Benign EEG for prognostication of favorable outcome after cardiac arrest: A reappraisal. (January 2023)

• Record Type: Journal Article
• Authors: Fenter, Hélène; Ben-Hamouda, Nawfel; Novy, Jan; Rossetti, Andrea O.
• Is Part Of: Resuscitation. Volume 182(2023)
• Publication Date: 2023-01
• Subjects: Prognosis -- Anoxic-ischemic encephalopathy -- Background -- Amplitude -- Electroencephalogram -- Cardiac arrest; ACNS American Clinical Neurophysiology Society -- CA Cardiac Arrest -- CHUV Centre Hospitalier Universitaire Vaudois -- CPC Cerebral Performance Category -- EEG Electroencephalogram -- cEEG continuous Electroencephalogram -- FOUR Full Outline of UnResponsiveness -- ICU Intensive Care Unit -- NSE Neuron-Specific Enolase -- PPV Positive Predictive Value -- ROC Receiver Operating Characteristic -- ROSC Return of Spontaneous Circulations -- SIRPID Stimulus Induced Rhythmic, Periodic or Ictal Discharges -- SSEP Somatosensory Evoked Potentials; Resuscitation -- Periodicals; Resuscitation -- Periodicals; Réanimation -- Périodiques; Electronic journals; 616.025
• DOI: 10.1016/j.resuscitation.2022.11.003
• Languages: English
• ISSNs: 0300-9572

Abstract

Abstract: Aim: The current EEG role for prognostication after cardiac arrest (CA) essentially aims at reliably identifying patients with poor prognosis ("highly malignant" patterns, defined by Westhall et al. in 2014). Conversely, "benign EEGs", defined by the absence of elements of "highly malignant" and "malignant" categories, has limited sensitivity in detecting good prognosis. We postulate that a less stringent "benign EEG" definition would improve sensitivity to detect patients with favorable outcomes. Methods: Retrospectively assessing our registry of unconscious adults after CA (1.2018–8.2021), we scored EEGs within 72 h after CA using a modified "benign EEG" classification (allowing discontinuity, low-voltage, or reversed anterio-posterior amplitude development), versus Westhall's "benign EEG" classification (not allowing the former items). We compared predictive performances towards good outcome (Cerebral Performance Category 1–2 at 3 months), using 2x2 tables (and binomial 95% confidence intervals) and proportions comparisons. Results: Among 381 patients (mean age 61.9 ± 15.4 years, 104 (27.2%) females, 240 (62.9%) having cardiac origin), the modified "benign EEG" definition identified a higher number of patients with potential good outcome (252, 66%, vs 163, 43%). Sensitivity of the modified EEG definition was 0.97 (95% CI: 0.92–0.97) vs 0.71 (95% CI: 0.62–0.78) (p < 0.001). Positive predictive values (PPV) were 0.53 (95% CI: 0.46–0.59) versus 0.59 (95% CI: 0.51–0.67; p = 0.17). Similar statistics were observed at definite recording times, and for survivors. Discussion: The modified "benign EEG" classification demonstrated a markedly higher sensitivity towards favorable outcome, with minor impact on PPV. Adaptation of "benign EEG" criteria may improve efficient identification of patients who may reach a good outcome.