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1. Predicting 90-day survival of patients with COVID-19: Survival of Severely Ill COVID (SOSIC) scores

Author

Schmidt, Matthieu, Guidet, Bertrand, Demoule, Alexandre, Ponnaiah, Maharajah, Fartoukh, Muriel, Puybasset, Louis, Combes, Alain, Hajage, David, Mercat, Alain, Asfar, Pierre, Beloncle, François, Demiselle, Julien, Pham, Tài, Pavot, Arthur, Monnet, Xavier, Richard, Christian, Dres, Martin, Mayaux, Julien, Beurton, Alexandra, Daubin, Cédric, Descamps, Richard, Joret, Aurélie, Du Cheyron, Damien, Pene, Frédéric, Chiche, Jean-Daniel, Jozwiak, Mathieu, Jaubert, Paul, Voiriot, Guillaume, Teulier, Marion, Blayau, Clarisse, L’her, Erwen, Aubron, Cécile, Bodenes, Laetitia, Ferriere, Nicolas, Auchabie, Johann, Le Meur, Anthony, Pignal, Sylvain, Mazzoni, Thierry, Quenot, Jean-Pierre, Andreu, Pascal, Roudau, Jean-Baptiste, Labruyère, Marie, Nseir, Saad, Preau, Sébastien, Poissy, Julien, Mathieu, Daniel, Benhamida, Sarah, Paulet, Rémi, Roucaud, Nicolas, Thyrault, Martial, Daviet, Florence, Hraiech, Sami, Parzy, Gabriel, Sylvestre, Aude, Jochmans, Sébastien, Bouilland, Anne-Laure, Monchi, Mehran, Danguy Des Déserts, Marc, Mathais, Quentin, Rager, Gwendoline, Pasquier, Pierre, Jean, Reignier, Amélie, Seguin, Charlotte, Garret, Emmanuel, Canet, Dellamonica, Jean, Saccheri, Clément, Lombardi, Romain, Kouchit, Yanis, Jacquier, Sophie, Mathonnet, Armelle, Nay, Mai-Ahn, Runge, Isabelle, Martino, Frédéric, Flurin, Laure, Rolle, Amélie, Carles, Michel, Coudroy, Rémi, Thille, Arnaud, Frat, Jean-Pierre, Rodriguez, Maeva, Beuret, Pascal, Tientcheu, Audrey, Vincent, Arthur, Michelin, Florian, Tamion, Fabienne, Carpentier, Dorothée, Boyer, Déborah, Girault, Christophe, Gissot, Valérie, Ehrmann, Stéphan, Salmon Gandonniere, Charlotte, Elaroussi, Djlali, Delbove, Agathe, Fedun, Yannick, Huntzinger, Julien, Lebas, Eddy, Kisoka, Grâce, Grégoire, Céline, Marchetta, Stella, Lambermont, Bernard, Argaud, Laurent, Baudry, Thomas, Bertrand, Pierre-Jean, Dargent, Auguste, Guitton, Christophe, Chudeau, Nicolas, Landais, Mickaël, Darreau, Cédric, Ferre, Alexis, Gros, Antoine, Lacave, Guillaume, Bruneel, Fabrice, Neuville, Mathilde, Devaquet, Jérôme, Tachon, Guillaume, Gallot, Richard, Chelha, Riad, Galbois, Arnaud, Jallot, Anne, Chalumeau Lemoine, Ludivine, Kuteifan, Khaldoun, Pointurier, Valentin, Jandeaux, Louise-Marie, Mootien, Joy, Damoisel, Charles, Sztrymf, Benjamin, Chommeloux, Juliette, Luyt, Charles-Edouard, Schortgen, Frédérique, Rusel, Leon, Jung, Camille, Gobert, Florent, Vimpere, Damien, Lamhaut, Lionel, Sauneuf, Bertrand, Charrrier, Liliane, Calus, Julien, Desmeules, Isabelle, Painvin, Benoît, Tadie, Jean-Marc, Castelain, Vincent, Michard, Baptiste, Herbrecht, Jean-Etienne, Baldacini, Mathieu, Weiss, Nicolas, Demeret, Sophie, Marois, Clémence, Rohaut, Benjamin, Moury, Pierre-Henri, Savida, Anne-Charlotte, Couadau, Emmanuel, Série, Mathieu, Alexandru, Nica, Bruel, Cédric, Fontaine, Candice, Garrigou, Sonia, Courtiade Mahler, Juliette, Leclerc, Maxime, Ramakers, Michel, Garçon, Pierre, Massou, Nicole, van Vong, Ly, Sen, Juliane, Lucas, Nolwenn, Chemouni, Franck, Stoclin, Annabelle, Avenel, Alexandre, Faure, Henri, Gentilhomme, Angélie, Ricome, Sylvie, Abraham, Paul, Monard, Céline, Textoris, Julien, Rimmele, Thomas, Montini, Florent, Lejour, Gabriel, Lazard, Thierry, Etienney, Isabelle, Kerroumi, Younes, Dupuis, Claire, Bereiziat, Marine, Coupez, Elisabeth, Thouy, François, Hoffmann, Clément, Donat, Nicolas, Chrisment, Anne, Blot, Rose-Marie, Kimmoun, Antoine, Jacquot, Audrey, Mattei, Matthieu, Levy, Bruno, Ravan, Ramin, Dopeux, Loïc, Liteaudon, Jean-Mathias, Roux, Delphine, Rey, Brice, Anghel, Radu, Schenesse, Deborah, Gevrey, Vincent, Castanera, Jermy, Petua, Philippe, Madeux, Benjamin, Hartman, Otto, Piagnerelli, Michael, Joosten, Anne, Noel, Cinderella, Biston, Patrick, Noel, Thibaut, Bouar, Gurvan, Boukhanza, Messabi, Demarest, Elsa, Bajolet, Marie-France, Charrier, Nathanaël, Quenet, Audrey, Zylberfajn, Cécile, Dufour, Nicolas, Mégarbane, Buno, Voicu, Sqébastian, Deye, Nicolas, Malissin, Isabelle, Legay, François, Debarre, Matthieu, Barbarot, Nicolas, Fillatre, Pierre, Delord, Bertrand, Laterrade, Thomas, Saghi, Tahar, Pujol, Wilfried, Cungi, Pierre-Julien, Esnault, Pierre, Cardinale, Mickael, Hong Tuan Ha, Vivien, Fleury, Grégory, Brou, Marie-Ange, Zafimahazo, Daniel, Tran-Van, David, Avargues, Patrick, Carenco, Lisa, Robin, Nicolas, Ouali, Alexandre, Houdou, Lucie, Le Terrier, Christophe, Suh, Noémie, Primmaz, Steve, Pugin, Jérome, Weiss, Emmanuel, Gauss, Tobias, Moyer, Jean-Denis, Paugam Burtz, Catherine, La Combe, Béatrice, Smonig, Rolland, Violleau, Jade, Cailliez, Pauline, Chelly, Jonathan, Marchalot, Antoine, Saladin, Cécile, Bigot, Christelle, Fayolle, Pierre-Marie, Fatséas, Jules, Ibrahim, Amr, Resiere, Dabor, Hage, Rabih, Cholet, Clémentine, Cantier, Marie, Trouiler, Pierre, Montravers, Philippe, Lortat-Jacob, Brice, Tanaka, Sebastien, Tran Dinh, Alexy, Duranteau, Jacques, Harrois, Anatole, Dubreuil, Guillaume, Werner, Marie, Godier, Anne, Hamada, Sophie, Zlotnik, Diane, Nougue, Hélène, Mekontso-Dessap, Armand, Carteaux, Guillaume, Razazi, Keyvan, de Prost, Nicolas, Mongardon, Nicolas, Langeron, Olivier, Levesque, Eric, Attias, Arié, de Roquetaillade, Charles, Chousterman, Benjamin, Mebazaa, Alexandre, Gayat, Etienne, Garnier, Marc, Pardo, Emmanuel, Satre-Buisson, Lea, Gutton, Christophe, Yvin, Elise, Marcault, Clémence, Azoulay, Elie, Darmon, Michael, Ait Oufella, Hafid, Hariri, Geoffroy, Urbina, Tomas, Mazerand, Sandie, Heming, Nicholas, Santi, Francesca, Moine, Pierre, Annane, Djillali, Bouglé, Adrien, Omar, Edris, Lancelot, Aymeric, Begot, Emmanuelle, Plantefeve, Gaétan, Contou, Damien, Mentec, Hervé, Pajot, Olivier, Faguer, Stanislas, Cointault, Olivier, Lavayssiere, Laurence, Nogier, Marie-Béatrice, Jamme, Matthieu, Pichereau, Claire, Hayon, Jan, Outin, Hervé, Dépret, François, Coutrot, Maxime, Chaussard, Maité, Guillemet, Lucie, Goffin, Pierre, Thouny, Romain, Guntz, Julien, Jadot, Laurent, Persichini, Romain, Jean-Michel, Vanessa, Georges, Hugues, Caulier, Thomas, Pradel, Gaël, Hausermann, Marie-Hélène, Nguyen-Valat, Thi My Hue, Boudinaud, Michel, Vivier, Emmanuel, Rosseli, Sylvène, Bourdin, Gaël, Pommier, Christian, Vinclair, Marc, Poignant, Simon, Mons, Sandrine, Bougouin, Wulfran, Bruna, Franklin, Maestraggi, Quentin, Roth, Christian, Bitker, Laurent, Dhelft, François, Bonnet-Chateau, Justine, Filippelli, Mathilde, Morichau-Beauchant, Tristan, Thierry, Stéphane, Le Roy, Charlotte, Saint Jouan, Mélanie, Goncalves, Bruno, Mazeraud, Aurélien, Daniel, Matthieu, Sharshar, Tarek, Cadoz, Cyril, Gaci, Rostane, Gette, Sébastien, Louis, Guillaune, Sacleux, Sophe-Caroline, Ordan, Marie-Amélie, Cravoisy, Aurélie, Conrad, Marie, Courte, Guilhem, Gibot, Sébastien, Benzidi, Younès, Casella, Claudia, Serpin, Laurent, Setti, Jean-Lou, Besse, Marie-Catherine, Bourreau, Anna, Pillot, Jérôme, Rivera, Caroline, Vinclair, Camille, Robaux, Marie-Aline, Achino, Chloé, Delignette, Marie-Charlotte, Mazard, Tessa, Aubrun, Frédéric, Bouchet, Bruno, Frérou, Aurélien, Muller, Laura, Quentin, Charlotte, Degoul, Samuel, Stihle, Xavier, Sumian, Claude, Bergero, Nicoletta, Lanaspre, Bernard, Quintard, Hervé, Maiziere, Eve