Objective The COVID-19 pandemic is rapidly spreading worldwide, notably in Europe and North America where obesity is highly prevalent. The relation between obesity and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has not been fully documented. Methods This retrospective cohort study analyzed the relationship between clinical characteristics, including BMI, and the requirement for invasive mechanical ventilation (IMV) in 124 consecutive patients admitted in intensive care for SARS-CoV-2 in a single French center. Results Obesity (BMI > 30) and severe obesity (BMI > 35) were present in 47.6% and 28.2% of cases, respectively. Overall, 85 patients (68.6%) required IMV. The proportion of patients who required IMV increased with BMI categories (P 35 (85.7%). In multivariate logistic regression, the need for IMV was significantly associated with male sex (P 35 versus patients with BMI Conclusions The present study showed a high frequency of obesity among patients admitted in intensive care for SARS-CoV-2. Disease severity increased with BMI. Obesity is a risk factor for SARS-CoV-2 severity, requiring increased attention to preventive measures in susceptible individuals.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/oby.22831

High Prevalence of Obesity in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Requiring Invasive Mechanical Ventilation.

aDepartment of Pharmacology and Therapeutics, University of Porto; MedInUP, Centre for Drug Discovery and Innovative Medicines; Centro Hospitalar São João, Porto, Portugal bIBD Unit, DIMEC, University of Bologna, Bologna, Italy cDepartment of Gastroenterology and Hepatology, Chaim Sheba Medical Center, Tel Hashomer, Israel dGastrointestinal Unit ASST Fatebenefratelli Sacco—University of Milan—Milan, Italy eIBD Unit Complesso Integrato Columbus, Gastroenterological and Endocrino-Metabolical Sciences Department, Fondazione Policlinico Universitario Gemelli Universita’ Cattolica del Sacro Cuore, Rome, Italy fDepartment of Gastroenterology, IBD Unit, University Hospital Santiago De Compostela (CHUS), A Coruña, Spain gDepartment of Gastroenterology, North Zealand University Hospital, Frederikssund, Denmark hFirst Department of Medicine, Semmelweis University, Budapest, Hungary iIBD Unit, St Mark’s Hospital, Middlesex, UK jDepartment of Gastroenterology, University Hospital of Ghent, Ghent, Belgium kInstitute of Pathology, Medical University of Graz, Graz, Austria lDepartment of Gastroenterology, Pennine Acute Hospitals NHS Trust; Institute of Inflammation and Repair, University of Manchester, Manchester, UK mUnit of General Surgery, Second University of Naples, Napoli, Italy nMaria Skłodowska-Curie Memorial Cancer Centre and Institute of Oncology, Department of Oncological Gastroenterology Warsaw; Medical Centre for Postgraduate Education, Department of Gastroenterology, Hepatology and Clinical Oncology, Warsaw, Poland oDepartment of Medicine, University of Cambridge, Cambridge, UK pImperial College London; Chelsea and Westminster Hospital, London, UK qDepartment of Pathobiology /NC22, Lerner Research Institute; Department of Gastroenterology, Hepatology and Nutrition/A3, Digestive Disease and Surgery Institute, Cleveland Clinic Foundation, Cleveland, OH, USA

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Third European Evidence-based Consensus on Diagnosis and Management of Ulcerative Colitis. Part 1: Definitions, Diagnosis, Extra-intestinal Manifestations, Pregnancy, Cancer Surveillance, Surgery, and Ileo-anal Pouch Disorders.

Since 2009 pandemic, international health authorities recommended monitoring severe and complicated cases of respiratory disease, that is, severe acute respiratory infection (SARI) and acute respiratory distress syndrome (ARDS). We evaluated the proportion of SARI/ARDS cases and deaths due to influenza A(H1N1)pdm09 infection and the impact of other respiratory viruses during pandemic and postpandemic period (2009–2011) in northern Italy; additionally we searched for unknown viruses in those cases for which diagnosis remained negative. 206 respiratory samples were collected from SARI/ARDS cases and analyzed by real-time RT-PCR/PCR to investigate influenza viruses and other common respiratory pathogens; also, a virus discovery technique (VIDISCA-454) was applied on those samples tested negative to all pathogens. Influenza A(H1N1)pdm09 virus was detected in 58.3% of specimens, with a case fatality rate of 11.3%. The impact of other respiratory viruses was 19.4%, and the most commonly detected viruses were human rhinovirus/enterovirus and influenza A(H3N2). VIDISCA-454 enabled the identification of one previously undiagnosed measles infection. Nearly 22% of SARI/ARDS cases did not obtain a definite diagnosis. In clinical practice, great efforts should be dedicated to improving the diagnosis of severe respiratory disease; the introduction of innovative molecular technologies, as VIDISCA-454, will certainly help in reducing such “diagnostic gap.”

