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      Clinical phenotypes and outcomes associated with SARS-CoV-2 Omicron sublineage JN.1 in critically ill COVID-19 patients: a prospective, multicenter cohort study in France, November 2022 to January 2024

      research-article
      1 , 2 , 3 , 4 , 32 , , 3 , 5 , 6 , 7 , 8 , 30 , 9 , 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 , 18 , 19 , 20 , 21 , 22 , 23 , 31 , 24 , 25 , 2 , 26 , 27 , 28 , 1 , 2 , 3 , 4 , 3 , 4 , 29 , 3 , 4 , 29 , the SEVARVIR investigators
      Annals of Intensive Care
      Springer International Publishing
      SARS-CoV-2, Omicron, Subvariant, JN.1, Acute respiratory failure

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          Abstract

          Background

          A notable increase in severe cases of COVID-19, with significant hospitalizations due to the emergence and spread of JN.1 was observed worldwide in late 2023 and early 2024. However, no clinical data are available regarding critically-ill JN.1 COVID-19 infected patients.

          Methods

          The current study is a substudy of the SEVARVIR prospective multicenter observational cohort study. Patients admitted to any of the 40 participating ICUs between November 17, 2022, and January 22, 2024, were eligible for inclusion in the SEVARVIR cohort study (NCT05162508) if they met the following inclusion criteria: age ≥ 18 years, SARS-CoV-2 infection confirmed by a positive reverse transcriptase-polymerase chain reaction (RT-PCR) in nasopharyngeal swab samples, ICU admission for acute respiratory failure. The primary clinical endpoint of the study was day-28 mortality. Evaluation of the association between day-28 mortality and sublineage group was conducted by performing an exploratory multivariable logistic regression model, after systematically adjusting for predefined prognostic factors previously shown to be important confounders (i.e. obesity, immunosuppression, age and SOFA score) computing odds ratios (OR) along with their corresponding 95% confidence intervals (95% CI).

          Results

          During the study period (November 2022–January 2024) 56 JN.1- and 126 XBB-infected patients were prospectively enrolled in 40 French intensive care units. JN.1-infected patients were more likely to be obese (35.7% vs 20.8%; p = 0.033) and less frequently immunosuppressed than others (20.4% vs 41.4%; p = 0.010). JN.1-infected patients required invasive mechanical ventilation support in 29.1%, 87.5% of them received dexamethasone, 14.5% tocilizumab and none received monoclonal antibodies. Only one JN-1 infected patient (1.8%) required extracorporeal membrane oxygenation support during ICU stay (vs 0/126 in the XBB group; p = 0.30). Day-28 mortality of JN.1-infected patients was 14.6%, not significantly different from that of XBB-infected patients (22.0%; p = 0.28). In univariable logistic regression analysis and in multivariable analysis adjusting for confounders defined a priori, we found no statistically significant association between JN.1 infection and day-28 mortality (adjusted OR 1.06 95% CI (0.17;1.42); p = 0.19). There was no significant between group difference regarding duration of stay in the ICU (6.0 [3.5;11.0] vs 7.0 [4.0;14.0] days; p = 0.21).

          Conclusions

          Critically-ill patients with Omicron JN.1 infection showed a different clinical phenotype than patients infected with the earlier XBB sublineage, including more frequent obesity and less immunosuppression. Compared with XBB, JN.1 infection was not associated with higher day-28 mortality.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s13613-024-01319-w.

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          Most cited references15

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          OpenSAFELY: factors associated with COVID-19 death in 17 million patients

          COVID-19 has rapidly impacted on mortality worldwide. 1 There is unprecedented urgency to understand who is most at risk of severe outcomes, requiring new approaches for timely analysis of large datasets. Working on behalf of NHS England we created OpenSAFELY: a secure health analytics platform covering 40% of all patients in England, holding patient data within the existing data centre of a major primary care electronic health records vendor. Primary care records of 17,278,392 adults were pseudonymously linked to 10,926 COVID-19 related deaths. COVID-19 related death was associated with: being male (hazard ratio 1.59, 95%CI 1.53-1.65); older age and deprivation (both with a strong gradient); diabetes; severe asthma; and various other medical conditions. Compared to people with white ethnicity, black and South Asian people were at higher risk even after adjustment for other factors (HR 1.48, 1.29-1.69 and 1.45, 1.32-1.58 respectively). We have quantified a range of clinical risk factors for COVID-19 related death in the largest cohort study conducted by any country to date. OpenSAFELY is rapidly adding further patients’ records; we will update and extend results regularly.
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            Acute respiratory distress syndrome: the Berlin Definition.

