Heart rate variability as possible marker of brain damage in neonates with hypoxic ischemic encephalopathy: a systematic review

Fusion Model Using Resting Neurophysiological Data to Help Mass Screening of Methamphetamine Use Disorder

Methamphetamine use disorder (MUD) is a substance use disorder. Because MUD has become more prevalent due to the COVID-19 pandemic, alternative ways to help the efficiency of mass screening of MUD are important. Previous studies used electroencephalogram (EEG), heart rate variability (HRV), and galvanic skin response (GSR) aberrations during the virtual reality (VR) induction of drug craving to accurately separate patients with MUD from the healthy controls. However, whether these abnormalities present without induction of drug-cue reactivity to enable separation between patients and healthy subjects remains unclear. Here, we propose a clinically comparable intelligent system using the fusion of 5-channel EEG, HRV, and GSR data during resting state to aid in detecting MUD. Forty-six patients with MUD and 26 healthy controls were recruited and machine learning methods were employed to systematically compare the classification results of different fusion models. The analytic results revealed that the fusion of HRV and GSR features leads to the most accurate separation rate of 79%. The use of EEG, HRV, and GSR features provides more robust information, leading to relatively similar and enhanced accuracy across different classifiers. In conclusion, we demonstrated that a clinically applicable intelligent system using resting-state EEG, ECG, and GSR features without the induction of drug cue reactivity enhances the detection of MUD. This system is easy to implement in the clinical setting and can save a lot of time on setting up and experimenting while maintaining excellent accuracy to assist in mass screening of MUD.

Effect of dural puncture epidural block technique on fetal heart rate variability during labor analgesia

PURPOSE

To explore the effect of dural puncture epidural (DPE) block technique on fetal heart rate variability (HRV) during labor analgesia.

METHODS

Sixty full-term primiparas who were in our hospital from April 2021 to October 2021 were selected and randomized into epidural analgesia (CEA) and dural puncture epidural analgesia (DPEA) groups (n = 30). After a successful epidural puncture, routine epidural catheter (EC) was performed in CEA group, and spinal anesthesia needle (as an EC) was used to puncture the dura mater to subarachnoid space in DPE group. Anesthetics were injected through EC. The time when the temperature sensation plane reached T10 (W1) and visual analog pain score (VAS), baseline heart rate score, amplitude variation score, cycle variation score, acceleration score, deceleration score, and total score of the first contraction after W1 were recorded. Apgar scores at 1 min, 5 min, and 10 min of neonates after delivery were recorded.

RESULTS

The onset time of anesthesia in CEA group was significantly longer than that in DPEA group (p < .05). However, there are no significant differences in W1, VAS, baseline heart rate score, amplitude variation score, cycle variation score, acceleration score, deceleration score, and total score of the first contraction after W1 between the two groups (p > .05). Moreover, the Apgar scores at 1 min, 5 min and 10 min of neonates after delivery were not notably different between the two groups (p > .05).

CONCLUSION

Compared with CEA, DPE block technique in labor analgesia relieves maternal pain without adverse effects on fetal HRV and newborns.

Using heart rate variability to predict neurological outcomes in preterm infants: a scoping review

Infants born preterm are at higher risk of neurological complications, including intraventricular haemorrhage and white matter injury. After discharge, these infants may experience adverse neurodevelopmental outcomes and exhibit lower educational attainment. Early detection of brain injury and accurate prediction of neurodevelopmental impairment would allow early intervention and support. Heart rate variability (HRV) describes the variation of time intervals between each subsequent heartbeat. HRV is controlled by the autonomic nervous system, which may be affected by hypoxia and compromised blood flow. While HRV has primarily been investigated in neonatal sepsis, the association between HRV, brain injury and neurodevelopmental outcomes in preterm infants is less established. The present scoping review examines the utility of HRV monitoring for predicting short-term and long-term neurological outcomes in preterm infants. Following systematic search of Medline, Embase, Web of Science and the Cochrane Library, 15 studies were included. Nine studies examined the relationship between HRV and brain injury, with all but two showed an association. Eight studies examined the relationship between HRV and long-term outcomes and all eight found an association. This scoping review suggests that decreased HRV in the neonatal period is associated with short- and long-term neurodevelopmental outcomes in preterm infants. IMPACT: Changes in heart rate variability correlate with the occurrence of intraventricular haemorrhage in preterm infants. A decrease in heart rate variability may precede the development of intraventricular haemorrhage. Alterations in heart rate variability correlate with long-term neurodevelopmental outcomes. Significant variability exists in metrics used in assessing heart rate variability.

