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Objective: To explore an effective surgical intervention strategy for hepatic echinococcosis complicated with intracystic bile leakage.
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Background: Since December 2019, Coronavirus disease 2019 (COVID-19) has emerged as an international pandemic. COVID-19 patients with myocardial injury might need special attention. However, understanding on this aspect remains unclear. This study aimed to illustrate clinical characteristics and the prognostic value of myocardial injury to COVID-19 patients. Methods: This retrospective, single-center study finally included 304 hospitalized COVID-19 cases confirmed by real-time RT-PCR from January 11 to March 25, 2020. Myocardial injury was determined by serum high-sensitivity troponin I (Hs-TnI). The primary endpoint was COVID-19 associated mortality. Results: Of 304 COVID-19 patients (median age, 65 years; 52.6% males), 88 patients (27.3%) died (61 patients with myocardial injury, 27 patients without myocardial injury on admission). COVID-19 patients with myocardial injury had more comorbidities (hypertension, chronic obstructive pulmonary disease, cardiovascular disease, and cerebrovascular disease); lower lymphocyte counts, higher C-reactive protein (CRP, median, 84.9 vs 28.5 mg/L, p<0.001), procalcitonin levels (median, 0.29 vs 0.06 ng/ml, p<0.001), inflammatory and immune response markers; more frequent need for noninvasive ventilation, invasive mechanical ventilation; and was associated with higher mortality incidence (hazard ratio, HR=7.02, 95% confidence interval, CI, 4.45-11.08, p<0.001) than those without myocardial injury. Myocardial injury (HR=4.55, 95% CI, 2.49-8.31, p<0.001), senior age, CRP levels, and novel coronavirus pneumonia (NCP) types on admission were independent predictors to mortality in COVID-19 patients. Conclusions: COVID patients with myocardial injury on admission is associated with more severe clinical presentation and biomarkers. Myocardial injury and higher HsTNI are both strongest independent predictors to COVID related mortality after adjusting confounding factors. In addition, senior age, CRP levels and NCP types are also associated with mortality. Trial registration: Not applicable.
Subject(s)
Pulmonary Embolism , Coronavirus Infections , Cardiovascular Diseases , Cerebrovascular Disorders , Hypertension , COVID-19 , CardiomyopathiesABSTRACT
Background: COVID-19 cases with suspected returned-positive SRAS-CoV-2 tests following consecutive negative tests have been reported, but evidence-based explanations for this phenomenon is still lacking. We aimed to describe the clinical and laboratory characteristics of returned-positive COVID-19 patients during treatment in comparison with other patients.Methods: From January 20 to April 10, 2020, all COVID-19 inpatient with at least three RT-PCR SARS-CoV-2 tests in Renmin Hospital in Wuhan, China were enrolled. Patients with 2 consecutively negative RT-PCR results followed by a positive result were classified as returned-positive patients, and their characteristics and repeatedly measured laboratory results were compared with the rest of the patients. Linear mixed effects models were performed.Results: A total of 789 COVID-19 patients were included and 22.8% patients returned positive in RT-PCR SARS-CoV-2 test. No significant differences were found for general characteristics between the returned-positive and the control groups. The trends of inflammatory and immune factors including the third component of complement (C3), C-reactive protein, procalcitonin (PCT), IL-4, IL-6, the counts of lymphocyte, CD3+, CD8+, white blood cell and immunoglobulin levels during hospitalization were significantly different between the two groups. During the returned-positive period, C3, PCT, serum IgM, anti-SARS-CoV-2 IgM and anti-SARS-CoV-2 IgG were significantly higher in the returned-positive patients at certain time points.Conclusions: Returned-positive COVID-19 patients appeared to be more sever at admission, and had periodically higher levels in C3, PCT, serum IgM and two specific antibodies during hospitalization. This suggests that positive return of SARS-COV-2 could not be completely explained by false-negative testing and longer observation of these patients is warranted.
Subject(s)
COVID-19ABSTRACT
Objective: To understand the epidemiological characteristics of coronavirus disease 2019 (COVID-19) outbreak in Ganzr Tibetan Autonomous Prefecture of Sichuan province in 2020 and provide scientific evidence for the control of local epidemic and the prevention of imported epidemic.
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This study integrates the daily intercity migration data with the classic Susceptible-Exposed-Infected-Removed (SEIR) model to construct a new model suitable for describing the dynamics of epidemic spreading of Coronavirus Disease 2019 (COVID-19) in China. Daily intercity migration data for 367 cities in China are collected from Baidu Migration, a mobile-app based human migration tracking data system. Historical data of infected, recovered and death cases from official source are used for model fitting. The set of model parameters obtained from best data fitting using a constrained nonlinear optimization procedure is used for estimation of the dynamics of epidemic spreading in the coming weeks. Our results show that the number of infections in most cities in China will peak between mid February to early March 2020, with about 0.8%, less than 0.1% and less than 0.01% of the population eventually infected in Wuhan, Hubei Province and the rest of China, respectively.