Lars Wik1, Jan-Aage Olsen2, David Persse3, Fritz Sterz4, Michael Lozano5, Marc A Brouwer6, Mark Westfall7, Chris M Souders3, David T Travis8, Ulrich R Herken9, E Brooke Lerner10. 1. Norwegian National Advisory Unit on Prehospital Emergency Medicine, Oslo University Hospital, Oslo, Norway. Electronic address: lars.wik@medisin.uio.no. 2. Norwegian National Advisory Unit on Prehospital Emergency Medicine, Oslo University Hospital, Oslo, Norway; Institute of Clinical Medicine, University of Oslo, Norway. 3. Houston Fire Department and the Baylor College of Medicine, Houston, TX, United States. 4. Department of Emergency Medicine, Medical University of Vienna, Vienna, Austria. 5. Hillsborough County Fire Rescue, Tampa, FL, United States; Department of Internal Medicine, University of South Florida, FL, United States. 6. Heart Lung Center, Department of Cardiology, Radboud University Nijmegen Medical Center, Nijmegen, The Netherlands. 7. Gold Cross Ambulance Service, Appleton Neenah-Menasha and Grand Chute Fire Departments, WI, United States; Theda Clark Regional Medical Center, Neenah, WI, United States. 8. Hillsborough County Fire Rescue, Tampa, FL, United States. 9. ZOLL Medical Corporation, Chelmsford, MA, United States. 10. Department of Emergency Medicine, Medical College of Wisconsin, Milwaukee, WI, United States.
Abstract
INTRODUCTION: An 80% chest compression fraction (CCF) during resuscitation is recommended. However, heterogeneous results in CCF studies were found during the 2015 Consensus on Science (CoS), which may be because chest compressions are stopped for a wide variety of reasons including providing lifesaving care, provider distraction, fatigue, confusion, and inability to perform lifesaving skills efficiently. OBJECTIVE: The effect of confounding variables on CCF to predict cardiac arrest survival. METHODS: A secondary analysis of emergency medical services (EMS) treated out-of-hospital cardiac arrest (OHCA) patients who received manual compressions. CCF (percent of time patients received compressions) was determined from electronic defibrillator files. Two Sample Wilcoxon Rank Sum or regression determined a statistical association between CCF and age, gender, bystander CPR, public location, witnessed arrest, shockable rhythm, resuscitation duration, study site, and number of shocks. Univariate and multivariate logistic regressions were used to determine CCF effect on survival. RESULTS: Of 2132 patients with manual compressions 1997 had complete data. Shockable rhythm (p<0.001), public location (p<0.004), treatment duration (p<0.001), and number of shocks (p<0.001) were associated with lower CCF. Univariate logistic regression found that CCF was inversely associated with survival (OR 0.07; 95% CI 0.01-0.36). Multivariate regression controlling for factors associated with survival and/or CCF found that increasing CCF was associated with survival (OR 6.34; 95% CI 1.02-39.5). CONCLUSION:CCF cannot be looked at in isolation as a predictor of survival, but in the context of other resuscitation activities. When controlling for the effects of other resuscitation activities, a higher CCF is predictive of survival. This may explain the heterogeneity of findings during the CoS review.
RCT Entities:
INTRODUCTION: An 80% chest compression fraction (CCF) during resuscitation is recommended. However, heterogeneous results in CCF studies were found during the 2015 Consensus on Science (CoS), which may be because chest compressions are stopped for a wide variety of reasons including providing lifesaving care, provider distraction, fatigue, confusion, and inability to perform lifesaving skills efficiently. OBJECTIVE: The effect of confounding variables on CCF to predict cardiac arrest survival. METHODS: A secondary analysis of emergency medical services (EMS) treated out-of-hospital cardiac arrest (OHCA) patients who received manual compressions. CCF (percent of time patients received compressions) was determined from electronic defibrillator files. Two Sample Wilcoxon Rank Sum or regression determined a statistical association between CCF and age, gender, bystander CPR, public location, witnessed arrest, shockable rhythm, resuscitation duration, study site, and number of shocks. Univariate and multivariate logistic regressions were used to determine CCF effect on survival. RESULTS: Of 2132 patients with manual compressions 1997 had complete data. Shockable rhythm (p<0.001), public location (p<0.004), treatment duration (p<0.001), and number of shocks (p<0.001) were associated with lower CCF. Univariate logistic regression found that CCF was inversely associated with survival (OR 0.07; 95% CI 0.01-0.36). Multivariate regression controlling for factors associated with survival and/or CCF found that increasing CCF was associated with survival (OR 6.34; 95% CI 1.02-39.5). CONCLUSION: CCF cannot be looked at in isolation as a predictor of survival, but in the context of other resuscitation activities. When controlling for the effects of other resuscitation activities, a higher CCF is predictive of survival. This may explain the heterogeneity of findings during the CoS review.
Authors: Morgann Loaec; Adam S Himebauch; Todd J Kilbaugh; Robert A Berg; Kathryn Graham; Richard Hanna; Heather A Wolfe; Robert M Sutton; Ryan W Morgan Journal: Resuscitation Date: 2020-05-15 Impact factor: 5.262
Authors: Christian Vaillancourt; Ashley Petersen; Eric N Meier; Jim Christenson; James J Menegazzi; Tom P Aufderheide; Graham Nichol; Robert Berg; Clifton W Callaway; Ahamed H Idris; Daniel Davis; Raymond Fowler; Debra Egan; Douglas Andrusiek; Jason E Buick; T J Bishop; M Riccardo Colella; Ritu Sahni; Ian G Stiell; Sheldon Cheskes Journal: Resuscitation Date: 2020-06-20 Impact factor: 5.262
Authors: Lone Due Vestergaard; Kasper Glerup Lauridsen; Niels Henrik Vinther Krarup; Jane Uhrenholt Kristensen; Lone Kaerslund Andersen; Bo Løfgren Journal: Open Access Emerg Med Date: 2021-12-16