Effectiveness of Auricular Acupressure on Improving Pain and Heart Rate Variability in Patients After Cervical Spine Surgery

Cervical spine surgery is a common neurosurgical procedure; however, postoperative pain remains a problem. This study aimed to examine the effectiveness of auricular acupressure, which is considered a noninvasive, convenient, and safe method for pain reduction and heart rate variability in patients after surgery. A total of 62 patients who underwent cervical spine surgery were randomly divided into experimental (32 patients) and control (30 patients) groups. Both groups received routine care, whereas the experimental group received auricular acupressure three times a day for four days. The Short-Form McGill Pain Questionnaire was administered, and heart rate variability measurements were obtained on the first, second, third, and fourth postoperative days. The results indicated that auricular acupressure was effective in reducing pain (P < .05) and improving heart rate variability (P < .05) in patients. Based on the findings, this study suggests that auricular acupressure can be used as a complementary treatment to reduce pain in patients after cervical spine surgery.

Assessing the Effectiveness of Heart Rate Variability as A Diagnostic Tool for Brain Injuries in Infants

Hypoxic-Ischemic Encephalopathy (HIE), marked by cerebral oxygen deprivation, prompts exploration beyond the electroencephalogram (EEG) modality. This study investigates heart rate variability (HRV) to assess its potential for seizure detection and HIE grading for neonates. This study utilizes two annotated datasets from real-world clinical settings. Heart Rate (HR) is calculated from the Electrocardiogram (ECG) signal, which are then denoised and segmented. Sixteen time and frequency domain features are extracted from each HR segment. Employing Random Forest (RF), Support Vector Machine (SVM), and Isolation Forest (IF) classifiers, the investigation addresses the detection of seizure and nonseizure segments in ECG, alongside categorizing HIE severity into two mild and normal or moderate and severe grades. While the patient-independent evaluation of the seizure detection system reveals promising outcomes for specific cases, there is a requirement for further refinement in this aspect and exploration into the correlation between HR and EEG, considering the modest AUC of 68.54 percent gained across the entire dataset. In contrast, the HIE grading results present a more promising scenario, attaining an AUC of 77.13 percent. This emphasizes the efficacy of the HIE grading system as a significant diagnostic tool, suggesting its potential for broader clinical applications.

Heart Rate and Pulse Oximetry Dynamics in the First Week after Birth in Neonatal Intensive Care Unit Patients and the Risk of Cerebral Palsy

OBJECTIVE

Infants in the neonatal intensive care unit (NICU) are at high risk of adverse neuromotor outcomes. Atypical patterns of heart rate (HR) and pulse oximetry (SpO2) may serve as biomarkers for risk assessment for cerebral palsy (CP). The purpose of this study was to determine whether atypical HR and SpO2 patterns in NICU patients add to clinical variables predicting later diagnosis of CP.

STUDY DESIGN

This was a retrospective study including patients admitted to a level IV NICU from 2009 to 2017 with archived cardiorespiratory data in the first 7 days from birth to follow-up at >2 years of age. The mean, standard deviation (SD), skewness, kurtosis and cross-correlation of HR and SpO2 were calculated. Three predictive models were developed using least absolute shrinkage and selection operator regression (clinical, cardiorespiratory and combined model), and their performance for predicting CP was evaluated.

RESULTS

Seventy infants with CP and 1,733 controls met inclusion criteria for a 3.8% population prevalence. Area under the receiver operating characteristic curve for CP prediction was 0.7524 for the clinical model, 0.7419 for the vital sign model, and 0.7725 for the combined model. Variables included in the combined model were lower maternal age, outborn delivery, lower 5-minute Apgar's score, lower SD of HR, and more negative skewness of HR.

