Infection-associated Hemophagocytic Syndrome in Critically Ill Patients with COVID-19.

Infection-associated hemophagocytic syndrome (IAHS), a severe complication of various infections, is potentially fatal. This study aims to determine whether IAHS occurs in critically ill patients with coronavirus disease 2019 (COVID-19). We conducted a retrospective observational study on 268 critically ill patients with COVID-19 between February 1st, 2020 and February 26th, 2020. Demographics, clinical characteristics, laboratory results, information on concurrent treatments and outcomes were collected. A diagnosis of secondary hemophagocytic lymphohistiocytosis (sHLH) was made when the patients had an HScore greater than 169. Histopathological examinations were performed to confirm the presence of hemophagocytosis. Of 268 critically ill patients with confirmed SARS-CoV-2 infection, 17 (6.3%) patients had an HScore greater than 169. All the 17 patients with sHLH died. The interval from the onset of symptom of COVID-19 to the time of a diagnosis of sHLH made was 19 days and the interval from the diagnosis of sHLH to death was 4 days. Ten (59%) patients were infected with only SARS-CoV-2. Hemophagocytosis in the spleen and the liver, as well as lymphocyte infiltration in the liver on histopathological examinations, was found in 3 sHLH autopsy patients. Mortality in sHLH patients with COVID-19 is high. And SARS-CoV-2 is a potential trigger for sHLH. Prompt recognition of IAHS in critically ill patients with COVID-19 could be beneficial for improving clinical outcomes.

[Effect of cyclic GMP-AMP synthase on EMT in breast cancer cells].

OBJECTIVE: To investigate the effects of cyclic GMP-AMP synthase (cGAS) on the proliferation, migration and epithelial to mesenchymal transition (EMT) of breast cancer cells. METHODS: The cGAS lentiviral vector and control fluorescence vector were transfected into breast cancer MCF7 cells and were divided into negative group (NC) and MCF7-cGAS group. The effect of cGAS on proliferation in the MCF7 cells was detected by MTT. The effect of cGAS on cell migration was detected by Transwell assay. The expressions of EMT related proteins were analyzed by Western blot. RESULTS: After over-expressed with cGAS, the proliferation and migration of MCF7 cells were increased (P＜0.05). The expression level of the epithelial markers E-cadherin was decreased, while the expression level of the mesenchymal markers N-cadherin was increased(P＜0.05). CONCLUSION: The over-expression of cGAS increased the proliferation and migration of breast cancer cells and induced EMT in breast cancer cells.

Combined clinical parameters improve the diagnostic efficacy of 18F-FDG PET/CT in patients with fever of unknown origin (FUO) and inflammation of unknown origin (IUO): A prospective study in China.

OBJECTIVES: To improve the diagnostic efficacy of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) for Chinese patients with fever of unknown origin (FUO) and inflammation of unknown origin (IUO), with combined clinical parameters. MATERIALS AND METHODS: FUO/IUO patients who underwent a standard diagnostic work-up and 18F-FDG PET/CT scanning were enrolled and divided into a local uptake lesion subgroup and a non-specific abnormal uptake subgroup. Beneficial clinical parameters for improving the diagnostic efficacy of PET/CT were identified. RESULTS: From January 2014 to January 2019, 253 FUO/IUO patients were studied. In total, 147 patients had local uptake lesions and 106 patients had non-specific abnormal uptake. In the local uptake lesion group, the positioning accuracy of PET/CT was 37.2% in grades 1 and 2, and 66.3% in grades 3 and 4. With the following combination of clinical parameters, the positioning accuracy increased to 75.0% and 90.0%, respectively: time from admission to performing PET/CT scanning <6.5 days and C-reactive protein level >95 mg/l. In the non-specific abnormal uptake group, the combination of sex (male), bicytopenia, and lactic dehydrogenase improved the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for diagnosing malignancy from 64.3%, 69%, 60%, and 72.7%, respectively, to 83.3%, 81%, 81.4%, and 82.9%, respectively. With the combination of sex (male), white blood count, serum ferritin level, and hepatosplenomegaly, the infection prediction model had a sensitivity, specificity, PPV, and NPV of 78%, 76.2%, 76.6%, and 77.6%, respectively. CONCLUSIONS: Combined clinical parameters improved the localization diagnostic value of 18F-FDG PET/CT in the local uptake lesion subgroup and the etiological diagnostic value in the non-specific abnormal uptake subgroup.

A Diagnostic Tool for Identification of Etiologies of Fever of Unknown Origin in Adult Patients.

The diagnosis and treatment of fever of unknown origin (FUO) are huge challenges to clinicians. Separating the etiologies of FUO into infectious and non-infectious disease is conducive to clinical physicians not only on making decisions rapidly concerning the prescription of suitable antibiotics but also on further analysis of the final diagnosis. In order to develop and validate a diagnostic tool to efficiently distinguish the etiologies of adult FUO patients as infectious or non-infectious disease, FUO patients from the departments of infectious disease and internal medicine in three Chinese tertiary hospitals were enrolled retrospectively and prospectively. By using polynomial logistic regression analysis, the diagnostic formula and the associated scoring system were developed. The variables included in this diagnostic formula were from clinical evaluations and common laboratory examinations. The proposed tool could discriminate infectious and non-infectious causes of FUO with an area under receiver operating characteristic curve (AUC) of 0.83, sensitivity of 0.80 and specificity of 0.75. This diagnosis tool could predict the infectious and non-infectious causes of FUO in the validation cohort with an AUC of 0.79, sensitivity of 0.79 and specificity of 0.70. The results suggested that this diagnostic tool could be a reliable tool to discriminate between infectious and non-infectious causes of FUO.

Establishment of a Predictive Model Related to Pathogen Invasion for Infectious Diseases and Its Diagnostic Value in Fever of Unknown Origin.

The present study aimed to establish a list of parameters indicative of pathogen invasion and develop a predictive model to distinguish the etiologies of fever of unknown origin (FUO) into infectious and non-infectious causes. From January 2014 to September 2017, 431 patients with FUO were prospectively enrolled in the study population. This study established a list of 26 variables from the following 4 aspects: host factors, epidemiological factors, behavioral factors, and iatrogenic factors. Predefined predicted variables were included in a multivariate logistic regression analysis to develop a predictive model. The predictive model and the corresponding scoring system were developed using data from the confirmed diagnoses and 9 variables were eventually identified. These factors were incorporated into the predictive model. This model discriminated between infectious and non-infectious causes of FUO with an AUC of 0.72, sensitivity of 0.71, and specificity of 0.63. The predictive model and corresponding scoring system based on factors concerning pathogen invasion appear to be reliable screening tools to discriminate between infectious and non-infectious causes of FUO.