Predictors for the severe coronavirus disease 2019 (COVID-19) infection in patients with underlying liver disease: a retrospective analytical study in Iran

Predictors of COVID-19 Readmission Among Patients Previously Hospitalized for SARS-CoV-2

INTRODUCTION

Predictors of coronavirus disease 2019 (COVID-19)-related rehospitalization remain underexplored. This study aims to identify the main risk factors associated with rehospitalizations due to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) reinfections among residents of Lombardy, northern Italy.

METHODS

A retrospective observational study was conducted using two linked administrative databases covering demographic data, comorbidities, hospital records, and COVID-19 data of Lombardy residents. The study population included patients hospitalized for COVID-19 between February 2020 and August 2021. Rehospitalization was defined as a second COVID-19-related hospitalization occurring at least 90 days after the first admission. The Fine-Gray subdistribution hazard model was used to identify risk factors, accounting for death as a competing risk.

RESULTS

Out of 98,369 patients hospitalized for COVID-19 between February 1, 2020 and August 31, 2021, 72,593 were alive 90 days after admission and 610 of these (0.8%) were rehospitalized. A higher rehospitalization risk was observed in older male patients with multiple comorbidities. Renal failure, liver disease, and use of diuretics were significantly associated with rehospitalization risk, while female biological sex and the use of lipid-lowering drugs were associated with a lower risk.

CONCLUSIONS

This is the first study conducted on regional administrative databases to investigate COVID-19 rehospitalizations. Through the availability of a huge cohort, it provides a groundwork for optimizing care for individuals at higher risk for COVID-19-related rehospitalizations. It underlines the need for patient-management approaches that extend beyond the initial recovery. This stresses the importance of ongoing monitoring and personalized interventions for those at heightened risk not only of SARS-CoV-2 reinfection but also related rehospitalizations.

Paxlovid reduces the 28-day mortality of patients with COVID-19: a retrospective cohort study

PURPOSE

In this study, we aim to explore the efficacy of paxlovid on reducing mortality of COVID-19 patients in clinical setting, especially whether paxlovid modifies the risk of death in these severe and critical patients.

METHODS

Our retrospective cohort study was conducted on the medical records of patients, consecutively admitted for COVID-19 to five hospitals in Chongqing, China from Dec 8, 2022 to Jan 20, 2023. Based on whether patients received paxlovid during their hospitalization, patients were grouped as paxlovid group and non-paxlovid group. We used 1:1 ratio propensity score matching (PSM) in our study to adjust for confounding factors and differences between groups. Statistical analysis were performed by SPSS 23.0. The differences in 28-day mortality between these two groups and its influencing factors were the main results we focused on.

RESULTS

There were 1018 patients included in our study cohort. With 1:1 ratio PSM, each of the paxlovid group and non-paxlovid group included 237 patients. The results showed that patients using paxlovid have a lower 28-day mortality in overall population either before PSM (OR 0.594, 95% CI 0.385-0.917, p = 0.019) or after PSM (OR 0.458, 95% CI 0.272-0.774, p = 0.003) with multivariable adjusted logistic regression models. Meanwhile, in severe subgroup, it showed similar findings.With paxlovid treatment, it showed a significantly lower 28-day mortality in severe subgroup both before PSM (28% vs.41%, p = 0.008) and after PSM (19% vs.32%, p = 0.007).

CONCLUSION

Paxlovid can significantly reduce the risk of 28-day mortality in overall population and severe subgroup patients.This study distinguished the severe subgroup patients with COVID-19 who benefit more from paxlovid treatment.

Best Evidence Topic report: does blood group type O decrease the risk of severe COVID-19 infection?

A short-cut systematic review was conducted using a described protocol. The three-part question addressed was: In patients with COVID-19 infection, does blood group type O versus non-O blood groups lead to a lower risk of severe COVID-19 infection? MEDLINE, Embase, and Cochrane databases were searched for relevant evidence. Altogether, 238 papers were found using the search strategy developed. Seventeen provided the best evidence to answer the three-part question. The data on first author name, publication year, country of origin, study type, study sample size, participant's gender, reported effect sizes, main findings and limitations were extracted from the relevant studies and listed in a table. Finally, 4 out of 17 studies revealed that having blood group type O may be associated with a lower risk of severe COVID-19 among patients with COVID-19 infection and the 13 remaining studies reported no significant relationship between having O blood group and risk of COVID-19 severity among the infected individuals. Of three systematic reviews and meta-analyses identified, none detected a protective effect of blood group type O. The clinical bottom line is that the best available evidence does not support the notion that blood group type O is protective against serious outcomes in COVID-19.