Marie, Egreteau, Pierre-Yves, Leloup, Guillaume, Berteau, Florin, Cottrel, Marjolaine, Bouteloup, Marie, Jeannot, Matthieu, Blanc, Quentin, Saison, Julien, Geneau, Isabelle, Grenot, Romaric, Ouchike, Abdel, Hazera, Pascal, Masse, Anne-Lyse, Demiri, Suela, Vezinet, Corinne, Baron, Elodie, Benchetrit, Deborah, Monsel, Antoine, Trebbia, Grégoire, Schaack, Emmanuelle, Lepecq, Raphaël, Bobet, Mathieu, Vinsonneau, Christophe, Dekeyser, Thibault, Delforge, Quentin, Rahmani, Imen, Vivet, Bérengère, Paillot, Jonathan, Hierle, Lucie, Chaignat, Claire, Valette, Sarah, Her, Benoït, Brunet, Jennifier, Page, Mathieu, Boiste, Fabienne, Collin, Anthony, Bavozet, Florent, Garin, Aude, Dlala, Mohamed, Mhamdi, Kais, Beilouny, Bassem, Lavalard, Alexandra, Perez, Severine, Veber, Benoit, Guitard, Pierre-Gildas, Gouin, Philippe, Lamacz, Anna, Plouvier, Fabienne, Delaborde, Bertrand, Kherchache, Aïssa, Chaalal, Amina, Ricard, Jean-Damien, Amouretti, Marc, Freita-Ramos, Santiago, Roux, Damien, Constantin, Jean-Michel, Assefi, Mona, Lecore, Marine, Selves, Agathe, Prevost, Florian, Lamer, Christian, Shi, Ruiying, Knani, Lyes, Pili Floury, Sébastien, Vettoretti, Lucie, Levy, Michael, Marsac, Lucile, Dauger, Stéphane, Guilmin-Crépon, Sophie, Winiszewski, Hadrien, Piton, Gael, Soumagne, Thibaud, Capellier, Gilles, Putegnat, Jean-Baptiste, Bayle, Frédérique, Perrou, Maya, Thao, Ghyslaine, Géri, Guillaume, Charron, Cyril, Repessé, Xavier, Vieillard-Baron, Antoine, Guilbart, Mathieu, Roger, Pierre-Alexandre, Hinard, Sébastien, Macq, Pierre-Yves, Chaulier, Kevin, Goutte, Sylvie, Chillet, Patrick, Pitta, Anaïs, Darjent, Barbara, Bruneau, Amandine, Lasocki, Sigismond, Leger, Maxime, Gergaud, Soizic, Lemarie, Pierre, Terzi, Nicolas, Schwebel, Carole, Dartevel, Anaïs, Galerneau, Louis-Marie, Diehl, Jean-Luc, Hauw-Berlemont, Caroline, Péron, Nicolas, Guérot, Emmanuel, Mohebbi Amoli, Abolfazl, Benhamou, Michel, Deyme, Jean-Pierre, Andremont, Olivier, Lena, Diane, Cady, Julien, Causeret, Arnaud, de la Chapelle, Arnaud, Cracco, Christophe, Rouleau, Stéphane, Schnell, David, Foucault, Camille, Lory, Cécile, Chapelle, Thibault, Bruckert, Vincent, Garcia, Julie, Sahraoui, Abdlazize, Abbosh, Nathalie, Bornstain, Caroline, Pernet, Pierre, Poirson, Florent, Pasem, Ahmed, Karoubi, Philippe, Poupinel, Virginie, Gauthier, Caroline, Bouniol, François, Feuchere, Philippe, Heron, Anne, Carreira, Serge, Emery, Malo, Le Floch, Anne Sophie, Giovannangeli, Luana, Herzog, Nicolas, Giacardi, Christophe, Baudic, Thibaut, Thill, Chloé, Lebbah, Said, Palmyre, Jessica, Tubach, Florence, Bonnet, Nicolas, Ebstein, Nathan, Gaudry, Stéphane, Cohen, Yves, Noublanche, Julie, Lesieur, Olivier, Sément, Arnaud, Roca-Cerezo, Isabel, Pascal, Michel, Sma, Nesrine, Colin, Gwenhaël, Lacherade, Jean-Claude, Bionz, Gauthier, Maquigneau, Natacha, Bouzat, Pierre, Durand, Michel, Hérault, Marie-Christine, Payen, Jean-Francois, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), 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), REanimation et Soins intensifs du Patient en Insuffisance Respiratoire aigüE [CHU Pitié-Salpêtrière] (GRC RESPIRE), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut Pierre Louis d'Epidémiologie et de Santé Publique (iPLESP), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Neurophysiologie Respiratoire Expérimentale et Clinique (UMRS 1158), Département Médico-Universitaire APPROCHES, CHU Tenon [AP-HP], Groupe de recherche clinique CARMAS (Cardiovascular and Respiratory Manifestations of Acute lung injury and Sepsis) (CARMAS), 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 Henri Mondor, Laboratoire d'Imagerie Biomédicale (LIB), Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre de Pharmacoépidémiologie de l'AP-HP (Cephepi), INSERM UMRS-1144, Université Paris Cité, Réanimation Médicale et Toxicologique, Hôpital Lariboisière, and Mégarbane, Bruno

