Quantitative measures of EEG for prediction of outcome in cardiac arrest subjects treated with hypothermia: a literature review

Asgari, Shadnaz; Moshirvaziri, Hana; Scalzo, Fabien; Ramezan‐Arab, Nima

doi:10.1007/s10877-018-0118-3

Cited by 11 publications

(4 citation statements)

References 78 publications

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“…Otherwise, we only performed a visual analysis of the EEG background and nor quantitative analysis using machine learning. As visual EEG interpretation could be subjective and requires medical expertise, quantitative EEG analysis could be a promising alternative to visual analysis [29,30]. As our study was designed to evaluate the amplitudes SSEP prognostic value and not specifically the EEG performance, we only compared SSEP prognostic performance to markers of neuro-prognostication already use in the ERC/ESICM guidelines [2].…”

Section: Discussionmentioning

confidence: 99%

“…Lowering the N20-baseline 3). Regarding the second SSEP component i.e N20-P25, an amplitude > 3.2 µV predicted good outcome with a specificity of 93 [90-96]% and sensitivity of 29 [23][24][25][26][27][28][29][30][31][32][33][34]%, although a threshold of 4 µV increased specificity (sp = 95 [92-97] %) but decreased sensitivity (se = 14 [10-18]%) (Table 3). The combination of N20-baseline > 2 µV with a benign EEG presented a higher specificity (sp = 96.9 [95-99]%) with a similar sensitivity (se = 33.3 [28-39]%) although combination of N20-P25 with benign EEG was also highly specific (sp = 97 [93-98]%) but poorly sensitive (se = 17 [13-21]%).…”

Section: Prediction Of Good Outcomementioning

confidence: 99%

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SSEP N20 and P25 amplitudes predict poor and good neurologic outcomes after cardiac arrest

Benghanem

Nguyen

Gavaret

et al. 2022

Ann. Intensive Care

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Background To assess in comatose patients after cardiac arrest (CA) if amplitudes of two somatosensory evoked potentials (SSEP) responses, namely, N20-baseline (N20-b) and N20–P25, are predictive of neurological outcome. Methods Monocentric prospective study in a tertiary cardiac center between Nov 2019 and July-2021. All patients comatose at 72 h after CA with at least one SSEP recorded were included. The N20-b and N20–P25 amplitudes were automatically measured in microvolts (µV), along with other recommended prognostic markers (status myoclonus, neuron-specific enolase levels at 2 and 3 days, and EEG pattern). We assessed the predictive value of SSEP for neurologic outcome using the best Cerebral Performance Categories (CPC1 or 2 as good outcome) at 3 months (main endpoint) and 6 months (secondary endpoint). Specificity and sensitivity of different thresholds of SSEP amplitudes, alone or in combination with other prognostic markers, were calculated. Results Among 82 patients, a poor outcome (CPC 3–5) was observed in 78% of patients at 3 months. The median time to SSEP recording was 3(2–4) days after CA, with a pattern “bilaterally absent” in 19 patients, “unilaterally present” in 4, and “bilaterally present” in 59 patients. The median N20-b amplitudes were different between patients with poor and good outcomes, i.e., 0.93 [0–2.05]µV vs. 1.56 [1.24–2.75]µV, respectively (p < 0.0001), as the median N20–P25 amplitudes (0.57 [0–1.43]µV in poor outcome vs. 2.64 [1.39–3.80]µV in good outcome patients p < 0.0001). An N20-b > 2 µV predicted good outcome with a specificity of 73% and a moderate sensitivity of 39%, although an N20–P25 > 3.2 µV was 93% specific and only 30% sensitive. A low voltage N20-b < 0.88 µV and N20–P25 < 1 µV predicted poor outcome with a high specificity (sp = 94% and 93%, respectively) and a moderate sensitivity (se = 50% and 66%). Association of “bilaterally absent or low voltage SSEP” patterns increased the sensitivity significantly as compared to “bilaterally absent” SSEP alone (se = 58 vs. 30%, p = 0.002) for prediction of poor outcome. Conclusion In comatose patient after CA, both N20-b and N20–P25 amplitudes could predict both good and poor outcomes with high specificity but low to moderate sensitivity. Our results suggest that caution is needed regarding SSEP amplitudes in clinical routine, and that these indicators should be used in a multimodal approach for prognostication after cardiac arrest.

