- Email: [email protected]
Accurate Neuroprognostication in Cardiac Arrest Survivors: Details Matter!
Accepted Manuscript Title: Accurate Neuroprognostication in Cardiac Arrest Survivors: Details Matter! Authors: Carolina B. Maciel, Lawrence J. Hirsch PII: DOI: Reference:
S0300-9572(17)30130-2 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.030 RESUS 7122
To appear in:
Resuscitation
Author: David M. Greer PII: DOI: Reference:
S0300-9572(17)30130-2 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.030 RESUS 7122
To appear in:
Resuscitation
Author: Rafeed Alkawadri PII: DOI: Reference:
S0300-9572(17)30130-2 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.030 RESUS 7122
To appear in:
Resuscitation
Received date:
21-3-2017
Please cite this article as: Alkawadri Rafeed.Accurate Neuroprognostication in Cardiac Arrest Survivors: Details Matter!.Resuscitation http://dx.doi.org/10.1016/j.resuscitation.2017.03.030 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Letter to the editor regarding: “Excellent neurologic recovery after prolonged coma in a cardiac arrest patient with multiple poor prognostic indicators” Accurate Neuroprognostication in Cardiac Arrest Survivors: Details Matter! Carolina B. Maciel, MD1; Lawrence J. Hirsch, MD1; David M. Greer, MD, MA2; and Rafeed Alkawadri, MD1,3 1
Division of Epilepsy and EEG, Critical Care EEG Monitoring Program, Department of Neurology, Yale School of Medicine, New Haven, CT, 06510 2
Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT, 06510 3
The Human Brain Mapping Program, Department of Neurology, Yale School of Medicine 333 Cedar Street, New Haven, CT, 06510 Corresponding Author: Carolina Barbosa Maciel, MD ICU EEG fellow Yale School of Medicine P.O. Box 208018 New Haven, CT 06520 Tel: 917-355-2504 Fax: 203 – 785 - 2238 Email: [email protected]
Acknowledgments: Dr. Carolina B. Maciel reports no disclosures. Dr. Lawrence J. Hirsch reports no relevant disclosures. Dr. David M. Greer serves as Editor-in-Chief of Seminars in Neurology and has received compensation for medicallegal consultation. Dr. Rafeed Alkawadri reports no disclosures.
Funding: None Word Count/Number of Total Word Count: 659 Title (character count): 75 Text: 498 References: 5 Tables: 1
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Dear Sir, We read with interest the report by Weinstein et al of a cardiac arrest survivor with an unexpected good outcome despite absent cortical potentials on somatosensory evoked potentials (SSEP) performed on post-cardiac arrest day 20 [1]. While we commend the authors for discussing the important effect of the self-fulfilling prophecy bias, and supporting the use of multiple modalities when predicting neurologic outcome, we would like to express our concerns about their report, in particular the reliability of their SSEP results.
Regarding the technical aspects of the SSEP testing, the following important aspects are not provided: the nerve stimulated (presumably median), the montage used, the stimulation intensity and how it was adjusted, the artifact rejection methods implemented, and the number of rejections in the cortical channels out of the 2000 responses. It is unusual to see such a discrepancy in signal-to-noise ratio between cortical and subcortical channels (seen in all channels bilaterally). Minimal requirements for median nerve SSEP recordings in unresponsive patients are summarized in Table 1 [2-4].
Accounting for confounders is one of the most significant challenges in neuroprognostication following cardiac arrest. Of these, the effect of body temperature and sedating medications are of significant importance. The authors mentioned that the patient received continuous infusions of midazolam and propofol targeting burst suppression for 48 hours; however, it remains unclear at what point this occurred and the timing of last administration of any sedatives relative to
2
3
neurologic examination and whether sedation boluses were administered at the time of recording, as those may result in transient attenuation of cortical responses.
