Markov model for detection of ECG instability prior to cardiac arrest in single-ventricle patients.

OBJECTIVES: Assess the degree of instability in the electrocardiogram (ECG) waveform in patients with single-ventricle physiology before a cardiac arrest and compare them with similar patients who did not experience a cardiac arrest. METHODS: Retrospective control study in patients with single-ventricle physiology who underwent Norwood, Blalock-Taussig shunt, pulmonary artery band, and aortic arch repair from 2013 to 2018. Electronic medical records were obtained for all included patients. For each subject, 6 h of ECG data were analyzed. In the arrest group, the end of the sixth hour coincides with the cardiac arrest. In the control group, the 6-h windows were randomly selected. We used a Markov chain framework and the likelihood ratio test to measure the degree of ECG instability and to classify the arrest and control groups. RESULTS: The study dataset consists of 38 cardiac arrest events and 67 control events. Our Markov model was able to classify the arrest and control groups based on the ECG instability with an ROC AUC of 82% at the hour preceding the cardiac arrests. CONCLUSION: We designed a method using the Markov chain framework to measure the level of instability in the beat-to-beat ECG morphology. Furthermore, we were able to show that the Markov model performed well to distinguish patients in the arrest group compared to the control group.

Quantification of electrocardiogram instability prior to cardiac arrest in patients with single-ventricle physiology.

OBJECTIVE: To quantify the instability measured in the electrocardiogram (ECG) waveform in patients with single-ventricle physiology before a cardiac arrest and compare with similar patients who did not have a cardiac arrest. METHODS: We measure the instability in the ECG morphology using variance, entropy, and decorrelation of polynomial fit coefficients of the beat-to-beat segmented data. These three metrics quantify the spread of the ECG morphology, the lack of beat-to-beat periodicity and the lack of predictability, respectively. For each subject, 3 h of ECG data were analyzed. In the arrest group, the end of the third hour coincides with the cardiac arrest. In the control group, the 3-h windows were randomly selected. RESULTS: The study dataset consists of 38 cardiac arrest events and 67 control events. In the hour prior to the cardiac arrest, the variance, entropy, and decorrelation of the polynomial fit coefficients were higher in the arrest group than in the control group (p = 0.003, p = 0.009, and p = 0.035, respectively). For the second and third hours prior to the arrests, the differences in variance, entropy, and decorrelation between the arrest and control groups lost statistical significance. Using these metrics of instability as predictive features in a support vector machine algorithm, we found an area under the receiver operating characteristic curve of 0.8 to distinguish the arrest event from the control events. CONCLUSION: By taking a holistic assessment of the ECG waveform in patients with single-ventricle physiology to measure the instability in its beat-to-beat morphology, the ECG waveform variance, entropy, and decorrelation are found to be statistically different in the patients who arrested compared with patients in the control group.

RBC Transfusion Induced ST Segment Variability Following the Norwood Procedure.

The transfusion of stored RBCs decreases nitric oxide bioavailability, which may have an adverse effect on vascular function. We assessed the effects of RBC transfusion on coronary vascular function by evaluating the relationship between myocardial oxygen delivery and demand as evidenced by ST segment variability. DESIGN: Retrospective case-control study. SETTING: Nine-hundred seventy-three-bed pediatric hospital with a 54-bed cardiovascular ICU. PATIENTS: Seventy-three neonates with hypoplastic left heart syndrome following the Norwood procedure, 38 with a Blalock-Taussig shunt and 35 with a right ventricle to pulmonary artery shunt. INTERVENTIONS: RBC transfusion. MATERIALS AND MAIN RESULTS: High-frequency physiologic data were captured 30 minutes prior to the initiation of (baseline) and during the 120 minutes of the transfusion. A rate pressure product was calculated for each subject and used as an indicator of myocardial oxygen demand. Electrocardiogram leads (aVL, V1, II) were used to construct a 3D ST segment vector to assess ST segment variability and functioned as a surrogate indicator of myocardial ischemia. One-hundred thirty-eight transfusions occurred in the Blalock-Taussig shunt group and 139 in the right ventricle to pulmonary artery shunt group. There was no significant change in the rate pressure product for either group; however, ST segment variability progressively increased for the entire cohort during the transfusion, becoming statistically significant by the end of the transfusion. Upon subgroup analysis, this finding was noted with statistical significance in the Blalock-Taussig shunt group and trending toward significance in the right ventricle to pulmonary artery shunt group. CONCLUSIONS: We found a significant increase in the ST segment variability and evidence of myocardial ischemia temporally associated with RBC transfusions in neonates following the Norwood procedure, specifically among those in the Blalock-Taussig shunt group, which may impact immediate and long-term outcomes.