Subjects
[SDV.MHEP.ME] Life Sciences [q-bio]/Human health and pathology/Emerging diseases, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, Acute respiratory distress syndrome, RC86-88.9, Research, COVID-19, Medical emergencies. Critical care. Intensive care. First aid, Critical Care and Intensive Care Medicine, Predictive survival model, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.TOX] Life Sciences [q-bio]/Toxicology, Mechanical ventilation, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.TOX]Life Sciences [q-bio]/Toxicology, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.MHEP.PSR] Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Outcome
Abstract

Background Predicting outcomes of critically ill intensive care unit (ICU) patients with coronavirus-19 disease (COVID-19) is a major challenge to avoid futile, and prolonged ICU stays. Methods The objective was to develop predictive survival models for patients with COVID-19 after 1-to-2 weeks in ICU. Based on the COVID–ICU cohort, which prospectively collected characteristics, management, and outcomes of critically ill patients with COVID-19. Machine learning was used to develop dynamic, clinically useful models able to predict 90-day mortality using ICU data collected on day (D) 1, D7 or D14. Results Survival of Severely Ill COVID (SOSIC)-1, SOSIC-7, and SOSIC-14 scores were constructed with 4244, 2877, and 1349 patients, respectively, randomly assigned to development or test datasets. The three models selected 15 ICU-entry variables recorded on D1, D7, or D14. Cardiovascular, renal, and pulmonary functions on prediction D7 or D14 were among the most heavily weighted inputs for both models. For the test dataset, SOSIC-7’s area under the ROC curve was slightly higher (0.80 [0.74–0.86]) than those for SOSIC-1 (0.76 [0.71–0.81]) and SOSIC-14 (0.76 [0.68–0.83]). Similarly, SOSIC-1 and SOSIC-7 had excellent calibration curves, with similar Brier scores for the three models. Conclusion The SOSIC scores showed that entering 15 to 27 baseline and dynamic clinical parameters into an automatable XGBoost algorithm can potentially accurately predict the likely 90-day mortality post-ICU admission (sosic.shinyapps.io/shiny). Although external SOSIC-score validation is still needed, it is an additional tool to strengthen decisions about life-sustaining treatments and informing family members of likely prognosis.

