Mathieu Pasquier1, Olivier Hugli2, Peter Paal3, Tomasz Darocha4, Marc Blancher5, Paul Husby6, Tom Silfvast7, Pierre-Nicolas Carron8, Valentin Rousson9. 1. Emergency Department, Lausanne University Hospital, Lausanne, Switzerland. Electronic address: Mathieu.Pasquier@chuv.ch. 2. Emergency Department, Lausanne University Hospital, Lausanne, Switzerland. Electronic address: olivier.hugli@chuv.ch. 3. Department of Anesthesiology and Intensive Care Medicine, Hospitaller Brothers Hospital, Paracelsus Medical University, Strubergasse 21, 5020 Salzburg, Austria. Electronic address: peter.paal@icloud.com. 4. Severe Accidental Hypothermia Center, Department of Anaesthesiology and Intensive Care, Medical University of Silesia, 055, Poniatowskiego 15, Katowice, Poland. Electronic address: tomekdarocha@wp.pl. 5. SAMU 38, Pôle Urgences - Médecine Aiguë, CHU de Grenoble, BP 217, 38043 Grenoble Cedex 09, France. Electronic address: MBlancher@chu-grenoble.fr. 6. Department of Anesthesia and Intensive Care, Haukeland University Hospital, 5021 Bergen, Norway. Electronic address: Paul.Husby@uib.no. 7. Department of Anaesthesiology, Intensive Care and Pain Medicine, University of Helsinki and Helsinki University Hospital, PO Box 340, 00029 Helsinki, Finland. Electronic address: Tom.Silfvast@hus.fi. 8. Emergency Department, Lausanne University Hospital, Lausanne, Switzerland. Electronic address: pierre-nicolas.carron@chuv.ch. 9. Institute of Social and Preventive Medicine, Lausanne University Hospital, route de la Corniche 10, 1010 Lausanne, Switzerland. Electronic address: valentin.rousson@chuv.ch.
Abstract
AIMS: Currently, the decision to initiate extracorporeal life support for patients who suffer cardiac arrest due to accidental hypothermia is essentially based on serum potassium level. Our goal was to build a prediction score in order to determine the probability of survival following rewarming of hypothermic arrested patients based on several covariates available at admission. METHODS: We included consecutive hypothermic arrested patients who underwent rewarming with extracorporeal life support. The sample comprised 237 patients identified through the literature from 18 studies, and 49 additional patients obtained from hospital data collection. We considered nine potential predictors of survival: age; sex; core temperature; serum potassium level; mechanism of hypothermia; cardiac rhythm at admission; witnessed cardiac arrest, rewarming method and cardiopulmonary resuscitation duration prior to the initiation of extracorporeal life support. The primary outcome parameter was survival to hospital discharge. RESULTS: Overall, 106 of the 286 included patients survived (37%; 95% CI: 32-43%), most (84%) with a good neurological outcome. The final score included the following variables: age, sex, core temperature at admission, serum potassium level, mechanism of cooling, and cardiopulmonary resuscitation duration. The corresponding area under the receiver operating characteristic curve was 0.895 (95% CI: 0.859-0.931) compared to 0.774 (95% CI: 0.720-0.828) when based on serum potassium level alone. CONCLUSIONS: In this large retrospective study we found that our score was superior to dichotomous triage based on serum potassium level in assessing which hypothermic patients in cardiac arrest would benefit from extracorporeal life support. External validation of our findings is required.
AIMS: Currently, the decision to initiate extracorporeal life support for patients who suffer cardiac arrest due to accidental hypothermia is essentially based on serum potassium level. Our goal was to build a prediction score in order to determine the probability of survival following rewarming of hypothermic arrestedpatients based on several covariates available at admission. METHODS: We included consecutive hypothermic arrestedpatients who underwent rewarming with extracorporeal life support. The sample comprised 237 patients identified through the literature from 18 studies, and 49 additional patients obtained from hospital data collection. We considered nine potential predictors of survival: age; sex; core temperature; serum potassium level; mechanism of hypothermia; cardiac rhythm at admission; witnessed cardiac arrest, rewarming method and cardiopulmonary resuscitation duration prior to the initiation of extracorporeal life support. The primary outcome parameter was survival to hospital discharge. RESULTS: Overall, 106 of the 286 included patients survived (37%; 95% CI: 32-43%), most (84%) with a good neurological outcome. The final score included the following variables: age, sex, core temperature at admission, serum potassium level, mechanism of cooling, and cardiopulmonary resuscitation duration. The corresponding area under the receiver operating characteristic curve was 0.895 (95% CI: 0.859-0.931) compared to 0.774 (95% CI: 0.720-0.828) when based on serum potassium level alone. CONCLUSIONS: In this large retrospective study we found that our score was superior to dichotomous triage based on serum potassium level in assessing which hypothermicpatients in cardiac arrest would benefit from extracorporeal life support. External validation of our findings is required.
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Authors: Lars J Bjertnæs; Kristian Hindberg; Torvind O Næsheim; Evgeny V Suborov; Eirik Reierth; Mikhail Y Kirov; Konstantin M Lebedinskii; Torkjel Tveita Journal: Front Med (Lausanne) Date: 2021-05-13
Authors: Carsten Lott; Anatolij Truhlář; Anette Alfonzo; Alessandro Barelli; Violeta González-Salvado; Jochen Hinkelbein; Jerry P Nolan; Peter Paal; Gavin D Perkins; Karl-Christian Thies; Joyce Yeung; David A Zideman; Jasmeet Soar Journal: Notf Rett Med Date: 2021-06-10 Impact factor: 0.826
Authors: Tomasz Darocha; Olivier Hugli; Sylweriusz Kosiński; Paweł Podsiadło; David Caillet-Bois; Mathieu Pasquier Journal: Resusc Plus Date: 2021-05-26