Summary Background Since December, 2019, Wuhan, China, has experienced an outbreak of coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Epidemiological and clinical characteristics of patients with COVID-19 have been reported but risk factors for mortality and a detailed clinical course of illness, including viral shedding, have not been well described. Methods In this retrospective, multicentre cohort study, we included all adult inpatients (≥18 years old) with laboratory-confirmed COVID-19 from Jinyintan Hospital and Wuhan Pulmonary Hospital (Wuhan, China) who had been discharged or had died by Jan 31, 2020. Demographic, clinical, treatment, and laboratory data, including serial samples for viral RNA detection, were extracted from electronic medical records and compared between survivors and non-survivors. We used univariable and multivariable logistic regression methods to explore the risk factors associated with in-hospital death. Findings 191 patients (135 from Jinyintan Hospital and 56 from Wuhan Pulmonary Hospital) were included in this study, of whom 137 were discharged and 54 died in hospital. 91 (48%) patients had a comorbidity, with hypertension being the most common (58 [30%] patients), followed by diabetes (36 [19%] patients) and coronary heart disease (15 [8%] patients). Multivariable regression showed increasing odds of in-hospital death associated with older age (odds ratio 1·10, 95% CI 1·03–1·17, per year increase; p=0·0043), higher Sequential Organ Failure Assessment (SOFA) score (5·65, 2·61–12·23; p Interpretation The potential risk factors of older age, high SOFA score, and d-dimer greater than 1 μg/mL could help clinicians to identify patients with poor prognosis at an early stage. Prolonged viral shedding provides the rationale for a strategy of isolation of infected patients and optimal antiviral interventions in the future. Funding Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences; National Science Grant for Distinguished Young Scholars; National Key Research and Development Program of China; The Beijing Science and Technology Project; and Major Projects of National Science and Technology on New Drug Creation and Development.

Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study

EASL 2017 Clinical Practice Guidelines on the management of hepatitis B virus infection.

1. Type 1 diabetes (due to b-cell destruction, usually leading to absolute insulin deficiency) 2. Type 2 diabetes (due to a progressive insulin secretory defect on the background of insulin resistance) 3. Gestational diabetes mellitus (GDM) (diabetes diagnosed in the second or third trimester of pregnancy that is not clearly overt diabetes) 4. Specific types of diabetes due to other causes, e.g., monogenic diabetes syndromes (such as neonatal diabetes and maturity-onset diabetes of the young [MODY]), diseases of the exocrine pancreas (such as cystic fibrosis), and drugor chemical-induced diabetes (such as in the treatment of HIV/AIDS or after organ transplantation)

Classification and diagnosis of diabetes

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen responsible for the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in global healthcare crises and strained health resources. As the population of patients recovering from COVID-19 grows, it is paramount to establish an understanding of the healthcare issues surrounding them. COVID-19 is now recognized as a multi-organ disease with a broad spectrum of manifestations. Similarly to post-acute viral syndromes described in survivors of other virulent coronavirus epidemics, there are increasing reports of persistent and prolonged effects after acute COVID-19. Patient advocacy groups, many members of which identify themselves as long haulers, have helped contribute to the recognition of post-acute COVID-19, a syndrome characterized by persistent symptoms and/or delayed or long-term complications beyond 4 weeks from the onset of symptoms. Here, we provide a comprehensive review of the current literature on post-acute COVID-19, its pathophysiology and its organ-specific sequelae. Finally, we discuss relevant considerations for the multidisciplinary care of COVID-19 survivors and propose a framework for the identification of those at high risk for post-acute COVID-19 and their coordinated management through dedicated COVID-19 clinics.

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Post-acute COVID-19 syndrome.

Review of recent research on hepatitis C therapy for 54th annual meeting of the American association for the study of liver diseases