            The acute respiratory distress syndrome (ARDS) was defined in 1994 by the American-European Consensus Conference (AECC); since then, issues regarding the reliability and validity of this definition have emerged. Using a consensus process, a panel of experts convened in 2011 (an initiative of the European Society of Intensive Care Medicine endorsed by the American Thoracic Society and the Society of Critical Care Medicine) developed the Berlin Definition, focusing on feasibility, reliability, validity, and objective evaluation of its performance. A draft definition proposed 3 mutually exclusive categories of ARDS based on degree of hypoxemia: mild (200 mm Hg < PaO2/FIO2 ≤ 300 mm Hg), moderate (100 mm Hg < PaO2/FIO2 ≤ 200 mm Hg), and severe (PaO2/FIO2 ≤ 100 mm Hg) and 4 ancillary variables for severe ARDS: radiographic severity, respiratory system compliance (≤40 mL/cm H2O), positive end-expiratory pressure (≥10 cm H2O), and corrected expired volume per minute (≥10 L/min). The draft Berlin Definition was empirically evaluated using patient-level meta-analysis of 4188 patients with ARDS from 4 multicenter clinical data sets and 269 patients with ARDS from 3 single-center data sets containing physiologic information. The 4 ancillary variables did not contribute to the predictive validity of severe ARDS for mortality and were removed from the definition. Using the Berlin Definition, stages of mild, moderate, and severe ARDS were associated with increased mortality (27%; 95% CI, 24%-30%; 32%; 95% CI, 29%-34%; and 45%; 95% CI, 42%-48%, respectively; P < .001) and increased median duration of mechanical ventilation in survivors (5 days; interquartile [IQR], 2-11; 7 days; IQR, 4-14; and 9 days; IQR, 5-17, respectively; P < .001). Compared with the AECC definition, the final Berlin Definition had better predictive validity for mortality, with an area under the receiver operating curve of 0.577 (95% CI, 0.561-0.593) vs 0.536 (95% CI, 0.520-0.553; P < .001). This updated and revised Berlin Definition for ARDS addresses a number of the limitations of the AECC definition. The approach of combining consensus discussions with empirical evaluation may serve as a model to create more accurate, evidence-based, critical illness syndrome definitions and to better inform clinical care, research, and health services planning.
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              A global clinical measure of fitness and frailty in elderly people.

              There is no single generally accepted clinical definition of frailty. Previously developed tools to assess frailty that have been shown to be predictive of death or need for entry into an institutional facility have not gained acceptance among practising clinicians. We aimed to develop a tool that would be both predictive and easy to use. We developed the 7-point Clinical Frailty Scale and applied it and other established tools that measure frailty to 2305 elderly patients who participated in the second stage of the Canadian Study of Health and Aging (CSHA). We followed this cohort prospectively; after 5 years, we determined the ability of the Clinical Frailty Scale to predict death or need for institutional care, and correlated the results with those obtained from other established tools. The CSHA Clinical Frailty Scale was highly correlated (r = 0.80) with the Frailty Index. Each 1-category increment of our scale significantly increased the medium-term risks of death (21.2% within about 70 mo, 95% confidence interval [CI] 12.5%-30.6%) and entry into an institution (23.9%, 95% CI 8.8%-41.2%) in multivariable models that adjusted for age, sex and education. Analyses of receiver operating characteristic curves showed that our Clinical Frailty Scale performed better than measures of cognition, function or comorbidity in assessing risk for death (area under the curve 0.77 for 18-month and 0.70 for 70-month mortality). Frailty is a valid and clinically important construct that is recognizable by physicians. Clinical judgments about frailty can yield useful predictive information.
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                Author and article information

