Dataset Information

Simultaneous Heart Rate Variability and Electroencephalographic Monitoring in Children in the Emergency Department.

ABSTRACT: Changes in heart rate variability (HRV) and electroencephalographic (EEG) background are promising tools for risk stratification and outcome prediction in children seen in the Emergency Department (ED). Novel monitoring technologies offer an opportunity for determining the clinical value of these physiologic variables, however, studies evaluating these measurements obtained in the Pediatric ED are sparse. The current study used a single center, prospective, observational cohort study of HRV and EEG as early predictors of outcome in children with acute trauma. ECG and HRV data were successfully collected in 167 subjects and simultaneous collection of ECG and EEG data using a wireless monitoring device was piloted in 17 patients with 15 patients having EEG data rated as appropriate for clinical interpretation. The mean time from ED arrival to ECG and EEG recording start was 7.5 (SD 11.6) and 34.5 (SD 15.5) minutes, respectively. The mean time required for EEG electrode placement was 9.3 min (SD 5.8 min). Results showed recording early HRV and EEG is feasible in children with acute injury seen in the ED. This study suggests that high consent rates are possible with the adequate research infrastructure and physiologic variables may offer an early, non-invasive marker for injury stratification and prognosis in children.

SUBMITTER: Piantino JA

PROVIDER: S-EPMC8099962 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature

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Simultaneous Heart Rate Variability and Electroencephalographic Monitoring in Children in the Emergency Department.

Piantino Juan A JA Lin Amber A Luther Madison M Centeno Luis D LD Williams Cydni N CN Newgard Craig D CD

Journal of child & adolescent trauma 20200610 2

Changes in heart rate variability (HRV) and electroencephalographic (EEG) background are promising tools for risk stratification and outcome prediction in children seen in the Emergency Department (ED). Novel monitoring technologies offer an opportunity for determining the clinical value of these physiologic variables, however, studies evaluating these measurements obtained in the Pediatric ED are sparse. The current study used a single center, prospective, observational cohort study of HRV and ...[more]

PMID: 33986903

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Project description:ObjectivesHeart rate variability is controlled by the autonomic nervous system. After brain death, this autonomic control stops, and heart rate variability is significantly decreased. However, it is unknown if early changes in heart rate variability are predictive of progression to brain death. We hypothesized that in brain-injured children, lower heart rate variability is an early indicator of autonomic system failure, and it predicts progression to brain death. We additionally explored the association between heart rate variability and markers of brain dysfunction such as electroencephalogram and neurologic examination between brain-injured children who progressed to brain death and those who survived.DesignRetrospective case-control study.SettingPICU, single institution.PatientsChildren up to 18 years with a Glasgow Coma Scale score of less than 8 admitted between August of 2016 and December of 2017, who had electrocardiographic data available for heart rate variability analysis, were included.Exclusion criteriapatients who died of causes other than brain death. Twenty-three patients met inclusion criteria: six progressed to brain death (cases), and 17 survived (controls). Five-minute electrocardiogram segments were used to estimate heart rate variability in the time domain (SD of normal-normal intervals, root mean square successive differences), frequency domain (low frequency, high frequency, low frequency/high frequency ratio), Poincaré plots, and approximate entropy.InterventionsNone.Measurements and main resultsPatients who progressed to brain death exhibited significantly lower heart rate variability in the time domain, frequency domain, and Poincaré plots (p < 0.01). The odds of death increased with decreasing low frequency (odds ratio, 4.0; 95% CI, 1.2-13.6) and high frequency (odds ratio, 2.5; 95% CI, 1.2-5.4) heart rate variability power (p < 0.03). Heart rate variability was significantly lower in those with discontinuous or attenuated/featureless electroencephalogram versus those with slow/disorganized background (p < 0.03).ConclusionsThese results support the concept of autonomic system failure as an early indicator of impending brain death in brain-injured children. Furthermore, decreased heart rate variability is associated with markers of CNS dysfunction such as electroencephalogram abnormalities.

Project description:BACKGROUND:Chest pain is one of the most common complaints among patients presenting to the emergency department (ED). Causes of chest pain can be benign or life threatening, making accurate risk stratification a critical issue in the ED. In addition to the use of established clinical scores, prior studies have attempted to create predictive models with heart rate variability (HRV). In this study, we proposed heart rate n-variability (HRnV), an alternative representation of beat-to-beat variation in electrocardiogram (ECG), and investigated its association with major adverse cardiac events (MACE) in ED patients with chest pain. METHODS:We conducted a retrospective analysis of data collected from the ED of a tertiary hospital in Singapore between September 2010 and July 2015. Patients >?20?years old who presented to the ED with chief complaint of chest pain were conveniently recruited. Five to six-minute single-lead ECGs, demographics, medical history, troponin, and other required variables were collected. We developed the HRnV-Calc software to calculate HRnV parameters. The primary outcome was 30-day MACE, which included all-cause death, acute myocardial infarction, and revascularization. Univariable and multivariable logistic regression analyses were conducted to investigate the association between individual risk factors and the outcome. Receiver operating characteristic (ROC) analysis was performed to compare the HRnV model (based on leave-one-out cross-validation) against other clinical scores in predicting 30-day MACE. RESULTS:A total of 795 patients were included in the analysis, of which 247 (31%) had MACE within 30?days. The MACE group was older, with a higher proportion being male patients. Twenty-one conventional HRV and 115 HRnV parameters were calculated. In univariable analysis, eleven HRV and 48 HRnV parameters were significantly associated with 30-day MACE. The multivariable stepwise logistic regression identified 16 predictors that were strongly associated with MACE outcome; these predictors consisted of one HRV, seven HRnV parameters, troponin, ST segment changes, and several other factors. The HRnV model outperformed several clinical scores in the ROC analysis. CONCLUSIONS:The novel HRnV representation demonstrated its value of augmenting HRV and traditional risk factors in designing a robust risk stratification tool for patients with chest pain in the ED.

