S Seewald1, J Wnent2, R Lefering3, M Fischer4, A Bohn5, T Jantzen6, S Brenner7, S Masterson8, B Bein9, J Scholz10, J T Gräsner11. 1. Department of Anesthesiology and Intensive Care Medicine, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, building 12, Kiel, 24105, Germany; Institute for Emergency Medicine, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, building 808, Kiel, 24105, Germany. Electronic address: seewald@reanimationsregister.de. 2. Department of Anesthesiology and Intensive Care Medicine, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, building 12, Kiel, 24105, Germany; Institute for Emergency Medicine, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, building 808, Kiel, 24105, Germany; University of Namibia, School of Medicine, Private Bag 13301, Windhoek, Namibia, Germany. 3. University Witten/Herdecke, Faculty of Health, Institute for Research in Operative Medicine, Ostmerheimer Straße 200, Cologne, 51109, Germany. 4. Department of Anesthesiology and Intensive Care, Klinik am Eichert, Eichertstraße 3, Göppingen, 73035, Germany. 5. City of Münster Fire Department, York-Ring 25, Münster, 48159, Germany; Department of Anesthesiology, Intensive Care and Pain Medicine, University Hospital Münster, Albert-Schweitzer-Campus 1, building A1, York-Ring 25, Münster, 48149, Germany. 6. Interhospital-Transfer-Service Mecklenburg-Vorpommern, German Red Cross Parchim, Ventschowerstraße 1, Cambs, 19067, Germany. 7. Department of Anesthesiology and Intensive Care Medicine, University Hospital Dresden, Fetscherstraße 74, Dresden, 01307, Germany. 8. National Ambulance Service Lead - Strategy and Evaluation, St. Eunan's Hall, St. Conal's Hospital, Letterkenny, Co. Donegal, Ireland and Discipline of General Practice School of Medicine, National University of Ireland Galway F92 XK84, Ireland. 9. Department of Anesthesiology and Intensive Care Medicine, Asklepios Klinik St. Georg, Lohmühlenstraße 5, Hamburg, 20099, Germany. 10. University Hospital Schleswig-Holstein, Arnold-Heller-Straße 3, Kiel, 24105, Germany. 11. Institute for Emergency Medicine, University Hospital Schleswig-Holstein, Campus Kiel, Arnold-Heller-Straße 3, building 808, Kiel, 24105, Germany.
Abstract
AIM: The aim of this study was to develop a score to predict the outcome for patients brought to hospital following out-of-hospital cardiac arrest (OHCA). METHODS: All patients recorded in the German Resuscitation Registry (GRR) who suffered OHCA 2010-2017, who had ROSC or ongoing CPR at hospital admission were included. The study population was divided into development (2010-2016: 7985) and validation dataset (2017: 1806). Binary logistic regression analysis was used to derive the score. The probability of hospital discharge with good neurological outcome was defined as 1/(1 + e-X), where X is the weighted sum of independent variables. RESULTS: The following variables were found to have a significant positive (+) or negative (-) impact: age 61-70 years (-0·5), 71-80 (-0·9), 81-90 (-1·3) and > = 91 (-2·3); initial PEA (-0·9) and asystole (-1·4); presumable trauma (-1·1); mechanical CPR (-0·3); application of adrenalin > 0 - < 2 mg (-1·1), 2 - <4 mg (-1·6), 4 - < 6 mg (-2·1), 6 - < 8 mg (-2·5) and > = 8 mg (-2·8); pre emergency status without previous disease (+0·5) or minor disease (+0·2); location at nursing home (-0·6), working place/school (+0·7), doctor's office (+0·7) and public place (+0·3); application of amiodarone (+0·4); hospital admission with ongoing CPR (-1·9) or normotension (+0·4); witnessed arrest (+0·6); time from collapse until start CPR 2 - < 10 min (-0·3) and > = 10 min (-0·5); duration of CPR <5 min (+0·6). The AUC in the development dataset was 0·88 (95% CI 0·87-0·89) and in the validation dataset 0·88 (95% CI 0·86-0·90). CONCLUSION: The CaRdiac Arrest Survival Score (CRASS) represents a tool for calculating the probability of survival with good neurological function for patients brought to hospital following OHCA.
AIM: The aim of this study was to develop a score to predict the outcome for patients brought to hospital following out-of-hospital cardiac arrest (OHCA). METHODS: All patients recorded in the German Resuscitation Registry (GRR) who suffered OHCA 2010-2017, who had ROSC or ongoing CPR at hospital admission were included. The study population was divided into development (2010-2016: 7985) and validation dataset (2017: 1806). Binary logistic regression analysis was used to derive the score. The probability of hospital discharge with good neurological outcome was defined as 1/(1 + e-X), where X is the weighted sum of independent variables. RESULTS: The following variables were found to have a significant positive (+) or negative (-) impact: age 61-70 years (-0·5), 71-80 (-0·9), 81-90 (-1·3) and > = 91 (-2·3); initial PEA (-0·9) and asystole (-1·4); presumable trauma (-1·1); mechanical CPR (-0·3); application of adrenalin > 0 - < 2 mg (-1·1), 2 - <4 mg (-1·6), 4 - < 6 mg (-2·1), 6 - < 8 mg (-2·5) and > = 8 mg (-2·8); pre emergency status without previous disease (+0·5) or minor disease (+0·2); location at nursing home (-0·6), working place/school (+0·7), doctor's office (+0·7) and public place (+0·3); application of amiodarone (+0·4); hospital admission with ongoing CPR (-1·9) or normotension (+0·4); witnessed arrest (+0·6); time from collapse until start CPR 2 - < 10 min (-0·3) and > = 10 min (-0·5); duration of CPR <5 min (+0·6). The AUC in the development dataset was 0·88 (95% CI 0·87-0·89) and in the validation dataset 0·88 (95% CI 0·86-0·90). CONCLUSION: The CaRdiac Arrest Survival Score (CRASS) represents a tool for calculating the probability of survival with good neurological function for patients brought to hospital following OHCA.
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