Discrepancy between invasive and non-invasive blood pressure readings in extremely preterm infants in the first four weeks of life

Blood Pressure in Critically Ill Children: Exploratory Analyses of Concurrent Invasive and Noninvasive Measurements

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OBJECTIVES:

Differences and biases between directly measured intra-arterial blood pressure and intermittingly measured noninvasive blood pressure using an oscillometric cuff method have been reported in adults and children. At the bedside, clinicians are required to assign a confidence to a specific blood pressure measurement before acting upon it, and this is challenging when there is discordance between measurement techniques. We hypothesized that big data could define and quantify the relationship between noninvasive blood pressure and intra-arterial blood pressure measurements and how they can be influenced by patient characteristics, thereby aiding bedside decision-making.

DESIGN:

A retrospective analysis of cuff blood pressure readings with associated concurrent invasive arterial blood pressure measurements (452,195 noninvasive blood pressure measurements).

SETTING:

Critical care unit at The Hospital for Sick Children, Toronto.

PATIENTS:

Six-thousand two-hundred ninety-seven patients less than or equal to 18 years old, hospitalized in a critical care unit with an indwelling arterial line.

INTERVENTIONS:

None.

MEASUREMENTS AND MAIN RESULTS:

Two-dimensional distributions of intra-arterial blood pressure and noninvasive blood pressure were generated and the conditional distributions of intra-arterial blood pressure examined as a function of the noninvasive systolic, diastolic, or mean blood pressure. Modification of these distributions according to age and gender were examined using a multilevel mixed-effects model. For any given combination of patient age and noninvasive blood pressure, the expected distribution of intra-arterial blood pressure readings exhibited marked variability at the population level and a bias that significantly depended on the noninvasive blood pressure value and age. We developed an online tool that allows exploration of the relationship between noninvasive blood pressure and intra-arterial blood pressure and the conditional probability distributions according to age.

CONCLUSIONS:

A large physiologic dataset provides clinically applicable insights into the relationship between noninvasive blood pressure and intra-arterial blood pressure measurements that can help guide decision-making at the patient bedside.

Echocardiographic assessment of hemodynamic changes in preterm neonates with shock: a prospective pragmatic cohort study

Shock is a state of circulatory dysfunction and its diagnosis is complex in neonates. Hemodynamic assessment using echocardiography has potential to guide better management regimes in neonates with shock. Objective of this study is to analyze changes in the echocardiographic parameters in preterm neonates with shock at presentation and after resolution. In this prospective pragmatic Cohort study, eligible neonates with shock were monitored for changes in echocardiographic parameters at onset of shock and after resolution of shock. Paired data analysis was done for observed changes in the parameters. Based on initial clinical parameters and echocardiographic parameters, infants were assigned into different types of shock. Data of 37 infants were analyzed for baseline clinical and echocardiographic parameters, and data of 31 infants were analyzed for the changes in the observed parameters after shock resolution. Statistically significant changes were observed in inferior vena cava collapsibility index (ICI), left ventricular end diastolic volume (LVEDV), isovolemic ventricular relaxation time (IVRT), left and right ventricular stroke volume, and ejection fraction (EF). There was no agreement between clinical and echocardiographic definitions of shock.Conclusion: We noticed shock has overlapping pathophysiologic features. Our study highlights the importance of baseline documentation of echocardiographic parameters of all infants who are at risk of shock and repeat echocardiography at onset of shock to observe the changes in ICI, LVEDV, IVRT, stroke volume, and EF. This would guide pathophysiological management of shock in neonates. What is Known: • In neonates pathophysiology of shock is overlapping. • Echocardiography can help in better understanding and management of shock. What is New: • Study gives median changes in major echocardiographic parameters in neonatal shock. • These changes can guide for selection of volume and inotropes in management.

Heart Rate Variability in the Perinatal Period: A Critical and Conceptual Review

Neonatal intensive care units (NICUs) greatly expand the use of technology. There is a need to accurately diagnose discomfort, pain, and complications, such as sepsis, mainly before they occur. While specific treatments are possible, they are often time-consuming, invasive, or painful, with detrimental effects for the development of the infant. In the last 40 years, heart rate variability (HRV) has emerged as a non-invasive measurement to monitor newborns and infants, but it still is underused. Hence, the present paper aims to review the utility of HRV in neonatology and the instruments available to assess it, showing how HRV could be an innovative tool in the years to come. When continuously monitored, HRV could help assess the baby’s overall wellbeing and neurological development to detect stress-/pain-related behaviors or pathological conditions, such as respiratory distress syndrome and hyperbilirubinemia, to address when to perform procedures to reduce the baby’s stress/pain and interventions, such as therapeutic hypothermia, and to avoid severe complications, such as sepsis and necrotizing enterocolitis, thus reducing mortality. Based on literature and previous experiences, the first step to efficiently introduce HRV in the NICUs could consist in a monitoring system that uses photoplethysmography, which is low-cost and non-invasive, and displays one or a few metrics with good clinical utility. However, to fully harness HRV clinical potential and to greatly improve neonatal care, the monitoring systems will have to rely on modern bioinformatics (machine learning and artificial intelligence algorithms), which could easily integrate infant’s HRV metrics, vital signs, and especially past history, thus elaborating models capable to efficiently monitor and predict the infant’s clinical conditions. For this reason, hospitals and institutions will have to establish tight collaborations between the obstetric, neonatal, and pediatric departments: this way, healthcare would truly improve in every stage of the perinatal period (from conception to the first years of life), since information about patients’ health would flow freely among different professionals, and high-quality research could be performed integrating the data recorded in those departments.

Continuous vital sign analysis for predicting and preventing neonatal diseases in the twenty-first century: big data to the forefront

In the neonatal intensive care unit (NICU), heart rate, respiratory rate, and oxygen saturation are vital signs (VS) that are continuously monitored in infants, while blood pressure is often monitored continuously immediately after birth, or during critical illness. Although changes in VS can reflect infant physiology or circadian rhythms, persistent deviations in absolute values or complex changes in variability can indicate acute or chronic pathology. Recent studies demonstrate that analysis of continuous VS trends can predict sepsis, necrotizing enterocolitis, brain injury, bronchopulmonary dysplasia, cardiorespiratory decompensation, and mortality. Subtle changes in continuous VS patterns may not be discerned even by experienced clinicians reviewing spot VS data or VS trends captured in the monitor. In contrast, objective analysis of continuous VS data can improve neonatal outcomes by allowing heightened vigilance or preemptive interventions. In this review, we provide an overview of the studies that have used continuous analysis of single or multiple VS, their interactions, and combined VS and clinical analytic tools, to predict or detect neonatal pathophysiology. We make the case that big-data analytics are promising, and with continued improvements, can become a powerful tool to mitigate neonatal diseases in the twenty-first century.