Susceptibility of Patients with Inflammatory Bowel Disease to COVID-19 Compared with Their Households.

BACKGROUND: Immunosuppressive agents used in the treatment of inflammatory bowel diseases (IBDs) could potentially increase the risk of coronavirus disease 2019 (COVID-19). We aimed to compare COVID-19 frequency in patients with IBD with their households and identify the related risk factors. METHODS: Firstly, a multi-centered, observational study on 2110 patients with IBD and 2110 age-matched household members was conducted to compare COVID-19 frequency. Secondly, the data of patients with IBD and COVID-19 who had called the COVID-19 hotline were added. Multivariable logistic regression was used to evaluate the effect of age, type and severity of IBD, the number of comorbidities, and medications on the frequency of COVID-19 among the patients with IBD. RESULTS: The prevalence of COVID-19 in patients with IBD and household groups was similar (34 [1.61%] versus 35 [1.65%]; P = 0.995). The prevalence of COVID-19 increased from 2.1% to 7.1% in those with three or more comorbidities (P = 0.015) and it was significantly higher in those with severe IBD (P = 0.026). The multivariable analysis only showed a significant association with anti-TNF monotherapy (OR: 2.5, CI: 0.97-6.71, P = 0.05), and other medications were not associated with COVID-19. CONCLUSION: The prevalence of COVID-19 in patients with IBD was similar to the household members. Only patients with IBD receiving anti-TNF monotherapy had a higher risk of COVID-19 susceptibility. This finding could be attributed to the higher exposure to the virus during administration in health care facilities.

Outcomes of COVID-19 in Patients with Inflammatory Bowel Disease: Comparison with Household Members and the Role of IBD Medications.

BACKGROUND: Most data on the effect of inflammatory bowel disease (IBD) and its treatments on coronavirus disease 2019 (COVID-19) outcomes have not had non-IBD comparators. Hence, we aimed to describe COVID-19 outcomes in IBD compared to non-IBD patients. METHODS: We conducted a prospective cohort study of registered IBD patients with confirmed COVID-19 from six provinces in Iran from February to April 2020. Proven COVID-19 patients were followed up at four weeks and the frequency of outcomes was assessed. Multivariable logistic regression was used to assess associations between demographics, clinical characteristics and COVID-19 outcomes. RESULTS: Overall, 2159 IBD patients and 4721 household members were enrolled, with 84 (3.9%) and 49 (1.1%) participants having confirmed COVID-19, respectively. Household spread of COVID-19 was not common in this cohort (1.2%). While hospitalization was significantly more frequent in IBD patients compared with non-IBD household members (27.1% vs. 6.0%, P=0.002), there was no significant difference in the frequency of severe cases. Age and presence of IBD were positively associated with hospitalization in IBD compared with non-IBD household members (OR: 1.06, 95% CI: 1.03-1.10; OR: 5.7, 95% CI: 2.02- 16.07, respectively). Age, presence of new gastrointestinal symptoms, and 5-aminosalicylic acid (5-ASA) use were associated with higher hospitalization rate in IBD patients (OR: 1.13, 95% CI: 1.05-1.23; OR: 6.49, 95% CI: 1.87-22.54; OR: 6.22, 95% CI: 1.90-20.36, respectively). Anti-tumor necrosis factor (TNF) was not associated with more severe outcomes. CONCLUSION: Age, presence of new gastrointestinal symptoms and use of 5-ASA were associated with increased hospitalization rate among IBD patients, while anti-TNF therapy had no statistical association.

Effectiveness of COVID-19 Vaccines against Delta (B.1.617.2) Variant: A Systematic Review and Meta-Analysis of Clinical Studies.