Published
2021
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2. Comparison of high flow nasal cannula oxygen and conventional oxygen therapy on ventilatory support duration during acute-on-chronic respiratory failure: study protocol of a multicentre, randomised, controlled trial. The 'HIGH-FLOW ACRF' study

Author

Jean-Damien, Ricard, Fadia, Dib, Marina, Esposito-Farese, Jonathan, Messika, Christophe, Girault, Lise, Piquilloud, Ecologie et Evolution des Microorganismes (EEM), Université Paris Diderot - Paris 7 (UPD7)-Université Paris 13 (UP13)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre de Pharmacoépidémiologie de l'AP-HP (Cephepi), 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), Hôpital Louis Mourier - AP-HP [Colombes], CHU Rouen, Normandie Université (NU), Hémodynamique, Interaction Fibrose et Invasivité tumorales Hépatiques (HIFIH), and Université d'Angers (UA)

Subjects
Adult, Lung Diseases, Male, medicine.medical_specialty, [SDV]Life Sciences [q-bio], medicine.medical_treatment, Population, medicine.disease_cause, law.invention, Hypercapnia, 03 medical and health sciences, 0302 clinical medicine, Randomized controlled trial, law, Oxygen therapy, medicine, Humans, 030212 general & internal medicine, education, Monitoring, Physiologic, education.field_of_study, Noninvasive Ventilation, business.industry, Oxygen Inhalation Therapy, General Medicine, Intensive care unit, 3. Good health, Outcome and Process Assessment, Health Care, 030228 respiratory system, Emergency medicine, Good clinical practice, Breathing, Female, business, Respiratory Insufficiency, Nasal cannula, Respiratory care
Abstract

