47 research outputs found
Characterization of cardiorespiratory phase synchronization and directionality in late premature and full term infants
Objective: Though the mutual influence of cardiovascular and respiratory rhythms in healthy newborns has been documented, its full characterization is still pending. In general, the activity of many physiological subsystems has a well-expressed rhythmic character, and often an interdependency between physiological rhythms emerges early in development. Traditional methods of data analysis only address the quantification of the strength of subsystem interactions. In this work, we will investigate system interrelationships in terms of the possible presence of causal or directional interplays. Approach: In this paper, we propose a methodological application that quantifies phase coupling and its directionality in a population of newborn infants born between 35 and 40 weeks of gestational age (GA). The aim is to assess whether GA at birth significantly influences the development of phase synchronization and the directionality of the coupling between the cardiovascular and respiratory system activity. Several studies indicating irregular cardiorespiratory coupling as a leading cause of several pathologies underscore the need to investigate this phenomenon in this at-risk population. Main results: Results from our investigation show a different directionality profile as a function of GA and sleep state. Significance: These findings are a contribution to the understanding of higher risk for the documented negative outcomes in the late preterm population. Moreover, these parameters could provide a tool for the development of early markers of cardiorespiratory dysregulation in infants
Associations Between Brain Structure and Connectivity in Infants and Exposure to Selective Serotonin Reuptake Inhibitors During Pregnancy
Importance Selective serotonin reuptake inhibitor (SSRI) use among pregnant women is increasing, yet the association between prenatal SSRI exposure and fetal neurodevelopment is poorly understood. Animal studies show that perinatal SSRI exposure alters limbic circuitry and produces anxiety and depressive-like behaviors after adolescence, but literature on prenatal SSRI exposure in humans is limited and mixed.
Objective To examine associations between prenatal SSRI exposure and brain development using structural and diffusion magnetic resonance imaging (MRI).
Design, Setting, and Participants A cohort study conducted at Columbia University Medical Center and New York State Psychiatric Institute included 98 infants: 16 with in utero SSRI exposure, 21 with in utero untreated maternal depression exposure, and 61 healthy controls. Data were collected between January 6, 2011, and October 25, 2016.
Exposures Selective serotonin reuptake inhibitors and untreated maternal depression.
Main Outcomes and Measures Gray matter volume estimates using structural MRI with voxel-based morphometry and white matter structural connectivity (connectome) using diffusion MRI with probabilistic tractography.
Results The sample included 98 mother (31 [32%] white, 26 [27%] Hispanic/Latina, 26 [27%] black/African American, 15 [15%] other) and infant (46 [47%] boys, 52 [53%] girls) dyads. Mean (SD) age of the infants at the time of the scan was 3.43 (1.50) weeks. Voxel-based morphometry showed significant gray matter volume expansion in the right amygdala (Cohen d = 0.65; 95% CI, 0.06-1.23) and right insula (Cohen d = 0.86; 95% CI, 0.26-1.14) in SSRI-exposed infants compared with both healthy controls and infants exposed to untreated maternal depression (P < .05; whole-brain correction). In connectome-level analysis of white matter structural connectivity, the SSRI group showed a significant increase in connectivity between the right amygdala and the right insula with a large effect size (Cohen d = 0.99; 95% CI, 0.40-1.57) compared with healthy controls and untreated depression (P < .05; whole connectome correction).
Conclusions and Relevance Our findings suggest that prenatal SSRI exposure has an association with fetal brain development, particularly in brain regions critical to emotional processing. The study highlights the need for further research on the potential long-term behavioral and psychological outcomes of these neurodevelopmental changes
Beyond the Bayley: Neurocognitive Assessments of Development During Infancy and Toddlerhood
The use of global, standardized instruments is conventional among clinicians and researchers interested in assessing neurocognitive development. Exclusively relying on these tests for evaluating effects may underestimate or miss specific effects on early cognition. The goal of this review is to identify alternative measures for possible inclusion in future clinical trials and interventions evaluating early neurocognitive development. The domains included for consideration are attention, memory, executive function, language and socio-emotional development. Although domain-based tests are limited, as psychometric properties have not yet been well-established, this review includes tasks and paradigms that have been reliably used across various developmental psychology laboratories
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Gestational diabetes mellitus, prenatal maternal depression, and risk for postpartum depression: an Environmental influences on Child Health Outcomes (ECHO) Study
Background
Prior research has demonstrated bidirectional associations between gestational diabetes mellitus (GDM) and perinatal maternal depression. However, the association between GDM, prenatal depression, and postpartum depression (PPD) has not been examined in a prospective cohort longitudinally.
Methods
Participants in the current analysis included 5,822 women from the National Institutes of Health’s Environmental influences on Child Health Outcomes (ECHO) Research Program: N = 4,606 with Neither GDM nor Prenatal Maternal Depression (Reference Category); N = 416 with GDM only; N = 689 with Prenatal Maternal Depression only; and N = 111 with Comorbid GDM and Prenatal Maternal Depression. The PROMIS-D scale was used to measure prenatal and postnatal maternal depressive symptoms. Primary analyses consisted of linear regression models to estimate the independent and joint effects of GDM and prenatal maternal depression on maternal postpartum depressive symptoms.
Results
A higher proportion of women with GDM were classified as having prenatal depression (N = 111; 21%) compared to the proportion of women without GDM who were classified as having prenatal depression (N = 689; 13%), however this finding was not significant after adjustment for covariates. Women with Comorbid GDM and Prenatal Maternal Depression had significantly increased postpartum depressive symptoms measured by PROMIS-D T-scores compared to women with Neither GDM nor Prenatal Maternal Depression (mean difference 7.02, 95% CI 5.00, 9.05). Comorbid GDM and Prenatal Maternal Depression was associated with an increased likelihood of PPD (OR 7.38, 95% CI 4.05, 12.94). However, women with GDM only did not have increased postpartum PROMIS-D T-scores or increased rates of PPD.