The high transmissibility, mortality, and morbidity rate of the SARS-CoV-2 Delta (B.1.617.2) variant have raised concerns regarding vaccine effectiveness (VE). To address this issue, all publications relevant to the effectiveness of vaccines against the Delta variant were searched in the Web of Science, Scopus, EMBASE, and Medline (via PubMed) databases up to 15 October 2021. A total of 15 studies (36 datasets) were included in the meta-analysis. After the first dose, the VE against the Delta variant for each vaccine was 0.567 (95% CI 0.520-0.613) for Pfizer-BioNTech, 0.72 (95% CI 0.589-0.822) for Moderna, 0.44 (95% CI 0.301-0.588) for AstraZeneca, and 0.138 (95% CI 0.076-0.237) for CoronaVac. Meta-analysis of 2,375,957 vaccinated cases showed that the Pfizer-BioNTech vaccine had the highest VE against the infection after the second dose, at 0.837 (95% CI 0.672-0.928), and third dose, at 0.972 (95% CI 0.96-0.978), as well as the highest VE for the prevention of severe infection or death, at 0.985 (95% CI 0.95-0.99), amongst all COVID-19 vaccines. The short-term effectiveness of vaccines, especially mRNA-based vaccines, for the prevention of the Delta variant infection, hospitalization, severe infection, and death is supported by this study. Limitations include a lack of long-term efficacy data, and under-reporting of COVID-19 infection cases in observational studies, which has the potential to falsely skew VE rates. Overall, this study supports the decisions by public health decision makers to promote the population vaccination rate to control the Delta variant infection and the emergence of further variants.

A Reliable Prognostic Marker for Liver Dysfunction in COVID-19 Infection.

BACKGROUND In December 2019, COVID-19 emerged from China and spread to become a pandemic, killing over 1,350,000 up to November 18, 2020. Some patients with COVID-19 have abnormal liver function tests. We aimed to determine the clinical significance of liver chemistries in patients with COVID-19. METHODS We performed a cross-sectional study of 1044 consecutive patients with confirmed COVID-19 in two referral hospitals in Tehran, Iran, from February to April 2020. All cases were diagnosed by clinical criteria and confirmed by characteristic changes in the spiral chest computed tomography (CT) and nucleic acid testing of the nasopharyngeal samples. We evaluated the association between abnormal liver enzymes or function tests and survival, intensive care unit (ICU) admission and fatty liver changes in CT scans. RESULTS The mean age was 61.01 ± 16.77 years, and 57.68% were male. Of 495 patients with elevated alanine transaminase (ALT) levels, 194 had chest CT scans, in which fatty liver disease was seen in 38.1%. 41 patients (21.13%) had moderate to severe, and 33 (17.01%) had borderline fatty liver disease. Bilirubin, albumin, and partial thromboplastin time (PTT), along with other markers such as HCO3, C-reactive protein (CRP), triglyceride, and length of admission, were significantly associated with ICU admission and mortality. Prothrombin time (PT), platelet count, and low-density lipoprotein (LDL) levels were also correlated with mortality. Fasting blood sugar (FBS) and pH were important indices in ICU admitted patients. CONCLUSION Liver function tests accurately predict a worse prognosis in patients with COVID-19. However, liver enzymes were only slightly increased in those who died or needed ICU admission and were not related to the fatty liver changes.

Machine learning-based prognostic modeling using clinical data and quantitative radiomic features from chest CT images in COVID-19 patients.

OBJECTIVE: To develop prognostic models for survival (alive or deceased status) prediction of COVID-19 patients using clinical data (demographics and history, laboratory tests, visual scoring by radiologists) and lung/lesion radiomic features extracted from chest CT images. METHODS: Overall, 152 patients were enrolled in this study protocol. These were divided into 106 training/validation and 46 test datasets (untouched during training), respectively. Radiomic features were extracted from the segmented lungs and infectious lesions separately from chest CT images. Clinical data, including patients' history and demographics, laboratory tests and radiological scores were also collected. Univariate analysis was first performed (q-value reported after false discovery rate (FDR) correction) to determine the most predictive features among all imaging and clinical data. Prognostic modeling of survival was performed using radiomic features and clinical data, separately or in combination. Maximum relevance minimum redundancy (MRMR) and XGBoost were used for feature selection and classification. The receiver operating characteristic (ROC) curve and the area under the ROC curve (AUC), sensitivity, specificity, and accuracy were used to assess the prognostic performance of the models on the test datasets. RESULTS: For clinical data, cancer comorbidity (q-value < 0.01), consciousness level (q-value < 0.05) and radiological score involved zone (q-value < 0.02) were found to have high correlated features with outcome. Oxygen saturation (AUC = 0.73, q-value < 0.01) and Blood Urea Nitrogen (AUC = 0.72, q-value = 0.72) were identified as high clinical features. For lung radiomic features, SAHGLE (AUC = 0.70) and HGLZE (AUC = 0.67) from GLSZM were identified as most prognostic features. Amongst lesion radiomic features, RLNU from GLRLM (AUC = 0.73), HGLZE from GLSZM (AUC = 0.73) had the highest performance. In multivariate analysis, combining lung, lesion and clinical features was determined to provide the most accurate prognostic model (AUC = 0.95 ± 0.029 (95%CI: 0.95-0.96), accuracy = 0.88 ± 0.046 (95% CI: 0.88-0.89), sensitivity = 0.88 ± 0.066 (95% CI = 0.87-0.9) and specificity = 0.89 ± 0.07 (95% CI = 0.87-0.9)). CONCLUSION: Combination of radiomic features and clinical data can effectively predict outcome in COVID-19 patients. The developed model has significant potential for improved management of COVID-19 patients.

