Resuscitation 85 (2014) 1621–1622

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Editorial

Do we really know who benefits from targeted temperature management?

The concept of post cardiac arrest targeted temperature management (TTM) is now well-established in out-of-hospital cardiac arrest (OHCA). However, the optimal cooling temperature and length are still debated. A recent efficacy study found no difference in survival between patients cooled to 33 ◦ C and patients kept at 36 ◦ C for 24 h.1 But, how does a well-controlled efficacy study reflect what happens in real life when TTM is applied to a larger group of un-selected OHCA patients? In order words, how do we gather information on the effectiveness2 of TTM? The larger group of unconscious post cardiac arrest patients incorporates numerous sub-groups3,4 with different clinical profiles and prognosis compared to those studied in efficacy studies. As most OHCA patients die from anoxic–ischemic brain injury,5 more information on the interaction between patient and cardiac arrest factors and TTM is warranted to identify what patients benefit the most from TTM. Several recent studies2,6–9,14–19 have tried to single out the effect of TTM in various sub-groups of OHCA patients. As a specific biomarker to grade the extent of anoxic–ischemic injury (“anoxic load”) is still missing, surrogate measures like time from cardiac arrest to return of spontaneous circulation (ROSC) (“down time”), serum lactate and blood pressure at arrival in the hospital have been used. Kim et al.6 found that prolonged down-time was associated with lower survival in patients undergoing TTM, but even with down-times exceeding 20 min the survival was substantial. Testori et al.7 used time of no CPR (“no flow time”) in 1200 unconscious OHCA survivors to try to elucidate who benefited from TTM and not. They found that TTM seemed to have a marked effect on survival only with no flow times exceeding 3 min. Using time as a marker of anoxic load seems logical. However, it is difficult to compare the results of recent studies as slightly different definitions were used.6–9 To further complicate matters, the task of register time-dependent critical events during resuscitation in an accurate manner is not simple.10 It is also self-evident that with prolonged down-time the influence of bystander CPR increases. Recent registry-based studies11–13 have reported notable increases in bystander CPR rates and linked this to significant increases in survival. What is clear is that we need more data on the interaction between no flow times, low flow times (time from start of CPR of uncertain and variable quality to ROSC), total down time and the clinical effects of post resuscitation TTM. Serum lactate has also been used as a marker of anoxic injury,14–17 with many authors now using a lactate value of http://dx.doi.org/10.1016/j.resuscitation.2014.09.003 0300-9572/© 2014 Elsevier Ireland Ltd. All rights reserved.

5 mmol l−1 as some sort of cut-off. However, lactate levels are linked to the use of adrenaline during resuscitation and lactate clearance may be a better prognostic marker than single values. Some authors have also found initial systolic blood pressure to be a good prognostic marker of outcome in OHCA patients.18 Still, we do not know how to use such differences in down-time, lactate and initial circulatory status when deciding whether to apply TTM or not. What we do know is that physicians use prognostic factors when deciding to use TTM,3 and that TTM seems to have the most impact on survival in the group of patients with an initial shockable rhythm.3,18 In this issue of Resuscitation, Drennan et al.19 present data from a cardiac arrest registry which covers a Canadian population of over 6.6 million residents. They studied a selected cohort of unconscious OHCA survivors with a witnessed arrest and a shockable rhythm. All patients were eligible for post resuscitation TTM. Further, use of TTM was encouraged in the network, but its use was left to the discretion of the local physician. Actually, 69% of patients received it. The authors applied the theoretical 3 phase model of cardiac arrest (electric, circulatory, metabolic) proposed by Weisfeldt and Becker in 200220 to split their cohort into 3 groups with incremental length (10 min) from collapse to defibrillation. Not surprisingly, they found that functional outcome was inversely related to time to defibrillation. On the other side, even with down times >10 min they found good survival rates exceeding 50%. The overall bystander CPR rate in the study was quite high with 50%.19 Surprisingly, bystander CPR was not an independent predictor of good functional survival in their multivariable analysis, while time to defibrillation and TTM was.19 Further, the benefit of TTM seemed to increase with time to defibrillation or using other words the low-flow time. When trying to interpret these findings it is important to remember that although this was a large study from a well-established research network with tightly controlled data entry, there are inherent weaknesses in retrospective analysis of registry data, the major one here being that use of TTM was left to the discretion of the attending physician.3 As stated by the authors, it was not known if local physicians decided to abstain from use of TTM due to what they consider poor or good prognostic factors, or both. This may have blurred some of the analysis of the relationship between TTM and survival. So, is the present work19 just another registry based study trying to “skin the cat” a little differently or an important new piece in the resuscitation science conundrum? We think the latter. To learn more about the effectiveness of new therapies like TTM, we need

