Electrophysiology for prognostication (ALS): Systematic Review

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This Review is a draft version prepared by ILCOR, with the purpose to allow the public to comment and is labeled “Draft for Public Comment". The comments will be considered by ILCOR. The next version will be labelled “draft" to comply with copyright rules of journals. The final Review will be published on this website once a summary article has been published in a scientific Journal and labeled as “final”.

Conflict of Interest Declaration

The ILCOR Continuous Evidence Evaluation process is guided by a rigorous ILCOR Conflict of Interest policy. The following Task Force members and other authors were recused from the discussion as they declared a conflict of interest: none applicable

The following Task Force members and other authors declared an intellectual conflict of interest and this was acknowledged and managed by the Task Force Chairs and Conflict of Interest committees: Tobias Cronberg and Marlijn Kamps are co-authors of some of the included studies in the present review. They were excluded from the bias assessment of these studies.

CoSTR Citation

Sandroni C, Cacciola S, Cronberg T, D’Arrigo S, Hoedemaekers CWE, Kamps M, Nolan JP, Böttiger BW, Andersen LW , Callaway CW, Deakin CD, Donnino MW, Drennan I, Hsu C, Morley PM, Nicholson TC, O’Neil BJ, Neumar RW, Paiva EF, Parr MJ, Reynolds JC, Wang TL, Welsford M, Berg KM, Soar J. Electrophysiology for prognostication. Consensus on Science with Treatment Recommendations [Internet] Brussels, Belgium: International Liaison Committee on Resuscitation (ILCOR) Advanced Life Support Task Force, 2020 Jan 1. Available from: http://ilcor.org.

Methodological preamble

The continuous evidence evaluation process for the production of Consensus on Science with Treatment Recommendations (CoSTR) started with a systematic review of prognostication after cardiac arrest (Sandroni C 2020 – PROSPERO: CRD 420 1914 1169) conducted by a systematic review team with involvement of clinical content experts from the ILCOR ALS Task Force.

Systematic review

Sandroni C et al. Electrophysiology for prognostication in comatose survivors of cardiac arrest. In preparation.

PICOST

The PICOST (Population, Intervention, Comparator, Outcome, Study Designs and Timeframe)

Population: Adults who are comatose after resuscitation from cardiac arrest (either in-hospital or out-of-hospital), regardless of target temperature.

Intervention: Electrophysiology studies assessed within one week from cardiac arrest.

Comparator: none.

Outcome: Prediction of poor neurological outcome defined as Cerebral Performance Categories (CPC) 3-5 or modified Rankin Score (mRS) 4-6 at hospital discharge/1 month or later.

Study Design: Prognostic accuracy studies where the 2 x 2 contingency table (i.e., the number of true/false negatives and positives for prediction of poor outcome) was reported, or where those variables could be calculated from reported data, are eligible for inclusion. Unpublished studies, reviews, case reports, case series, studies including less than 10 patients, letters, editorials, conference abstracts, and studies published in abstract form were excluded.

Timeframe: In 2015, an ILCOR evidence review identified four categories of predictors of neurological outcome after cardiac arrest, namely clinical examination, biomarkers, electrophysiology and imaging. In the last four years, several studies have been published and new predictors have been identified, therefore the topic needs an update.

The most recent search of the previous systematic reviews on neuroprognostication was launched on May 31, 2013. We searched studies published from January 1, 2013 onwards.

PROSPERO: CRD 420 1914 1169

Consensus on science

SSEPs

SSEPs were investigated in twenty observational studies [Grippo 2017 641; Scarpino 2019 (a) 115; Choi 2017 70; Maciel 2017 469; Dhakal 2016 116; Fatuzzo 2018 29; Leao 2015 322; Noirhomme 2014 6; Rossetti 2017 e674; De Santis 2017 119; Kim 2018 (a) 33; Ruijter 2019 203; Ruijter 2018 1534; Oddo 2018 2102; Sondag 2017 111; Hofmeijer 2015 137; Admiraal 2019 17; Dragancea 2015 (a) 164; Kim 2018 (b) e545; Scarpino 2019 (b) in press].

In four studies [Grippo 2017 641, 78 pts; Choi 2017 70, 80 pts; Maciel 2017 469, 41 pts; Scarpino 2019 (b) in press, 218 pts] a bilaterally absent N20 SSEPs wave within 24h from ROSC predicted poor neurological outcome from hospital discharge to 6 months with 100% specificity and sensitivity ranging from 33.3% to 57.7% (very-low certainty of evidence).