Clinical characteristics and outcomes of diabetics hospitalized for COVID-19 infection: a single-centered, retrospective, observational study.

Some debates exist regarding the association of diabetes mellitus (DM) with COVID-19 infection severity and mortality. In this study, we aimed to describe and compare the clinical characteristics and outcomes of hospitalized COVID-19 patients with and without DM. In this single-centered, retrospective, observational study, we enrolled adult patients with COVID-19 who were admitted to the Shariati hospital, Tehran, Iran, from February 25, 2020, to April 21, 2020. The clinical and paraclinical information as well as the clinical outcomes of patients were collected from inpatient medical records. A total of 353 cases were included (mean age, 61.67 years; 57.51 % male), of whom 111 patients were diabetics (mean age, 63.66 years; 55.86 % male). In comparison to those without DM, diabetic patients with COVID-19 were more likely to have other comorbidities, elevated systolic blood pressure (SBP), elevated blood sugar (BS), lower estimated glomerular filtration rate (eGFR) and elevated blood urea nitrogen (BUN). The association of DM with severe outcomes of COVID-19 infection (i.e. mechanical ventilation, median length of hospital stay and mortality) remained non-significant before and after adjustments for several factors including age, sex, body mass index (BMI), smoking status, and comorbidities. Based on our results DM has not been associated with worse outcomes in hospitalized patients for COVID-19 infection.

Clinical characteristics, outcomes, and risk factors for mortality in hospitalized patients with COVID-19 and cancer history: a propensity score-matched study.

BACKGROUND: COVID-19 has caused great concern for patients with underlying medical conditions. We aimed to determine the prognosis of patients with current or previous cancer with either a PCR-confirmed COVID-19 infection or a probable diagnosis according to chest CT scan. METHODS: We conducted a case control study in a referral hospital on confirmed COVID-19 adult patients with and without a history of cancer from February25th to April21st, 2020. Patients were matched according to age, gender, and underlying diseases including ischemic heart disease (IHD), diabetes mellitus (DM), and hypertension (HTN). Demographic features, clinical data, comorbidities, symptoms, vital signs, laboratory findings, and chest computed tomography (CT) images have been extracted from patients' medical records. Multivariable logistic regression was used to estimate odd ratios and 95% confidence intervals of each factor of interest with outcomes. RESULTS: Fifty-three confirmed COVID-19 patients with history of cancer were recruited and compared with 106 non-cancerous COVID-19 patients as controls. Male to female ratio was 1.33 and 45% were older than 65. Dyspnea and fever were the most common presenting symptoms in our population with 57.86 and 52.83% respectively. Moreover, dyspnea was significantly associated with an increased rate of mortality in the cancer subgroup (p = 0.013). Twenty-six patients (49%) survived among the cancer group while 89 patients (84%) survived in control (p = 0.000). in cancer group, patients with hematologic cancer had 63% mortality while patients with solid tumors had 37%. multivariate analysis model for survival prediction showed that history of cancer, impaired consciousness level, tachypnea, tachycardia, leukocytosis and thrombocytopenia were associated with an increased risk of death. CONCLUSION: In our study, cancer increased the mortality rate and hospital stay of COVID-19 patients and this effect remains significant after adjustment of confounders. Compared to solid tumors, hematologic malignancies have been associated with worse consequences and higher mortality rate. Clinical and para-clinical indicators were not appropriate to predict death in these patients.

Metabolic risk factors and risk of Covid-19: A systematic review and meta-analysis.