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Editorial / Resuscitation 85 (2014) 1621–1622

to make use of registry data that reflect real life clinical practice.2 We think the key message to clinicians from this study is not to use prolonged down time as a factor to withhold TTM in patients with an initial shockable rhythm. As researchers we need to continue the quest for better markers of irreversible anoxic–ischemic and reperfusion injury. This will make it easier to identify patients who are worth treating aggressively – given our present knowledge and constrained resources. Conflicts of interest statement No conflicts of interest to declare. References 1. Nielsen N, Wetterslev J, Cronberg T, et al. Targeted temperature management at 33 ◦ C versus 36 ◦ C after cardiac arrest. N Engl J Med 2013;369:2197–206. 2. El-Serag HB, Talwalkar J, Kim WR. Efficacy, effectiveness, and comparative effectiveness in liver disease. Hepatology 2010;52:403–7. 3. Lindner T, Langørgen J, Sunde K, et al. Factors predicting the use of therapeutic hypothermia and survival in unconscious out-of-hospital cardiac arrest patients admitted to the ICU. Crit Care 2013;17:R147. 4. Dumas F, Rea TD. Long-term prognosis following resuscitation from outof-hospital cardiac arrest: role of aetiology and presenting arrest rhythm. Resuscitation 2012;83:1001–5. 5. Dragancea I, Rundgren M, Englund E, et al. The influence of induced hypothermia and delayed prognostication on the mode of death after cardiac arrest. Resuscitation 2013;84:337–42. 6. Kim WY, Giberson TA, Uber A, et al. Neurologic outcome in comatose patients resuscitated from out-of-hospital cardiac arrest with prolonged downtime and treated with therapeutic hypothermia. Resuscitation 2014 [Epub ahead of print]. 7. Testori C, Sterz F, Holzer M, et al. The beneficial effect of mild therapeutic hypothermia depends on the time of complete circulatory standstill in patients with cardiac arrest. Resuscitation 2012;83:596–601. 8. Avalli L, Mauri T, Citerio G, et al. New treatment bundles improve survival in out-of-hospital cardiac arrest patients: a historical comparison. Resuscitation 2014;85:1240–4. 9. Bray JE, Bernard S, Cantwell K, et al. The association between systolic blood pressure on arrival at hospital and outcome in adults surviving from out-of-hospital cardiac arrests of presumed cardiac aetiology. Resuscitation 2014;85:509–15. 10. Frisch A, Reynolds JC, Condle J, et al. Documentation discrepancies of timedependent critical events in out of hospital cardiac arrest. Resuscitation 2014;85:1111–4.

11. Adielsson A, Hollenberg J, Karlsson T, et al. Increase in survival and bystander CPR in out-of-hospital shockable arrhythmia: bystander CPR and female gender are predictors of improved outcome. Experiences from Sweden in an 18-year perspective. Heart 2011;97:1391–6. 12. Lindner TW, Søreide E, Nilsen OB, et al. Good outcome in every fourth resuscitation attempt is achievable – an Utstein template report from the Stavanger region. Resuscitation 2011;82:1508–13. 13. Wissenberg M, Lippert FK, Folke F, et al. Association of national initiatives to improve cardiac arrest management with rates of bystander intervention and patient survival after out-of-hospital cardiac arrest. JAMA 2013;310: 1377–84. 14. Starodub R, Abella BS, Grossestreuer AV, et al. Association of serum lactate and survival outcomes in patients undergoing therapeutic hypothermia after cardiac arrest. Resuscitation 2013;84:1078–82. 15. Lee TR, Kang MJ, Cha WC, et al. Better lactate clearance associated with good neurologic outcome in survivors who treated with therapeutic hypothermia after out-of-hospital cardiac arrest. Crit Care 2013;17:R260. 16. Grimaldi D, Dumas F, Perier MC, et al. Short- and long-term outcome in elderly patients after out-of-hospital cardiac arrest: a cohort study. Crit Care Med 2014 [Epub ahead of print]. 17. Kaji AH, Hanif AM, Bosson N, et al. Predictors of neurologic outcome in patients resuscitated from out-of-hospital cardiac arrest using classification and regression tree analysis. Am J Cardiol 2014 [Epub ahead of print]. 18. Kocjancic ST, Jazbec A, Noc M. Impact of intensified postresuscitation treatment on outcome of comatose survivors of out-of-hospital cardiac arrest according to initial rhythm. Resuscitation 2014 [Epub ahead of print]. 19. Drennan IR, Lin S, Thorpe KE, Morrison LJ. The effect of time to defibrillation and targeted temperature management on functional survival after out-of-hospital cardiac arrest. Resuscitation 2014;85:1623–8. 20. Weisfeldt ML, Becker LB. Resuscitation after cardiac arrest: a 3-phase timesensitive model. JAMA 2002;288:3035–8.

Eldar Søreide ∗ Michael Busch Department of Anaesthesiology and Intensive Care, Stavanger University Hospital, 4068 Stavanger, Norway ∗ Corresponding author. E-mail address: [email protected] (E. Søreide)

4 September 2014

Do we really know who benefits from targeted temperature management?

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