Separating Daily 1 km PM2.5 Inorganic Chemical Composition in China since 2000 via Deep Learning Integrating Ground, Satellite, and Model Data.

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 µg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

The predictive role of lymphocyte subsets and laboratory measurements in COVID-19 disease: a retrospective study.

AIM: The aim of this study was to investigate the predictive role of lymphocyte subsets and other laboratory measurements in patients with COVID-19. METHODS: Electronic medical records of adult patients with confirmed diagnosis of COVID-19 from the Shanghai Public Health Clinical Center were reviewed retrospectively to obtain relevant data. RESULTS: The mean age of patients was 40.98 ± 15.95 years, with 58% of the patients being males. The cutoff values at the intensive care unit (ICU) admission, mechanical ventilation, and mortality were CD4+ cells (267, 198, and 405), CD8+ cells (263, 203, and 182), and CD4+ /CD8+ cells (1.4, 1.8, and 1.4). The cutoffs below these values indicate the higher chances of disease progression. Higher CD4+ cell count led to lesser chances for ICU admission [odds ratio (OR) (95% confidence interval (CI): 0.994 (0.991, 0.997); p = 0.0002] and mortality [OR (95% CI): 0.988 (0.979, 0.99); p = 0.001], higher CD8+ count was an independent risk factor for ICU admission. T-cell count positively correlated with total lymphocyte count and platelets, while negatively correlated with D-dimer and lactate dehydrogenase (LDH). Among patients with non-severe COVID-19, median CD8+ T cell, CD4+ T cell, total lymphocyte count, and platelets were 570, 362, 1.45, and 211, respectively, while median values decreased to 149, 106, 0.64, and 172, respectively, in patients with severe COVID-19. CONCLUSION: Lower T lymphocyte subsets were significantly associated with higher admission to ICU, mechanical ventilation, and mortality among patients with COVID-19. A cutoff value of ICU admission, mechanical ventilation, and mortality below CD4+ cells (267, 198, and 405), CD8+ cells (263, 203, 182), and CD4+/CD8+ cells (1.4, 1.8, 1.4) may help identify patients at high risk of disease progression. The continuous evaluation of laboratory indices may help with dismal prognosis and prompt intervention to improve outcomes.

The effect of coagulation factors in 2019 novel coronavirus patients: A systematic review and meta-analysis.

BACKGROUND: The role of coagulation dysfunction in Severe Coronavirus Disease 2019 (COVID-19) is inconsistent. We aimed to explore the impact of coagulation dysfunction amongst patients with COVID-19. METHODS: We searched PubMed, Cochrane and Embase databases from December 1, 2019 to April 27, 2020 following Meta-analysis of Observational Studies in Epidemiology (MOOSE) guidelines. Data about coagulation (Platelets, PT, APTT, fibrin, fibrinogen degradation products, D-dimer), prevalence of coagulation dysfunction and mortality were extracted. Meta regression was used to explore the heterogeneity. RESULTS: Sixteen observational studies were included, comprising 2, 139 patients with confirmed COVID-19. More severe COVID-19 cases tended to have higher mean D-dimer (SMD 0.78, 95% CI 0.53 to 1.03, P < .001). The similar pattern occurred with PT and fibrin, with a contrary trend for PLTs. Coagulation dysfunction was more frequent in severe cases compared to less severe (SMD 0.46, 95% CI 0.25 to 0.67, P < .001). Higher mortality was associated with COVID-19-related coagulopathy (RR 10.86, 2.86 to 41.24, P < .001). Prevalence of ARDS was increased in more severe patients than less severe cases (RR 16.52, 11.27 to 24.22, P < .001). PT, fibrin and D-dimer levels elevated significantly in non-survivors during hospitalization. CONCLUSION: Presence of coagulation dysfunction might be associated with COVID-19 severity, and coagulopathy might be associated with mortality. Coagulation markers including PT, fibrin and D-dimer may imply the progression of COVID-19. This illuminates the necessity of effectively monitoring coagulation function for preventing COVID-19-related coagulopathy, especially in severe patients. For the obvious heterogeneity, the quality of the evidence is compromised. Future rigorous randomized controlled trials that assess the correlation between coagulation and COVID-19 are needed. TRIAL REGISTRATION: PROSPERO (CRD42020183514).

Clinical risk factors for mortality of hospitalized patients with COVID-19: systematic review and meta-analysis.