OBJECTIVE: Based on the epidemiologic findings of Covid-19 incidence; illness and mortality seem to be associated with metabolic risk factors. This systematic review and meta-analysis aimed to assess the association of metabolic risk factors and risk of Covid-19. METHODS: This study was designed according to PRISMA guidelines. Two independent researchers searched for the relevant studies using PubMed, Web of Science, Cochrane Library, and Scopus. The search terms developed focusing on two main roots of "Covid-19" and "metabolic risk factors". All relevant observational, analytical studies, review articles, and a meta-analysis on the adult population were included in this meta-analysis. Meta-analysis was performed using the random effect model for pooling proportions to address heterogeneity among studies. Data were analyzed using STATA package version 11.2, (StataCorp, USA). RESULTS: Through a comprehensive systematic search in the targeted databases we found 1124 papers, after running the proses of refining, 13 studies were included in the present meta-analysis. The pooled prevalence of obesity in Covid-19 patients was 29% (95% CI: 14-47%). For Diabetes and Hypertension, these were 22% (95% CI: 12% 33%) and 32% (95% CI: 12% 56%), respectively. There was significant heterogeneity in the estimates of the three pooled prevalence without any significant small-study effects. Such warning points, to some extent, guide physicians and clinicians to better understand the importance of controlling co-morbid risk factors in prioritizing resource allocation and interventions. CONCLUSION: The meta-analysis showed that hypertension is more prevalent than obesity and diabetes in patients with Covid-19 disease. The prevalence of co-morbid metabolic risk factors must be adopted for better management and priority settings of public health vaccination and other required interventions. The results may help to improve services delivery in COVID-19 patients, while helping to develop better policies for prevention and response to COVID-19 and its critical outcomes.

A Multicenter Survey on the Trend of Chest CT Scan Utilization: Tracing the First Footsteps of COVID-19 in Iran.

BACKGROUND: Chest computed tomography (CT) scan has been used widely to diagnose COVID-19 in Iran. OBJECTIVES: To trace the footsteps of COVID-19 in Iran by exploring the trend in using chest CT scans and its economic impact on radiology departments. Methods: In this cross-sectional study, the number of imaging examinations from 33 tertiary radiology departments in 9 large cities of Iran was collected from September 23, 2019 to March 20, 2020 (Months 1 to 6) and the corresponding months in 2018-2019. RESULTS: A 50.2% increase was noted in the chest CT scan utilization in 2019-2020 compared to 2018-2019. This increase was +15%, +15%, +27%, +2%, +1% in Months 1-5 of 2019-2020, respectively. In Month 6 of 2019-2020, a 251% increase in the acquisition of chest CT scans was observed compared to the Month 6 of 2018-2019. Following negative balance of revenue from Month 1 to 5 with respect to the inflation rate, the total income in Month 6 was further 1.5% less than the same Month in 2018-19. CONCLUSION: The observed peak in chest CT utilization in Month 3 prior to the surge in Month 6 could be explained by the seasonal influenza. However, unawareness about an emerging viral disease, i.e. COVID-19, might have underutilized chest CT in Months 4 and 5 before the official announcement in Month 6. The unbalanced increase in the workload of radiology departments in the shortage of cardiothoracic radiologists with the simultaneous decrease in income initiated a vicious cycle that worsened the economic repercussions of the pandemic.

Predictive value of initial CT scan for various adverse outcomes in patients with COVID-19 pneumonia.

BACKGROUND: Chest computed tomography (CT) scan is frequently used in the diagnosis of COVID-19 pneumonia. OBJECTIVES: This study investigates the predictive value of CT severity score (CSS) for length-of-stay (LOS) in hospital, initial disease severity, ICU admission, intubation, and mortality. METHODS: In this retrospective study, initial CT scans of consecutively admitted patients with COVID-19 pneumonia were reviewed in a tertiary hospital. The association of CSS with the severity of disease upon admission and the final adverse outcomes was assessed using Pearson's correlation test and logistic regression, respectively. RESULTS: Total of 121 patients (60±16 years), including 54 women and 67 men, with positive RT-PCR tests were enrolled. We found a significant but weak correlation between CSS and qSOFA, as a measure of disease severity (r: 0.261, p = 0.003). No significant association was demonstrated between CSS and LOS. Patients with CSS>8 had at least three-fold higher risk of ICU admission, intubation, and mortality. CONCLUSIONS: CSS in baseline CT scan of patients with COVID-19 pneumonia can predict adverse outcomes and is weakly correlated with initial disease severity.