Project description:BackgroundSepsis is a life-threatening disease with an in-hospital mortality rate of approximately 20%. Physicians at the emergency department (ED) have to estimate the risk of deterioration in the coming hours or days and decide whether the patient should be admitted to the general ward, ICU or can be discharged. Current risk stratification tools are based on measurements of vital parameters at a single timepoint. Here, we performed a time, frequency, and trend analysis on continuous electrocardiograms (ECG) at the ED to try and predict deterioration of septic patients.MethodsPatients were connected to a mobile bedside monitor that continuously recorded ECG waveforms from triage at the ED up to 48 h. Patients were post-hoc stratified into three groups depending on the development of organ dysfunction: no organ dysfunction, stable organ dysfunction or progressive organ dysfunction (i.e., deterioration). Patients with de novo organ dysfunction and those admitted to the ICU or died were also stratified to the group of progressive organ dysfunction. Heart rate variability (HRV) features over time were compared between the three groups.ResultsIn total 171 unique ED visits with suspected sepsis were included between January 2017 and December 2018. HRV features were calculated over 5-min time windows and summarized into 3-h intervals for analysis. For each interval, the mean and slope of each feature was calculated. Of all analyzed features, the average of the NN-interval, ultra-low frequency, very low frequency, low frequency and total power were different between the groups at multiple points in time.ConclusionsWe showed that continuous ECG recordings can be automatically analyzed and used to extract HRV features associated with clinical deterioration in sepsis. The predictive accuracy of our current model based on HRV features derived from the ECG only shows the potential of HRV measurements at the ED. Unlike other risk stratification tools employing multiple vital parameters this does not require manual calculation of the score and can be used on continuous data over time. Trial registration The protocol of this study is published by Quinten et al., 2017.

Project description:We previously developed and retrospectively validated the estimated percentage of heart rate variation (EHRV) as a predictor of the composite outcome of ≥ 5% dehydration and/or acute kidney injury (AKI) in non-febrile children. The current study aimed to prospectively validate EHRV as a predictor for dehydration or AKI in a different cohort of children attending the Pediatric Emergency Department. From July 2022 to August 2023, 256 pediatric patients aged 0-18 years attending the Pediatric Emergency Department were enrolled. EHRV was calculated as follows: [(HR at admission - 50th percentile of HR for age and sex)/HR at admission] × 100. Dehydration was categorized as < 5% or ≥ 5% fluid deficit. AKI was defined according to KDIGO creatinine criteria. Statistical analyses included receiver-operating characteristic (ROC) curves and logistic regression analysis. Among enrolled patients, 52 had ≥ 5% dehydration, 50 had AKI, and 16 had both conditions. EHRV demonstrated significant predictive ability for both ≥ 5% dehydration (AUROC = 0.71; 95% confidence interval (CI), 0.63-0.78; p < 0.001) and AKI (AUROC = 0.78; 95% CI, 0.71-0.84; p < 0.001). An EHRV > 24.5% was associated with an increased odds ratio (OR), adjusted for confounders, of ≥ 5% dehydration (OR = 3.5; 95% CI, 1.6-8.0; p = 0.003) and AKI (OR = 3.4; 95% CI, 1.6-7.3; p = 0.002). The sensitivity and specificity of this cut-off were 34% and 83% for ≥ 5% dehydration and 36% and 84% for AKI, respectively.ConclusionsThis study prospectively validates the clinical utility of EHRV in predicting dehydration and AKI in a pediatric emergency care setting. An EHRV > 24.5% could serve as a marker for suspecting dehydration or AKI. Further validation across diverse patient populations and settings is needed.What is known• An increased heart rate (HR) is a readily detectable sign of dehydration in children. • In a retrospective validation cohort, an estimated HR variation (EHRV) greater than 24.5% compared to the 50th percentile of HR was predictive of ≥ 5% dehydration and/or acute kidney injury (AKI) in non-febrile patients.What is new• We prospectively validated the clinical utility of EHRV in predicting dehydration and AKI in a pediatric emergency care setting. • We confirmed that an EHRV greater than 24.5% is associated with increased odds of ≥ 5% dehydration and AKI.

Dataset Information

Simultaneous Heart Rate Variability and Electroencephalographic Monitoring in Children in the Emergency Department.

Publications

Simultaneous Heart Rate Variability and Electroencephalographic Monitoring in Children in the Emergency Department.

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