Without evidence of benefit, an intervention should not be presumed to be beneficial or safe.

- Rogue Medic

How Effective Is Epinephrine for Improving Survival Among Patients in Cardiac Arrest?


There have been two studies comparing epinephrine with placebo to treat out of hospital cardiac arrest. The Jacobs study was stopped early, because of interference by those who do not want to know if their medicine actually works.[1] The purpose of research is to determine, as objectively as possible, if a treatment is better than placebo nothing.  

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Even the small sample size shows a impressive p values of <0.001 for both ROSC (Return Of Spontaneous Circulation) and being admitted to the hospital. Unfortunately, that does not lead to outcomes that are better than placebo.

The Perkins study (PARAMEDIC2) did not find a significant difference between adrenaline (epinephrine in non-Commonwealth countries) and placebo.[2] The Jacobs study also did not find a difference, but the numbers were small, due to the interference by the less than knowledgeable. Following the Jacobs study, some intervention proponents have suggested that the problem is not a lack of evidence of benefit, but need to look at the evidence from the right perspective. The inadequate evidence is not “inadequate”, but really just misunderstood. All we need to do is use a method of analysis that compensates for the tiny sample size. A Bayesian approach will produce the positive outcome that is not justified by so few patients.[3]

What happens when the numbers are combined, so that the sample size is large enough to eliminate the need for statistical chicanery to come up with something positive?

The outcomes do not improve.  

Neither standard dose adrenaline, high-dose adrenaline,vasopressin nor a combination of adrenaline and vasopressin improved survival with a favourable neurological outcome.[4]

If the Bayesian approach were appropriate, then the much larger sample size would have provided more than enough patients to confirm the optimism of the epinephrine advocates. The result is still not statistically significant. Maybe a much, much larger study will show a statistically significant, but tiny, improvement in outcomes with epinephrine, but don’t hold your breath for that. It took half a century to produce the first study, then seven more years for the second. With the cost of research and the problems coordinating such a large study, it is more likely that the guidelines will continue to recommend spending a lot of time and money giving a drug that diverts attention from the interventions that do improve outcomes.

There is still no evidence that adrenaline provides better outcomes than placebo in human cardiac arrest patients.




[1] Effect of adrenaline on survival in out-of-hospital cardiac arrest: A randomised double-blind placebo-controlled trial Jacobs IG, Finn JC, Jelinek GA, Oxer HF, Thompson PL. Resuscitation. 2011 Sep;82(9):1138-43. doi: 10.1016/j.resuscitation.2011.06.029. Epub 2011 Jul 2. PMID: 21745533

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This study was designed as a multicentre trial involving five ambulance services in Australia and New Zealand and was accordingly powered to detect clinically important treatment effects. Despite having obtained approvals for the study from Institutional Ethics Committees, Crown Law and Guardianship Boards, the concerns of being involved in a trial in which the unproven “standard of care” was being withheld prevented four of the five ambulance services from participating.

In addition adverse press reports questioning the ethics of conducting this trial, which subsequently led to the involvement of politicians, further heightened these concerns. Despite the clearly demonstrated existence of clinical equipoise for adrenaline in cardiac arrest it remained impossible to change the decision not to participate.


[2] A Randomized Trial of Epinephrine in Out-of-Hospital Cardiac Arrest. Perkins GD, Ji C, Deakin CD, Quinn T, Nolan JP, Scomparin C, Regan S, Long J, Slowther A, Pocock H, Black JJM, Moore F, Fothergill RT, Rees N, O’Shea L, Docherty M, Gunson I, Han K, Charlton K, Finn J, Petrou S, Stallard N, Gates S, Lall R; PARAMEDIC2 Collaborators. N Engl J Med. 2018 Aug 23;379(8):711-721. doi: 10.1056/NEJMoa1806842. Epub 2018 Jul 18. PMID: 30021076

Free Full Text from N Engl J Med.


[3] Regarding “Effect of adrenaline on survival in out-of-hospital cardiac arrest: A randomised double-blind placebo-controlled trial”. Youngquist ST, Niemann JT. Resuscitation. 2012 Apr;83(4):e105; author reply e107. doi: 10.1016/j.resuscitation.2011.09.035. Epub 2012 Jan 18. No abstract available. PMID: 22266068

Free Full Text from Resuscitation.


