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Prove It: Stay and play or load and go?

For patients who do not achieve ROSC early, is it better to stay on scene and continue resuscitation efforts or transport to the ED with CPR in progress?


For patients who do not achieve ROSC early in the resuscitation attempt, is it better to stay on scene and continue resuscitation efforts until you obtain ROSC or terminate the attempt, or should you load the patient as soon as you can and transport to the emergency department with CPR in progress?

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Case review. Medic 14 and Engine 27 respond to a report of an unconscious person. On the way, the crew learns the emergency medical dispatcher is providing CPR instructions to the caller. The engine crew arrives six minutes later to find a pulseless and apneic 67-year-old male, whose collapse was unwitnessed. The firefighters perform high-quality CPR and apply the AED, which does not recommend a shock. Once the medics arrive, (about 2 minutes later), the monitor/defibrillator confirms the presence of asystole.

After establishing an IV and inserting a supraglottic airway, the patient receives the first dose of epinephrine about 6 minutes after the medics arrive. The team learns the patient has a history of heart problems and was feeling poorly this morning. The patient’s wife left him alone while she went to church and came home to find him on the floor.

The initial capnography reading is 12 mmHg. However, just before administration of the second dose of epinephrine, that value rose to 19 mmHg. Two minutes after administration of the second epinephrine dose, the ECG monitor displays an idioventricular rhythm at a rate of 20 complexes per minute. There is no pulse. As it has been 21 minutes since the arrival of the firefighters, the team prepares the patient for transport. During the eight-minute trip to the hospital, the patient receives continued manual CPR and two additional doses of epinephrine. The ECG complexes ultimately disappear and the patient arrives in asystole. After 10-minutes in the emergency department, the physician terminates the resuscitation attempt.

Back at the station, the firefighters and medics discuss the call. The firefighters wonder if the idioventricular rhythm represented a positive response to the resuscitation efforts, despite the absence of a pulse. Because the ECG reverted to asystole shortly after transport began, they also wondered whether staying on the scene a bit longer might have optimized the resuscitation effort and increased the probability of return of spontaneous circulation (ROSC).

Arguably, beginning transport after 21 minutes on the scene is not really a load-and-go strategy. However, the central question is when to begin transporting patients who suffer an OOH cardiac arrest. For patients who do not achieve ROSC early in the resuscitation attempt, is it better to stay on scene and continue resuscitation efforts until you obtain ROSC or terminate the attempt, or should you load the patient as soon as you can and transport to the emergency department with CPR in progress?

ROSC study review

Using a large population-based OOH cardiac arrest registry containing data from 192 EMS agencies, researchers from the Resuscitation Outcomes Consortium (ROC) evaluated the difference in survival rates for out-of-hospital (OOH) cardiac arrest between those transported as soon as possible (transport before ROSC) and those transported after achieving ROSC [1]. The study included all adults who suffered a non-traumatic OOH cardiac arrest between April 2011 and June 2015, and received either external defibrillation by bystanders or EMS or chest compressions from EMS. Eligibility for study inclusion did not require advanced life support in the field; about 6% of the cases came from systems providing only basic life support (BLS) interventions. The primary outcome variable was survival-to-hospital discharge. Secondary analysis evaluated the survivor’s neurological outcome.

At face value, this may seem like a straightforward analysis. Divide the OOH cardiac arrest cases into a group who achieved ROSC before transport and a group who achieved ROSC after transport, and then count how many in each group survived long enough for hospital discharge. When applied to this data set, 43,969 cases met the inclusion criteria without any missing case data during the five-year study period. Overall, transport began before ROSC in about one-fourth of the patients, although about 15.8% of them did achieve ROSC before arriving in the ED. Survival to hospital discharge in this group was 3.8%. By comparison, survival to hospital discharge was 12.6% for patients with transport delayed until after achieving ROSC on scene.

