Elsevier

Resuscitation

Volume 135, February 2019, Pages 145-152
Resuscitation

Clinical paper
Post resuscitation prognostication by EEG in 24 vs 48 h of targeted temperature management

https://doi.org/10.1016/j.resuscitation.2018.10.035Get rights and content

Abstract

Objective

To test if prognostic performance is affected by prolonged targeted temperature management (TTM) in comatose out-of-hospital cardiac arrest patients using two recently proposed EEG pattern classification models.

Methods

In this sub-study of the “Target Temperature Management for 48 vs. 24hand Neurologic Outcome after Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial”, EEGs of 20–30 min duration were collected 24 h and 48 h after reaching the target temperature of 33 ± 1 °C. We classified EEGs according to two EEG classification models by Westhall et al. (“highly malignant”, “malignant” and “benign”) and Hofmeijer et al. (“unfavorable”, “intermediate” and “favorable”). We tested prognostic ability against 6 months functional outcome using the Cerebral Performance Category score.

Results

We recorded EEGs in 120 patients at 24 h and in 44 patients at 48 h. We found no difference in specificities or sensitivities of the two models between the two TTM groups (all p-values >0.19) or in prognostication at 24 h compared to 48 h (all p-values >0.13), except for the presence of EEG reactivity favoring prognostication at 24 h (p < 0.001). Being classified in the “benign” or “favorable” category was strongly associated with good outcome with specificities of 100% (90–100) and 97% (85–100) for the Westhall and Hofmeijer models respectively.

Conclusions

We found no difference in the prognostic performance of the two studied EEG classification models during prolonged TTM for 48 h compared to standard duration, nor between EEG classification performed at 24 h versus 48 h after reaching target temperature. The two models performed best in good outcome prediction.

Introduction

Out-of-hospital cardiac arrest (OHCA) affects an estimated 400,000 people in Europe each year.1 Survival rates are approximately 10% in overall survival and 50%2 in patients admitted to the intensive care unit (ICU). Post-resuscitation care in the ICU includes target temperature management (TTM) to 32–36 °C for at least 24 h, but optimal depth3 and duration3 is still subject to research and discussion.

The most common cause of death in the ICU after OHCA, is hypoxic-ischemic encephalopathy, accounting for 60–70% of deaths.6, 7, 8 Further, 2–4% of survivors have serious neurologic deficits.3, 4

Timely and correct prognostication is of vital importance, both to avoid self-fulfilling prophecies and to guide physicians in decisions on withdrawal of care. EEG is an important prognostic tool and also recommended for ruling out subclinical seizures.5 However, inter-rater variability6 and the confounding effects of sedation and TTM together with the variety of classification systems makes it difficult to define optimal use of EEG for prognostic purposes.7 It is important to study the effects of TTM on EEG patterns in order to understand how to refine prognostication and evaluate possible treatment effects of different TTM regimens. The aim of the present study was to investigate the impact of prolonged TTM on prognostic performance and EEG evolution over time, using two recently proposed EEG pattern classification models; the Hofmeijer model8 and the Westhall9 model, following the standardized EEG terminology proposed by the American Clinical Neurophysiology Society (ACNS).10

Section snippets

Patients

The present study is a sub-study of the “Targeted Temperature Management for 48 vs. 24h and Neurologic Outcome After Out-of-Hospital Cardiac Arrest: A Randomized Clinical Trial” (the TTH48 trial)3 involving the 159 patients enrolled in the ICUs at Aarhus University Hospital, Denmark, and Stavanger University Hospital, Norway. The inclusion criteria of the TTH48 trial were the following: OHCA with a presumed cardiac origin, Glasgow Coma Scale below 8, sustained spontaneous circulation after

Results

We recorded 120 EEGs at 24 h (Fig. 1), median hours from TT to EEG; 20 h (IQR: 16–23, range: 8–36) and median hours from cardiac arrest to EEG; 25 h (IQR: 21–28, range: 14–40). In 44 of these patients, we also recorded EEGs at 48 h, median hours from TT to EEG; 43 h (IQR: 38–46, range: 25–65) and median hours from cardiac arrest to EEG; 49 h (IQR: 43–53, range: 31–68). We found no differences between TTM groups in time from cardiac arrest to TT or cardiac arrest to EEG (all p-values above

Discussion

We found no significant differences between TTM groups in specificity and sensitivity as assessed on a dichotomized CPC-scale after six months, however, numbers were small in each group at 48 h and our results should be validated in larger trials. We found no significant differences between prognostication at 24 h compared to 48 h measured in specificity and sensitivity of EEG categories, but using EEG reactivity, prognostication was best at 24 h compared to 48 h. Both classification models

Conclusion

Our results suggest no differences in prognostication between TTM groups using two models proposed by Westhall and Hofmeijer. We found no significant differences at 24 h compared to 48 h measured in specificity and sensitivity of EEG categories, but using EEG reactivity, prognostication was significantly better at 24 h compared to 48 h. Both classification models performed very well in good outcome prediction. Models for prediction of poor outcome within 48 h should not include non-identical

Conflicts of interest

Christophe H. V. Duez received funding from the following private foundations: The Viggo and Helene Bruun foundation, the Lily Benthine Lunds foundation of 1st of june 1978, the Director Jacob Madsen & wife Olga Madsen foundation and the Grocer A. V. Lykfeldt and wife foundation. Foundations had no influence on study design, data collection, analysis or data interpretation.

Acknowledgements

We wish to thank the staffs at the intensive care units of Stavanger University Hospital and Aarhus University hospital.

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