BACKGROUND: Patients admitted to a cardiac intensive care unit are often unconscious with uncertain prognosis. Automated infrared pupillometry for neurological assessment in the intensive care unit may provide early prognostic information. This study aimed to determine the prognostic value of automated pupillometry in different subgroups of patients in a cardiac intensive care unit with 30-day mortality as the primary endpoint and neurological outcome as the secondary endpoint. METHODS: A total of 221 comatose patients were divided into three groups: out-of-hospital cardiac arrest, in-hospital cardiac arrest and others (i.e. patients with cardiac diagnoses other than cardiac arrest). Automated pupillometry was serially performed until discharge or death and pupil measurements were analysed using the neurological pupil index algorithm. We applied receiver operating characteristic curves in univariable and multivariable logistic regression models and a calculated Youden index identified neurological pupil index cut-off values at different specificities. RESULTS: In out-of-hospital cardiac arrest patients higher neurological pupil index values were independently associated with lower 30-day mortality. The univariable model for 30-day mortality had an area under the curve of 0.87 and the multivariable model achieved an area under the curve of 0.94. The Youden index identified a neurological pupil index cut-off in out-of-hospital cardiac arrest patients of 2.40 for a specificity of 100%. For patients with in-hospital cardiac arrest and other cardiac diagnoses, we found no association between neurological pupil index values and 30-day mortality, and the univariable models showed poor predictive values. CONCLUSION: Automated infrared pupillometry has promising predictive value after out-of-hospital cardiac arrest, but poor predictive value in patients with in-hospital cardiac arrest or cardiac diagnoses unrelated to cardiac arrest. Our data suggest a possible neurological pupil index cut-off of 2.40 for poor outcome in out-of-hospital cardiac arrest patients.
BACKGROUND: Patients admitted to a cardiac intensive care unit are often unconscious with uncertain prognosis. Automated infrared pupillometry for neurological assessment in the intensive care unit may provide early prognostic information. This study aimed to determine the prognostic value of automated pupillometry in different subgroups of patients in a cardiac intensive care unit with 30-day mortality as the primary endpoint and neurological outcome as the secondary endpoint. METHODS: A total of 221 comatose patients were divided into three groups: out-of-hospital cardiac arrest, in-hospital cardiac arrest and others (i.e. patients with cardiac diagnoses other than cardiac arrest). Automated pupillometry was serially performed until discharge or death and pupil measurements were analysed using the neurological pupil index algorithm. We applied receiver operating characteristic curves in univariable and multivariable logistic regression models and a calculated Youden index identified neurological pupil index cut-off values at different specificities. RESULTS: In out-of-hospital cardiac arrest patients higher neurological pupil index values were independently associated with lower 30-day mortality. The univariable model for 30-day mortality had an area under the curve of 0.87 and the multivariable model achieved an area under the curve of 0.94. The Youden index identified a neurological pupil index cut-off in out-of-hospital cardiac arrest patients of 2.40 for a specificity of 100%. For patients with in-hospital cardiac arrest and other cardiac diagnoses, we found no association between neurological pupil index values and 30-day mortality, and the univariable models showed poor predictive values. CONCLUSION: Automated infrared pupillometry has promising predictive value after out-of-hospital cardiac arrest, but poor predictive value in patients with in-hospital cardiac arrest or cardiac diagnoses unrelated to cardiac arrest. Our data suggest a possible neurological pupil index cut-off of 2.40 for poor outcome in out-of-hospital cardiac arrest patients.
Authors: Claudio Sandroni; Sonia D'Arrigo; Sofia Cacciola; Cornelia W E Hoedemaekers; Marlijn J A Kamps; Mauro Oddo; Fabio S Taccone; Arianna Di Rocco; Frederick J A Meijer; Erik Westhall; Massimo Antonelli; Jasmeet Soar; Jerry P Nolan; Tobias Cronberg Journal: Intensive Care Med Date: 2020-09-11 Impact factor: 17.440
Authors: Sansuthan Paramanathan; Anders Morten Grejs; Eldar Søreide; Christophe Henri Valdemar Duez; Anni Nørgaard Jeppesen; Åse Johanne Reinertsen; Kristian Strand; Hans Kirkegaard Journal: Acta Anaesthesiol Scand Date: 2022-05-29 Impact factor: 2.274
Authors: Jasmeet Soar; Katherine M Berg; Lars W Andersen; Bernd W Böttiger; Sofia Cacciola; Clifton W Callaway; Keith Couper; Tobias Cronberg; Sonia D'Arrigo; Charles D Deakin; Michael W Donnino; Ian R Drennan; Asger Granfeldt; Cornelia W E Hoedemaekers; Mathias J Holmberg; Cindy H Hsu; Marlijn Kamps; Szymon Musiol; Kevin J Nation; Robert W Neumar; Tonia Nicholson; Brian J O'Neil; Quentin Otto; Edison Ferreira de Paiva; Michael J A Parr; Joshua C Reynolds; Claudio Sandroni; Barnaby R Scholefield; Markus B Skrifvars; Tzong-Luen Wang; Wolfgang A Wetsch; Joyce Yeung; Peter T Morley; Laurie J Morrison; Michelle Welsford; Mary Fran Hazinski; Jerry P Nolan Journal: Resuscitation Date: 2020-10-21 Impact factor: 5.262