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Author Spotlight: A Unique Mouse Model of Asphyxia-Induced Cardiac Arrest
Published on: April 14, 2023
Prognostication of neurological outcome after cardiac arrest using wavelet phase coherence analysis of cerebral
Tae Jung Kim1, Jae-Myoung Kim2, Ji Sung Lee3
1Department of Neurology, Seoul National University Hospital, Seoul, Republic of Korea; Department of Critical Care Medicine, Seoul National University Hospital, Seoul, Republic of Korea.
Insights
Predicting cardiac arrest outcomes is possible by analyzing cerebral oxyhemoglobin (HbO2) coherence. This method, using HbO2 phase coherence and neuron-specific enolase (NSE), aids in prognostication after cardiac arrest.
Area of Science:
- Neuroscience
- Cardiology
- Biomedical Engineering
Background:
- Prognosis after cardiac arrest (CA) is linked to cerebral ischemia severity.
- Investigating cerebral oxyhemoglobin (HbO2) coherence can predict CA outcomes.
- Developing novel prognostication methods for CA is crucial.
Purpose of the Study:
- To explore the relationship between wavelet coherence of cerebral HbO2 and patient outcomes post-CA.
- To develop a predictive model for CA prognosis using HbO2 coherence.
Main Methods:
- Functional near-infrared spectroscopy (fNIRS) measured HbO2 in 83 post-resuscitation patients.
- Analyzed prefrontal HbO2 oscillations coherence across five frequency intervals.
- Assessed outcomes using Cerebral Performance Category (CPC) scores at 3 months post-CA.
Main Results:
- Lower phase coherence in myogenic interval III was observed in the poor outcome group (CPC ≥ 3).
- A predictive model combining neuron-specific enolase (NSE) and interval III coherence showed high discrimination (AUC 0.919).
Conclusions:
- NSE combined with HbO2 phase coherence in interval III shows promise for CA prognostication.
- Cerebral ischemia evaluation via HbO2 phase coherence may serve as a valuable outcome predictor post-CA.
Background:
The prognosis for cardiac arrest (CA) is associated with the degree of cerebral ischemia. We investigated the relationship between the wavelet coherence of cerebral oxyhemoglobin (HbO2) among different channels and outcomes after CA. Moreover, we aimed to develop a prognostication method after CA.
Methods:
Eighty-three post-resuscitation patients were included. The HbO2 data were collected during the post-resuscitation period (median day, 1) using functional near-infrared spectroscopy. The coherence between sections of prefrontal HbO2 oscillations in five frequency intervals (I, 0.6-2 Hz; II, 0.15-0.6 Hz; III, 0.05-0.15 Hz; IV, 0.02-0.05 Hz; and V, 0.0095-0.02 Hz) were analyzed. We evaluated the outcomes using cerebral performance category (CPC) scores (good outcome, CPC ≤ 2 and poor outcome, CPC ≥ 3) at 3 months after CA. Additionally, the predictive method was developed using the biomarker and coherence value after CA.
Results:
Among the included patients, 19 patients (22.9%) had a good outcome. Poor outcome group had significantly lower phase coherence in the myogenic frequency interval III compared to good outcome group (0.36 ± 0.14 vs. 0.54 ± 0.18, P < 0.001). The predictive method using neuron-specific enolase (NSE) and interval III value demonstrated good discrimination (area under the curve 0.919; 95% confidence interval, 0.850-0.989).
Conclusions:
The predictive method using NSE and phase coherence of HbO2 in the interval III from the vascular smooth muscle cells could be a useful tool for prognosticating after CA. This suggests that evaluating cerebral ischemia using phase coherence of HbO2 might be a helpful outcome predictor following CA.