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Section: Discussionmentioning

confidence: 99%

Section: Prediction Of Good Outcomementioning

confidence: 99%

SSEP N20 and P25 amplitudes predict poor and good neurologic outcomes after cardiac arrest

Benghanem

Nguyen

Gavaret

et al. 2022

Ann. Intensive Care

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“…Considering that visual analysis remains subjective, quantitative analyses of the EEG signals (qEEG) using machine learning have been recently developed [89]. These qEEG modalities may be broadly categorized into spectral and connectivity analyses [90].…”

Section: Eeg Quantitative Analysesmentioning

confidence: 99%

Prognostication after cardiac arrest: how EEG and evoked potentials may improve the challenge

Benghanem

Pruvost-Robieux

Bouchereau

et al. 2022

Ann. Intensive Care

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About 80% of patients resuscitated from CA are comatose at ICU admission and nearly 50% of survivors are still unawake at 72 h. Predicting neurological outcome of these patients is important to provide correct information to patient’s relatives, avoid disproportionate care in patients with irreversible hypoxic–ischemic brain injury (HIBI) and inappropriate withdrawal of care in patients with a possible favorable neurological recovery. ERC/ESICM 2021 algorithm allows a classification as “poor outcome likely” in 32%, the outcome remaining “indeterminate” in 68%. The crucial question is to know how we could improve the assessment of both unfavorable but also favorable outcome prediction. Neurophysiological tests, i.e., electroencephalography (EEG) and evoked-potentials (EPs) are a non-invasive bedside investigations. The EEG is the record of brain electrical fields, characterized by a high temporal resolution but a low spatial resolution. EEG is largely available, and represented the most widely tool use in recent survey examining current neuro-prognostication practices. The severity of HIBI is correlated with the predominant frequency and background continuity of EEG leading to “highly malignant” patterns as suppression or burst suppression in the most severe HIBI. EPs differ from EEG signals as they are stimulus induced and represent the summated activities of large populations of neurons firing in synchrony, requiring the average of numerous stimulations. Different EPs (i.e., somato sensory EPs (SSEPs), brainstem auditory EPs (BAEPs), middle latency auditory EPs (MLAEPs) and long latency event-related potentials (ERPs) with mismatch negativity (MMN) and P300 responses) can be assessed in ICU, with different brain generators and prognostic values. In the present review, we summarize EEG and EPs signal generators, recording modalities, interpretation and prognostic values of these different neurophysiological tools. Finally, we assess the perspective for futures neurophysiological investigations, aiming to reduce prognostic uncertainty in comatose and disorders of consciousness (DoC) patients after CA.

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“…Finally, the spectrogram is obtained. Studies have shown that QEEG has achieved good results in the evaluation of neurocognitive function in patients with Parkinson's and Alzheimer's [ 7 ]. Montreal cognitive assessment (MoCA) is a cognitive assessment tool widely used in clinical practice worldwide.…”

Section: Introductionmentioning

confidence: 99%

Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination

Li¹,

Li²,

Ma³

et al. 2021

Contrast Media & Molecular Imaging

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This paper aimed to explore the clinical value of combined adoption of magnetic resonance diffusion tensor imaging (DTI) and quantitative electroencephalogram (QEEG) in assessing microstructure changes and mild neurocognitive dysfunction in patients with white matter demyelination. 128 cases of white matter demyelination admitted to the hospital from October 2018 to October 2019 were rolled into the research group, and 100 healthy patients physically examined during the same period were rolled into the control (ctrl) group. QEEG and magnetic resonance DTI examinations were performed for all patients. The wave power of δ, θ, α, and β and the ratio of α/θ and (δ + θ)/(α + β) were recorded. The FA values of white matter fibers in different brain areas were measured, and the Montreal Cognitive Assessment (MoCA) and Addenbrooke Cognitive Evaluation rating (ACE-R) were adopted to assess the neurocognitive function of patients. It was found that the dominant frequency of each brain area in the research group was 8-9 Hz slow α wave. In contrast with the ctrl, the α wave and α/θ values in the research group were lower, while θ wave and δ + θ/α + β values were higher ( P < 0.05 ); the scores of ACE-R and MoCA were lower ( P < 0.01 ); the fractional anisotropy (FA) values of the right frontal lobe white matter (0.335 ± 0.068), the left temporal lobe white matter (0.391 ± 0.032), and the corpus callosum knee white matter (0.658 ± 0.053) were lower ( P < 0.05 ). The FA values of these three areas were positively correlated with attention and calculation, memory, and memory of MoCA scale, respectively ( P < 0.05 ). The FA value of the right frontal white matter was positively correlated with the attention and calculation score of the ACE-R scale ( P < 0.05 ). In conclusion, magnetic resonance DTI combined with QEEG could reflect the microstructural changes of white matter, which may be associated with mild neurocognitive impairment. The primary objective of the study was to explore the clinical value of combined adoption of magnetic resonance DTI and QEEG in assessing microstructure changes and mild neurocognitive dysfunction in patients with white matter demyelination, expected to provide a theoretical basis for the treatment of white matter demyelination.

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Quantitative measures of EEG for prediction of outcome in cardiac arrest subjects treated with hypothermia: a literature review

Cited by 11 publications

References 78 publications

SSEP N20 and P25 amplitudes predict poor and good neurologic outcomes after cardiac arrest

SSEP N20 and P25 amplitudes predict poor and good neurologic outcomes after cardiac arrest

Prognostication after cardiac arrest: how EEG and evoked potentials may improve the challenge

Value of Magnetic Resonance Diffusion Tensor Imaging Combined with Quantitative Electroencephalogram in Diagnosis of Neurocognitive Impairment in Patients with White Matter Demyelination

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