Inflammatory Profiles and Clinical Features of Coronavirus 2019 Survivors 3 Months After Discharge in Wuhan, China.

BACKGROUND: Postdischarge immunity and its correlation with clinical features among patients recovered from coronavirus disease 2019(COVID-19) are poorly described. This prospective cross-sectional study explored the inflammatory profiles and clinical recovery of patients with COVID-19 at 3 months after hospital discharge. METHODS: Patients with COVID-19 discharged from 4 hospitals in Wuhan, recovered asymptomatic patients (APs) from an isolation hotel, and uninfected healthy controls (HCs) were recruited. Viral nucleic acid and antibody detection, laboratory examination, computed tomography, pulmonary function assessment, multiplex cytokine assay, and flow cytometry were performed. RESULTS: The72 age-, sex- and body mass index-matched participants included 19 patients with severe/critical COVID-19 (SPs), 20 patients with mild/moderate COVID-19 (MPs), 16 APs, and 17 HCs. At 3 months after discharge, levels of proinflammatory cytokines and factors related to vascular injury/repair in patients recovered from COVID-19 had not returned to those of the HCs, especially among recovered SPs compared with recovered MPs and APs. These cytokines were significantly correlated with impaired pulmonary function and chest computed tomographic abnormalities. However, levels of immune cells had returned to nearly normal levels and were not significantly correlated with abnormal clinical features. CONCLUSION: Vascular injury, inflammation, and chemotaxis persisted in patients with COVID-19 and were correlated with abnormal clinical features 3 months after discharge, especially in recovered SPs.

Multisystem Inflammatory Syndrome Following SARS-CoV-2 Infection in Children: One Year after the Onset of the Pandemic in a High-Incidence Area.

SARS-CoV-2 infection in children can trigger cardiovascular manifestations potentially requiring an intensive treatment and defining a new entity named Multisystem Inflammatory Syndrome in Children (MIS-C), whose features partially overlap with Kawasaki Disease (KD). A cross-sectional study including all diagnoses of MIS-C and KD from April 2020 to May 2021 in our metropolitan area was conducted evaluating clinical, laboratory (including immunological response, cytokines, and markers of myocardial damage), and cardiac (coronary and non-coronary) features at onset of the diseases. Evolution of ventricular dysfunction, valve regurgitations, and coronary lesions was documented. The severity of the disease was also considered based on the need for inotropic support and ICU admission. Twenty-four MIS-C were diagnosed (14 boys, median age 82 months): 13/24 cases (54.17%) presented left ventricular dysfunction, 12/24 (50%) required inotropic support, and 10/24 (41.67%) developed coronary anomalies (CALs). All patients received steroids and IVIG at a median time of 5 days (IQR1:4, IQR3:6.5) from onset of fever and heart function normalized 6 days (IQR1: 5, IQR3: 7) after therapy, while CALs persisted in one. One patient (12.5%) required infliximab because of refractory disease and still presented CALs 18 days after therapy. During the same study period, 15 KD were diagnosed: none had ventricular dysfunction, while 7/15 (46.67%) developed CALs. Three out of 15 patients (20%) still presented CALs 46 days from onset. Compared to KD, MIS-C pts have significantly higher IL8 and similar lymphocytes subpopulations. Despite a more severe presentation and initial cardiac findings compared to KD, the myocardial injury in MIS-C has a rapid response to immunomodulatory treatment (median time 6 days), in terms of ventricular function, valve regurgitations, and troponin. Incidence of CALs is similar at onset, but it tends to regress in most of the cases of MIS-C differently than in KD where CALs persist in up to 40% in the subacute stage after treatment.

Two novel nomograms based on inflammatory cytokines or lymphocyte subsets to differentially diagnose severe or critical and Non-Severe COVID-19.

We intend to evaluate the differences of the clinical characteristics, cytokine profiles and immunological features in patients with different severity of COVID-19, and to develop novel nomograms based on inflammatory cytokines or lymphocyte subsets for the differential diagnostics for severe or critical and non-severe COVID-19 patients. We retrospectively studied 254 COVID-19 patients, 90 of whom were severe or critical patients and 164 were non-severe patients. Severe or critical patients had significantly higher levels of inflammatory cytokines than non-severe patients as well as lower levels of lymphocyte subsets. Significantly positive correlations between cytokine profiles were observed, while they were all significantly negatively correlated with lymphocyte subsets. Two effective nomograms were developed according to two multivariable logistic regression cox models based on inflammatory cytokine profiles and lymphocyte subsets separately. The areas under the receiver operating characteristics of two nomograms were 0.834 (95% CI: 0.779-0.888) and 0.841 (95% CI: 0.756-0.925). The bootstrapped-concordance indexes of two nomograms were 0.834 and 0.841 in training set, and 0.860 and 0.852 in validation set. Calibration curves and decision curve analyses demonstrated that the nomograms were well calibrated and had significantly more clinical net benefits. Our novel nomograms can accurately predict disease severity of COVID-19, which may facilitate the identification of severe or critical patients and assist physicians in making optimized treatment suggestions.

Inflammation-associated factors for predicting in-hospital mortality in patients with COVID-19.

The aim is to explore the relation between inflammation-associated factors and in-hospital mortality and investigate which factor is an independent predictor of in-hospital death in patients with coronavirus disease-2019. This study included patients with coronavirus disease-2019, who were hospitalized between February 9, 2020, and March 30, 2020. Univariate Cox regression analysis and least absolute shrinkage and selection operator regression (LASSO) were used to select variables. Multivariate Cox regression analysis was applied to identify independent risk factors in coronavirus disease-2019. A total of 1135 patients were analyzed during the study period. A total of 35 variables were considered to be risk factors after the univariate regression analysis of the clinical characteristics and laboratory parameters (p < .05), and LASSO regression analysis screened out seven risk factors for further study. The six independent risk factors revealed by multivariate Cox regression were myoglobin (HR, 5.353; 95% CI, 2.633-10.882; p < .001), C-reactive protein (HR, 2.063; 95% CI, 1.036-4.109; p = .039), neutrophil count (HR, 2.015; 95% CI, 1.154-3.518; p = .014), interleukin 6 (Il-6; HR, 9.753; 95% CI, 2.952-32.218; p < .001), age (HR, 2.016; 95% CI, 1.077-3.773; p = .028), and international normalized ratio (HR, 2.595; 95% CI, 1.412-4.769; p = .002). Our results suggested that inflammation-associated factors were significantly associated with in-hospital mortality in coronavirus disease-2019 patients. C-reactive protein, neutrophil count, and interleukin 6 were independent factors for predicting in-hospital mortality and had a better independent predictive ability. We believe these findings may allow early identification of the patients at high risk for death, and can also assist in better management of these patients.