Clinical Characteristics,Diagnosis,and Therapeutics of COVID-19:A Review

The novel severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)that suddenly emerged at the end of December 2019 and caused coronavirus disease 2019(COVID-19)continues to afflict humanity,not only seriously affecting healthcare systems but also leading to global social and economic imbalances.As of August 2022,there were approximately 580 million confirmed cases of COVID-19 and approximately 6.4 million confirmed deaths due to this disease.The data are sufficient to highlight the seriousness of SARS-CoV-2 infection.Although most patients with COVID-19 present primarily with respiratory symptoms,an increasing number of extrapulmonary systemic symptoms and manifestations have been associated with COVID-19.Since the outbreak of COVID-19,much has been learned about the disease and its causative agent.Therefore,great effort has been aimed at developing treatments and drug interventions to treat and reduce the incidence of COVID-19.In this narrative review,we provide a brief overview of the epidemiology,mechanisms,clinical manifestations,diagnosis,and therapeutics of COVID-19.

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 noninfectious 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 4aspects: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.

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.

CAPRL Scoring System for Prediction of 30-day Mortality in 949 Patients with Coronavirus Disease 2019 in Wuhan,China:A Retrospective,Observational Study

Background:Coronavirus disease 2019(COVID-19)is a serious and even lethal respiratory illness.The mortality of critically ill patients with COVID-19,especially short term mortality,is considerable.It is crucial and urgent to develop risk models that can predict the mortality risks of patients with COVID-19 at an early stage,which is helpful to guide clinicians in making appropriate decisions and optimizing the allocation of hospital resoureces.Methods:In this retrospective observational study,we enrolled 949 adult patients with laboratory-confirmed COVID-19 admitted to Tongji Hospital in Wuhan between January 28 and February 12,2020.Demographic,clinical and laboratory data were collected and analyzed.A multivariable Cox proportional hazard regression analysis was performed to calculate hazard ratios and 95%confidence interval for assessing the risk factors for 30-day mortality.Results:The 30-day mortality was 11.8%(112 of 949 patients).Forty-nine point nine percent(474)patients had one or more comorbidities,with hypertension being the most common(359[37.8%]patients),followed by diabetes(169[17.8%]patients)and coronary heart disease(89[9.4%]patients).Age above 50 years,respiratory rate above 30 beats per minute,white blood cell count of more than 10×109/L,neutrophil count of more than 7×109/L,lymphocyte count of less than 0.8×109/L,platelet count of less than 100×109/L,lactate dehydrogenase of more than 400 U/L and high-sensitivity C-reactive protein of more than 50 mg/L were independent risk factors associated with 30-day mortality in patients with COVID-19.A predictive CAPRL score was proposed integrating independent risk factors.The 30-day mortality were 0%(0 of 156),1.8%(8 of 434),12.9%(26 of 201),43.0%(55 of 128),and 76.7%(23 of 30)for patients with 0,1,2,3,≥4 points,respectively.Conclusions:We designed an easy-to-use clinically predictive tool for assessing 30-day mortality risk of COVID-19.It can accurately stratify hospitalized patients with COVID-19 into relevant risk categories and could provide guidance to make further clinical decisions.