Effect of treatment regimen of the rheumatoid arthritis patients on the risk of coronavirus disease 2019 by modulating the inflammatory mediators

BACKGROUND

The therapeutic profile of the patients with rheumatoid arthritis (RA) commonly consists of immunosuppressive and anti-inflammatory compounds. Here in this research, we assessed the potential effect of drug treatment in the RA patients in increasing the risk of coronavirus disease 2019 (COVID-19) infection.

METHODS

In this retrospective cross-sectional study, 200 subjects with RA were recruited. The treatment profile of the subjects for the past 6 months was collected. The COVID-19 diagnosis was implemented based on the standard molecular tests and clinical examinations. Serum concentration of cytokines was measured using enzyme-linked immunosorbent assay (ELISA).

RESULTS

It was detected that there was an increased risk of COVID-19 in RA subjects receiving Etanercept (OR = 3.51, 95% CI 1.19-10.30, P = 0.022). Concentrations of Interleukin (IL)-1β, Interferon (IFN)-γ, Tumor necrosis factor (TNF)-α, IL-6, IL-17A, and IL-23 were significantly higher in the RA patients with COVID-19 relative to RA cases without COVID-19. In RA/COVID-19 cases receiving Etanercept, serum levels of TNF-α, IL-1β, and IL-6 were significantly lower than RA/COVID-19 subjects without Etanercept therapy.

CONCLUSIONS

It seems that Etanercept therapy in RA cases might increase proneness of the COVID-19 risk in these cases. The mechanism of this increased risk may stem from suppressing a protective immunity state in the RA cases.

Early decrease in blood lymphocyte count is associated with poor prognosis in COVID-19 patients: a retrospective cohort study

BACKGROUND

Previous studies have declared that baseline lymphocyte count is associated with COVID-19-related death. However, whether dynamic lymphocyte change over time affects prognosis in COVID-19 patients is unknown. This study aims to investigate the significance of lymphocyte count during the progression of the disease in COVID-19 patients.

METHODS

The retrospective cohort study recruited COVID-19 patients at the First People's Hospital of Jiangxia District in Wuhan from January 7, 2020, to February 28, 2020. The demographics, medical histories, results of the blood routine test, and patients' outcomes were collected. We utilized a generalized additive mixed model to compare trends in lymphocyte count over time among survivors and non-survivors, with an adjustment for potential confounders. The statistical analysis used R software and EmpowerStats. Significance was determined at a P-value of less than 0.05 (two-sided).

RESULTS

A total of 532 patients were included in the study. Overall, there were 29/532 in-hospital deaths (5.45%). Lymphocytes declined over time in the non-survivor group and increased in the survivor group in the first 10 days of hospitalization. Within 10 days after admission, lymphocyte count increased in the survivor group and decreased in the non-survivor group. The difference in lymphocyte counts between survivors and non-survivors increased by an average of 0.0732 × 109/L daily. After adjusting for several covariables, the increasing value remained at 0.0731 × 109/L per day.

CONCLUSION

In the early stage, lymphocyte count can dynamically reflect the pathophysiological changes in COVID-19 patients. An early decrease in lymphocyte count is associated with mortality in COVID-19 patients.

Association between acute liver injury & severity and mortality of COVID-19 patients: A systematic review and meta-analysis

BACKGROUND

Acute liver injury (ALI), a complication often seen in COVID-19 patients, can lead to severe liver damage, multi-organ failure, acute vascular events, and can potentially escalate to patient mortality. Given this, we initiated a meta-analysis to investigate the correlation between ALI and adverse outcomes in COVID-19 patients.

