Heart Rate Variability Analysis in Patients Who Have Bradycardia Presenting to the Emergency Department with Chest Pain.

BACKGROUND: Heart rate variability (HRV) is a noninvasive method to measure the function of the autonomic nervous system. It has been used to risk stratify patients with undifferentiated chest pain in the emergency department (ED). However, bradycardia can have a modifying effect on HRV. OBJECTIVE: In this study, we aimed to determine how bradycardia affected HRV analysis in patients who presented with chest pain to the ED. METHODS: Adult patients presenting to the ED at Singapore General Hospital with chest pain were included in the study. Patients with non-sinus rhythm on electrocardiogram (ECG) were excluded. HRV parameters, including time domain, frequency domain, and nonlinear variables, were analyzed from a 5-min ECG segment. Occurrence of a major adverse cardiac event ([MACE], e.g., acute myocardial infarction, percutaneous coronary intervention, coronary artery bypass graft, or mortality) within 30 days of presentation to the ED was also recorded. RESULTS: A total of 797 patients were included for analysis with 248 patients (31.1%) with 30-day MACE and 135 patients with bradycardia (16.9%). Compared to non-bradycardic patients, bradycardic patients had significant differences in all HRV parameters suggesting an increased parasympathetic component. Among non-bradycardic patients, comparing those who did and did not have 30-day MACE, there were significant differences predominantly in time domain variables, suggesting decreased HRV. In bradycardic patients, the same analysis revealed significant differences in predominantly frequency-domain variables suggesting decreased parasympathetic input. CONCLUSIONS: Chest pain patients with bradycardia have increased HRV compared to those without bradycardia. This may have important implications on HRV modeling strategies for risk stratification of bradycardic and non-bradycardic chest pain patients.

Integrating heart rate variability, vital signs, electrocardiogram, and troponin to triage chest pain patients in the ED.

BACKGROUND: Current triage methods for chest pain patients typically utilize symptoms, electrocardiogram (ECG), and vital sign data, requiring interpretation by dedicated triage clinicians. In contrast, we aimed to create a quickly obtainable model integrating the objective parameters of heart rate variability (HRV), troponin, ECG, and vital signs to improve accuracy and efficiency of triage for chest pain patients in the emergency department (ED). METHODS: Adult patients presenting to the ED with chest pain from September 2010 to July 2015 were conveniently recruited. The primary outcome was a composite of revascularization, death, cardiac arrest, cardiogenic shock, or lethal arrhythmia within 72-h of presentation to the ED. To create the chest pain triage (CPT) model, logistic regression was done where potential covariates comprised of vital signs, ECG parameters, troponin, and HRV measures. Current triage methods at our institution and modified early warning score (MEWS) were used as comparators. RESULTS: A total of 797 patients were included for final analysis of which 146 patients (18.3%) met the primary outcome. Patients were an average age of 60years old, 68% male, and 56% triaged to the most acute category. The model consisted of five parameters: pain score, ST-elevation, ST-depression, detrended fluctuation analysis (DFA) α1, and troponin. CPT model>0.09, CPT model>0.15, current triage methods, and MEWS≥2 had sensitivities of 86%, 74%, 75%, and 23%, respectively, and specificities of 45%, 71%, 48%, and 78%, respectively. CONCLUSION: The CPT model may improve current clinical triage protocols for chest pain patients in the ED.

Comparing HEART, TIMI, and GRACE scores for prediction of 30-day major adverse cardiac events in high acuity chest pain patients in the emergency department.

BACKGROUND: The HEART, TIMI, and GRACE scores have been applied in the Emergency Department (ED) to risk stratify patients with undifferentiated chest pain. This study aims to compare the accuracy of HEART, TIMI, and GRACE for the prediction of major adverse cardiac events (MACE) in high acuity chest pain patients. METHODS: Adult patients who presented with chest pain suggestive of cardiac origin in the most acute triage category at an academic ED from September 2010 to October 2015 were included. The HEART, TIMI, and GRACE scores were calculated retrospectively from prospectively collected data. The primary outcome was occurrence of MACE (mortality, AMI, PCI, CABG) within 30-days of initial presentation. RESULTS: 604 patients were included in the study. Patient demographics include an average age of 61years, 69% male, and 48% with history of ischemic heart disease. 36% of patients met the primary outcome. The c-statistics of HEART, TIMI, and GRACE were 0.78 (95% CI: 0.74-0.81), 0.65 (95% CI: 0.60-0.69), and 0.62 (95% CI: 0.58-0.67), respectively. For the purpose of accurately ruling out patients for 30-day MACE, a HEART score of ≤3 had a sensitivity and NPV of 99% and 98%, respectively, compared to 97% and 91%, respectively, for TIMI=0, and 94% and 85%, respectively, for GRACE ≤75. The percent of patients with 30-day MACE with HEART scores between 0 and 3, 4-6, and 7-10 was 2%, 28%, and 63%, respectively. CONCLUSION: In high acuity chest pain patients, the HEART score is superior to the TIMI and GRACE scores in predicting 30-day MACE.

A novel cardiovascular risk stratification model incorporating ECG and heart rate variability for patients presenting to the emergency department with chest pain.

BACKGROUND: Risk stratification models can be employed at the emergency department (ED) to evaluate patient prognosis and guide choice of treatment. We derived and validated a new cardiovascular risk stratification model comprising vital signs, heart rate variability (HRV) parameters, and demographic and electrocardiogram (ECG) variables. METHODS: We conducted a single-center, observational cohort study of patients presenting to the ED with chest pain. All patients above 21 years of age and in sinus rhythm were eligible. ECGs were collected and evaluated for 12-lead ECG abnormalities. Routine monitoring ECG data were processed to obtain HRV parameters. Vital signs and demographic data were obtained from electronic medical records. Thirty-day major adverse cardiac events (MACE) were the primary endpoint, including death, acute myocardial infarction, and revascularization. Candidate variables were identified using univariate analysis; the model for the final risk score was derived by multivariable logistic regression. We compared the performance of the new model with that of the thrombolysis in myocardial infarct (TIMI) score using receiver operating characteristic (ROC) analysis. RESULTS: In total, 763 patients were included in this study; 254 (33 %) met the primary endpoint, the mean age was 60 (σ = 13) years, and the majority was male (65 %). Nineteen candidate predictors were entered into the multivariable model for backward variable elimination. The final model contained 10 clinical variables, including age, gender, heart rate, three HRV parameters (average R-to-R interval (RR), triangular interpolation of normal-to-normal (NN) intervals, and high-frequency power), and four 12-lead ECG variables (ST elevation, ST depression, Q wave, and QT prolongation). Our proposed model outperformed the TIMI score for prediction of MACE (area under the ROC curve 0.780 versus 0.653). At the cutoff score of 9 (range 0-37), our model had sensitivity of 0.709 (95 % CI 0.653, 0.765), specificity of 0.674 (95 % CI 0.633, 0.715), positive predictive value of 0.520 (95 % CI 0.468, 0.573), and negative predictive value of 0.823 (95 % CI 0.786, 0.859). CONCLUSIONS: A non-invasive and objective ECG- and HRV-based risk stratification tool performed well against the TIMI score, but future research warrants use of an external validation cohort.