In one study [Scarpino 2019 (a) 115, 346 pts] an absent N20 wave on one side and an absent or low-voltage N20 wave on the other side within 24h from ROSC predicted poor neurological outcome at 6 months with 100% specificity and sensitivity 49.6% (very low certainty of evidence)

In eighteen studies [Dhakal 2016 116, 35 pts; Fatuzzo 2018 29, 457 pts; Leao 2015 322, 67 pts; Noirhomme 2014 6, 44 pts; Rossetti 2017 e674, 260 pts; De Santis 2017 119, 65 pts; Kim 2018 (a) 33, 127 pts; Ruijter 2019 203, 850 pts; Grippo 2017 641, 76 pts; Ruijter 2018 1534, 559 pts; Oddo 2018 2102, 188 pts; Sondag 2017 111, 178 pts; Hofmeijer 2015 137, 139 pts; Admiraal 2019 17, 38 pts; Scarpino 2019 (b) in press, 240 pts; Choi 2017 70, 81 pts; Dragancea 2015 (a) 164, 201 pts; Kim 2018 (b) e545, 116 pts] a bilaterally absent SSEPs N20 wave at 24-96h predicted poor neurological outcome from hospital discharge to 6 months with specificity ranging from 50% to 100% and sensitivity ranging from 18.2% to 69.1% (very-low certainty of evidence).

Unreactive EEG

Unreactive EEG was investigated in fourteen observational studies [Grippo 2017 641; Noirhomme 2014 6; Admiraal 2019 17; Alvarez 2015 128; Juan 2015 403; Rossetti 2017 e674; Duez 2019 145; Fatuzzo 2018 29; Liu 2016 8273716; Westhall 2016 1482; Amorim 2016 121; Sivaraju 2015 1264; Benarous 2019 20; Zhou 2019 343].

In twelve studies [Grippo 2017 641, 78 pts; Noirhomme 2014 6, 45 pts; Admiraal 2019 17, 149 pts; Alvarez 2015 128, 18 pts; Rossetti 2017 e674, 357 pts; Duez 2019 145, 120 pts; Fatuzzo 2018 29, 434 pts; Liu 2016 8273716, 12 pts; Amorim 2016 121, 373 pts; Sivaraju 2015 1264, 89 pts; Benarous 2019 20, 48 pts; Zhou 2019 343, 149 pts] unreactive EEG within 72h predicted poor neurological outcome from hospital discharge to 6 months with specificity ranging from 41.7% to 100% and sensitivity ranging from 50% to 97.1% (certainty of evidence from moderate to very low). Specificity was below 90% in most of these studies, and it reached 100% in only in two of them.

In one study [Westhall 2016 1482, 87 pts] unreactive EEG at a median of 77h (IQR 53-102) predicted poor neurological outcome at 6 months with 70% specificity and 88.1% sensitivity (very-low certainty of evidence).

Rhythmic/ Periodic Discharges

Rhythmic/periodic discharges were investigated in nine observational studies [Lamartine 2016 153; Scarpino 2019 (a) 115; Scarpino 2019 (b) in press; Rossetti 2017 e674; Fatuzzo 2018 29; Westhall 2016 1482; Backman 2018 24; Benarous 2019 20; Beretta 2019 in press].

In two studies [Lamartine 2016 153, 89 pts; Scarpino 2019 (a) 115, 218] Rhythmic/periodic discharges within 24h predicted poor neurological outcome from 3 months to 6 months with 100% specificity and sensitivity ranging from 2.4% to 7.9% (certainty of evidence from moderate to very low).

In four studies [Lamartine 2016 153, 80 pts; Scarpino 2019 (b) in press, 346 pts; Rossetti 2017 e674, 175; Fatuzzo 2018 29, 200 pts] Rhythmic/periodic discharges within 48h predicted poor neurological outcome from 3 months to 6 months with specificity ranging from 97.2% to 100% and sensitivity ranging from 8.1% to 42.9% (certainty of evidence from moderate to very low).

In three studies [Benarous 2019 20, 48 pts; Rossetti 2017 e674, 173 pts; Scarpino 2019 (b) in press, 240 pts] Rhythmic/periodic discharges at 48-72h predicted poor neurological outcome from 1 month to 6 months with specificity ranging from 66.7% to 96.1% and sensitivity ranging from 11.4% to 50.8% (certainty of evidence from low to very low).

