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3 results on '"Beeker, Nathanael"'

1. External validation of prognostic scores for COVID-19: a multicenter cohort study of patients hospitalized in Greater Paris University Hospitals

Author

Lombardi, Yannis, Azoyan, Loris, Szychowiak, Piotr, Bellamine, Ali, Lemaitre, Guillaume, Bernaux, Mélodie, Daniel, Christel, Leblanc, Judith, Riller, Quentin, Steichen, Olivier, Ancel, Pierre-Yves, Bauchet, Alain, Beeker, Nathanael, Benoit, Vincent, Bey, Romain, Bourmaud, Aurélie, Bréant, Stéphane, Burgun, Anita, Carrat, Fabrice, Caucheteux, Charlotte, Champ, Julien, Cormont, Sylvie, Dubiel, Julien, Duclos, Catherine, Esteve, Loic, Frank, Marie, Garcelon, Nicolas, Gramfort, Alexandre, Griffon, Nicolas, Grisel, Olivier, Guilbaud, Martin, Hassen-Khodja, Claire, Hemery, François, Hilka, Martin, Jannot, Anne Sophie, Lambert, Jerome, Layese, Richard, Lebouter, Léo, Leprovost, Damien, Lerner, Ivan, Sallah, Kankoe Levi, Maire, Aurélien, Mamzer, Marie-France, Martel, Patricia, Mensch, Arthur, Moreau, Thomas, Neuraz, Antoine, Orlova, Nina, Paris, Nicolas, Rance, Bastien, Ravera, Hélène, Rozes, Antoine, Rufat, Pierre, Salamanca, Elisa, Sandrin, Arnaud, Serre, Patricia, Tannier, Xavier, Treluyer, Jean-Marc, van Gysel, Damien, Varoquaux, Gael, Vie, Jill-Jênn, Wack, Maxime, Wajsburt, Perceval, Wassermann, Demian, Zapletal, Eric, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), CHU Trousseau [Tours], Centre Hospitalier Régional Universitaire de Tours (CHRU Tours), Méthodes computationnelles et mathématiques pour comprendre la société et la santé à partir de données (SODA), Inria Saclay - Ile de France, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Laboratoire d'Informatique Médicale et Ingénierie des Connaissances en e-Santé (LIMICS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Sorbonne Paris Nord, Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité), Health data- and model- driven Knowledge Acquisition (HeKA), Inria de Paris, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre de Recherche des Cordeliers (CRC (UMR_S_1138 / U1138)), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris Cité (UPCité)-École Pratique des Hautes Études (EPHE), Imagine - Institut des maladies génétiques (IHU) (Imagine - U1163), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité), Centre d'Immunologie et de Maladies Infectieuses (CIMI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau et de la Moëlle Epinière = Brain and Spine Institute (ICM), Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Direction générale déléguée à l'innovation (DGD-I), Institut National de Recherche en Informatique et en Automatique (Inria), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre National de Référence Maladies auto-immunes Systémiques Rares [CHU Pitié-Salpêtrière], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Sorbonne Université (SU), Inria Siège, Service de Département de médecine interne et immunologie clinique [CHU Pitié-Salpêtrière] (DMIIC), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), and Gestionnaire, HAL Sorbonne Université 5

Subjects
Adult, Paris, medicine.medical_specialty, Coronavirus disease 2019 (COVID-19), Original, [SDV]Life Sciences [q-bio], 030204 cardiovascular system & hematology, Critical Care and Intensive Care Medicine, law.invention, Cohort Studies, Hospitals, University, 03 medical and health sciences, 0302 clinical medicine, law, Anesthesiology, medicine, Humans, 030212 general & internal medicine, Mortality, Retrospective Studies, [SDV.MP.VIR] Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Receiver operating characteristic, SARS-CoV-2, business.industry, External validation, COVID-19, Prognosis, University hospital, Intensive care unit, 3. Good health, Intensive Care Units, Editorial, SARS-CoV2, [SDV.MP.VIR]Life Sciences [q-bio]/Microbiology and Parasitology/Virology, Emergency medicine, Cohort, business, Cohort study
Abstract

Purpose The Coronavirus disease 2019 (COVID-19) has led to an unparalleled influx of patients. Prognostic scores could help optimizing healthcare delivery, but most of them have not been comprehensively validated. We aim to externally validate existing prognostic scores for COVID-19. Methods We used “COVID-19 Evidence Alerts” (McMaster University) to retrieve high-quality prognostic scores predicting death or intensive care unit (ICU) transfer from routinely collected data. We studied their accuracy in a retrospective multicenter cohort of adult patients hospitalized for COVID-19 from January 2020 to April 2021 in the Greater Paris University Hospitals. Areas under the receiver operating characteristic curves (AUC) were computed for the prediction of the original outcome, 30-day in-hospital mortality and the composite of 30-day in-hospital mortality or ICU transfer. Results We included 14,343 consecutive patients, 2583 (18%) died and 5067 (35%) died or were transferred to the ICU. We examined 274 studies and found 32 scores meeting the inclusion criteria: 19 had a significantly lower AUC in our cohort than in previously published validation studies for the original outcome; 25 performed better to predict in-hospital mortality than the composite of in-hospital mortality or ICU transfer; 7 had an AUC > 0.75 to predict in-hospital mortality; 2 had an AUC > 0.70 to predict the composite outcome. Conclusion Seven prognostic scores were fairly accurate to predict death in hospitalized COVID-19 patients. The 4C Mortality Score and the ABCS stand out because they performed as well in our cohort and their initial validation cohort, during the first epidemic wave and subsequent waves, and in younger and older patients. Supplementary Information The online version contains supplementary material available at 10.1007/s00134-021-06524-w.