CONCLUSION

In this study including NICU patients of all gestational ages, HR but not SpO2 patterns added to clinical variables to predict the eventual diagnosis of CP. Identification of risk of CP within the first few days of life could result in improved therapy resource allocation and risk stratification in clinical trials of new therapeutics.

KEY POINTS

· SD and skewness of HR have some added predictive value of later diagnosis of CP.. · SpO2 measures do not add to CP prediction.. · Combining clinical variables with early HR measures may improve the prediction of later CP..

Heart rate patterns predicting cerebral palsy in preterm infants

BACKGROUND

Heart rate (HR) patterns can inform on central nervous system dysfunction. We previously used highly comparative time series analysis (HCTSA) to identify HR patterns predicting mortality among patients in the neonatal intensive care unit (NICU) and now use this methodology to discover patterns predicting cerebral palsy (CP) in preterm infants.

METHOD

We studied NICU patients <37 weeks' gestation with archived every-2-s HR data throughout the NICU stay and with or without later diagnosis of CP (n = 57 CP and 1119 no CP). We performed HCTSA of >2000 HR metrics and identified 24 metrics analyzed on HR data from two 7-day periods: week 1 and 37 weeks' postmenstrual age (week 1, week 37). Multivariate modeling was used to optimize a parsimonious prediction model.

RESULTS

Week 1 HR metrics with maximum AUC for CP prediction reflected low variability, including "RobustSD" (AUC 0.826; 0.772-0.870). At week 37, high values of a novel HR metric, "LongSD3," the cubed value of the difference in HR values 100 s apart, were added to week 1 HR metrics for CP prediction. A combined birthweight + early and late HR model had AUC 0.853 (0.805-0.892).

CONCLUSIONS

Using HCTSA, we discovered novel HR metrics and created a parsimonious model for CP prediction in preterm NICU patients.

IMPACT

We discovered new heart rate characteristics predicting CP in preterm infants. Using every-2-s HR from two 7-day periods and highly comparative time series analysis, we found a measure of low variability HR week 1 after birth and a pattern of recurrent acceleration in HR at term corrected age that predicted CP. Combined clinical and early and late HR features had AUC 0.853 for CP prediction.

Neonatal Seizure Detection Using a Wearable Multi-Sensor System

Neonatal seizure is an important clinical symptom of brain dysfunction, which is more common in infancy than in childhood. At present, video electroencephalogram (VEEG) technology is widely used in clinical practice. However, video electroencephalogram technology has several disadvantages. For example, the wires connecting the medical instruments may interfere with the infant's movement and the gel patch electrode or disk electrode commonly used to monitor EEG may cause skin allergies or even tears. For the above reasons, we developed a wearable multi-sensor platform for newborns to collect physiological and movement signals. In this study, we designed a second-generation multi-sensor platform and developed an automatic detection algorithm for neonatal seizures based on ECG, respiration and acceleration. Data for 38 neonates were recorded at the Children's Hospital of Fudan University in Shanghai. The total recording time was approximately 300 h. Four of the patients had seizures during data collection. The total recording time for the four patients was approximately 34 h, with 30 seizure episodes recorded. These data were evaluated by the algorithm. To evaluate the effectiveness of combining ECG, respiration and movement, we compared the performance of three types of seizure detectors. The first detector included features from ECG, respiration and acceleration records; the second detector incorporated features based on respiratory movement from respiration and acceleration records; and the third detector used only ECG-based features from ECG records. Our study illustrated that, compared with the detector utilizing individual modal features, multi-modal feature detectors could achieve favorable overall performance, reduce false alarm rates and give higher F-measures.

Clinical applications of contactless photoplethysmography for vital signs monitoring in pediatrics: A systematic review and meta-analysis

Background

Contactless photoplethysmography (PPG) potentially affords the ability to obtain vital signs in pediatric populations without disturbing the child. Most validity studies have been conducted in laboratory settings or with healthy adult volunteers. This review aims to evaluate the current literature on contactless vital signs monitoring in pediatric populations and within a clinical setting.

