Background The roles of inflammation and hypercoagulation in predicting outcomes of coronavirus disease 2019 (COVID-19) are unclear. Methods Adult patients diagnosed with COVID-19 from 28 January 2020 to 4 March 2020 in Tongji Hospital, Wuhan were recruited. Data on related parameters were collected. Univariate analysis and multivariable binary logistic regression were used to explore predictors of critical illness and mortality. Results In total, 199 and 44 patients were enrolled in the training and testing sets, respectively. Elevated ferritin, tumor necrosis factor-α and D-dimer and decreased albumin concentration were associated with disease severity. Older age, elevated ferritin and elevated interleukin-6 were associated with 28-day mortality. The FAD-85 score, defined as age + 0.01 * ferritin +D-dimer, was used to predict risk of mortality. The sensitivity, specificity and accuracy of FAD-85 were 86.4%, 81.8% and 86.4%, respectively. A nomogram was established using age, ferritin and D-dimer to predict the risk of 28-day mortality. Conclusions Thrombo-inflammatory parameters provide key information on the severity and prognosis of COVID-19 and can be used as references for clinical treatment to correct inflammatory and coagulation abnormalities.

Objective:This systemic review and meta-analysis was conducted to explore the impact of dispatcher-assisted bystander cardiopulmonary resuscitation (DA-BCPR) on bystander cardiopulmonary resuscitation (BCPR) probability, survival, and neurological outcomes with out-of-hospital cardiac arrest (OHCA).Methods:Electronically searching of PubMed, Embase, and Cochrane Library, along with manual retrieval, were done for clinical trials about the impact of DA-BCPR which were published from the date of inception to December 2018. The literature was screened according to inclusion and exclusion criteria, the baseline information, and interested outcomes were extracted. Two reviewers assessed the methodological quality of the included studies. Pooled odds ratio (OR) and 95% confidence interval (CI) were calculated by STATA version 13.1.Results:In 13 studies, 235,550 patients were enrolled. Compared with no dispatcher instruction, DA-BCPR tended to be effective in improving BCPR rate (I2 = 98.2%; OR = 5.84; 95% CI, 4.58-7.46; P <.01), return of spontaneous circulation (ROSC) before admission (I2 = 36.0%; OR = 1.17; 95% CI, 1.06-1.29; P <.01), discharge or 30-day survival rate (I2 = 47.7%; OR = 1.25; 95% CI, 1.06-1.46; P <.01), and good neurological outcome (I2 = 30.9%; OR = 1.24; 95% CI, 1.04-1.48; P = .01). However, no significant difference in hospital admission was found (I2 = 29.0%; OR = 1.09; 95% CI, 0.91-1.30; P = .36).Conclusion:This review shows DA-BPCR plays a positive role for OHCA as a critical section in the life chain. It is effective in improving the probability of BCPR, survival, ROSC before admission, and neurological outcome.

Purpose. At present, not enough is known about the symptoms before cardiac arrest. The purpose of this study is to describe the precursor symptoms of cardiac arrest, focusing on the relationship between symptoms and cardiac arrest, and to establish a quick scoring model of symptoms for predicting cardiac arrest. Patients and Methods. A retrospective case-control study was carried out on cardiac arrest patients who visited the emergency department of Peking University Third Hospital from January 2018 to June 2019. Symptoms that occurred or were obviously aggravated within the 14 days before CA were defined as warning symptoms. Results. More than half the cardiac arrest patients experienced warning symptoms within 14 days before cardiac arrest. Dyspnea ( p < 0.001 ) was found to be associated with cardiac arrest; syncope and cold sweat are other symptoms that may have particular clinical significance. Gender ( p < 0.001 ), age ( p < 0.001 ), history of heart failure ( p = 0.006 ), chronic kidney disease ( p = 0.011 ), and hyperlipidemia ( p = 0.004 ) were other factors contributing to our model. Conclusions. Warning symptoms during the 14 days prior to cardiac arrest are common for CA patients. The Quick Scoring Model for Cardiac Arrest (QSM-CA) was developed to help emergency physicians and emergency medical services (EMS) personnel quickly identify patients with a high risk of cardiac arrest.