin/creatinine ratio (ACR) > 30 mg/g. PA was self-reported by participants and classified into transportation-related PA (TPA), occupation-related PA (OPA), and leisure-time PA (LTPA). Weighted logistic regression was conducted to compute the odds ratios (ORs) and 95% confidence intervals (CIs). Restricted cubic spline (RCS) was used to evaluate the dose-response of PA domains with the risk of albuminuria. RESULTS: A total of 6739 diabetic/prediabetic patients (mean age: 56.52 ± 0.29 years) were enrolled in our study, including 3181 (47.20%) females and 3558 (52.80%) males. Of them, 1578 (23.42%) were identified with albuminuria, and 5161(76.58%) were without albuminuria. Diabetic/prediabetic patients who adhered the PA guidelines for total PA had a 22% decreased risk of albuminuria (OR = 0.78, 95%CI 0.64-0.95), and those met the PA guidelines for LTPA had a 28% decreased of albuminuria (OR = 0.72, 95%CI 0.57-0.92). However, OPA and TPA were both not associated with decreased risk of albuminuria. RCS showed linear relationship between the risk of albuminuria with LTPA. CONCLUSIONS: Meeting the PA guideline for LTPA, but not OPA and TPA, was inversely related to the risk of albuminuria among diabetic/prediabetic patients. Additionally, achieving more than 300 min/week of LTPA conferred the positive effects in reducing albuminuria among diabetic/prediabetic patients.

Associations of starchy and non-starchy vegetables with risk of metabolic syndrome: evidence from the NHANES 1999-2018.

BACKGROUND: Higher dietary quality, including increased vegetable consumption, was associated with a reduced risk of metabolic syndrome (MetS). However, specific vegetable consumption in the development of MetS remains obscure. Our study aimed to investigate the correlation between starchy and non-starchy vegetables and MetS. METHODS: Secondary data analysis from the National Health and Nutrition Examination Survey (NHANES 1999-2018). MetS was defined by National Cholesterol Education Program-Adult treatment Panel III (NCEP ATPIII) and dietary consumption was assessed by trained staff using two 24-h diet recall methods. Weighted logistic regression analysis was carried out to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Subgroup analyses and restricted cubic spline (RCS) regression were performed to further investigate specific vegetable subtypes and MetS. RESULTS: This research enrolled 24,646 individuals (11,725 females and 12,921 males), with an average age of 45.84 ± 0.23 years. Approximately 15,828(64.22%) participants were defined to be with non-MetS and 8818(35.78%) were with MetS. Both total starchy vegetables and potatoes were associated with increased MetS risk, with the corresponding OR per standard deviation (SD) (95%CI, p-trend) being 1.06(1.02-1.11, p-trend = 0.028) and 1.08(1.04-1.13, p-trend = 0.011), respectively. However, an inverse correlation was found between dark-green vegetables and MetS, and the OR per SD (95%CI, p-trend) was 0.93(0.90-0.97, p-trend = 0.010). Subgroup analyses showed that the positive associations of starchy vegetables and potatoes on MetS risk were stronger in non-Hispanic White participants (p for interaction < 0.050). CONCLUSION: Total starchy vegetables and white potatoes were both associated with an increased risk of MetS, while consumption of dark-green vegetables was negatively associated with MetS risk. These findings might provide a promising and healthy dietary strategy for preventing MetS.

A prospective cohort study on radiological and physiological outcomes of recovered COVID-19 patients 6 months after discharge.