IntroductionThis study protocol describes a trial designed to investigate whether high-flow heated and humidified nasal oxygen (HFHO) therapy in patients with hypercapnic acute respiratory failure (ARF) reduces the need of non-invasive ventilation (NIV).Methods and analysisThis is an open-label, superiority, international, parallel-group, multicentre randomised controlled two-arm trial, with an internal feasibility pilot phase. 242 patients with hypercapnic ARF requiring NIV admitted to an intensive care unit, an intermediate care or a respiratory care unit will be randomised in a 1:1 ratio to receive HFHO or standard oxygen in between NIV sessions. Randomisation will be centralised and stratified by centre and pH at admission (pH ≤7.25 or >7.25). The primary outcome will be the number of ventilator-free days (VFDs) and alive at day 28 postrandomisation. The secondary outcomes will encompass parameters related to the VFDs, comfort and tolerance variables, hospital length of stay and mortality. VFDs at 28 days postrandomisation will be compared between the two groups by Wilcoxon-Mann-Whitney two-sample rank-sum test in the intention-to-treat population. A sensitivity analysis will be conducted in the population of patients for whom the criteria of switching from NIV to spontaneous breathing, or conversely, are not strictly verified.Ethics and disseminationThe protocol has been approved by theComité de Protection des Personnes(CPP)Sud-Ouest & Outre-Mer IV(ref CPP17-049a/2017-A01830-53) and will be carried out in accordance with the Declaration of Helsinki and Good Clinical Practice guidelines. A trial steering committee will oversee the progress of the study. Findings will be disseminated through national and international scientific conferences, and publication in peer-reviewed journals.Trial registration numberNCT03406572.

Published
2018
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3. Online training on skin cancer diagnosis in rheumatologists: results from a nationwide randomized web-based survey

Author

Viguier, Manuelle, Rist, Stéphanie, Aubin, François, Leccia, Marie-Thérèse, Richard, Marie-Aleth, Esposito-Farèse, Marina, Gaudin, Philippe, Pham, Thao, Richette, Pascal, Wendling, Daniel, Sibilia, Jean, Tubach, Florence, Dufrene, Charles, Darras, Yannick, Sauvage, Eric, Carret, Sophie, Amoura, Zahir, Benveniste, Olivier, Boyer, Olivier, Durez, Patrick, Fautrel, Bruno, Guerne, Pierre-André, Hachulla, Eric, Jullien, Denis, Mouthon, Luc, Puechal, Xavier, Sellam, Jérémie, Hôpital Saint-Louis, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Diderot - Paris 7 (UPD7), Service de Rhumatologie, Centre Hospitalier Régional d'Orléans (CHRO), Carcinogénèse épithéliale : facteurs prédictifs et pronostiques - UFC (EA 3181) (CEF2P / CARCINO), Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Clinique de Dermatologie Allergologie et Photobiologie, Centre Hospitalier Universitaire [Grenoble] (CHU), Centre de Recherches en Oncologie biologique et Oncopharmacologie (CRO2), Aix Marseille Université (AMU)- Hôpital de la Timone [CHU - APHM] (TIMONE)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de Dermatologie, Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Centre de Pharmacoépidémiologie de l'AP-HP (Cephepi), 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), Clinique Universitaire de Rhumatologie, hôpital Sud, CHU de Grenoble, Assistance Publique - Hôpitaux de Marseille (APHM)-CHU Marseille, Université Paris Diderot - Paris 7 (UPD7)-Hôpital Lariboisière-APHP, Centre Hospitalier Régional Universitaire de Besançon (CHRU Besançon), Immuno-Rhumatologie Moléculaire, Université de Strasbourg (UNISTRA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Club Rhumatismes et Inflammation, HAL AMU, Administrateur, Carcinogénèse épithéliale : facteurs prédictifs et pronostiques - UFC (UR 3181) (CEF2P / CARCINO), Assistance publique - Hôpitaux de Paris (AP-HP)-Université Paris Diderot - Paris 7 ( UPD7 ), Centre Hospitalier Régional d'Orléans ( CHR ), Carcinogénèse épithéliale : facteurs prédictifs et pronostiques - UFC ( CEF2P / CARCINO ), Centre Hospitalier Régional Universitaire [Besançon] ( CHRU Besançon ) -Université Bourgogne Franche-Comté ( UBFC ) -Université de Franche-Comté ( UFC ), Centre Hospitalier Universitaire [Grenoble] ( CHU ), Centre de Recherches en Oncologie biologique et Oncopharmacologie ( CRO2 ), Aix Marseille Université ( AMU ) - Hôpital de la Timone [CHU - APHM] ( TIMONE ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Assistance Publique - Hôpitaux de Marseille ( APHM ) - Hôpital de la Timone [CHU - APHM] ( TIMONE ), Centre de Pharmaco-épidémiologie (Céphépi), Université Paris Diderot - Paris 7 ( UPD7 ) -AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance Publique - Hôpitaux de Marseille ( APHM ) -CHU Marseille, Université Paris Diderot - Paris 7 ( UPD7 ) -Hôpital Lariboisière-APHP, Centre Hospitalier Régional Universitaire [Besançon] ( CHRU Besançon ), Immunorhumathologie moléculaire, Institut National de la Santé et de la Recherche Médicale ( INSERM ), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
Adult, Male, medicine.medical_specialty, Randomization, Skin Neoplasms, Population, lcsh:Medicine, [SDV.CAN]Life Sciences [q-bio]/Cancer, THERAPY, [ SDV.CAN ] Life Sciences [q-bio]/Cancer, [SDV.CAN] Life Sciences [q-bio]/Cancer, Rheumatology, Internal medicine, Physicians, Surveys and Questionnaires, medicine, NECROSIS-FACTOR INHIBITORS, Humans, Medical diagnosis, education, lcsh:Science, METAANALYSIS, RISK, education.field_of_study, Internet, Multidisciplinary, integumentary system, business.industry, Incidence (epidemiology), lcsh:R, Middle Aged, medicine.disease, Confidence interval, 3. Good health, Surgery, RHEUMATOID-ARTHRITIS, Rheumatoid arthritis, lcsh:Q, Education, Medical, Continuing, Female, Skin cancer, business, Research Article
Abstract

