PupillOmetry for preDIction of DeliriUM in ICU (PODIUM): protocol for a prospective multicentre cohort study
,
Emmanuel Guerot,
Bertrand Hermann,
Stéphane Gaudry,
Jean-François Timsit,
Maxens Decavèle,
Alain Combes,
Jean-Paul Mira,
Benjamin Assouline,
Alexandre Demoule,
Muriel Fartoukh,
Romain Sonneville,
Lila Bouadma,
Yves Cohen,
Guillaume Voiriot,
Camille Couffignal,
Etienne De Montmollin,
Jean-Luc Diehl,
Pierre Jaquet,
Coralie Tardivon,
Sarah Benghanem,
Thomas Rambaud,
Virginie Godard,
Romane Bellot,
Daniel Da Silva,
Julien Dessajan,
Michael Thy,
Marc Doman,
Hermann Do Rego,
Michael Ejzenberg,
Erwann Cariou,
Simona Presente,
Paul-Henri Wicky,
Mario Rienzo,
Mariem Dlela,
Fariza Lamara,
Nathalie Marin,
Juliette Pelle,
Stephanie Cossec,
Smina Hadj Mahfoud,
Tchoubou Tona,
Khalil Chaibi,
Eleonore Bouchereau,
Antoine Troger,
Julie Langlais,
Nicolas Peron,
Caroline Hauw-Berlemont,
Nicolas Brechot
Affiliations
1Research Evaluation and Audit for Child Health (REACH)
Emmanuel Guerot
Bertrand Hermann
Medical Intensive Care Unit, Assistance Publique - Hôpitaux de Paris Centre, Université Paris Cité, Hôpital Européen Georges Pompidou, Paris, France
Stéphane Gaudry
Jean-François Timsit
1Université Paris Diderot, Paris, France
Maxens Decavèle
Medical Intensive Care Unit, Département R3S, Assistance Publique - Hôpitaux de Paris, Sorbonne Université, Pitié-Salpêtrière Hospital, Paris, France
Alain Combes
2Hôpital La Pitié-Salpêtrière, Assistance Publique-Hôpitaux de Paris, Service de médecine intensive-réanimation, institut de cardiométabolisme et nutrition (ICAN), Sorbonne Université, Paris, France
Jean-Paul Mira
Benjamin Assouline
Medical Intensive Care Unit, Département de Cardiologie, Assistance Publique - Hôpitaux de Paris, Sorbonne Université, Pitié-Salpêtrière Hospital, Paris, France
Alexandre Demoule
Muriel Fartoukh
Romain Sonneville
1 Médecine Intensive Réanimation, APHP.Nord, Hôpital Bichat Claude Bernard, Paris, France
Lila Bouadma
1Université Paris Diderot, Paris, France
Yves Cohen
Guillaume Voiriot
Medical Intensive Care Unit, Assistance Publique—Hopitaux de Paris, Tenon Hospital, Paris, France
Camille Couffignal
2 INSERM UMR 1137, IAME, Université Paris Cité, Paris, France
Etienne De Montmollin
Jean-Luc Diehl
Pierre Jaquet
10 Médecine Intensive Réanimation, Hopital Delafontaine, Saint Denis, France
Coralie Tardivon
Research Clinic, Epidemiology, Biostatistic Department Bichat hospital, DMU PRISME, Assistance Publique des Hôpitaux de Paris Nord, Groupe Hospitalier Universitaire Paris Cité, Paris, France
Sarah Benghanem
Medical Intensive Care Unit, Assistance Publique - Hôpitaux de Paris, Cochin University Hospital, Paris, France
Thomas Rambaud
Medical Intensive Care Unit, Assistance Publique - Hôpitaux de Paris, Avicenne Hospital, Bobigny, France
Virginie Godard
3 Epidemiologie, Biostatistique, Recherche Clinique, APHP.Nord, Hôpital Bichat Claude Bernard, Paris, France
Romane Bellot
3 Epidemiologie, Biostatistique, Recherche Clinique, APHP.Nord, Hôpital Bichat Claude Bernard, Paris, France
Daniel Da Silva
Intensive Care Unit, Delafontaine Hospital, Saint Denis, France
Julien Dessajan
Medical Intensive Care Unit, Assistance Publique-Hôpitaux de Paris Nord, Bichat Claude Bernard Hospital, Paris, France
Michael Thy
Marc Doman
Hermann Do Rego
Michael Ejzenberg
Erwann Cariou
Simona Presente
Paul-Henri Wicky
Mario Rienzo
Mariem Dlela
Fariza Lamara
1 Médecine Intensive Réanimation, APHP.Nord, Hôpital Bichat Claude Bernard, Paris, France
Introduction Delirium is a severe complication that is associated with short-term adverse events, prolonged hospital stay and neurological sequelae in survivors. Automated pupillometry is an easy-to-use device that allows for accurate objective assessment of the pupillary light responses in comatose patients in the intensive care unit (ICU). Whether automated pupillometry might predict delirium in critically ill patients is not known. We hypothesise that automated pupillometry could predict the occurrence of delirium in critically ill patients without primary brain injury, requiring more than 48 hours of invasive mechanical ventilation in the ICU.Methods and analysis The PupillOmetry for preDIction of DeliriUM in ICU (PODIUM) study is a prospective cohort study, which will be conducted in eight French ICUs in the Paris area. We aim to recruit 213 adult patients requiring invasive mechanical ventilation for more than 48 hours. Automated pupillometry (Neurological Pupil Index; NPi-200, Neuroptics) will be assessed two times per day for 7 days. Delirium will be assessed using the Confusion Assessment Method in ICU two times per day over 14 days in non-comatose patients (Richmond Agitation and Sedation Scale ≥−3).The predictive performances of the seven automated pupillometry parameters (ie, pupillary diameter, variation of the pupillary diameter, pupillary constriction speed, pupillary dilatation speed, photomotor reflex latency, NPi and symmetry of pupillary responses) measured to detect the delirium occurrence within 14 days will be the main outcomes. Secondary outcomes will be the predictive performances of the seven automated pupillometry parameters to detect complications related to delirium, ICU length of stay, mortality, functional and cognitive outcomes at 90 days.Ethics and dissemination The PODIUM study has been approved by an independent ethics committee, the Comité de Protection des Personnes (CPP) OUEST IV—NANTES (CPP21.02.15.45239 32/21_3) on 06 April 2021). Participant recruitment started on 15 April 2022. Results will be published in international peer-reviewed medical journals and presented at conferences.Trial registration number NCT05248035; clinicaltrials.gov.