However, many variables influence a patient’s ability to achieve early ROSC, including whether the collapse was a witnessed event, bystander CPR or defibrillation, response time for the resuscitation team, and the presenting rhythm, just to name a few [2]. In addition, observational cardiac arrest research (such as this) often contains a resuscitation time bias that overestimates harmful outcomes because longer duration resuscitation attempts are more strongly associated with worse outcomes [3, 4-6]. Without some control over these variables, differences in baseline characteristics between the groups do not permit an apples-to-apples comparison and can provide misleading study results [7].

One strategy to help reduce this measurement error and bring clarity to the research results is with a statistical technique called time-dependent propensity score analysis [8]. Computer modeling uses resuscitation time variables and baseline characteristics to assign a value (score) between 0 and 1 to each cardiac arrest case [9]. Researchers can then use the scores to match cases from one group to similar cases in the second group based on prehospital resuscitation time. This helps to ensure researchers are not comparing cases from those who achieved ROSC in only a few minutes to those who did not achieve ROSC until they arrived in the emergency department (apples to oranges comparison). In essence, this apples to apples comparison mimics the distribution of baseline characteristics found in a randomized trial and provides for an unbiased estimate of the treatment effect [10].

ROSC results

Of the roughly 44,000 cases in the overall sample, statisticians could reliably match 27,705 cases for the time-dependent propensity score analysis. For the primary outcome, survival to hospital discharge was higher in the transport after ROSC group compared to the transport before ROSC group (8.5% vs. 4.0%). For the 15,383 cases with available outcome data, survival with favorable neurologic outcome was also higher in the transport after ROSC group compared to transport before ROSC (7.1% vs. 2.9%).

ROSC: What this means for you

When controlling for variables known to influence the outcome of OOH resuscitation attempts, transporting patients without first achieving ROSC is significantly associated with decreased survival to hospital discharge. In this study, the majority of survivors transported before achieving ROSC actually did achieve ROSC before arriving in the ED, which calls into question the contribution of ED resuscitation efforts into overall survival measures for patients who suffer an OOH cardiac arrest. One might argue that in order to survive OOH cardiac arrest, patients must first achieve ROSC in the field.

As occurs in most studies, researchers performed a number of secondary analyses, which provide a rich source of questions meriting exploration in future studies. One interesting secondary investigation involved a matched propensity analysis (apples-to-apples comparison) based on the total scene time, measured from when responders first arrived on the scene until the ambulance left the scene to go to the hospital. When medics spent 30 minutes or longer on the scene, rates of survival to hospital discharge increased when medics initiated transport before ROSC compared to continuing to stay on the scene until achieving ROSC. This could reflect a selection bias whereby medics choose to continue resuscitation efforts during transport for some patients while terminating resuscitation efforts on scene for those deemed unlikely to survive.

However, when the total on scene time was less than 15 minutes, survival to hospital discharge decreased in the transport before ROSC group compared to the transport after ROSC group. This suggests a detrimental effect of initiating transport too early. This is supported by another analysis of data from the Resuscitation Outcomes Consortium which found participating sites with the lowest scene time before transport (median: 15 minutes) had the lowest survival rates [11].

As the firefighters suggested at the beginning of this essay, some patients who might achieve ROSC never have the opportunity because of CPR quality changes once transport begins. More than a decade ago, researchers demonstrated the mean hands-off ratio and number of chest compressions delivered each minute significantly decreased during transport compared to the resuscitation period before placing the patient into the ambulance [12]. Researchers in Arizona found significantly greater variability in chest compression rate and depth during transport and in the emergency department compared to on scene [13]. Even with the assistance of visual feedback technology, the proportion of chest compressions with correct depth is significantly worse during transport compared to compressions provided on-scene (14.0% vs. 75.7%, p < 0.0001) [14]. Moving the patient from the arrest location to the back of the ambulance can result in no-flow times approaching four minutes in both BLS and ALS systems [15].

On the other hand, data from Europe suggests CPR quality does not significantly deteriorate during transport, although researchers acknowledge CPR quality measures were poor both on the scene and during transport [16]. Utilization of a real time, audiovisual feedback device during transport improves chest compression depth; however, mattress movement may make the compressions appear more effective than they really are [17]. Finally, even with measurable differences in compression depth, compression rate, and chest compression fraction, both on scene and in transit quality CPR variables often continue to meet predetermined performance standards [18].