METHODS

We conducted an exhaustive search of databases, including Medline, Embase, PubMed Central, ScienceDirect, Google Scholar, and the Cochrane Library, from the November 2019 until January 2022. The quality of the included studies was evaluated using the Newcastle Ottawa (NO) scale. Our meta-analysis was carried out using a random-effects model and results were presented as pooled odds ratios (ORs) with their corresponding 95% confidence intervals (CIs).

RESULTS

Our analysis incorporated 20 studies involving a total of 13,850 participants, predominantly from China and the United States. According to the NO scale, the majority of these studies were categorized as low-quality. Patients with ALI faced approximately 7 times higher odds of severe COVID-19 symptoms (pooled OR = 7.09; 95%CI: 4.97 to 10.12) and over 5 times higher odds of mortality (pooled OR = 5.50; 95%CI: 3.37 to 8.99) when compared to those without ALI.

CONCLUSION

Our findings affirm that ALI is a potent predictor of adverse outcomes, including severity and mortality, among COVID-19 patients. Recognizing and promptly addressing ALI in COVID-19 patients could be pivotal in improving prognosis and tailoring individualized patient management strategies. This underscores the need for clinicians to be vigilant about liver complications in the COVID-19 patients and integrate appropriate interventions in the treatment paradigm.

Outcomes of COVID-19 among patients with liver disease

Coronavirus disease 2019 (COVID-19) is primarily a respiratory disease with multi-organ involvement, including impaired liver function. It has been noticed that a significant proportion of COVID-19 patients have liver dysfunction, especially those with a more severe disease course. The coronavirus causes direct damage to the liver using the angiotensin-converting enzyme 2, a cell-surface receptor for cellular entry, that is expressed in the liver. According to previous research, liver enzyme abnormalities were observed in a considerable proportion of COVID-19 patients, and elevated liver transaminases were found in about 20% of these patients, alkaline phosphatase in 6.1%, and gamma-glutamyl transferase in 21.1%. COVID-19 might trigger a deterioration of liver function in patients with pre-existing chronic liver diseases (CLDs) and also in those without previous liver disorders. The majority of COVID-19 patients who develop liver injury are men, the elderly, and those with a higher body mass index. Compared to the general population, COVID-19 is associated with significant morbidity and mortality in patients with liver disease (cirrhosis and liver transplantation recipients). However, some studies indicate that CLDs have a lesser role in determining patient progression towards higher disease severity.

A comparison of machine learning algorithms in predicting COVID-19 prognostics

ML algorithms are used to develop prognostic and diagnostic models and so to support clinical decision-making. This study uses eight supervised ML algorithms to predict the need for intensive care, intubation, and mortality risk for COVID-19 patients. The study uses two datasets: (1) patient demographics and clinical data (n = 11,712), and (2) patient demographics, clinical data, and blood test results (n = 602) for developing the prediction models, understanding the most significant features, and comparing the performances of eight different ML algorithms. Experimental findings showed that all prognostic prediction models reported an AUROC value of over 0.92, in which extra tree and CatBoost classifiers were often outperformed (AUROC over 0.94). The findings revealed that the features of C-reactive protein, the ratio of lymphocytes, lactic acid, and serum calcium have a substantial impact on COVID-19 prognostic predictions. This study provides evidence of the value of tree-based supervised ML algorithms for predicting prognosis in health care.

Association of underlying comorbidities and progression of COVID-19 infection amongst 2586 patients hospitalised in the National Capital Region of India: a retrospective cohort study

This study is conducted to observe the association of diabetes (DM), hypertension (HTN) and chronic kidney disease (CKD) on the prognosis and mortality of COVID-19 infection in hospital admitted patients with above mentioned comorbidities. This is a single centre, observational, retrospective study carried out at Sir Ganga Ram Hospital, Delhi, India. The burden of comorbidities on the prognosis and clinical outcome of COVID-19 patients admitted patients from April 8, 2020, to October 4, 2020. Chi-square and relative risk test were used to observe the association of comorbidities and disease prognosis. A total of 2586 patients were included in the study consisting of 69.6% of male patients. All the comorbidities were significantly associated with ICU admission and mortality. The relative risk showed that CKD is most prone to severity as well as mortality of the COVID-19 infection followed by HTN and DM. Further with the increase in number of underlying comorbidities, the risk of ICU admission and mortality also increases. Relative risk of the severity of COVID-19 infection in younger patients with underlying comorbidities are relatively at higher risk of severity of disease as well as to mortality compared to the elderly patients with similar underlying condition. Similarly, it is found that females are relatively at higher risk of mortality as compared to the males having same comorbid conditions except for the hypertensive patients. Diabetes, hypertension and CKD, all are associated with progression of COVID-19 disease to severity and higher mortality risk. The number of underlying comorbid condition is directly proportional to the progression of disease severity and mortality.