BACKGROUND: New evidence from retrospective cohort studies on risk of death from COVID-19 infection became available. We aimed to systematically review the clinical risk factors for fatal outcome of COVID-19. METHODS: We performed meta-analysis, using PubMed, EMBASE and Cochrane databases from December 1 2019 to June 10 2020. The meta-analysis summarized clinical, laboratory, radiological features, and complications of non-survivors with confirmed COVID-19. In addition, a fixed- or random-effects model was adopted based on the heterogeneity among studies. We also used funnel-plot with Egger's tests to screen potential publication bias. RESULTS: In total, twenty studies with 15,408 COVID-19 cases were included in our meta-analysis. Male, current smoking, and older age were associated with in-hospital death. Patients aged 60 years or over had the highest pooled ORs [OR 4.94 (2.89, 8.44)]. Non-survivors were more likely to have diabetes, hypertension, cardiovascular disease (CVD), respiratory disease, or chronic kidney disease (CKD). Respiratory disease had the highest pooled ORs [OR 2.55 (2.14, 3.05)]. Dyspnea [OR 3.31 (1.78, 6.16); I2 : 83%] and fatigue [OR 1.36 (1.07, 1.73); I2 : 0%] were associated with increased risk of death. Increased white blood cell count, decreased lymphocyte and platelet counts, were also associated with increased risk of death. Biomarkers of coagulation function, inflammation, liver and kidney function, cardiac and muscle injury were also elevated in nonsurvivors. CONCLUSIONS: Male, current smoking patients aged 60 years or over might face a greater risk of in-hospital death and the comorbidities such as diabetes, hypertension, CVD, respiratory disease, and CKD could also influence the prognosis of the COVID-19. Clinical feature such as dyspnea and fatigue could imply the exacerbation and even death. Our findings highlighted early markers of mortality which were beneficial to identify fatal COVID-19.

Clinical characteristics of 71 patients with coronavirus disease 2019. / 71例2019å† çŠ¶ç— æ¯’ç— ä¸´åºŠç‰¹å¾åˆ†æž.

OBJECTIVES: To analyze the clinical characteristics of 71 patients with coronavirus disease 2019 (COVID-19). METHODS: The general data, epidemiological data, laboratory tests, imaging examinations, and treatment of 71 patients with COVID-19 admitted to the Sixth People's Hospital of Zhengzhou from January 19, 2020 to March 3, 2020 were retrospectively analyzed. RESULTS: Of the 71 COVID-19 patients, the ages were 4-84 (41.29±15.21) years, 38 (53.5%) patients were male, 33 (46.5%) were female, and 52 (73.2%) were in 22 clusters. The main clinical manifestations were fever (78.9%), cough (64.8%), and sputum (38.0%). The fever was mainly low and moderate, with 49 patients (69.0%) at 37.3-39.0 ℃. Most of the leukocytes, neutrophils, and lymphocytes were normal, accounting for 47 (66.2%), 51 (71.8%), and 51 (71.8%) patients, respectively; a few of them were decreased, accounting for 21 (29.6%), 16 (22.5%), and 20 (28.2%) patients, respectively. There were 38 (53.5%) and 31 (43.7%) patients with the decreased CD4+ and CD8+ T cell counts, respectively. There were 41 (57.7%), 38 (53.5%), 32 (45.1%), 26(36.6%), 22 (31.0%), 20 (28.2%), 14 (19.7%), 14 (19.7%), and 9 (12.7%) patients with the increased levels of C-reactive protein, erythrocyte sedimentation rate, procalcitonin, fibrinogen,interleukin 6, lactate dehydrogenase,D-dimer,alanine aminotransferase, and aspartate aminotransferase, respectively. Of the 71 patients, the lung was involved in 60 (84.5%) patients, the double lung was involved in 47 (66.2%) patients, and the single lung was involved in 13 (18.3%) patients. The course of the disease was long, and the time from symptom onset to the second severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid negative transformation was (17.22±6.34) days.There were no significant differences in the incubation period (t=-0.453, P>0.05), the complicates (χ2=0.042, P>0.05), and the time from symptom onset to diagnosis (t=-1.330, P>0.05) in patients between the non-severe group and the severe group. The onset age, gender, SARS-CoV-2 nucleic acid negative time, lymphocyte count, D-dimer, C-reactive protein, total bilirubin, direct bilirubin, lactate dehydrogenase, calcium ion, CD4+ T cell count, CD8+ T cell count, calcitonin, procalcitonin, and troponin were significantly different between the severe group and the non-severe group (all P<0.05). Among the 71 patients, 4 (5.6%) patients were mild, 59 (83.1%) were normal, and 8 (11.3%) were severe or critical. CONCLUSIONS: The aggregation phenomenon of COVID-19 is obvious. Fever and cough are the main clinical manifestations. White blood cells, neutrophils, and lymphocytes in the most patients in the early onset are normal. Most COVID-19 patients are light and ordinary type, with good prognosis.

The Course of Mild and Moderate COVID-19 Infections-The Unexpected Long-Lasting Challenge.