Finally, because the majority of survivors in this study achieved ROSC before arriving in the ED (either on scene or en route), this data calls into question the contribution of continued ED resuscitation attempts to overall survival for patients who remain pulseless upon EMS arrival. Survival to hospital discharge following OOH cardiac arrest is independently associated with three factors; achieving ROSC on scene, receiving at least one defibrillation shock in the field, or having the arrest witnessed by EMS personnel [19], meaning that patients who do not meet any of the three criteria do not survive. A field termination of resuscitation (TOR) protocol incorporating these criteria demonstrate a 99.5% positive predictive value for death and would reduce transport rates for futile cases of OOH cardiac arrest by two-thirds, thereby reducing the risk of injury or death to EMS personnel providing care in transit [20]. The same TOR rule applied retrospectively to data from the Resuscitation Outcomes Consortium demonstrated a 100% positive predictive value for death and with a reduction in predicted transport rates by one-third in the ALS systems and 54% in the BLS systems [21]. Cardiac Arrest Registry to Enhance Survival (CARES) data found similar results for BLS and ALS systems in eight US cities [22]. More than half of all patients transported by 30 EMS systems in Arizona during a two-year period met these TOR criteria and only one survived to hospital discharge [23]. For patients who achieve ROSC despite meeting TOR criteria, neurologic outcome is poor [24].

Limitations of the ROSC study

One should be cautious in interpreting these results. The authors are not claiming that staying on the scene until the patient achieves ROSC causes long-term survival in patients who suffer an out-of-hospital cardiac arrest. Observational studies such as this require validation in randomized experiments, although those can be difficult to execute properly and very expensive to conduct.

The data used in this study came from a collection of EMS systems specifically trained for cardiac arrest research. Despite this training, there is wide variability in treatment and transport decision within these agencies, which may not reflect how other agencies in the United States provide care. The overwhelming majority of the patients in this study received advanced care in the field, with only about 6% of the cases receiving BLS-only care. Thus, the results probably reflect minimal impact of BLS-only systems. If someone repeated this study with a higher percentage of BLS-only agencies, different results and conclusions might occur. Additionally, most the systems participating in this study performed manual chest compressions only. As a result, one should not generalize the results to systems that use mechanical CPR devices.

Finally, the data does not reflect how medics made the determination of when to transport the patient. This gives way to prognostication bias, whereby medics may continue resuscitation attempts beyond a termination threshold if there is a belief the patient may benefit while terminating at that same threshold for cases deemed futile.

ROSC: Stay and play or load and go?

This study suggests EMS systems may improve resuscitation efforts by providing a certain amount of the on-scene care before attempting to move the patient to the hospital. The optimal time medics should spend on the scene remains unknown. Further, absent extraordinary circumstances, it may not be possible to produce favorable neurological outcomes without the patient first achieving ROSC in the field.


