Ventricular fibrillation waveform characteristics of the surface ECG: Impact of the left ventricular diameter and mass.

BACKGROUND: Despite a promising association between VF waveform characteristics and prognosis after resuscitation, studies with VF-guided treatment have so far not improved outcomes. While driven by the idea that the VF waveform reflects arrest duration, increasing evidence suggests that pre-existent disease-related changes of the myocardium affect ECG-characteristics of VF as well. In this context, we studied the impact of the left ventricular (LV) diameter and mass. METHODS: Cohort of 193 ICD-patients with defibrillation testing at the Radboudumc (2010-2014). Surface ECG-recordings (leads I,II,aVF,V1,V3,V6) were analysed to study amplitude and frequency characteristics of the induced VF. Both for LV diameter and mass, patients were categorised in two groups, using echocardiographic data (ASE-guidelines). RESULTS: In all ECG-leads, dominant and median frequencies were significantly lower in patients with (n=40) than in patients without (n=151) an increased LV diameter. The mean amplitude and amplitude spectrum area (AMSA) did not differ. In contrast, we observed no differences in frequency characteristics in relation to the LV mass, whereas mean amplitude (I,aVF,V3) and AMSA (I,V3) were significantly higher in patients with (n=57) than in patients without (n=120) an increased LV mass. CONCLUSIONS: Frequency characteristics of VF were consistently lower in case of an increased LV diameter. Whereas LV mass does not affect the frequency of the VF waveform, amplitudes seem higher with increasing mass. These findings add to the current knowledge of factors that modulate VF characteristics of the surface ECG and provide insight into factors which may be accounted for in future studies on VF-guided resuscitative interventions.

Ventricular fibrillation waveform characteristics differ according to the presence of a previous myocardial infarction: A surface ECG study in ICD-patients.

BACKGROUND: Characteristics of the ventricular fibrillation (VF) waveform reflect arrest duration and have been incorporated in studies on algorithms to guide resuscitative interventions. Findings in animals indicate that VF characteristics are also affected by the presence of a previous myocardial infarction (MI). As studies in humans are scarce, we assessed the impact of a previous MI on VF characteristics in ICD-patients. METHODS: Prospective cohort of ICD-patients (n=190) with defibrillation testing at the Radboudumc (2010-2013). VF characteristics of the 12-lead surface ECG were compared between three groups: patients without a history of MI (n=88), with a previous anterior (n=47) and a previous inferior MI (n=55). RESULTS: As compared to each of the other groups, the mean amplitude and amplitude spectrum area were lower, for an anterior MI in lead V3 and for an inferior MI in leads II and aVF. Across the three groups, the bandwidth was broader in the leads corresponding with the infarct localisation. In contrast, the dominant and median frequencies only differed between previous anterior MI and no history of MI, being lower in the former. CONCLUSIONS: The VF waveform is affected by the presence of a previous MI. Amplitude-related measures were lower and VF was less organised in the ECG-lead(s) adjacent to the area of infarction. Although VF characteristics of the surface ECG have so far primarily been considered a proxy for arrest duration and metabolic state, our findings question this paradigm and may provide additional insights into the future potential of VF-guided resuscitative interventions.

A Cerebral Recovery Index (CRI) for early prognosis in patients after cardiac arrest.

INTRODUCTION: Electroencephalogram (EEG) monitoring in patients treated with therapeutic hypothermia after cardiac arrest may assist in early outcome prediction. Quantitative EEG (qEEG) analysis can reduce the time needed to review long-term EEG and makes the analysis more objective. In this study, we evaluated the predictive value of qEEG analysis for neurologic outcome in postanoxic patients. METHODS: In total, 109 patients admitted to the ICU for therapeutic hypothermia after cardiac arrest were included, divided over a training and a test set. Continuous EEG was recorded during the first 5 days or until ICU discharge. Neurologic outcomes were based on the best achieved Cerebral Performance Category (CPC) score within 6 months. Of the training set, 27 of 56 patients (48%) and 26 of 53 patients (49%) of the test set achieved good outcome (CPC 1 to 2). In all patients, a 5 minute epoch was selected each hour, and five qEEG features were extracted. We introduced the Cerebral Recovery Index (CRI), which combines these features into a single number. RESULTS: At 24 hours after cardiac arrest, a CRI <0.29 was always associated with poor neurologic outcome, with a sensitivity of 0.55 (95% confidence interval (CI): 0.32 to 0.76) at a specificity of 1.00 (CI, 0.86 to 1.00) in the test set. This results in a positive predictive value (PPV) of 1.00 (CI, 0.73 to 1.00) and a negative predictive value (NPV) of 0.71 (CI, 0.53 to 0.85). At the same time, a CRI >0.69 predicted good outcome, with a sensitivity of 0.25 (CI, 0.10 to 0.14) at a specificity of 1.00 (CI, 0.85 to 1.00) in the test set, and a corresponding NPV of 1.00 (CI, 0.54 to 1.00) and a PPV of 0.55 (CI, 0.38 to 0.70). CONCLUSIONS: We introduced a combination of qEEG measures expressed in a single number, the CRI, which can assist in prediction of both poor and good outcomes in postanoxic patients, within 24 hours after cardiac arrest.