Methods

OVID, Webofscience, Cochrane library, and clinicaltrials.org were systematically searched by two authors for research studies which used contactless PPG to assess vital signs in children and within a clinical setting.

Results

Fifteen studies were included with a total of 170 individuals. Ten studies were included in a meta-analysis for neonatal heart rate (HR), which demonstrated a pooled mean bias of -0.25 (95% limits of agreement (LOA), -1.83 to 1.32). Four studies assessed respiratory rate (RR) in neonates, and meta-analysis demonstrated a pooled mean bias of 0.65 (95% LOA, -3.08 to 4.37). All studies were small, and there were variations in the methods used and risk of bias.

Conclusion

Contactless PPG is a promising tool for vital signs monitoring in children and accurately measures neonatal HR and RR. Further research is needed to assess children of different age groups, the effects of skin type variation, and the addition of other vital signs.

Heart rate variability analysis for the prediction of EEG grade in infants with hypoxic ischaemic encephalopathy within the first 12 h of birth

Background and aims

Heart rate variability (HRV) has previously been assessed as a biomarker for brain injury and prognosis in neonates. The aim of this cohort study was to use HRV to predict the electroencephalography (EEG) grade in neonatal hypoxic-ischaemic encephalopathy (HIE) within the first 12 h.

Methods

We included 120 infants with HIE recruited as part of two European multi-centre studies, with electrocardiography (ECG) and EEG monitoring performed before 12 h of age. HRV features and EEG background were assessed using the earliest 1 h epoch of ECG-EEG monitoring. HRV was expressed in time, frequency and complexity features. EEG background was graded from 0-normal, 1-mild, 2-moderate, 3-major abnormalities to 4-inactive. Clinical parameters known within 6 h of birth were collected (intrapartum complications, foetal distress, gestational age, mode of delivery, gender, birth weight, Apgar at 1 and 5, assisted ventilation at 10 min). Using logistic regression analysis, prediction models for EEG severity were developed for HRV features and clinical parameters, separately and combined. Multivariable model analysis included 101 infants without missing data.

Results

Of 120 infants included, 54 (45%) had normal-mild and 66 (55%) had moderate-severe EEG grade. The performance of HRV model was AUROC 0.837 (95% CI: 0.759-0.914) and clinical model was AUROC 0.836 (95% CI: 0.759-0.914). The HRV and clinical model combined had an AUROC of 0.895 (95% CI: 0.832-0.958). Therapeutic hypothermia and anti-seizure medication did not affect the model performance.

Conclusions

Early HRV and clinical information accurately predicted EEG grade in HIE within the first 12 h of birth. This might be beneficial when EEG monitoring is not available in the early postnatal period and for referral centres who may want some objective information on HIE severity.

Optimal neuromonitoring techniques in neonates with hypoxic ischemic encephalopathy

Neonates with hypoxic ischemic encephalopathy (HIE) are at significant risk for adverse outcomes including death and neurodevelopmental impairment. Neuromonitoring provides critical diagnostic and prognostic information for these infants. Modalities providing continuous monitoring include continuous electroencephalography (cEEG), amplitude-integrated electroencephalography (aEEG), near-infrared spectroscopy (NIRS), and heart rate variability. Serial bedside neuromonitoring techniques include cranial ultrasound and somatic and visual evoked potentials but may be limited by discrete time points of assessment. EEG, aEEG, and NIRS provide distinct and complementary information about cerebral function and oxygen utilization. Integrated use of these neuromonitoring modalities in addition to other potential techniques such as heart rate variability may best predict imaging outcomes and longer-term neurodevelopment. This review examines available bedside neuromonitoring techniques for the neonate with HIE in the context of therapeutic hypothermia.

Parasympathetic evaluation for procedural pain assessment in neonatology

INTRODUCTION

The Newborn Infant Parasympathetic Evaluation (NIPE) index is an instrument that enables continuous, fast and objective assessment of neonatal discomfort. The aim of the study was to analyse changes in NIPE values after performance of blood draws and the factors involved in this variation.

MATERIAL AND METHODS

We conducted a prospective observational study. We included infants admitted to the neonatal intensive care unit between June and December 2021 who underwent blood draws. We recorded demographic data, aspects related to the procedure, the NIPE index and the heart rate at baseline and 1, 2, 3, 4, 5, 10 and 15 min after the procedure.