  1. Grunau, B., Kime, N., Leroux, B., Rea, T., Van Belle, G., Menegazzi, J. J., Kudenchuk, P. J., Vaillancourt, C., Morrison, L. J., Elmer, J., Zive, D. M., Le, N. M., Austin, M., Richmond, N. J., Herren, H., & Christenson, J. (2020). Association of intra-arrest transport vs continued on-scene resuscitation with survival to hospital discharge among patients with out-of-hospital cardiac arrest. Journal of the American Medical Association, 324(11), 1058-1067. doi:10.1001/jama.2020.14185
  2. Perkins, G. D., Jacobs, I. G., Nadkarni, V. M., Berg, R. A., Bhanji, F., Biarent, D., Bossaert, L. L,. Brett, S. J., Chamberlain, D., de Caen, A. R., Deakin, C. D., Finn, J. C., Gräsner, J. T., Hazinski, M. F., Iwami, T., Koster, R. W., Lim, S. H., Ma, M. H., McNally, B. F., Morley, P. T., Morrison, L. J., Monsieurs, K. G., Montgomery, W., Nichol, G., Okada, K., Ong, M. E., Travers, A. H., & Nolan, J. P. (2015). Cardiac arrest and cardiopulmonary resuscitation outcome reports: Update of the Utstein Resuscitation Registry templates for out-of-hospital cardiac arrest. Resuscitation, 96, 328-340. doi:10.1016/j.resuscitation.2014.11.002
  3. Andersen, L. W., Grossestreuer, A. V., & Donnino, M. W. (2018). Resuscitation time bias: A unique challenge for observational cardiac arrest research. Resuscitation, 125, 79-82. doi:10.1016/j.resuscitation.2018.02.006
  4. Chan, P. S., Spertus, J. A., Krumholz, H. M., Berg, R. A., Li, Y., Sasson, C., & Nallamothu, B. K. (2012). A validated prediction tool for initial survivors of in-hospital cardiac arrest. Archives of Internal Medicine, 172(12), 947-953. doi:10.1001/archinternmed.2012.2050
  5. Nagao, K., Nonogi, H., Yonemoto, N., Gaieski, D. F., Ito, N., Takayama, M., Shirai, S., Furuya, S., Tani, S., Kimura, T., & Saku, K. (2016). Duration of prehospital resuscitation efforts after out-of-hospital cardiac arrest. Circulation, 133(14), 1386-1396. doi:10.1161/CIRCULATIONAHA.115.018788
  6. Reynolds, J. C., Grunau, B. E., Rittenberger, J. C., Sawyer, K. N., Kurz, M. C., & Callaway, C. W. (2016). Association between duration of resuscitation and favorable outcome after out-of-hospital cardiac arrest: Implications for prolonging or terminating resuscitation. Circulation, 134(25), 2084-2094. doi:10.1161/CIRCULATIONAHA.116.023309
  7. Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41-55. doi:10.1093/biomet/70.1.41
  8. Lu, B. (2005). Propensity score matching with time-dependent covariates. Biometrics, 61(3), 721-728. doi:10.1111/j.1541-0420.2005.00356.x
  9. Lee, J., & Little, T. D. (2017). A practical guide to propensity score analysis for applied clinical research. Behaviour Research and Therapy, 98, 76-90. doi:10.1016/j.brat.2017.01.005
  10. Austin, P. C. (2013). The use of propensity score methods with survival or time-to-event outcomes: Reporting measures of effect similar to those used in randomized experiments. Statistics in Medicine, 33(7), 1242-1258. doi:10.1002/sim.5984
  11. Zive, D., Koprowicz, K., Schmidt, T., Stiell, I., Sears, G., Van Ottingham, L., Idris, A., Stephens, S., & Daya, M. (2011). Variation in out-of-hospital cardiac arrest resuscitation and transport practices in the Resuscitation Outcomes Consortium: ROC Epistry-Cardiac Arrest. Resuscitation, 82(3), 277-284. doi:10.1016/j.resuscitation.2010.10.022
  12. Olasveengen, T. M., Wik, L., & Steen, P. A. (2008). Quality of cardiopulmonary resuscitation before and during transport in out-of-hospital cardiac arrest. Resuscitation, 76(2), 185–190. doi:10.1016/j.resuscitation.2007.07.001
  13. Roosa, J. R., Vadeboncoeur, T. F., Dommer, P. B., Panchal, A. R., Venuti, M., Smith, G., Silver, A., Mullins, M., Spaite, D., & Bobrow, B. J. (2013). CPR variability during ground ambulance transport of patients in cardiac arrest. Resuscitation, 84(5), 592–595. doi:10.1016/j.resuscitation.2012.07.042