BACKGROUND: The course of disease in mild and moderate COVID-19 has many implications for mobile patients, such as the risk of spread of the infection, precautions taken, and investigations targeted at preventing transmission. METHODS: Three hundred thirty-one adults were hospitalized from January 21 to February 22, 2020, and classified as severe (10%) or critical (4.8%) cases; 1.5% died. Two hundred eighty-two (85.2%) mild or moderate cases were admitted to regular wards. Epidemiological, demographic, clinical, chest computed tomography (CT) scan, laboratory, treatment, and outcome data from patient records were analyzed retrospectively. RESULTS: Patients were symptomatic for 9.82±5.75 (1-37) days. Pulmonary involvement was demonstrated on a chest CT scan in 97.9% of cases. It took 16.81±8.54 (3-49) days from the appearance of the first symptom until 274 patients tested virus-negative in naso- and oropharyngeal (NP) swabs, blood, urine, and stool, and 234 (83%) patients were asymptomatic for 9.09±7.82 (1-44) days. Subsequently, 131 patients were discharged. One hundred sixty-nine remained in the hospital; these patients tested virus-free and were clinically asymptomatic because of widespread persisting or increasing pulmonary infiltrates. Hospitalization took 16.24±7.57 (2-47) days; the time interval from the first symptom to discharge was 21.37±7.85 (3-52) days. CONCLUSIONS: With an asymptomatic phase, disease courses are unexpectedly long until the stage of virus negativity. NP swabs are not reliable in the later stages of COVID-19. Pneumonia outlasts virus-positive tests if sputum is not acquired. Imminent pulmonary fibrosis in high-risk groups demands follow-up examinations. Investigation of promising antiviral agents should heed the specific needs of mild and moderate COVID-19 patients.

Dysfunction of adaptive immunity is related to severity of COVID-19: a retrospective study.

BACKGROUND: In December of 2019, coronavirus disease 2019 (Covid-19) was reported in Wuhan, China, and has now rapidly swept around the world. Much research has been carried out since the outbreak, but few studies have focused on the dysfunction of the adaptive immunity. METHODS: In this retrospective and multi-center study, 373 patients with laboratory-confirmed COVID-19 from Shanghai Public Health Clinical Center and Affiliated Hospital of Putian University were recruited. Demographic, clinical, radiological features, and laboratory data were recorded and analyzed at admission and at discharge. Results of immunological tests were followed up until the patients were discharged. RESULTS: Of the 373 patients with COVID-19 pneumonia, 322 were in the non-severe group and 51 were in the severe group. Number of T cells, CD4+ and CD8+ T cells, and total lymphocytes declined remarkably upon admission and elevated when the patients were discharged. At admission, counts of total lymphocytes, T cells, CD4+ and CD8+ T cells, and levels of C3 and C4 in the severe group were lower than those in the non-severe group, whereas the neutrophil to lymphocyte ratio (NLR) was higher in the severe group. Counts of T cells, CD4+ and CD8+ T cells, and total lymphocytes were negatively correlated with lactate dehydrogenase and C-reactive protein. CONCLUSION: COVID-19 might target adaptive immunity and cause a decrease in lymphocytes, especially T cells and subsets. Physicians should pay close attention to the adaptive immunity of patients upon admission. Monitoring NLR, T lymphocytes, and subsets would help physicians with the proper diagnosis and treatment of COVID-19.The reviews of this paper are available via the supplemental material section.

COVID-19 with Different Severities: A Multicenter Study of Clinical Features.

Rationale: The coronavirus disease (COVID-19) pandemic is now a global health concern.Objectives: We compared the clinical characteristics, laboratory examinations, computed tomography images, and treatments of patients with COVID-19 from three different cities in China.Methods: A total of 476 patients were recruited from January 1, 2020, to February 15, 2020, at three hospitals in Wuhan, Shanghai, and Anhui. The patients were divided into four groups according to age and into three groups (moderate, severe, and critical) according to the fifth edition of the Guidelines on the Diagnosis and Treatment of COVID-19 issued by the National Health Commission of China.Measurements and Main Results: The incidence of comorbidities was higher in the severe (46.3%) and critical (67.1%) groups than in the moderate group (37.8%). More patients were taking angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers in the moderate group than in the severe and critical groups. More patients had multiple lung lobe involvement and pleural effusion in the critical group than in the moderate group. More patients received antiviral agents within the first 4 days in the moderate group than in the severe group, and more patients received antibiotics and corticosteroids in the critical and severe groups. Patients >75 years old had a significantly lower survival rate than younger patients.Conclusions: Multiple organ dysfunction and impaired immune function were the typical characteristics of patients with severe or critical illness. There was a significant difference in the use of angiotensin-converting enzyme inhibitors/angiotensin II receptor blockers among patients with different severities of disease. Involvement of multiple lung lobes and pleural effusion were associated with the severity of COVID-19. Advanced age (≥75 yr) was a risk factor for mortality.