A Predictive Model for 30-Day Mortality of Fungemia in ICUs

Background

Few predictive models have been established to predict the risk of 30-day mortality from fungemia. This study aims to create a nomogram to predict the 30-day mortality of fungemia in ICUs.

Methods

Data of ICU patients with fungemia from both the Medical Information Mart for Intensive Care (MIMIC-III) database and the Grade-III Class-A hospital in China were collected. The data extracted from the MIMIC-III database functioned as the training dataset, which was used to construct a predictive model for 30-day mortality risk in ICU patients with fungemia; the data from the hospital functioned as the validation dataset, which was used to validate the model. A predictive model for 30-day mortality risk in ICU patients with fungemia was then built based on R software. Such indicators as C-index and calibration curve were utilized to evaluate the prediction ability of the model. Data of ICU patients with fungemia from the hospital were used as a validation dataset to validate the model.

Results

Predictive models were constructed by age, international normalized ratio (INR), renal failure, liver disease, respiratory rate (RR), glucocorticoid therapy, antifungal therapy, and platelets. The C-index value of the models was 0.838 (95% CI: 0.79096-0.88504). Attested by external validation results, the model has satisfactory predictive ability.

Conclusion

The 30-day mortality risk predictive model for ICU patients with fungemia constructed in this study has good predictive ability and may hopefully provide a 30-day mortality risk screening tool for ICU patients with fungemia.

Liver injury in COVID-19: A minireview

Coronavirus disease 2019 (COVID-19), caused by infection with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has escalated into a global tragedy afflicting human health, life, and social governance. Through the increasing depth of research and a better understanding of this disease, it has been ascertained that, in addition to the lungs, SARS-CoV-2 can also induce injuries to other organs including the liver. Liver injury is a common clinical manifestation of COVID-19, particularly in severe cases, and is often associated with a poorer prognosis and higher severity of COVID-19. This review focuses on the general existing information on liver injury caused by COVID-19, including risk factors and subpopulations of liver injury in COVID-19, the association between preexisting liver diseases and the severity of COVID-19, and the potential mechanisms by which SARS-CoV-2 affects the liver. This review may provide some useful information for the development of therapeutic and preventive strategies for COVID-19-associated liver injury.

COVID-19 Severity and Mortality Among Chronic Liver Disease Patients: A Systematic Review and Meta-Analysis

INTRODUCTION

Pre-existing comorbid conditions in COVID-19 patients are risk factors for developing severe disease and death. We aimed to determine the association of chronic liver disease (CLD), a comorbid condition, with severity of disease and death among COVID-19 patients.

METHODS

We searched for studies reporting COVID-19 outcomes among CLD and non-CLD patients in databases including Medline, EMBASE, ScienceDirect, Google Scholar, and Cochrane Library from inception of the pandemic until February 2022. Risk of bias assessment was conducted by using the Newcastle-Ottawa Scale for assessing the quality of nonrandomized studies in meta-analyses. We conducted a meta-analysis with a random-effects model and reported pooled odds ratios (ORs) with 95% CIs.

RESULTS

We included 40 studies with 908,032 participants. Most studies were conducted in China and the US. COVID-19 patients with CLD had significantly higher odds of having a severe form of COVID-19 (pooled OR = 2.44; 95% CI, 1.89-3.16) and death (pooled OR = 2.35; 95% CI, 1.85-3.00) when compared with COVID-19 patients without CLD.

CONCLUSION

The presence of CLD is significantly related to adverse clinical outcomes among COVID-19 patients in terms of severity and mortality. Clinicians should develop a comprehensive intervention plan to manage these high-risk patients and reduce COVID-19-related deaths.