                Contributors
                nicolas.de-prost@aphp.fr
                Journal
                Ann Intensive Care
                Ann Intensive Care
                Annals of Intensive Care
                Springer International Publishing (Cham )
                2110-5820
                28 June 2024
                28 June 2024
                2024
                : 14
                : 101
                Affiliations
                [1 ]GRID grid.412116.1, ISNI 0000 0004 1799 3934, Médecine Intensive Réanimation, , Hôpitaux Universitaires Henri Mondor, Assistance Publique – Hôpitaux de Paris (AP-HP), ; Créteil, France
                [2 ]Groupe de Recherche Clinique CARMAS, Université Paris-Est-Créteil (UPEC), ( https://ror.org/05ggc9x40) Créteil, France
                [3 ]Université Paris-Est-Créteil (UPEC), ( https://ror.org/05ggc9x40) Créteil, France
                [4 ]GRID grid.462410.5, ISNI 0000 0004 0386 3258, INSERM U955, Team Viruses, Hepatology, Cancer, ; Créteil, France
                [5 ]GRID grid.412116.1, ISNI 0000 0004 1799 3934, Department of Public Health, , Hôpitaux Universitaires Henri Mondor, Assistance Publique – Hôpitaux de Paris (AP-HP), ; Créteil, France
                [6 ]GRID grid.462410.5, ISNI 0000 0004 0386 3258, IMRB INSERM U955, Team CEpiA, ; Créteil, France
                [7 ]Intensive Care Unit, Research Center for Respiratory Diseases (CEPR), INSERM U1100, Tours University Hospital, University of Tours, ( https://ror.org/02wwzvj46) Tours, France
                [8 ]INSERM U1259, Université de Tours, Tours, France
                [9 ]GRID grid.523099.4, ISNI 0000 0005 1237 6862, U1167 – RID-AGE Facteurs de Risque et Déterminants Moléculaires des Maladies Liées au Vieillissement, , University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, ; 59000 Lille, France
                [10 ]Service de Virologie, CHU de Lille, ( https://ror.org/02ppyfa04) 59000 Lille, France
                [11 ]GRID grid.414205.6, ISNI 0000 0001 0273 556X, DMU ESPRIT, Service de Médecine Intensive Réanimation, , Université Paris Cité, APHP, Hôpital Louis Mourier, ; Colombes, France
                [12 ]GRID grid.508487.6, ISNI 0000 0004 7885 7602, INSERM UMR-S1151, CNRS UMR-S8253, Institut Necker-Enfants Malades (INEM), , Université Paris Cité, ; Paris, France
                [13 ]IAME INSERM UMR 1137, Service de Virologie, Université Paris Cité, Hôpital Bichat-Claude Bernard, Assistance Publique – Hôpitaux de Paris, Paris, France
                [14 ]CHU Rennes, Maladies Infectieuses et Réanimation Médicale, ( https://ror.org/05qec5a53) Rennes, France
                [15 ]Laboratoire de Virologie, CHU Rennes, ( https://ror.org/05qec5a53) Rennes, France
                [16 ]GRID grid.41724.34, ISNI 0000 0001 2296 5231, Service de Médecine Intensive-Réanimation, , CHU De Rouen, ; 76000 Rouen, France
                [17 ]GRID grid.41724.34, ISNI 0000 0001 2296 5231, INSERM DYNAMICURE UMR 1311 Department of Virology, , Univ Rouen Normandie, Université de Caen Normandie, Normandie Univ, CHU Rouen, National Reference Center of HIV, ; 76000 Rouen, France
                [18 ]Service de Réanimation Médico-Chirurgicale, Centre Hospitalier du Mans, ( https://ror.org/03bf2nz41) Le Mans, France
                [19 ]Laboratoire de Microbiologie, Centre Hospitalier du Mans, ( https://ror.org/03bf2nz41) Le Mans, France
                [20 ]GRID grid.414474.6, ISNI 0000 0004 0639 3263, Service de Réanimation, , Hôpital Victor Dupouy, ; Argenteuil, France
                [21 ]GRID grid.414474.6, ISNI 0000 0004 0639 3263, Service de Virologie, , Hôpital Victor Dupouy, ; Argenteuil, France
                [22 ]GRID grid.411178.a, ISNI 0000 0001 1486 4131, INSERM CIC 1435 and UMR 1092, , Réanimation Polyvalente, CHU Limoges, ; Limoges, France
                [23 ]GRID grid.411178.a, ISNI 0000 0001 1486 4131, Bacteriology, Virology, Hygiene Department, , French National Reference Center for Herpesviruses, CHU Limoges, ; 87000 Limoges, France
                [24 ]Service de Réanimation Médicale, CHU de Nice, ( https://ror.org/05qsjq305) Nice, France
                [25 ]Laboratoire de Virologie, CHU de Nice, ( https://ror.org/05qsjq305) Nice, France
                [26 ]Service de Médecine Intensive-Réanimation, DMU 4 CORREVE Maladies du Cœur Et Des Vaisseaux, Assistance Publique – Hôpitaux de Paris, Hôpital de Bicêtre, FHU Sepsis, ( https://ror.org/00pg5jh14) Le Kremlin-Bicêtre, France
                [27 ]GRID grid.463845.8, ISNI 0000 0004 0638 6872, Inserm U1018, , Equipe d’Epidémiologie Respiratoire Intégrative, CESP, ; 94807 Villejuif, France
                [28 ]GRID grid.413133.7, ISNI 0000 0001 0206 8146, Laboratoire de Virologie, , Hôpital Paul Brousse, Assistance Publique – Hôpitaux de Paris, ; Villejuif, France
                [29 ]GRID grid.412116.1, ISNI 0000 0004 1799 3934, Department of Virology, , Hôpitaux Universitaires Henri Mondor, Assistance Publique – Hôpitaux de Paris, ; Créteil, France
                [30 ]GRID grid.411167.4, ISNI 0000 0004 1765 1600, National Reference Center for HIV-Associated Laboratory, , , CHRU de Tours, ; Tours, France
                [31 ]INSERM, RESINFIT, U1092, ( https://ror.org/02vjkv261) 87000 Limoges, France
                [32 ]GRID grid.412116.1, ISNI 0000 0004 1799 3934, Service de Médecine Intensive Réanimation, , Hôpital Henri Mondor, ; Créteil, France
                Author information
                http://orcid.org/0000-0002-4833-4320
                Article
                1319
                10.1186/s13613-024-01319-w
                11213836
                38940865
                ca3a58be-2762-4b1a-8aa5-26cc4f6211e6
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 11 March 2024
                : 25 May 2024
                Funding
                Funded by: EMERGEN consortium—ANRS Maladies Infectieuses Emergentes
                Award ID: ANRS0153
                Categories
                Research
                Custom metadata
                © La Société de Réanimation de Langue Francaise = The French Society of Intensive Care (SRLF) 2024

                Emergency medicine & Trauma
                sars-cov-2,omicron,subvariant,jn.1,acute respiratory failure
                Emergency medicine & Trauma
                sars-cov-2, omicron, subvariant, jn.1, acute respiratory failure

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