BACKGROUND: This study investigated patients' long-term radiological and physiological outcomes with coronavirus disease 2019 (COVID-19). METHODS: A total of 52 patients (26 men and 26 women, 32 with moderate COVID-19 and 20 with severe COVID-19, with a median age of 50.5 years) who had COVID-19 participated in this study. Follow-up thin-section chest computed tomography (CT) scans were performed at 1, 3, and 6 months after discharge. Cardiopulmonary exercise testing was performed on 37 patients 6 months after discharge. The clinical data and the chest CT findings were recorded and analyzed. RESULTS: The predominant chest CT patterns of abnormalities observed at 6 months after discharge were parenchymal band, interlobular septal thickening, and traction bronchiectasis. The cumulative percentage of the complete radiological resolution was 17%, 42%, 67%, and 75% at discharge and 1, 3, and 6 months after discharge, respectively. A subgroup analysis revealed that 88% of patients with moderate type and 55% of patients with severe type COVID-19 achieved complete radiological resolution at 6 months after discharge, and the difference between the 2 groups was significant (P<0.001). The following risk factors were found to be associated with an incomplete radiological resolution at 6 months after discharge: an age >50 years old, the severe type of COVID-19, a hospital stay >18 days, mechanical ventilation, steroid therapy, immunoglobin therapy, an opacity score at discharge >4, and a volume of opacity at discharge >235 mL. CONCLUSIONS: Chest CT lesions were absorbed without any sequelae in most patients with COVID-19; however, fibrotic-like changes and cardiopulmonary insufficiency were still present in a considerable proportion of COVID-19 survivors at 6 months after discharge, especially in patients with severe type COVID-19.

Antibodies Can Last for More Than 1 Year After SARS-CoV-2 Infection: A Follow-Up Study From Survivors of COVID-19.

Background: COVID-19 is a global pandemic. The prevention of SARS-CoV-2 infection and the rehabilitation of survivors are currently the most urgent tasks. However, after patients with COVID-19 are discharged from the hospital, how long the antibodies persist, whether the lung lesions can be completely absorbed, and whether cardiopulmonary abnormalities exist remain unclear. Methods: A total of 56 COVID-19 survivors were followed up for 12 months, with examinations including serum virus-specific antibodies, chest CT, and cardiopulmonary exercise testing. Results: The IgG titer of the COVID-19 survivors decreased gradually, especially in the first 6 months after discharge. At 6 and 12 months after discharge, the IgG titer decreased by 68.9 and 86.0%, respectively. The IgG titer in patients with severe disease was higher than that in patients with non-severe disease at each time point, but the difference did not reach statistical significance. Among the patients, 11.8% were IgG negative up to 12 months after discharge. Chest CT scans showed that at 3 and 10 months after discharge, the lung opacity had decreased by 91.9 and 95.5%, respectively, as compared with that at admission. 10 months after discharge, 12.5% of the patients had an opacity percentage >1%, and 18.8% of patients had pulmonary fibrosis (38.5% in the severe group and 5.3% in the non-severe group, P < 0.001). Cardiopulmonary exercise testing showed that 22.9% of patients had FEV1/FVC%Pred <92%, 17.1% of patients had FEV1%Pred <80%, 20.0% of patients had a VO2 AT <14 mlO2/kg/min, and 22.9% of patients had a VE/VCO2 slope >30%. Conclusions: IgG antibodies in most patients with COVID-19 can last for at least 12 months after discharge. The IgG titers decreased significantly in the first 6 months and remained stable in the following 6 months. The lung lesions of most patients with COVID-19 can be absorbed without sequelae, and a few patients in severe condition are more likely to develop pulmonary fibrosis. Approximately one-fifth of the patients had cardiopulmonary dysfunction 6 months after discharge.

Predicting the Key Genes Involved in Aortic Valve Calcification Through Integrated Bioinformatics Analysis.