Coronavirus Disease 2019 (COVID-19) Infection-Related Stigma, Depression, Anxiety, and Stress in Iranian Healthcare Workers

Background

Psychological conditions aggravate during outbreaks. Here, we have discussed the existing COVID-19 depression, anxiety, and stress and the resulting stigma and its different aspects in Iranian health care workers and their 1^st-degree relatives.

Methods

In this cross-sectional study, information of our study groups (237 participants including health care workers and their nuclear family members) was collected via two online stigma and depression, anxiety, and stress scale (DASS) questionnaires.

Results

The DASS questionnaire's mean depression, anxiety, and stress scores were 13.59 ± 5.76, 11.07 ± 4.38, and 15.05 ± 5.86, respectively, in our study population. Marriage status was effective on depression and stress scores. Married participants were having less depression (P = 0.008) but more stressful (P = 0.029) than single ones. Education was found to be effective on anxiety and stress scores. Those with an associate, master, Ph.D., and higher college degrees were significantly less anxious and stressed than those with a diploma or bachelor's degrees (P = 0.032 and 0.016, respectively, for anxiety and stress). Participants with a history of psychiatric conditions showed significantly higher depression, anxiety, and stress rates than those without a past psychiatric condition (P = 0.001). Healthcare workers and their nuclear family members suffer from severe stigma (mean stigma scores were 33.57 and 33.17, respectively).

Conclusions

Healthcare workers and their nuclear family members in Iran suffer from severe COVID-19 related stigma. We also showed that depression, anxiety, and stress are common among Iranian Healthcare workers and their nuclear family members during this pandemic. This study showed that people with preexisting psychiatric conditions need extra mental care during the pandemic.

Inflammation/Coagulopathy/Immunology Responsive Index Predicts Poor COVID-19 Prognosis

In the early stage of coronavirus disease 2019 (COVID-19), most cases are identified as mild or moderate illnesses. Approximately 20% of hospitalised patients become severe or critical at the middle or late stage of the disease. The predictors and risk factors for prognosis in those with mild or moderate disease remain to be determined. Of 694 patients with COVID-19, 231 patients with mild or moderate disease, who were hospitalised at 10 hospitals in Wenzhou and nearby counties in China, were enrolled in this retrospective study from 17 January to 20 March 2020. The outcomes of these patients included progression from mild/moderate illness to severe or critical conditions. Among the 231 patients, 49 (21.2%) had a poor prognosis in the hospital. Multivariate logistic regression analysis showed that higher inflammation/coagulopathy/immunology responsive index (ICIRI=[c-reactive protein × fibrinogen × D-dimer]/CD8 T cell count) on admission (OR=345.151, 95% CI=23.014−5176.318) was associated with increased odds ratios for poor prognosis. The area under the receiver operating characteristic curve for ICIRI predicting severe and critical condition progression was 0.65 (95% CI=0.519−0.782) and 0.80 (95% CI=0.647−0.954), with cut-off values of 870.83 and 535.44, respectively. Conversely, age, sex, comorbidity, neutrophil/lymphocyte ratio, CD8 T cell count, and c-reactive protein, fibrinogen, and D-dimer levels alone at admission were not good predictors of poor prognosis in patients with mild or moderate COVID-19. At admission, a novel index, ICIRI, tends to be the most promising predictor of COVID-19 progression from mild or moderate illness to severe or critical conditions.

Evaluation of early complications, outcome, and mortality in Coronavirus Disease 2019 (COVID-19) infection in patients who underwent orthopedic surgery

BACKGROUND

A higher mortality and morbidity rate has been reported in COVID-19 patients undergoing surgery. To reduce the morbidity and mortality rate in COVID-19 patients undergoing orthopedic procedures, we aimed to increase the threshold for surgical planning.

METHODS

In a prospective cohort study, COVID-19 patients who underwent elective or emergent orthopedic surgery in three orthopedic surgery centers from February 2020 to September 2020 were included. In this period, 6751 patients were scheduled for orthopedic surgery. To increase surgical threshold planning, all patients with grade 5 of the American Society of Anesthesiologists (ASA) classification and patients with COVID-19 related moderate to severe pulmonary involvement were identified as high-risk patients and were excluded.