Withdrawal of life-sustaining therapies due to perceived poor neurologic prognosis is the main determinant of mortality in initially unresponsive resuscitated patients. None of the traditional predictors has maintained a positive predictive value (PPV) of 100% for poor outcome prediction, and all are subject to the effect of confounders and the self-fulfilling prophecy bias [5]; thus, using tests with high specificity and adopting a multimodal strategy is crucial. The authors suggest that prolonged unresponsiveness and the presence of “frequent epileptiform discharges” were negative predictors in this case. Prolonged unresponsiveness has never carried a high PPV for predicting poor outcome, and delayed awakening is increasingly being reported, particularly in the setting of prolonged use of sedatives. Similarly, the occurrence of “frequent epileptiform discharges” is not specific for non-awakening (and neither are more malignant EEG patterns), but their absence has been associated with good outcomes [6]. Whenever the prognosis is uncertain, or when different prognostic modalities point towards conflicting outcomes, it is prudent to allow more time before definite neuroprognostication is made.
There is no “Holy Grail” in neuroprognostication for acute brain injuries. Adopting a multimodal approach is a practical strategy to improve prognostic accuracy; however, it is imperative to choose the most specific parameters with time windows of higher yields, as well as having meticulous technique so that the tools used can be trusted. This attention to detail, both
3
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technically and regarding confounders, is particularly important when publishing “exceptions” in peer-reviewed literature.
REFERENCES
1. Weinstein J, Mallela AN, Abella BS, Levine JM, Balu R. Excellent neurologic recovery after prolonged coma in a cardiac arrest patient with multiple poor prognostic indicators. Resuscitation. 2017. doi:10.1016/j.resuscitation.2017.01.022. 2. Chatrian GE, Bergamasco B, Bricolo A, Frost JD, Jr., Prior PF. IFCN recommended standards for electrophysiologic monitoring in comatose and other unresponsive states. Report of an IFCN committee. Electroencephalogr Clin Neurophysiol. 1996;99(2):103-22. 3. - ACNS. Guideline 9D: Guidelines on short-latency somatosensory evoked potentials. J Clin Neurophysiol. 2006;23(2):168-79. 4. Taccone FS, Baar I, De Deyne C, Druwe P, Legros B, Meyfroidt G et al. Neuroprognostication after adult cardiac arrest treated with targeted temperature management: task force for Belgian recommendations. Acta neurologica Belgica. 2017. doi:10.1007/s13760-017-0755-1. 5. Dragancea I, Horn J, Kuiper M, Friberg H, Ullen S, Wetterslev J et al. Neurological prognostication after cardiac arrest and targeted temperature management 33 degrees C versus 36 degrees C: Results from a randomised controlled clinical trial. Resuscitation. 2015;93:164-70. doi:10.1016/j.resuscitation.2015.04.013. 6. Sivaraju A, Gilmore EJ, Wira CR, Stevens A, Rampal N, Moeller JJ et al. Prognostication of post-cardiac arrest coma: early clinical and electroencephalographic predictors of outcome. Intensive Care Med. 2015;41(7):1264-72. doi:10.1007/s00134-015-3834-x.