Background: Valvular heart disease is obtaining growing attention in the cardiovascular field and it is believed that calcific aortic valve disease (CAVD) is the most common valvular heart disease (VHD) in the world. CAVD does not have a fully effective treatment to delay its progression and the specific molecular mechanism of aortic valve calcification remains unclear. Materials and Methods: We obtained the gene expression datasets GSE12644 and GSE51472 from the public comprehensive free database GEO. Then, a series of bioinformatics methods, such as GO and KEGG analysis, STING online tool, Cytoscape software, were used to identify differentially expressed genes in CAVD and healthy controls, construct a PPI network, and then identify key genes. In addition, immune infiltration analysis was used via CIBERSORT to observe the expression of various immune cells in CAVD. Results: A total of 144 differential expression genes were identified in the CAVD samples in comparison with the control samples, including 49 up-regulated genes and 95 down-regulated genes. GO analysis of DEGs were most observably enriched in the immune response, signal transduction, inflammatory response, proteolysis, innate immune response, and apoptotic process. The KEGG analysis revealed that the enrichment of DEGs in CAVD were remarkably observed in the chemokine signaling pathway, cytokine-cytokine receptor interaction, and PI3K-Akt signaling pathway. Chemokines CXCL13, CCL19, CCL8, CXCL8, CXCL16, MMP9, CCL18, CXCL5, VCAM1, and PPBP were identified as the hub genes of CAVD. It was macrophages that accounted for the maximal proportion among these immune cells. The expression of macrophages M0, B cells memory, and Plasma cells were higher in the CAVD valves than in healthy valves, however, the expression of B cells naïve, NK cells activated, and macrophages M2 were lower. Conclusion: We detected that chemokines CXCL13, CXCL8, CXCL16, and CXCL5, and CCL19, CCL8, and CCL18 are the most important markers of aortic valve disease. The regulatory macrophages M0, plasma cells, B cells memory, B cells naïve, NK cells activated, and macrophages M2 are probably related to the occurrence and the advancement of aortic valve stenosis. These identified chemokines and these immune cells may interact with a subtle adjustment relationship in the development of calcification in CAVD.

Follow-Up Study of the Chest CT Characteristics of COVID-19 Survivors Seven Months After Recovery.

Background: It has remained a concern whether any long-term pulmonary sequelae exist for COVID-19 survivors. Methods: Forty-one patients (22 men and 19 women, 50 ± 14 years) confirmed with COVID-19 performed follow-up chest CT and cardiopulmonary exercise testing at 7 months after discharge. Patients were divided into fibrosis group and non-fibrosis group according to the evidence of fibrosis on follow-up CT. The clinical data and the CT findings were recorded and analyzed. Results: The predominant CT patterns of abnormalities observed at 7 months after discharge were parenchymal band (41%), interlobular septal thickening (32%), and traction bronchiectasis (29%). Sixty-one percent of the patients achieved complete radiological resolution, and 29% of patients developed pulmonary fibrosis. Compared with the patients in the non-fibrosis group, the patients in the fibrosis group were older, with a longer hospital stay, a higher rate of steroid and mechanical ventilation therapy, lower levels of lymphocyte and T cell count, higher levels of D-dimer and lactic dehydrogenase, and higher quantitative CT parameters (opacity score, volume of opacity, and percentage of opacity) at discharge. Besides, oxygen consumption and metabolic equations were decreased and ventilatory equivalent for carbon dioxide was increased in patients in the fibrosis group. Logistic regression analyses revealed that age, steroid therapy, presence of traction bronchiectasis on chest CT at discharge, and opacity score at discharge, were independent risk factors for developing pulmonary fibrosis at 7 months after discharge. Receiver operating characteristic analysis revealed that the combined clinical-radiological model was better than the clinical-only model in the prediction of pulmonary fibrosis. Conclusions: The chest CT lesions could be absorbed without any sequelae for most patients with COVID-19, whereas older patients with severe conditions are more prone to develop fibrosis, which may further lead to cardiopulmonary insufficiency. The combined clinical-radiological model may predict the formation of pulmonary fibrosis early.

COVID-19 pneumonia: CT findings of 122 patients and differentiation from influenza pneumonia.