International audience; Patients with inflammatory rheumatisms, such as rheumatoid arthritis, are more prone to develop skin cancers than the general population, with an additional increased incidence when receiving TNF blockers. There is therefore a need that physicians treating patients affected with inflammatory rheumatisms with TNF blockers recognize malignant skin lesions, requiring an urgent referral to the dermatologist and a potential withdrawal or modification of the immunomodulatory treatment. We aimed to demonstrate that an online training dedicated to skin tumors increase the abilities of rheumatologists to discriminate skin cancers from benign skin tumors. A nationwide randomized web-based survey involving 141 French rheumatologists was conducted. The baseline evaluation included short cases with skin lesion pictures and multiple choice questions assessing basic knowledge on skin cancers. For each case, rheumatologists had to indicate the nature of skin lesion (benign; premalignant/ malignant), their level of confidence in this diagnosis (10-points Likert scale), and the precise dermatological diagnosis among 5 propositions. Different scores were established. After randomization, only one group had access to the online formation consisting in 4 elearning modules on skin tumors, of 15 minutes each (online training group). After reevaluation, the trained and the non-trained group (control group) were compared. The primary end-point was the number of adequate diagnoses of the nature of the skin lesions. The mean number of adequate diagnosis for the benign versus premalignant/malignant nature of the lesions was higher in the online training group (13.4 vs. 11.2 points; p value

Published
2015
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4. Can we improve transthoracic echocardiography training in non-cardiologist residents? Experience of two training programs in the intensive care unit