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Table 1 –Recommended standards for SSEP testing in comatose and other unresponsive states. Parameter
Minimal Requirement
Stimulus duration*
0.1 – 0.3 ms 3-5 Hz
Stimulus rate* Stimulus intensity*
Above motor threshold (2 – 3 times sensory threshold)
Analysis sweep time**
≥40 ms (50 ms advised)
Filter band pass*
30 – 3000 Hz
Notch filter*
off
Number of trials
500 – 1000 averaged responses In low noise recordings, two replications are adequate (>2 if higher noise)
Artifact level
< 0.25 µV
Electrical Impedance*
< 5000 Ω
Channels*
≥4
Measurements
Erb’s point channel – N9 peak latency Posterior spinal cervical channel – N13 peak latency Parietal contralateral channel – N20 and P14 peaks latency N20 – N13 inter-peak interval N20 amplitude
Adapted from [2-4]. ** – recommended analysis sweep time not followed in the case reported according to their display of peak latencies. * – parameters not specified in the case reported: technical aspects of the stimulus used, impedance, use of filters, and labels for the channels used. SSEP – somatosensory evoked potentials
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S0300-9572(17)30130-2 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.030 RESUS 7122
To appear in:
Resuscitation
Author: David M. Greer PII: DOI: Reference:
S0300-9572(17)30130-2 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.030 RESUS 7122
To appear in:
Resuscitation
Author: Rafeed Alkawadri PII: DOI: Reference:
S0300-9572(17)30130-2 http://dx.doi.org/doi:10.1016/j.resuscitation.2017.03.030 RESUS 7122
To appear in:
Resuscitation
Received date:
21-3-2017
Please cite this article as: Alkawadri Rafeed.Accurate Neuroprognostication in Cardiac Arrest Survivors: Details Matter!.Resuscitation http://dx.doi.org/10.1016/j.resuscitation.2017.03.030 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
1
Letter to the editor regarding: “Excellent neurologic recovery after prolonged coma in a cardiac arrest patient with multiple poor prognostic indicators” Accurate Neuroprognostication in Cardiac Arrest Survivors: Details Matter! Carolina B. Maciel, MD1; Lawrence J. Hirsch, MD1; David M. Greer, MD, MA2; and Rafeed Alkawadri, MD1,3 1
Division of Epilepsy and EEG, Critical Care EEG Monitoring Program, Department of Neurology, Yale School of Medicine, New Haven, CT, 06510 2
Division of Neurocritical Care and Emergency Neurology, Department of Neurology, Yale School of Medicine, New Haven, CT, 06510 3
The Human Brain Mapping Program, Department of Neurology, Yale School of Medicine 333 Cedar Street, New Haven, CT, 06510 Corresponding Author: Carolina Barbosa Maciel, MD ICU EEG fellow Yale School of Medicine P.O. Box 208018 New Haven, CT 06520 Tel: 917-355-2504 Fax: 203 – 785 - 2238 Email: [email protected]
Acknowledgments: Dr. Carolina B. Maciel reports no disclosures. Dr. Lawrence J. Hirsch reports no relevant disclosures. Dr. David M. Greer serves as Editor-in-Chief of Seminars in Neurology and has received compensation for medicallegal consultation. Dr. Rafeed Alkawadri reports no disclosures.
Funding: None Word Count/Number of Total Word Count: 659 Title (character count): 75 Text: 498 References: 5 Tables: 1
1
2
Dear Sir, We read with interest the report by Weinstein et al of a cardiac arrest survivor with an unexpected good outcome despite absent cortical potentials on somatosensory evoked potentials (SSEP) performed on post-cardiac arrest day 20 [1]. While we commend the authors for discussing the important effect of the self-fulfilling prophecy bias, and supporting the use of multiple modalities when predicting neurologic outcome, we would like to express our concerns about their report, in particular the reliability of their SSEP results.
Regarding the technical aspects of the SSEP testing, the following important aspects are not provided: the nerve stimulated (presumably median), the montage used, the stimulation intensity and how it was adjusted, the artifact rejection methods implemented, and the number of rejections in the cortical channels out of the 2000 responses. It is unusual to see such a discrepancy in signal-to-noise ratio between cortical and subcortical channels (seen in all channels bilaterally). Minimal requirements for median nerve SSEP recordings in unresponsive patients are summarized in Table 1 [2-4].
Accounting for confounders is one of the most significant challenges in neuroprognostication following cardiac arrest. Of these, the effect of body temperature and sedating medications are of significant importance. The authors mentioned that the patient received continuous infusions of midazolam and propofol targeting burst suppression for 48 hours; however, it remains unclear at what point this occurred and the timing of last administration of any sedatives relative to
2
3
neurologic examination and whether sedation boluses were administered at the time of recording, as those may result in transient attenuation of cortical responses.