  14. Russi, C. S., Myers, L. A., Kolb, L. J., Lohse, C. M., Hess, E. P., & White, R. D. (2016). A comparison of chest compression quality delivered during on-scene and ground transport cardiopulmonary resuscitation. Western Journal of Emergency Medicine, 17(5), 634-639. doi:10.5811/westjem.2016.6.29949
  15. Krarup, N. H., Terkelsen, C. J., Johnsen, S. P., Clemmensen, P., Olivecrona, G. K., Hansen, T. M., Trautner, S., & Lassen, J. F. (2011). Quality of cardiopulmonary resuscitation in out-of-hospital cardiac arrest is hampered by interruptions in chest compressions—a nationwide prospective feasibility study. Resuscitation, 82(3), 263-269. doi:10.1016/j.resuscitation.2010.11.003
  16. Ødegaard, S., Olasveengen, T., Steen, P. A., & Kramer-Johansen, J. (2009). The effect of transport on quality of cardiopulmonary resuscitation in out-of-hospital cardiac arrest. Resuscitation, 80, 843–848. doi:10.1016/j.resuscitation.2009.03.032
  17. Hellevuo, H., Sainio, M., Huhtala, H., Olkkola, K. T., Tenhunen, J., & Hoppu, S. (2014). The quality of manual chest compressions during transport--effect of the mattress assessed by dual accelerometers. Acta Anaesthesiologica Scandinivica, 58(3), 323-328. doi:10.1111/aas.12245
  18. Cheskes, S., Byers, A., Zhan, C., Verbeek, P. R., Ko, D., Drennan, I. R., Buick, J. E., Brooks, S. C., Lin, S., Taher, A., & Morrison, L. J. (2017). CPR quality during out-of-hospital cardiac arrest transport. Resuscitation, 114, 34-39. doi:10.1016/j.resuscitation.2017.02.0160
  19. Verbeek, P. R., Vermeulen, M. J., Ali, F. H., Messenger, D. W., Summers, J., & Morrison, L. J. (2002). Derivation of a termination-of-resuscitation guideline for emergency medical technicians using automated external defibrillators. Academic Emergency Medicine, 9(7), 671-678. doi:10.1111/j.1553-2712.2002.tb02144.x
  20. Morrison, L. J., Visentin, L. M., Kiss, A., Theriault, R., Eby, D., Vermeulen, M., Sherbino, J., & Verbeek, P. R. (2006). Validation of a rule for termination of resuscitation in out-of-hospital cardiac arrest. New England Journal of Medicine, 355(5), 478-487. doi:10.1056/NEJMoa052620
  21. Morrison, L. J., Verbeek, P. R., Zhan, C., Kiss, A., & Allan, K. S. (2009). Validation of a universal prehospital termination of resuscitation clinical prediction rule for advanced and basic life support providers. Resuscitation, 80(3), 324-328. doi:10.1016/j.resuscitation.2008.11.014
  22. Sasson, C., Hegg, A. J., Macy, M., Park, A., Kellermann, A., & McNally, B. (2008). Prehospital termination of resuscitation in cases of refractory out-of-hospital cardiac arrest. Journal of the American Medical Association, 300(12), 1432-1438. doi:10.1001/jama.300.12.1432
  23. Richman, P. B., Vadeboncoeur, T. F., Chikani, V., Clark, L., & Bobrow, B. J. (2008). Independent evaluation of an out-of-hospital termination of resuscitation (TOR) clinical decision rule. Academic Emergency Medicine, 15(6), 517-521. doi:10.1111/j.1553-2712.2008.00110.x
  24. Ruygrok, M. L., Byyny, R. L., & Haukoos, J. S. (2009). Validation of 3 termination of resuscitation criteria for good neurologic survival after out-of-hospital cardiac arrest. Annals of Emergency Medicine, 54(2), 239-247. doi:10.1016/j.annemergmed.2008.11.012

The author has no financial interest, arrangement, or direct affiliation with any corporation that has a direct interest in the subject matter of this presentation, including manufacturer(s) of any products or provider(s) of services mentioned.

Kenny Navarro is Chief of EMS Education Development in the Department of Emergency Medicine at the University of Texas Southwestern Medical School at Dallas. He also serves as the AHA Training Center Coordinator for Tarrant County College. Mr. Navarro serves as an Emergency Cardiovascular Care Content Consultant for the American Heart Association, served on two education subcommittees for NIH-funded research projects, as the Coordinator for the National EMS Education Standards Project, and as an expert writer for the National EMS Education Standards Implementation Team.