RESULTS

35 deaths occurred during the study. The frequency of deaths was significantly higher in patients with COVID-19, 6 (9.4%) than patients without COVID-19, 29 (0. 43%). The average hospitalization stay was 12.8 ± 12.1 days. The odds ratio (OR) for death was significantly higher in patients with COVID-19 than patients without COVID-19. [OR: 8.13, Confidence interval 95% (CI95%) (5.02-11.25), P: 0.001]. Four (6.3%) COVID-19-associated complications were recorded in this series that all were respiratory failure requiring unexpected postoperative ventilation. Twenty surgical complications (31.3%) were recorded. The odds ratio for ICU admission was significantly higher in patients with COVID-19 than patients without COVID-19. [OR: 5.46, CI 95% (2.68-8.68), P: 0.001].

CONCLUSIONS

An increased threshold for orthopedic surgery is suggested for COVID-19 patients with a mortality rate of 9.3%, which is less than the mortality rate in other studies. Level of evidence III.

Incidence, characteristics, and outcome of COVID-19 in patients on liver transplant program: a retrospective study in the north of Iran

The risk of severe coronavirus disease-2019 (COVID-19) disease seems to be higher in individuals with solid organ transplantation. Therefore, the purpose of the present research is to investigate the incidence of COVID-19 and laboratory data and epidemiologic factors in liver transplant recipients and the patients on the waiting list for liver transplantation. In this study, we evaluated the records of patients on the waiting list for liver transplantation and of recipients of a liver transplant. Demographic data, underlying disease, history of drug use and participants' outcomes were collected. The diagnosis of SARS-CoV-2 infection for all patients was confirmed using a nasopharyngeal swab specimen with real-time RT-PCR. During the study period, 172 patients were enrolled, among whom 85 patients (49.4%) were on the waiting list for liver transplantation, and 87 patients (50.6%) were recipients of a liver transplant. Out of them, 10 (5.8%) had a positive result for SARS-CoV-2. Of these patients, 7.05% (6/85) and 4.6% (4/87) of patients on the waiting list and recipients of liver transplants were positive for SARS-CoV-2, respectively. Patients on the waiting list with COVID-19 infection had a higher median of albumin, ALT, AST, TBIL, DBIL, HDL and LDL value. In summary, the incidence of COVID-19 in liver transplant patients was slightly higher. The existence of underlying liver diseases should be well known as one of the poor predictive factors for worse outcomes in patients with COVID-19. So, comparative studies are recommended to identify risk factors for COVID-19 in patients with liver injury.

Correlation of Severity of COVID-19 Disease With Gastrointestinal Manifestations and Liver Injury - A North Brooklyn Community Hospital Experience: A Retrospective Cohort Study

Introduction The primary receptor for SARS-CoV-2 infection, angiotensin-converting enzyme-2 (ACE-2), is expressed in the gastrointestinal tract and liver parenchyma. The involvement of the gastrointestinal tract with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection has remained unclear. The following study retrospectively reviews gastrointestinal symptoms and liver function tests at the time of hospital admission to identify patient outcomes including prolonged hospital stay, the requirement for intensive care, and all-cause in-hospital 30-day mortality. Methods A retrospective review of patient charts at the Woodhull Medical and Mental Health Center (WMC) was conducted at the time of hospital admission, using a pre-determined selection criterion. All adult patients, both inpatient and outpatient, were included from March 2020 till May 2020. A 95% confidence interval was used to estimate the odds ratio (OR) for patient outcomes. Results Of the 520 patients, gastrointestinal symptoms including nausea (OR = 0.375, p = 0.015), and nausea and vomiting in combination (OR = 0.400, p = 0.016) had an inverse protective relationship with all-cause in-hospital 30-day mortality among COVID-19 patients. Gastrointestinal symptoms including diarrhea (OR = 1.008, p < 0.001), and nausea and vomiting (OR = 1.291, p = 0.043) had a mild impact on the length of hospital stay. Conclusion Elevated liver transaminases including alanine transaminase (ALT) and aspartate transaminase (AST) at the time of hospital admission can predict critical care requirement and all-cause 30-day hospital mortality in patients with COVID-19 infection. Presence of gastrointestinal symptoms is associated with worsened outcomes.