[4] Adrenaline and vasopressin for cardiac arrest. Finn J, Jacobs I, Williams TA, Gates S, Perkins GD. Cochrane Database Syst Rev. 2019 Jan 17;1:CD003179. doi: 10.1002/14651858.CD003179.pub2. PMID: 30653257    



  1. Some nit-picking about the table.
    What is ‘OR’? (Heading of fourth column).
    Why does ‘CPC i or 2’ have such high percentage numbers with such a small N?

    • OR is Odds Ratio. There is a good explanation of the way that works at the link below, but is roughly the expected multiplier of any benefit of the treatment. 1.0 would mean that there is any benefits and harms cancel each other out. The numbers are given in a range, which for survival to discharge in the Jacobs study is very wide. It extends from 0.7 to 6.3. 0.7 is roughly 1.5 times worse than placebo, while 6.3 is 6.3 times better. The broad range is due to the low number of people who survived to discharge. An important point is that these are only the patients who had not yet been resuscitated by the time epinephrine would be indicated in their protocols, but it is not clear how many patients had been resuscitated at that point and how many were not entered into the study because of opposition to the research by the paramedic.

      Finally, participation in the study by the SJA-WA paramedics was voluntary, hence only 40% of eligible patients were recruited.

      The problem with that statement is that the study lists 1,507 patients who had resuscitation efforts begun and 601 who were randomized to placebo or adrenaline, but 601 is 40% of 1,507. There is no explanation of this in the paper. Were the patients resuscitated prior to randomization included the 60% of patients not recruited, but attributed to the paramedic not participating? I have written an email to one of the coauthors and regular collaborators of Dr. Jacobs (he died in 2014), but have not received a reply.

      Why does ‘CPC i or 2’ have such high percentage numbers with such a small N?

      The CPC at the time of discharge do seem to have been much more polarized than in a larger study. As you can see from the Perkins study, there is much more diversity among the outcomes with larger numbers, although the bad outcomes are much more common with epinephrine. The numbers in the Jacobs study are too small to draw any conclusions.

      An explanation of the reason small numbers are not a basis for drawing conclusions is given in Thinking, Fast and Slow by Daniel Kahneman. Chapter 10 – The Law of Small Numbers:

      A study of the incidence of kidney cancer in the 3,141 counties of the United States reveals a remarkable pattern. The counties in which the incidence of kidney cancer is lowest are mostly rural, sparsely populated, and located in traditionally Republican states in the Midwest, the South, and the West. What do you make of this?

      Your mind has been very active in the last few seconds, and it was mainly a System 2 operation. You deliberately searched memory and formulated hypotheses. Some effort was involved; your pupils dilated, and your heart rate increased measurably. But System 1 was not idle: the operation of System 2 depended on the facts and suggestions retrieved from associative memory. You probably rejected the idea that Republican politics provide protection against kidney cancer. Very likely, you ended up focusing on the fact that the counties with low incidence of cancer are mostly rural. The witty statisticians Howard Wainer and Harris Zwerling, from whom I learned this example, commented, “It is both easy and tempting to infer that their low cancer rates are directly due to the clean living of the rural lifestyle—no air pollution, no water pollution, access to fresh food without additives.” This makes perfect sense.

      Now consider the counties in which the incidence of kidney cancer is highest. These ailing counties tend to be mostly rural, sparsely populated, and located in traditionally Republican states in the Midwest, the South, and the West. Tongue-in-cheek, Wainer and Zwerling comment: “It is easy to infer that their high cancer rates might be directly due to the poverty of the rural lifestyle—no access to good medical care, a high-fat diet, and too much alcohol, too much tobacco.” Something is wrong, of course. The rural lifestyle cannot explain both very high and very low incidence of kidney cancer.

      The key factor is not that the counties were rural or predominantly Republican. It is that rural counties have small populations. And the main lesson to be learned is not about epidemiology, it is about the difficult relationship between our mind and statistics. System 1 is highly adept in one form of thinking—it automatically and effortlessly identifies causal connections between events, sometimes even when the connection is spurious. When told about the high-incidence counties, you immediately assumed that these counties are different from other counties for a reason, that there must be a cause that explains this difference. As we shall see, however, System 1 is inept when faced with “merely statistical” facts, which change the probability of outcomes but do not cause them to happen.

      System 1 is intuitive thinking, which is much more rapid, but is not appropriate for answering questions that are complex. The thinking fast of the title.

      System 2 is more analytical. Thinking slow. It is an excellent book and important for understanding the ways that we let our brains mislead us.