RESULTS

The study included 86 records for 49 patients. In the first 4 min after the procedure, there was a significant decrease in the NIPE index, with a maximum decrease of 22.8% relative to baseline and the nadir at 2.79 min. The decrease in NIPE values was greater in infants born preterm, male, with lower 5-min Apgar scores and following procedures that had been performed previously, after caesarean section or in the morning. There were no differences when the blood draw was obtained during kangaroo care. The correlation between the NIPE index and the heart rate was weak.

CONCLUSIONS

After a painful procedure, such as a blood draw, the NIPE monitor showed a significant decrease in the first 4 min, which was more pronounced in preterm infants, in repeated procedures or after caesarean delivery. The NIPE index could help identify infants experiencing acute procedural pain, complementing clinical rating scales.

Hypothermia and heart rate variability in a healthy newborn piglet model

Decreased heart rate variability (HRV) may be a biomarker of brain injury severity in neonatal hypoxic-ischemic encephalopathy for which therapeutic hypothermia is standard treatment. While therapeutic hypothermia may influence the degree of brain injury; hypothermia may also affect HRV per se and obscure a potential association between HRV and hypoxic-ischemic encephalopathy. Previous results are conflicting. This study aimed to investigate the effect of hypothermia on HRV in healthy, anaesthetised, newborn piglets. Six healthy newborn piglets were anaesthetised. Three piglets were first kept normothermic (38.5-39.0 °C) for 3 h, then exposed to hypothermia (33.5-34.5 °C) for 3 h. Three piglets were first exposed to hypothermia for 3 h, then rewarmed to normothermia for 3 h. Temperature and ECG were recorded continuously. HRV was calculated from the ECG in 5 min epochs and included time domain and frequency domain variables. The HRV variables were compared between hypothermia and normothermia. All assessed HRV variables were higher during hypothermia compared to normothermia. Heart rate was lower during hypothermia compared to normothermia and all HRV variables correlated with heart rate. Hypothermia was associated with an increase in HRV; this could be mediated by bradycardia during hypothermia.

Impaired Brain-Heart Relation in Patients With Methamphetamine Use Disorder During VR Induction of Drug Cue Reactivity

Methamphetamine use disorder (MUD) is an illness associated with severe health consequences. Virtual reality (VR) is used to induce the drug-cue reactivity and significant EEG and ECG abnormalities were found in MUD patients. However, whether a link exists between EEG and ECG abnormalities in patients with MUD during exposure to drug cues remains unknown. This is important from the therapeutic viewpoint because different treatment strategies may be applied when EEG abnormalities and ECG irregularities are complications of MUD. We designed a VR system with drug cues and EEG and ECG were recorded during VR exposure. Sixteen patients with MUD and sixteen healthy subjects were recruited. Statistical tests and Pearson correlation were employed to analyze the EEG and ECG. The results showed that, during VR induction, the patients with MUD but not healthy controls showed significant [Formula: see text] and [Formula: see text] power increases when the stimulus materials were most intense. This finding indicated that the stimuli are indiscriminate to healthy controls but meaningful to patients with MUD. Five heart rate variability (HRV) indexes significantly differed between patients and controls, suggesting abnormalities in the reaction of patient's autonomic nervous system. Importantly, significant relations between EEG and HRV indexes changes were only identified in the controls, but not in MUD patients, signifying a disruption of brain-heart relations in patients. Our findings of stimulus-specific EEG changes and the impaired brain-heart relations in patients with MUD shed light on the understanding of drug-cue reactivity and may be used to design diagnostic and/or therapeutic strategies for MUD.

Splanchnic oxygen saturation during reoxygenation with 21% or 100% O2 in newborn piglets

BACKGROUND

Increasing evidence recognizes the harm of excess oxygen to lungs, eyes, and brain of preterm infants, but not yet to the intestine. We assessed changes in splanchnic oxygenation during reoxygenation with 21% compared to 100% O₂ in a newborn piglet model of perinatal asphyxia.

