COVID-19 and liver injury:Pathophysiology,risk factors,outcome and management in special populations

The coronavirus disease 2019(COVID-19)caused by severe acute respiratory syndrome coronavirus-2 is an ongoing health concern.In addition to affecting the respiratory system,COVID-19 can potentially damage other systems in the body,leading to extra-pulmonary manifestations.Hepatic manifestations are among the common consequences of COVID-19.Although the precise mechanism of liver injury is still questionable,several mechanisms have been hypothesized,including direct viral effect,cytokine storm,hypoxic-ischemic injury,hypoxiareperfusion injury,ferroptosis,and hepatotoxic medications.Risk factors of COVID-19-induced liver injury include severe COVID-19 infection,male gender,advanced age,obesity,and underlying diseases.The presentations of liver involvement comprise abnormalities in liver enzymes and radiologic findings,which can be utilized to predict the prognosis.Increased gamma-glutamyltransferase,aspartate aminotransferase,and alanine aminotransferase levels with hypoalbuminemia can indicate severe liver injury and anticipate the need for intensive care units’hospitalization.In imaging,a lower liver-to-spleen ratio and liver computed tomography attenuation may indicate a more severe illness.Furthermore,chronic liver disease patients are at a higher risk for severe disease and death from COVID-19.Nonalcoholic fatty liver disease had the highest risk of advanced COVID-19 disease and death,followed by metabolic-associated fatty liver disease and cirrhosis.In addition to COVID-19-induced liver injury,the pandemic has also altered the epidemiology and pattern of some hepatic diseases,such as alcoholic liver disease and hepatitis B.Therefore,it warrants special vigilance and awareness by healthcare professionals to screen and treat COVID-19-associated liver injury accordingly.

Conduction system disorders and electro-cardiographic findings in COVID-19 deceased patients in 2021,Shiraz,Iran

BACKGROUND Cardiac conduction disorders and electrocardiographic(ECG)changes may occur as a manifestation of coronavirus disease 2019(COVID-19),especially in severe cases.AIM To describe conduction system disorders and their association with other electrocardiographic parameters in patients who died of COVID-19.METHODS In this cross-sectional study,electrocardiographic and clinical data of 432 patients who expired from COVID-19 between August 1st,2021,and December 1st,2021,in a tertiary hospital were reviewed.RESULTS Among 432 patients who died from COVID-19,atrioventricular block(AVB)was found in 40(9.3%).Among these 40 patients,28(6.5%)suffered from 1st degree AVB,and 12(2.8%)suffered from complete heart block(CHB).Changes in ST-T wave,compatible with myocardial infarction or localized myocarditis,appeared in 189(59.0%).Findings compatible with myocardial injury,such as fragmented QRS and prolonged QTc,were found in 91 patients(21.1%)and 28 patients(6.5%),respectively.In patients who died of COVID-19,conduction disorder was unrelated to any underlying medical condition.Fragmented QRS,axis deviation,and ST-T changes were significantly related to conduction system disorder in patients who died of COVID-19(P value<0.05).CONCLUSION Conduction system disorders are associated with several other ECG abnormalities,especially those indicative of myocardial ischemia or inflammation.Most patients(73.14%)who died of COVID-19 demonstrated at least one ECG abnormality parameter.Since a COVID-19 patient's ECG gives important information regarding their cardiac health,our findings can help develop a risk stratification method for at-risk COVID-19 patients in future studies.

Association of risky driving behavior with psychiatric disorders among Iranian drivers:A case-control study

Purpose:This study aimed to investigate the possible association between psychological disorders and riskydriving behavior(RDB)in Iran.Methods:This case-control study conducted in Shiraz,Iran in 2021.The case group included drivers with psychological disorders and the control group included those without any disorders.The inclusion criteria for selecting patients were:active driving at the time of the study,being 18-65 years old,having a driving license,having a psychological disorder including depression,bipolar disorder,anxiety spectrum disorder,or psychotic disorder spectrum confirmed by a psychiatrist,and completing an informed consent form.The exclusion criterion was the existence of conditions that interfered with answering and understanding the questions.The inclusion criteria for selecting the healthy cases were:active driving at the time of the study,being 18-65 years old,having a driving license,lack of any past or present history of psychiatric problems,and completing an informed consent form.The data were gathered using a researcher-made checklist and Manchester driving behavior questionnaire.First,partition around medoids method was used to extract clusters of RDB.Then,backward logistic regression was applied to investigate the association between the independent variables and the clusters of RDB.Results:The sample comprised of 344(153 with psychological disorder and 191 without confirmed psychological disorder)drivers.Backward elimination logistic regression on total data revealed that share of medical expenditure≤10%of total household expenditure(OR=3.27,95%Cl:1.48-7.24),psychological disorder(OR=3.08,95%Cl:1.67-5.70),and substance abuse class(OR=6.38,95%CI:3.55-11.48)wereassociatedwithhighlevelof RDB.Conclusion:Substance abuse,psychological illnesses,and share of medical costs from total household expenditure were found to be main predictors of RDB.Further investigations are necessary to explain the impact of different psychological illnesses on driving behavior.