Conclusions
Our findings underscore the importance of universal depression screening during pregnancy and in the first postpartum year. Due to the joint association of GDM and prenatal maternal depression on risk of PPD, future studies should examine potential mechanisms underlying this relation
Update on hypertrophic cardiomyopathy and a guide to the guidelines
Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disorder, affecting 1 in 500 individuals worldwide. Existing epidemiological studies might have underestimated the prevalence of HCM, however, owing to limited inclusion of individuals with early, incomplete phenotypic expression. Clinical manifestations of HCM include diastolic dysfunction, left ventricular outflow tract obstruction, ischaemia, atrial fibrillation, abnormal vascular responses and, in 5% of patients, progression to a 'burnt-out' phase characterized by systolic impairment. Disease-related mortality is most often attributable to sudden cardiac death, heart failure, and embolic stroke. The majority of individuals with HCM, however, have normal or near-normal life expectancy, owing in part to contemporary management strategies including family screening, risk stratification, thromboembolic prophylaxis, and implantation of cardioverter-defibrillators. The clinical guidelines for HCM issued by the ACC Foundation/AHA and the ESC facilitate evaluation and management of the disease. In this Review, we aim to assist clinicians in navigating the guidelines by highlighting important updates, current gaps in knowledge, differences in the recommendations, and challenges in implementing them, including aids and pitfalls in clinical and pathological evaluation. We also discuss the advances in genetics, imaging, and molecular research that will underpin future developments in diagnosis and therapy for HCM
Influence of sleep state and position on cardio-respiratory regulation in newborn babies
Multi-parametric cardiorespiratory analysis in late-preterm, early-term, and full-term infants at birth
Infants born at 35–37 weeks’ gestational age (GA) are at higher risk for a range of pathological conditions and poorer neurodevelopmental outcomes. However, mechanisms responsible are not fully understood. The purpose of this paper is to use traditional and novel techniques to assess newborn autonomic development as a function of GA at birth, focusing on cardiorespiratory regulation. ECG and respiration were acquired during sleep on 329 healthy newborns. Infants were divided into GA groups: 35–36 weeks (late preterm (LPT)), 37–38 weeks (early term (ET)), and 39–40 weeks (full term (FT)). Time domain, frequency domain, and non-linear measures were calculated. Increased heart rate short-term variability and complexity as a function of GA were observed in time domain and non-linear measures. Decreasing inter-breath interval variability was found as a function of GA, with increasing linear cardiorespiratory coupling. A complexity parameter (quadratic sample entropy) was less affected by arrhythmias and artifacts when compared to traditional measures. Results suggest lower maturation in LPT, with less developed cardiorespiratory regulation. This may confer risk for altered outcome, convergent with epidemiological findings. Reported examples show that a combination of methodological approaches can be beneficial to characterize autonomic maturation. [Figure not available: see fulltext.
Feasibility study for the assessment of cardio-respiratory coupling in newborn infants
Cardio Respiratory Coupling (CRC) plays a key role during infant development. Nonetheless, mechanisms underlying it are still mostly unexplained and tools to assess it are often inadequate to understand its functioning. This study aims to evaluate the feasibility of CRC activity detection and quantification analyzing ECG and respiration of newborn healthy subjects. Cross-spectral analysis (coherence) and a novel application of a nonlinear method (Bivariate Phase Rectified Signal Averaging) were applied on 10 minutes recording from 4 subjects. Our preliminary results show that these methods can provide significant information about the occurrence and the strength of CRC, opening interesting perspectives in the evaluation of cardiorespiratory pathologies in newborn infants. In particular, the observed dynamic behavior appears stable and centered around one single frequency in Quiet Sleep, while being more variable and less consistent in Active Sleep
Multi-parametric Heart Rate Analysis in Premature Babies exposed to Sudden Infant Death Syndrome.
Severe premature babies present a risk profile higher than the normal population. Reasons are related to the incomplete development of physiological systems that support baby’s life. Heart Rate Variability (HRV) analysis can help the identification of distress conditions as it is sensitive to Autonomic Nervous System (ANS) behavior. This paper presents results obtained in 35 babies with severe prematurity, in quiet and active sleep and in prone and supine position. HRV was analyzed in time and frequency domain and with nonlinear parameters. The novelty of this approach lies in the combined use of parameters generally adopted in fetal monitoring and “adult” indices. Results show that most parameters succeed in classifying different experimental conditions. This is very promising as our final objective is to identify a set of parameters that could be the basis for a risk classifier to improve the care path of premature populatio
A Point Process Framework for the Characterization of Sleep States in Early Infancy
It is well known that the coordination among several subsystems in newborns is effectively changing as a function of behavioral states. For this reason, sleep state characterization is an essential procedure in neonatal monitoring. Despite its importance, methodologies assessing sleep states are discrete in time and usually based on visual inspection. In this work, we validate a point process framework on a population of 113 full-term infants with the aim of providing continuous sleep state characterization over time. After determining a suitable probability density distribution to best fit the neonatal RR series, we compare traditional heart rate variability (HRV) parameters with the point process-extracted sets of time and frequency domain instantaneous measures in order to validate the proposed framework. Our results provide insights into the point process ability to capture HRV dynamics with a high degree of reliability, thus providing evidence that our framework might be employed for an instantaneous estimate of behavioral states