METHODS

We randomized 25 piglets to control or intervention. Intervention groups underwent global hypoxia until acidosis and hypotension occurred. Piglets were reoxygenated for 30 min with 21% or 100% O₂ and observed for 9 h. We continuously measured regional splanchnic oxygen saturation (r_sSO₂) using near-infrared spectroscopy (NIRS). We calculated mean r_sSO₂ and r_sCoVar (as SD/mean). We measured PaO₂ and SaO₂, sampled from the right carotid artery.

RESULTS

Reoxygenation after global hypoxia restored r_sSO₂. Reoxygenation with 100% O₂ increased r_sSO₂ to values significantly higher than baseline. In intervention groups, r_sCoVar decreased during observation compared to baseline. We found a correlation between r_sSO₂ and PaO₂ (r = 0.420, P < 0.001) and between r_sSO₂ and SaO₂ (r = 0.648, P < 0.001) in pooled data from the entire experiment.

CONCLUSION

Reoxygenation after global hypoxia improves splanchnic oxygenation, but is associated with reduced variability of r_sSO₂. Reoxygenation with 100% O₂ exposes the intestine to hyperoxia. Splanchnic NIRS is able to detect intestinal hypoxia and hyperoxia.

IMPACT

Splanchnic oxygenation improves during reoxygenation after global hypoxia, though reoxygenation with 100% O₂ exposes the intestine to hyperoxia. Decreased variability of splanchnic oxygenation several hours after hypoxia and reoxygenation seems to be independent of the resuscitation strategy, and may indicate intestinal injury. Splanchnic NIRS monitoring was able to detect intestinal hypoxia and exposure to hyperoxia, as evidenced by a strong correlation between splanchnic oxygenation and arterial oxygen content.

Associations between fetal heart rate variability and umbilical cord occlusions-induced neural injury: An experimental study in a fetal sheep model

INTRODUCTION

This study evaluated the association between fetal heart rate variability (HRV) and the occurrence of hypoxic-ischemic encephalopathy in a fetal sheep model.

MATERIAL AND METHODS

The experimental protocol created a hypoxic condition with repeated cord occlusions in three phases (A, B, C) to achieve acidosis to pH <7.00. Hemodynamic, gasometric and HRV parameters were analyzed during the protocol, and the fetal brain, brainstem and spinal cord were assessed histopathologically 48 h later. Associations between the various parameters and neural injury were compared between phases A, B and C using Spearman's rho test.

RESULTS

Acute anoxic-ischemic brain lesions in all regions was present in 7/9 fetuses, and specific neural injury was observed in 3/9 fetuses. The number of brainstem lesions correlated significantly and inversely with the HRV fetal stress index (r = -0.784; p = 0.021) in phase C and with HRV long-term variability (r = -0.677; p = 0.045) and short-term variability (r = -0.837; p = 0.005) in phase B. The number of neurological lesions did not correlate significantly with other markers of HRV.

CONCLUSIONS

Neural injury caused by severe hypoxia was associated with HRV changes; in particular, brainstem damage was associated with changes in fetal-specific HRV markers.

Application Effect Analysis of Clinical Nursing Pathway in the Care of Neonatal Hypoxic-Ischemic Encephalopathy

This research focuses on the effectiveness of the clinical nursing pathway (CNP) in the treatment of infant hypoxic-ischemic encephalopathy (NHIE). This research enrolled 120 cases of NHIE admitted to the First Affiliated Hospital of Heilongjiang University of Chinese Medicine, including 70 cases (research group, the Res) who received CNP intervention and 50 cases (control group, the Con) treated by routine nursing pathway intervention. The psychomotor development index (PDI), mental development index (MDI), neurodevelopment (ND), physique growth, and incidence of adverse events (AEs) were recorded and analyzed. The results identified that in comparison with the Con (1) the PDI and MDI were obviously better in the Res 6 months postintervention; (2) the Res had significantly superior ND of behavioral capacity, passive tone, active tone, primitive reflex, and general assessment 1 month after intervention, as well as physical development of body weight, height, and head circumference after 40 days of birth, (3) the incidence of total AEs within 40 days was statistically lower in the Res. As a result, CNP is considerably superior to the traditional nursing pathway in the treatment of NHIE, and it merits clinical promotion.