In two studies [Westhall 2016 1482, 103 pts; Backman 2018 24, 207 pts] Rhythmic/periodic discharges at the median time of 76-77h predicted poor neurological outcome at 6 months with specificity ranging from 97% to 100% and sensitivity ranging from 5% to 40% (certainty of evidence from low to very low).

In one study [Beretta 2019 in press, 166 pts] Rhythmic/periodic discharges within 5 days predicted poor neurological outcome at 6 months with 100% specificity and 15.7% sensitivity (moderate certainty of evidence).

Sporadic, Non-Rhythmic/Periodic Discharges

Sporadic, non-rhythmic/periodic discharges were investigated in five observational studies [Lamartine 2016 153; Ruijter 2019 203; Scarpino 2019 (a) 115; Scarpino 2019 (b) in press; Benarous 2019 20]

In three studies [Lamartine 2016 153, 89 pts; Ruijter 2019 203, 469 pts; Scarpino 2019 (a) 115, 218 pts;] Sporadic, non-rhythmic/periodic discharges within 24h predicted poor neurological outcome from 3 months to 6 months with specificity ranging from 84.6% to 100% and sensitivity ranging from 0.5% to 7.9% (certainty of evidence from moderate to very low).

In three studies [Lamartine 2016 153, 80 pts; Ruijter 2019 203, 742 pts; Scarpino 2019 (b) in press, 346 pts] Sporadic, non-rhythmic/periodic discharges within 48h predicted poor neurological outcome from 3 months to 6 months with specificity ranging from 95.8% to 99.5% and sensitivity ranging from 0.4% to 13.3% (certainty of evidence from moderate to very low).

In three studies [Benarous 2019 20, 48 pts; Ruiter 2019 203, 517 pts; Scarpino 2019 (b) in press, 240 pts] Sporadic, non-rhythmic/periodic discharges at 48-72h predicted poor neurological outcome from 1 month to 6 months with specificity ranging from 88.9% to 97.3% and sensitivity ranging from 0.6% to 38.5% (certainty of evidence from low to very low).

In one study [Ruiter 2019 203, 133 pts] Sporadic, non-rhythmic/periodic discharges at 96-120h predicted poor neurological outcome at 6 months with specificity ranging from 66.7% to 82.1% and sensitivity ranging from 17.6% to 21.3% (very-low certainty of evidence).

Seizures

Seizures were investigated in five observational studies [Lamartine 2016 153, 89 pts; Sadaka 2015 292, 58 pts; Benarous 2019 20, 48 pts; Westhall 2016 1482, 103 pts; Amorim 2016 121, 373 pts].

In these studies seizures on EEG within 120h predicted poor neurological outcome from hospital discharge to 6 months with 100% specificity and sensitivity ranging from 0.6% to 26.8% (certainty of evidence from moderate to very low).

Status epilepticus

Status epilepticus was investigated in six studies [Oh 2015 1094, 130 pts; Leao 2015 322, 67 pts; Zhou 2019 343, 226 pts; Amorim 2016 121, 373 pts; Dragancea 2015 (b) 173, 122 pts; Beretta 2019 in press, 166 pts].

In these studies Status Epilepticus within 5 days predicted poor neurological outcome from hospital discharge to 6 months with specificity ranging from 82.6% to 100% and sensitivity ranging from 1.8% to 50% (certainty of evidence low or very low).

In three studies [Leao 2015 322, 67 pts; Zhou 2019 343, 226 pts; Amorim 2016 121, 373 pts] specificity was 100%. EEG was recorded within 72h from ROSC. In another study [Dragancea 2015 (b) 173] specificity was 100% only when status epilepticus originated from a discontinuous or burst-suppression background.

Burst-suppression

Burst suppression was investigated in five observational studies [Sadaka 2015 292; Leao 2015 322; Zhou 2019 343; Westhall 2016 1482; Backman 2018 24].

In one study [Sadaka 2015 292, 58 pts] burst suppression within 24h predicted poor neurological outcome to hospital discharge with 100% specificity and 51.5% sensitivity (certainty of evidence very low).

In four studies [Leao 2015 322, 67 pts; Zhou 2019 343, 197 pts; Westhall 2016 1482, 103 pts; Backman 2018 24, 207 pts] burst suppression at 24-76h predicted poor neurological outcome at 6 months with specificity ranging from 91.7% to 100% and sensitivity ranging from 13.9% to 21.8% (certainty of evidence from low to very low).