Published
2021

2. Prognosis of French COVID-19 patients with chronic liver disease: A national retrospective cohort study for 2020.

Author

Mallet, Vincent, Beeker, Nathanael, Bouam, Samir, Sogni, Philippe, and Pol, Stanislas

Subjects
*COVID-19, *ALCOHOLISM, *CHRONICALLY ill, *FATTY liver, *COHORT analysis, *PROGNOSIS
Abstract

The impact of chronic liver disease on outcomes in patients with COVID-19 is uncertain. Hence, we aimed to explore this association. We explored the outcomes of all adult inpatients with COVID-19 in France, in 2020. We computed adjusted odds ratios to measure the associations between chronic liver disease, alcohol use disorders, mechanical ventilation and day-30 in-hospital mortality. The sample comprised 259,110 patients (median [IQR] age 70 (54–83) years; 52% men), including 15,476 (6.0%) and 10,006 (3.9%) patients with chronic liver disease and alcohol use disorders, respectively. Death occurred in 38,203 (15%) patients, including 7,475 (28%) after mechanical ventilation, and 2,941 (19%) with chronic liver disease. The adjusted odds ratios for mechanical ventilation and day-30 mortality were 1.54 (95% CI 1.44–1.64, p < 0.001) and 1.79 (1.71–1.87, p < 0.001) for chronic liver disease; 0.55 (0.47–0.64, p < 0.001) and 0.54 (0.48–0.61, p < 0.001) for mild liver disease; 0.64 (0.53–0.76; p < 0.001) and 0.71 (0.63–0.80, p < 0.001) for compensated cirrhosis; 0.65 (0.52–0.81, p < 0.001) and 2.21 (1.94–2.51, p < 0.001) for decompensated cirrhosis; 0.34 (0.24–0.50; p < 0.001) and 1.38 (1.17–1.62, p < 0.001) for primary liver cancer; and 0.82 (0.76–0.89; p < 0.001) and 1.11 (1.05–1.17; p < 0.001) for alcohol use disorders. Chronic viral hepatitis; non-viral, non-alcoholic chronic hepatitis; organ, including liver, transplantation, and acquired immunodeficiency syndrome were not associated with COVID-19-related death. Chronic liver disease increased the risk of COVID-19-related death in France in 2020. Therapeutic effort limitation may have contributed to COVID-19-related death in French residents with a liver-related complication or an alcohol use disorder. We studied the outcomes, including mechanical ventilation and day-30 mortality, of all adults with COVID-19 who were discharged from acute and post-acute care in France in 2020 (N = 259,110). Patients with mild liver disease; compensated cirrhosis; organ, including liver, transplantation; or acquired immunodepression syndrome were not at increased risk of COVID-19-related mortality. Patients with alcohol use disorders, decompensated cirrhosis, or primary liver cancer were at increased risk of COVID-19-related mortality but were less likely to receive mechanical ventilation. Our results suggest that therapeutic effort limitation may have contributed to the excess mortality in French residents with a liver-related complication or an alcohol use disorder. [Display omitted] • We assessed the association between chronic liver disease and clinical outcomes of in-patients with COVID-19. • Chronic liver disease increased the risk of COVID-19-related death. • Therapeutic effort limitations may have contributed to death of patients with decompensated cirrhosis, primary liver cancer, or with an alcohol use disorder. [ABSTRACT FROM AUTHOR]

Published
2021
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3. Obesity Doubles Mortality in Patients Hospitalized for Severe Acute Respiratory Syndrome Coronavirus 2 in Paris Hospitals, France: A Cohort Study on 5,795 Patients.

Author

Czernichow, Sébastien, Beeker, Nathanael, Rives‐Lange, Claire, Guerot, Emmanuel, Diehl, Jean‐Luc, Katsahian, Sandrine, Hulot, Jean‐Sébastien, Poghosyan, Tigran, Carette, Claire, Jannot, Anne‐Sophie, Ancel, Pierre‐Yves, Bauchet, Alain, Benoit, Vincent, Bernaux, Mélodie, Bellamine, Ali, Bey, Romain, Bourmaud, Aurélie, Bréant, Stéphane, Burgun, Anita, and Carrat, Fabrice

Subjects
COVID-19, COHORT analysis, OBESITY, MORTALITY
Abstract

Objective: Preliminary data from different cohorts of small sample size or with short follow‐up indicate poorer prognosis in people with obesity compared with other patients. This study aims to precisely describe the strength of association between obesity in patients hospitalized with coronavirus disease 2019 (COVID‐19) and mortality and to clarify the risk according to usual cardiometabolic risk factors in a large cohort. Methods: This is a prospective cohort study including 5,795 patients aged 18 to 79 years hospitalized from February 1 to April 30, 2020, in the Paris area, with confirmed infection by severe acute respiratory syndrome coronavirus 2. Adjusted regression models were used to estimate the odds ratios (ORs) and 95% CIs for the mortality rate at 30 days across BMI classes, without and with imputation for missing BMI values. Results: Eight hundred ninety‐one deaths had occurred at 30 days. Mortality was significantly raised in people with obesity, with the following ORs for BMI of 30 to 35 kg/m2, 35 to 40 kg/m2, and >40 kg/m2: 1.89 (95% CI: 1.45‐2.47), 2.79 (95% CI: 1.95‐3.97), and 2.55 (95% CI: 1.62‐3.95), respectively (18.5‐25 kg/m2 was used as the reference class). This increase holds for all age classes. Conclusions: Obesity doubles mortality in patients hospitalized with COVID‐19. [ABSTRACT FROM AUTHOR]

Published
2020
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