Heart Rate Variability Analysis for Seizure Detection in Neonatal Intensive Care Units

In Neonatal Intensive Care Units (NICUs), the early detection of neonatal seizures is of utmost importance for a timely clinical intervention. Over the years, several neonatal seizure detection systems were proposed to detect neonatal seizures automatically and speed up seizure diagnosis, most based on the EEG signal analysis. Recently, research has focused on other possible seizure markers, such as electrocardiography (ECG). This work proposes an ECG-based NSD system to investigate the usefulness of heart rate variability (HRV) analysis to detect neonatal seizures in the NICUs. HRV analysis is performed considering time-domain, frequency-domain, entropy and multiscale entropy features. The performance is evaluated on a dataset of ECG signals from 51 full-term babies, 29 seizure-free. The proposed system gives results comparable to those reported in the literature: Area Under the Receiver Operating Characteristic Curve = 62%, Sensitivity = 47%, Specificity = 67%. Moreover, the system’s performance is evaluated in a real clinical environment, inevitably affected by several artefacts. To the best of our knowledge, our study proposes for the first time a multi-feature ECG-based NSD system that also offers a comparative analysis between babies suffering from seizures and seizure-free ones.

A Generalized Linear Model for an ECG-based Neonatal Seizure Detector

Seizures represent one of the most challenging issues of the neonatal period's neurological emergency. Due to the heterogeneity of etiologies and clinical characteristics, seizures recognition is tricky and time-consuming. Currently, the gold standard for seizure diagnosis is Electroencephalography (EEG), whose correct interpretation requires a highly specialized team. Thus, to speed up and facilitate the detection of ictal events, several EEG-based Neonatal Seizure Detectors (NSDs) have been proposed in the literature. Research is currently exploiting more simple and less invasive approaches, such as Electrocardiography (ECG). This work aims at developing an ECG-based NSD using a Generalized Linear Model with features extracted from Heart Rate Variability (HRV) measures as input. The method is validated on a public dataset of 52 subjects (33 with seizures and 19 seizure-free). Achieved encouraging results show 69% Concatenated Area Under the ROC Curve (AUCcc) for the automatic detection of windows with seizure events, confirming that HRV features can be useful to catch the cardio-regulatory system alterations due to neonatal seizure events, particularly those related to Hypoxic-Ischaemic Encephalopathies. Thus, results suggest the use of ECG-based NSDs in clinical practice, especially when a timely diagnosis is needed and EEG technologies are not readily available.Clinical Relevance- An ECG-based Neonatal Seizure Detector could be a valid support to speed up the diagnosis of neonatal seizures, especially when EEG technologies for infants' neurological assessment are not readily available.

Comprehensive Analysis of RNA Expression Profile Identifies Hub miRNA-circRNA Interaction Networks in the Hypoxic Ischemic Encephalopathy

Hypoxic ischemic encephalopathy (HIE) is classified as a sort of serious nervous system syndrome that occurs in the early life period. Noncoding RNAs had been confirmed to have crucial roles in human diseases. So far, there were few systematical and comprehensive studies towards the expression profile of RNAs in the brain after hypoxia ischemia. In this study, 31 differentially expressed microRNAs (miRNAs) with upregulation were identified. In addition, 5512 differentially expressed mRNAs, long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) were identified in HIE groups. Bioinformatics analysis showed these circRNAs and mRNAs were significantly enriched in regulation of leukocyte activation, response to virus, and neutrophil degranulation. Pathway and its related gene network analysis indicated that HLA - DPA1, HLA - DQA2, HLA - DQB1, and HLA - DRB4 have a more crucial role in HIE. Finally, miRNA-circRNA-mRNA interaction network analysis was also performed to identify hub miRNAs and circRNAs. We found that miR-592 potentially targeting 5 circRNAs, thus affecting 15 mRNA expressions in HIR. hsa_circ_0068397 and hsa_circ_0045698 were identified as hub circRNAs in HIE. Collectively, using RNA-seq, bioinformatics analysis, and circRNA/miRNA interaction prediction, we systematically investigated the differentially expressed RNAs in HIE, which could give a new hint of understanding the pathogenesis of HIE.