OBJECTIVES: To investigate the clinical and chest CT characteristics of COVID-19 pneumonia and explore the radiological differences between COVID-19 and influenza. MATERIALS AND METHODS: A total of 122 patients (61 men and 61 women, 48 ± 15 years) confirmed with COVID-19 and 48 patients (23 men and 25 women, 47 ± 19 years) confirmed with influenza were enrolled in the study. Thin-section CT was performed. The clinical data and the chest CT findings were recorded. RESULTS: The most common symptoms of COVID-19 were fever (74%) and cough (63%), and 102 patients (83%) had Wuhan contact. Pneumonia in 50 patients with COVID-19 (45%) distributed in the peripheral regions of the lung, while it showed mixed distribution in 26 patients (74%) with influenza (p = 0.022). The most common CT features of the COVID-19 group were pure ground-glass opacities (GGO, 36%), GGO with consolidation (51%), rounded opacities (35%), linear opacities (64%), bronchiolar wall thickening (49%), and interlobular septal thickening (66%). Compared with the influenza group, the COVID-19 group was more likely to have rounded opacities (35% vs. 17%, p = 0.048) and interlobular septal thickening (66% vs. 43%, p = 0.014), but less likely to have nodules (28% vs. 71%, p < 0.001), tree-in-bud sign (9% vs. 40%, p < 0.001), and pleural effusion (6% vs. 31%, p < 0.001). CONCLUSIONS: There are significant differences in the CT manifestations of patients with COVID-19 and influenza. Presence of rounded opacities and interlobular septal thickening, with the absence of nodules and tree-in-bud sign, and with the typical peripheral distribution, may help us differentiate COVID-19 from influenza. KEY POINTS: • Typical CT features of COVID-19 include pure ground-glass opacities (GGO), GGO with consolidation, rounded opacities, bronchiolar wall thickening, interlobular septal thickening, and a peripheral distribution. • Presence of rounded opacities and interlobular septal thickening, with the absence of nodules and tree-in-bud sign, and with the typical peripheral distribution, may help us differentiate COVID-19 from influenza.

Relationships among lymphocyte subsets, cytokines, and the pulmonary inflammation index in coronavirus (COVID-19) infected patients.

We explored the relationships between lymphocyte subsets, cytokines, pulmonary inflammation index (PII) and disease evolution in patients with (corona virus disease 2019) COVID-19. A total of 123 patients with COVID-19 were divided into mild and severe groups. Lymphocyte subsets and cytokines were detected on the first day of hospital admission and lung computed tomography results were quantified by PII. Difference analysis and correlation analysis were performed on the two groups. A total of 102 mild and 21 severe patients were included in the analysis. There were significant differences in cluster of differentiation 4 (CD4+ T), cluster of differentiation 8 (CD8+ T), interleukin 6 (IL-6), interleukin 10 (IL-10) and PII between the two groups. There were significant positive correlations between CD4+ T and CD8+ T, IL-6 and IL-10 in the mild group (r2  = 0·694, r 2  = 0·633, respectively; P < 0·01). After 'five-in-one' treatment, all patients were discharged with the exception of the four who died. Higher survival rates occurred in the mild group and in those with IL-6 within normal values. CD4+ T, CD8+ T, IL-6, IL-10 and PII can be used as indicators of disease evolution, and the PII can be used as an independent indicator for disease progression of COVID-19.

High-Resolution Computed Tomography Manifestations of 5 Pediatric Patients With 2019 Novel Coronavirus.

We present clinical and chest computed tomography (CT) features of 5 cases of pediatric patients with 2019 novel coronavirus. Two patients had fever and dry cough, whereas the rest of 3 patients were asymptomatic. Three patients had unilateral ground glass opacities with or without consolidation in the subpleural region on high-resolution chest CT, 1 patient had bilateral ground glass opacities, and 1 patient was negative for CT. We note that up to 66.7% asymptomatic patients had pulmonary lesions, so the asymptomatic children with Wuhan contact are recommended to do a 2019 novel coronavirus real-time fluorescence polymerase chain reaction screening. Unlike adult patients, only a small amount of patients had multilobes affected, so we speculate that the pediatric patients generally have milder CT findings than adults.