Withdrawal of life-sustaining therapies due to perceived poor neurologic prognosis is the main determinant of mortality in initially unresponsive resuscitated patients. None of the traditional predictors has maintained a positive predictive value (PPV) of 100% for poor outcome prediction, and all are subject to the effect of confounders and the self-fulfilling prophecy bias [5]; thus, using tests with high specificity and adopting a multimodal strategy is crucial. The authors suggest that prolonged unresponsiveness and the presence of “frequent epileptiform discharges” were negative predictors in this case. Prolonged unresponsiveness has never carried a high PPV for predicting poor outcome, and delayed awakening is increasingly being reported, particularly in the setting of prolonged use of sedatives. Similarly, the occurrence of “frequent epileptiform discharges” is not specific for non-awakening (and neither are more malignant EEG patterns), but their absence has been associated with good outcomes [6]. Whenever the prognosis is uncertain, or when different prognostic modalities point towards conflicting outcomes, it is prudent to allow more time before definite neuroprognostication is made.
There is no “Holy Grail” in neuroprognostication for acute brain injuries. Adopting a multimodal approach is a practical strategy to improve prognostic accuracy; however, it is imperative to choose the most specific parameters with time windows of higher yields, as well as having meticulous technique so that the tools used can be trusted. This attention to detail, both
3
4
technically and regarding confounders, is particularly important when publishing “exceptions” in peer-reviewed literature.
REFERENCES
1. Weinstein J, Mallela AN, Abella BS, Levine JM, Balu R. Excellent neurologic recovery after prolonged coma in a cardiac arrest patient with multiple poor prognostic indicators. Resuscitation. 2017. doi:10.1016/j.resuscitation.2017.01.022. 2. Chatrian GE, Bergamasco B, Bricolo A, Frost JD, Jr., Prior PF. IFCN recommended standards for electrophysiologic monitoring in comatose and other unresponsive states. Report of an IFCN committee. Electroencephalogr Clin Neurophysiol. 1996;99(2):103-22. 3. - ACNS. Guideline 9D: Guidelines on short-latency somatosensory evoked potentials. J Clin Neurophysiol. 2006;23(2):168-79. 4. Taccone FS, Baar I, De Deyne C, Druwe P, Legros B, Meyfroidt G et al. Neuroprognostication after adult cardiac arrest treated with targeted temperature management: task force for Belgian recommendations. Acta neurologica Belgica. 2017. doi:10.1007/s13760-017-0755-1. 5. Dragancea I, Horn J, Kuiper M, Friberg H, Ullen S, Wetterslev J et al. Neurological prognostication after cardiac arrest and targeted temperature management 33 degrees C versus 36 degrees C: Results from a randomised controlled clinical trial. Resuscitation. 2015;93:164-70. doi:10.1016/j.resuscitation.2015.04.013. 6. Sivaraju A, Gilmore EJ, Wira CR, Stevens A, Rampal N, Moeller JJ et al. Prognostication of post-cardiac arrest coma: early clinical and electroencephalographic predictors of outcome. Intensive Care Med. 2015;41(7):1264-72. doi:10.1007/s00134-015-3834-x.
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Table 1 –Recommended standards for SSEP testing in comatose and other unresponsive states. Parameter
Minimal Requirement
Stimulus duration*
0.1 – 0.3 ms 3-5 Hz
Stimulus rate* Stimulus intensity*
Above motor threshold (2 – 3 times sensory threshold)
Analysis sweep time**
≥40 ms (50 ms advised)
Filter band pass*
30 – 3000 Hz
Notch filter*
off
Number of trials
500 – 1000 averaged responses In low noise recordings, two replications are adequate (>2 if higher noise)
Artifact level
< 0.25 µV
Electrical Impedance*
< 5000 Ω
Channels*
≥4
Measurements
Erb’s point channel – N9 peak latency Posterior spinal cervical channel – N13 peak latency Parietal contralateral channel – N20 and P14 peaks latency N20 – N13 inter-peak interval N20 amplitude
Adapted from [2-4]. ** – recommended analysis sweep time not followed in the case reported according to their display of peak latencies. * – parameters not specified in the case reported: technical aspects of the stimulus used, impedance, use of filters, and labels for the channels used. SSEP – somatosensory evoked potentials
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