Multiscale Entropy Analysis of Heart Rate Variability in Neonatal Patients with and without Seizures

The complex physiological dynamics of neonatal seizures make their detection challenging. A timely diagnosis and treatment, especially in intensive care units, are essential for a better prognosis and the mitigation of possible adverse effects on the newborn's neurodevelopment. In the literature, several electroencephalographic (EEG) studies have been proposed for a parametric characterization of seizures or their detection by artificial intelligence techniques. At the same time, other sources than EEG, such as electrocardiography, have been investigated to evaluate the possible impact of neonatal seizures on the cardio-regulatory system. Heart rate variability (HRV) analysis is attracting great interest as a valuable tool in newborns applications, especially where EEG technologies are not easily available. This study investigated whether multiscale HRV entropy indexes could detect abnormal heart rate dynamics in newborns with seizures, especially during ictal events. Furthermore, entropy measures were analyzed to discriminate between newborns with seizures and seizure-free ones. A cohort of 52 patients (33 with seizures) from the Helsinki University Hospital public dataset has been evaluated. Multiscale sample and fuzzy entropy showed significant differences between the two groups (p-value < 0.05, Bonferroni multiple-comparison post hoc correction). Moreover, interictal activity showed significant differences between seizure and seizure-free patients (Mann-Whitney Test: p-value < 0.05). Therefore, our findings suggest that HRV multiscale entropy analysis could be a valuable pre-screening tool for the timely detection of seizure events in newborns.

Current Resources for Evidence-Based Practice, September 2021

An extensive review of new resources to support the provision of evidence-based care for women and infants. The current column includes an assessment of safety of birth centers in the United States and commentaries on reviews focused on aspirin prophylaxis in pregnancy and the new gestational weight gain evidence summary from the United States Preventive Services Task Force.

Cerebral cortical autonomic connectivity in low-risk term newborns

PURPOSE

The mature central autonomic network includes connectivity between autonomic nervous system brainstem centers and the cerebral cortex. The study objective was to evaluate the regional connectivity between the cerebral cortex and brainstem autonomic centers in term newborns by measuring coherence between high-density electroencephalography and heart rate variability as measured by electrocardiography.

METHODS

Low-risk term newborns with birth gestational age of 39-40 weeks were prospectively enrolled and studied using time-synced electroencephalography and electrocardiography for up to 60 min before discharge from the birth hospital. The ccortical autonomicc nervous system association was analyzed using coherence between electroencephalography-delta power and heart rate variability. Heart rate variability measured the parasympathetic tone (root mean square of successive differences of heart rate) and sympathetic tone (standard deviation of heart rate).

RESULTS

One hundred and twenty-nine low-risk term infants were included. High coherence delta-root mean square of successive differences was found in central, bitemporal, and occipital brain regions, with less robust coherence delta-standard deviation in the central region and bitemporal areas.

CONCLUSIONS

Our findings describe a topography of ccortical autonomicc connectivity present at term in low-risk newborns, which was more robust to parasympathetic than sympathetic brainstem centers and was independent of newborn state.

Cerebral Blood Flow Monitoring in High-Risk Fetal and Neonatal Populations

Cerebrovascular pressure autoregulation promotes stable cerebral blood flow (CBF) across a range of arterial blood pressures. Cerebral autoregulation (CA) is a developmental process that reaches maturity around term gestation and can be monitored prenatally with both Doppler ultrasound and magnetic resonance imaging (MRI) techniques. Postnatally, there are key advantages and limitations to assessing CA with Doppler ultrasound, MRI, and near-infrared spectroscopy. Here we review these CBF monitoring techniques as well as their application to both fetal and neonatal populations at risk of perturbations in CBF. Specifically, we discuss CBF monitoring in fetuses with intrauterine growth restriction, anemia, congenital heart disease, neonates born preterm and those with hypoxic-ischemic encephalopathy. We conclude the review with insights into the future directions in this field with an emphasis on collaborative science and precision medicine approaches.