We thank Lin et al. [1] for their comments on our manuscript entitled “Use of antibiotics during immune checkpoint inhibitors associates with lower survival in hepatocellular carcinoma” [2]. Several issues were raised in the letter including the start time for survival analysis, the details of survival time with Kaplan-Meier curve, and definition of cancer-related death. We would like to first highlight that a corrigendum has been made concerning the follow-up time [3]. The median follow-up should be 6.6 months (IQR: 2.3–17.8) with 4,810 person-months. The median time from receiving the first ICI to cancer-related and all-cause mortality should be 3.1 months (IQR: 1.6–6.7) and 3.2 months (IQR: 1.7–8.2), respectively. In the “Outcome definition” paragraph of our manuscript, it was mentioned that patients were observed from the start date of first immune checkpoint inhibitor as the index date till the occurrence of the outcome of interest or end of study. In the same paragraph, we have defined the primary outcome of cancer-related mortality as “liver cancer specified as the cause of death in the database” by the diagnosis codes. In the whole cohort, the 3-month, 6-month, 1-year, and 2-year probability of cancer-related survival was 70.7% (95% CI: 66.3–75.4%), 57.4% (95% CI: 52.6–62.6%), 45.9% (95% CI: 41.1–51.4%), and 37.4% (32.4–43.3%), respectively. Figure 1 shows the Kaplan-Meier survival plot of the whole cohort. Among the antibiotic users, the 3-month, 6-month, 1-year, and 2-year probability of cancer-related survival was 50.9% (95% CI: 42.0–61.7%), 35.3% (95% CI: 26.9– 46.4%), 26.8% (95% CI: 19.1–37.7%), and 19.3% (12.0– 31.1%), respectively. For antibiotic nonusers, the 3-month, 6-month, 1-year, and 2-year probability of cancer-related survival was 77.8% (95% CI: 73.1–82.8%), 64.7% (95% CI: 59.4–70.6%), 52.2% (95% CI: 46.5–58.5%), and 43.6% (37.7–50.5%), respectively. There was significant difference in cancer-related survival between the two groups (log-rank p < 0.001). Figure 2 shows the KaplanMeier survival plot according to antibiotic use.

https://www.karger.com/Article/Pdf/526003

Response to the Article on Antibiotics and Immune Checkpoint Inhibitors by Lin et al.

Background: We aimed to investigate the effect of non-alcoholic fatty liver disease (NAFLD) on BNT162b2 immunogenicity against wild-type SARS-CoV-2 and variants and infection outcome, as data are lacking. Methods: Recipients of two doses of BNT162b2 were prospectively recruited. Outcomes of interest were seroconversion of neutralizing antibody by live virus microneutralization (vMN) to SARS-CoV-2 strains (wild-type, delta and omicron variants) at day 21, 56 and 180 after first dose. Exposure of interest was moderate-to-severe NAFLD (controlled attenuation parameter ≥ 268 dB/M on transient elastography). We calculated adjusted odds ratio (aOR) of infection with NAFLD by adjusting for age, sex, overweight/obesity, diabetes and antibiotic use. Results: Of 259 BNT162b2 recipients (90 (34.7%) male; median age: 50.8 years (IQR: 43.6–57.8)), 68 (26.3%) had NAFLD. For wild type, there was no difference in seroconversion rate between NAFLD and control groups at day 21 (72.1% vs. 77.0%; p = 0.42), day 56 (100% vs. 100%) and day 180 (100% and 97.2%; p = 0.22), respectively. For the delta variant, there was no difference also at day 21 (25.0% vs. 29.5%; p = 0.70), day 56 (100% vs. 98.4%; p = 0.57) and day 180 (89.5% vs. 93.3%; p = 0.58), respectively. For the omicron variant, none achieved seroconversion at day 21 and 180. At day 56, there was no difference in seroconversion rate (15.0% vs. 18.0%; p = 0.76). NAFLD was not an independent risk factor of infection (aOR: 1.50; 95% CI: 0.68–3.24). Conclusions: NAFLD patients receiving two doses of BNT162b2 had good immunogenicity to wild-type SARS-CoV-2 and the delta variant but not the omicron variant, and they were not at higher risk of infection compared with controls.

https://www.mdpi.com/2076-393X/11/3/497/pdf?version=1676972813

Effect of Moderate to Severe Hepatic Steatosis on Vaccine Immunogenicity against Wild-Type and Mutant Virus and COVID-19 Infection among BNT162b2 Recipients

Liver fibrosis burden determines risk of hepatocellular carcinoma among patients with hepatitis B surface antigen seroclearance

In the published article, the estimates should have been exponentiated after obtaining the total standard error to calculate the confidence intervals in the simple ratio approach. This affected Table 2 and Supplementary Tables S6, S8 and S10. Only the confidence intervals were affected by this error. The corrections did not change the interpretation and conclusions of the study. The last author apologises for the errors.

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Ka Shing Cheung

Papers

Response to the Article on Antibiotics and Immune Checkpoint Inhibitors by Lin et al.

Effect of Moderate to Severe Hepatic Steatosis on Vaccine Immunogenicity against Wild-Type and Mutant Virus and COVID-19 Infection among BNT162b2 Recipients

Liver fibrosis burden determines risk of hepatocellular carcinoma among patients with hepatitis B surface antigen seroclearance

Correction to: Proton pump inhibitors and myocardial infarction: an application of active comparators in a self-controlled case series

Reply to GASTRO-D-20-01116.