Definitions of burst-suppression varied: in two studies (Westhall 2016 1482, Backman 2018 24) the ACNS (American Clinical Neurophysiology Society) definition was used. In one study a non-ACNS definition was used, while in other two studies no specific definition was used.

Synchronous BS

In one study [Ruijter, 2019 203, 742 pts] a synchronous BS at 6-96h predicted poor neurological outcome at 6 months with 100% specificity and sensitivity ranging from 1.1% to 31.7% (certainty of evidence from moderate to low).

Heterogeneous BS

In one study [Ruijter 2019 203, 742 pts] heterogeneous BS at 6-120h predicted poor neurological outcome at 6 months with specificity ranging from 90.7% to 100% and sensitivity ranging from 1.1% to 16.2% (certainty of evidence from moderate to very low).

Highly malignant patterns

Highly malignant EEG patterns were investigated in thirteen observational studies [Grippo 2017 641; Hofmeijer 2015 137; Admiraal 2019 17; Ruijter 2019 203; Scarpino 2019 (a) 115; Sivaraju 2015 1264; Duez 2019 145; Sondag 2017 111; Caporro 2019 146; Youn 2017 120; De Santis 2017 119; Backman 2018 24; Westhall 2016 1482].

In nine studies [Grippo 2017 641, 78 pts; Hofmeijer 2015 137, 230 pts; Admiraal 2019 17, 141 pts; Scarpino 2019 (a) 115, 346 pts; Sivaraju 2015 1264, 89 pts; Duez 2019 145, 120 pts; Sondag 2017 111, 357 pts; Caporro 2019 146, 184 pts; Rujter 2019 203, 742 pts] highly malignant EEG within 36h predicted poor neurological outcome from hospital discharge to 6 months with specificity ranging from 90.6% to 100% and sensitivity ranging from 0.4% to 97% (certainty of evidence from moderate to low).

In one study [De Santis 2017 119, 65 pts] highly malignant EEG (Suppression without or with GPEDs, burst suppression) at 0-48h predicted poor neurological outcome at 3 months with 93.3% specificity and 74.3% sensitivity (low certainty of evidence).

In five studies [Duez 2019 145, 44 pts; Hofmeijer 2015 137, 187 pts; Ruijter 2019 203, 497 pts; Youn 2017 120, 240 pts; Grippo 2017 641, 76 pts] highly malignant EEG at 48-72h predicted poor neurological outcome at 6 months with specificity ranging from 95.5% to 100% and sensitivity ranging from 4% to 48.3% (certainty of evidence from moderate to low).

In two studies [Backman 2018 24, 207 pts; Westhall 2016 1482, 103 pts] highly malignant EEG at the median time of 76-77h predicted poor neurological outcome at 6 months with specificity ranging from 98.5% to 100% and sensitivity ranging from 31.2% to 50% (moderate certainty of evidence).

In one study [Ruijter 2019 203, 133 pts] highly malignant EEG at 96-120h predicted poor neurological outcome at 6 months with 100% specificity and sensitivity ranging from 8.5% to 11.8% (certainty of evidence from low to very low).

Treatment recommendations

  • We suggest using a bilaterally absent N20 SSEP wave in combination with other indices to predict poor outcome in adult patients who are comatose after cardiac arrest (weak recommendation, very low-certainty evidence).
  • We suggest against EEG background reactivity alone to predict poor outcome in adult patients who are comatose after cardiac arrest (weak recommendation, very low-certainty evidence).
  • We suggest using the presence of epileptiform activity on EEG to predict poor outcome in adult patients who are comatose after cardiac arrest.
  • We suggest using seizures on EEG to predict poor outcome in adult patients who are comatose after cardiac arrest (weak recommendation, very low-certainty evidence).
  • We suggest against using Status Epilepticus to predict poor outcome in adult patients who are comatose after cardiac arrest (weak recommendation, very low-certainty evidence).
  • We suggest using burst-suppression on EEG to predict poor outcome in adult patients who are comatose and who are off sedation after cardiac arrest (weak recommendation, very low-certainty evidence
  • We suggest using highly malignant EEG patterns to predict poor outcome in adult patients who are comatose and who are off sedation after cardiac arrest (weak recommendation, very-low-certainty evidence).