Author

Stéphane Ederhy, Didier Dreyfuss, Blandine Pasquet, Vincent Labbé, Jean-Damien Ricard, Ariel Cohen, Cédric Rafat, David Hajage, Romain Miguel-Montanes, Muriel Fartoukh, Stéphane Gaudry, HAL-UPMC, Gestionnaire, Pôle Thorax Voies aériennes, Groupe Hospitalier des Hôpitaux Universitaires de l’Est Parisien, Service de Réanimation et USC Médico-Chirurgicale = Médecine intensive réanimation [CHU Tenon], CHU Tenon [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), Service de Cardiologie [CHU Saint-Antoine], CHU Saint-Antoine [AP-HP], Service d’épidémiologie et de recherche clinique [Hôpital Louis Mourier], Hôpital Louis Mourier - AP-HP [Colombes], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Intensive Care Department, University Hospital and University of Geneva, Service de Réanimation Médico-Chirurgicale [Hôpital Louis Mourier], Service d'Urgences néphrologiques et transplantation rénale [CHU Tenon], Epidémiologie Clinique et Evaluation Economique Appliquées aux Populations Vulnérables (ECEVE (U1123 / UMR_S_1123)), Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital universitaire Robert-Debré [Paris], CIC 1425, Hôpital Bichat - Claude Bernard, Centre de Pharmacoépidémiologie de l'AP-HP (Cephepi), CHU Pitié-Salpêtrière [AP-HP], Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Pierre et Marie Curie - Paris 6 (UPMC), Service de Réanimation et USC Médico-Chirurgicale [CHU Tenon], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Urgences néphrologiques et transplantation rénale [CHU Tenon], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-CHU Tenon [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Institut National de la Santé et de la Recherche Médicale (INSERM)-AP-HP Hôpital universitaire Robert-Debré [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Université Paris Diderot - Paris 7 (UPD7), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC), and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
medicine.medical_specialty, Transthoracic echocardiography, [SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging, 030204 cardiovascular system & hematology, Critical Care and Intensive Care Medicine, Inferior vena cava, law.invention, 03 medical and health sciences, 0302 clinical medicine, [SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, law, Internal medicine, Intensive care, Critical care nursing, medicine, Ejection fraction, business.industry, Research, Stroke volume, Academic training, Intensive care unit, Confidence interval, [SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system, [SDV.IB.IMA] Life Sciences [q-bio]/Bioengineering/Imaging, 030228 respiratory system, medicine.vein, SAPS II, Cardiology, Curriculum, business
Abstract

Background To evaluate the diagnostic performances of two training programs for residents with no prior ultrasound experience to reach competences in extended basic critical care transthoracic echocardiography (CCE) including Doppler capabilities. Methods This is a prospective observational study in two intensive care units of teaching hospitals. Group I (five residents) completed a short training program (4-h theory; 3-h practical); group II (six residents) completed a longer training program (6-h theory; 12-h practical). The residents and an expert examined all patients who required a transthoracic echocardiography. Their agreement studied by Cohen’s κ coefficient, concordance coefficient correlation (CCC) and Bland–Altman plots was used as an indicator of program effectiveness. Results Group I performed 136 CCEs (mean/resident 27; range 22–32; 65 in ventilated patients) in 115 patients (62 men; 64 ± 18 years; Simplified Acute Physiologic Score [SAPS] II 37 ± 18). Group II performed 158 CCEs (mean/resident 26; range 21–31; 65 in ventilated patients) in 108 patients (64 men; 58 ± 17 years; SAPS II 42 ± 22). Both groups adequately assessed left ventricular (LV) systolic function (κ 0.75, 95 % confidence interval [CI] 0.64–0.86; κ 0.77, 95 % CI 0.66–0.88, respectively) and pericardial effusion (κ 0.83, 95 % CI 0.67–0.99; κ 0.76, 95 % CI 0.60–0.93, respectively). Group II appraised severe right ventricular dilatation and significant left-sided valve disease with good to very good agreement (κ 0.80, 95 % CI 0.56–0.96; κ 0.79, 95 % CI 0.66–0.93, respectively). Regarding left ventricular ejection fraction, E/A ratio, E/e′ ratio and aortic peak velocity assessed by group II, CCCs were all >0.70 and the bias (mean difference) ±SD on Bland–Altman analysis was 1.3 ± 8.8 %, 0 ± 0.3, 0.4 ± 2.2 and 0.1 ± 0.4 m/s, respectively. Detection of paradoxical septum (κ 0.65, 95 % CI 0.37–0.93), of heterogeneous LV contraction (κ 0.49, 95 % CI 0.33–0.65) and of respiratory variation of the inferior vena cava (κ 0.27, 95 % CI 0.09–0.45), as well as stroke volume measurement (CCC 0.65, 95 % CI 0.54–0.74; bias ± SD −1.4 ± 4.7 cm), was appraised by group II with moderate agreement requiring probably more comprehensive training. Conclusions Although a training program blending 6-h theory and 12-h practical may be adapted to achieve some essential competences, it seems to be insufficiently to perform a complete extended basic critical care transthoracic echocardiography including Doppler capabilities. Electronic supplementary material The online version of this article (doi:10.1186/s13613-016-0150-8) contains supplementary material, which is available to authorized users.

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