Prevalence of bacteria, fungi, and virus coinfections with SARS-CoV-2 Omicron variant among patients with severe COVID-19 in Guangzhou, China, winter 2022

The status of coinfection during the national outbreak of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)Omicron BA.5.2 or BF.7 in China in the winter of 2022,which is suspected to contribute substantially to the overloaded severe cases,needs to be investigated.We analyzed the coinfection status of 385 severe patients infected with the Omicron variant in Guangzhou using metagenomic sequencing.We found that 317(82.3%)patients were coinfected with at least one additional pathogen(s),including bacteria(58.7%),fungi(27.1%)and viruses(73.5%).Pseudomonas aeruginosa(P.aeruginosa)(24.2%),Staphylococcus aureus(S.aureus)(14.0%),andKlebsiella pneumoniae(K.pneumonia)(13.4%)ranked as the top three coinfected bacteria.Aspergillus fumigatus(A.fumigatus)(39.5%),Pneumocystis jirovecii(P.jirovecii)(24.4%)andCanidia albicans(C.albicans)(22.1%)were the top three coinfected fungi.Epstein-Barr virus(EBV)(63.1%),Human herpesvirus 7(HHV-7)(34.8%),and Herpes simplex virus 1(HSV-1)(32.6%)were the top three coinfected viruses.Of note,the detection of multiple coinfections of potential pathogenic bacteria,fungi,and viruses,despite lacking consistent patterns,highlighted a complicated synergistic contribution to disease severity.Our study presents the most comprehensive spectrum of bacterial,fungal,and viral coinfections in Omicron-associated severe coronavirus disease 2019(COVID-19),implying that the coinfection of conditional pathogens might synergistically deteriorate the Omicron infection outcomes.

Red blood cell distribution width improves the prediction of 28-daymortality for patients with sepsis-induced acute kidney injury:A retrospective analysis from MIMIC-IV database usingpropensity score matching

Background:The predictive value of red blood cell distribution width(RDW)for mortality in patients withsepsis-induced acute kidney injury(SI-AKI)remains unclear.The present study aimed to investigate the potentialassociation between RDW at admission and outcomes in patients with SI-AKI.Methods:The Medical Information Mart for Intensive Care(MIMIC)-IV(version 2.0)database,released in Juneof 2022,provides medical data of SI-AKI patients to conduct our related research.Based on propensity scorematching(PSM)method,the main risk factors associated with mortality in SI-AKI were evaluated using Coxproportional hazards regression analysis to construct a predictive nomogram.The concordance index(C-index)and decision curve analysis were used to validate the predictive ability and clinical utility of this model.Patientswith SI-AKI were classified into the high-and low-RDW groups according to the best cut-off value obtained bycalculating the maximum value of the Youden index.Results:A total of 7574 patients with SI-AKI were identified according to the filter criteria.Compared withthe low-RDW group,the high-RDW group had higher 28-day(9.49%vs.31.40%,respectively,P<0.001)and7-day(3.96%vs.13.93%,respectively,P<0.001)mortality rates.Patients in the high-RDW group were moreprone to AKI progression than those in the low-RDW group(20.80%vs.13.60%,respectively,P<0.001).Basedon matched patients,we developed a nomogram model that included age,white blood cells,RDW,combinedhypertension and presence of a malignant tumor,treatment with vasopressor,dialysis,and invasive ventilation,sequential organ failure assessment,and AKI stages.The C-index for predicting the probability of 28-day survivalwas 0.799.Decision curve analysis revealed that the model with RDW offered greater net benefit than that withoutRDW.Conclusion:The present findings demonstrated the importance of RDW,which improved the predictive ability ofthe nomogram model for the probability of survival in patients with SI-AKI.