Justification and Evidence to Decision Framework Highlights

  • In making a recommendation about SSEPs, the task force considered that SSEP have a low risk of confounding from TTM or sedation and a large size of effect (high precision). However, in order to limit the risk of self-fulfilling prophecy, combining SSEP with other indices of poor neurological outcome is prudent.
  • In almost all studies we included the specificity of unreactive EEG background for predicting poor outcome, and its precision were low. In addition, both definitions and stimuli to induce EEG reactivity were inconsistent across studies.
  • In most of the studies we included the specificity of rhythmic/periodic epileptiform activity for predicting poor outcome was 100%. Specificity was lower for sporadic epileptiform discharges.
  • In all studies we included the specificity of ACNS-defined seizures on EEG for predicting poor outcome was 100%. This specificity was consistent along the first 72h after ROSC
  • Specificity of Status Epilepticus for predicting poor outcome was 100% in only half of the studies we included. In none of these studies status epilepticus was evaluated blindly, and in most of them it was included among the criteria for WLST. Although this is common for other predictors based on electrophysiology, an additional issue for status epilepticus was its largely inconsistent definition.
  • All studies we included showed that the presence of burst-suppression on EEG predicted poor neurological outcome with a specificity above 90%, and in most of the studies specificity was 100%. Due to the potential interference of sedative agents on EEG, evaluating burst-suppression as a predictor off sedation appears as the most prudent strategy.
  • The presence of highly malignant EEG patterns predicted poor outcome with 100% specificity in most of the studies we included. However, the combination of patterns corresponding to a highly malignant EEG was not consistent in studies. In most studies, the definition of these patterns was consistent with the American Clinical Neurophysiology Society (ACNS) terminology. EEG is prone to interference from sedation and evaluating these patterns off sedation is prudent.

Knowledge Gaps

  • Further studies are needed to evaluate the added value of assessing SSEPs in combination with other predictors of poor neurological outcome after cardiac arrest.
  • It is desirable that future studies will adopt a standard definition of background EEG reactivity. An international consensus statement on EEG reactivity testing (e.g. stimulus protocol) has been proposed (Admiraal 2018 36).
  • It is desirable that future studies will adopt a standard definition of epileptiform discharges.
  • The specific predictive value of the different epileptiform subtypes, their prevalence, and their combination with background EEG deserves further investigation.
  • Precision was low or very low in most studies on seizures. Further studies are needed to confirm the predictive value of seizures for poor outcome after cardiac arrest.
  • A standard definition of Status Epilepticus is urgently needed.
  • It is desirable that future studies will adopt a standard definition of burst suppression, such as the one included in the American Clinical Neurophysiology Society’s (ACNS) Standardized Critical Care EEG Terminology (Hirsch 2013 1).
  • The accuracy of synchronous burst-suppression (identical/highly epileptiform bursts) deserves further investigation.
  • Achieving a consensus definition of highly malignant EEG patterns in patients who are comatose after resuscitation from cardiac arrest is desirable.

Attachments

  1. Evidence-to-Decision Table: SSEP ETD
  2. Evidence-to-Decision Table: Unreactive EEG ETD
  3. Evidence-to-Decision Table: Epileptiform discharges ETD
  4. Evidence-to-Decision Table: Seizures ETD
  5. Evidence-to-Decision Table: Status Epilepticus ETD
  6. Evidence-to-Decision Table: Burst suppression ETD
  7. Evidence-to-Decision Table: Highly malignant EEG ETD

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Task Force Systematic Review

Discussion

GUEST
Karen Hirsch (218 posts)
The term "epileptiform" should not used any more to describe discharges, because it is unclear whether the discharges are actually epileptiform and the term epileptiform has clinical connotations. There are some discharges that are more benign and would not be considered epileptiform. This is outlined in a previous ACNS statement that is cited in the ETD table (Hirsch 2013 J Clin Neurophys) and the correct terminology should be used. It perpetuates the problems with this research (ie lack of standard definitions) when we use outdated terminology. Suggest removing the term "epileptiform" and simply saying "discharges" in order to be consistent with critical care EEG definitions.
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GUEST
Karen Hirsch (218 posts)
Re: Highly Malignant EEG - does not make sense to make a recommendation to use this to predict outcome when the definitions vary so broadly and the time-points at which they are evaluated also vary broadly. Other EEG patterns may have inconsistency in definitions, but they were still ultimately evaluating roughly the same thing. "Malignant EEG" patterns are all different here - thus this is not even appropriate to lump together in a single SR since there is such a major degree of inconsistency. How can a TR be based on different EEG findings evaluated at different time points post-arrest ?
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