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Influenza and other respiratory viruses involved in severe acute respiratory disease in northern Italy during the pandemic and postpandemic period (2009-2011).

https://hal.univ-reunion.fr/hal-01274568/document

Effectiveness of neuraminidase inhibitors in reducing mortality in patients admitted to hospital with influenza A H1N1pdm09 virus infection: a meta-analysis of individual participant data.

Pregnancy and pregnancy-associated hormones alter immune responses and disease pathogenesis

Background: Since the start of the 2009 influenza A pandemic (H1N1pdm), the World Health Organization and its member states have gathered information to characterize the clinical severity of H1N1pdm infection and to assist policy makers to determine risk groups for targeted control measures. Methods and Findings: Data were collected on approximately 70,000 laboratory-confirmed hospitalized H1N1pdm patients, 9,700 patients admitted to intensive care units (ICUs), and 2,500 deaths reported between 1 April 2009 and 1 January 2010 from 19 countries or administrative regions—Argentina, Australia, Canada, Chile, China, France, Germany, Hong Kong SAR, Japan, Madagascar, Mexico, the Netherlands, New Zealand, Singapore, South Africa, Spain, Thailand, the United States, and the United Kingdom—to characterize and compare the distribution of risk factors among H1N1pdm patients at three levels of severity: hospitalizations, ICU admissions, and deaths. The median age of patients increased with severity of disease. The highest per capita risk of hospitalization was among patients ,5 y and 5–14 y (relative risk [RR] = 3.3 and 3.2, respectively, compared to the general population), whereas the highest risk of death per capita was in the age groups 50–64 y and $65 y (RR = 1.5 and 1.6, respectively, compared to the general population). Similarly, the ratio of H1N1pdm deaths to hospitalizations increased with age and was the highest in the $65-y-old age group, indicating that while infection rates have been observed to be very low in the oldest age group, risk of death in those over the age of 64 y who became infected was higher than in younger groups. The proportion of H1N1pdm patients with one or more reported chronic conditions increased with severity (median = 31.1%, 52.3%, and 61.8% of hospitalized, ICU-admitted, and fatal H1N1pdm cases, respectively). With the exception of the risk factors asthma, pregnancy, and obesity, the proportion of patients with each risk factor increased with severity level. For all levels of severity, pregnant women in their third trimester consistently accounted for the majority of the total of pregnant women. Our findings suggest that morbid obesity might be a risk factor for ICU admission and fatal outcome (RR = 36.3). Conclusions: Our results demonstrate that risk factors for severe H1N1pdm infection are similar to those for seasonal influenza, with some notable differences, such as younger age groups and obesity, and reinforce the need to identify and protect groups at highest risk of severe outcomes. Please see later in the article for the Editors’ Summary.

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Risk Factors for Severe Outcomes following 2009 Influenza A (H1N1) Infection: A Global Pooled Analysis

Objective To analyze the reporting of unknown etiology pneumonia(UEP) cases from 2004 to 2009 in China and explore the possible influencing factors.Methods The analysis was conducted on the intervals between illness onset and diagnosing,diagnosing and reporting as well as reporting and verifying of the UEP cases reported through passive reporting surveillance system during this period.Results A total of 864 cases were reported from 2004 to 2009,the reported incidence peaked during the SARS epidemic in Beijing and Anhui from April to May in 2004,and during the epidemics of human avian influenza in winter of 2005 and spring of 2006 and in early 2009.The medians of interval between illness onset and diagnosing,diagnosing and reporting as well as reporting and verifying were 5.0 days,0.7 day and 0.1 day respectively.The median of interval(8.0 days) between illness onset and diagnosing of UEP cases reported during the two epidemic peak periods of human avian influenza were longer than that in other period.The median of interval(8.0 days) between illness onset and diagnosing of the UEP cases which were diagnosed as human avian influenza was longer than that of the UEP cases which weren't diagnosed as human avian influenza.ConclusionThough the UEP surveillance played an important role in the case finding of human avian influenza,the problems still exist.According to the surveillance situation,it is suggested that the case definition of UEP and surveillance procedure should be revised to improve the surveillance.

Yu Hongjie

Papers

Risk Factors for Severe Outcomes following 2009 Influenza A (H1N1) Infection: A Global Pooled Analysis

Analysis on reporting of unknown etiology pneumonia cases in China, 2004-2009.