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Heart rate variability (HRV) is a noninvasive indicator of the health of neurocardiac interactions of the autonomic nervous system. In adults, decreased HRV correlates with increased cardiovascular mortality. However, the relationship between HRV and outcomes in children with acute decompensated heart failure (ADHF) has not been described. Patients < 21 years old hospitalized with ADHF from 2013 to 2019 were included (N = 79). Primary outcome was defined as death, heart transplant, or mechanical circulatory support (MCS). The median standard deviation of the R-to-R interval in 5-min intervals (SDNN) was calculated from telemetry data obtained across the first 24 h of admission. Patients who met the primary outcome had significantly lower median SDNN (13.8 [7.8, 29.1]) compared to those who did not (24.6 [15.3, 84.4]; p = 0.004). A median SDNN of 20 ms resulted in a sensitivity of 68% and specificity of 69%. Median SDNN < 20 ms represented decreased freedom from primary outcome (p = 0.043) and a hazard ratio of 2.2 in multivariate analysis (p = 0.016). Pediatric patients with ADHF who died, underwent heart transplant, or required MCS had significantly decreased HRV at presentation compared to those that did not. This supports HRV as a noninvasive tool to improve prognostication in children in ADHF., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Background: Junctional ectopic tachycardia (JET) is a prevalent life-threatening arrhythmia in children with congenital heart disease. It has a marked resemblance to normal sinus rhythm, often leading to delay in diagnosis and management., Objective: The study sought to develop a novel multimodal automated arrhythmia detection tool that outperforms existing JET detection tools., Methods: This is a cohort study performed on 40 patients with congenital heart disease at Texas Children's Hospital. Electrocardiogram and central venous pressure waveform data produced by bedside monitors are captured by the Sickbay platform. Convolutional neural networks (CNNs) were trained to classify each heartbeat as either normal sinus rhythm or JET based only on raw electrocardiogram signals., Results: Our best model improved the area under the curve from 0.948 to 0.952 and the true positive rate at 5% false positive rate from 71.8% to 80.6%. Using a 3-model ensemble further improved the area under the curve to 0.953 and the true positive rate at 5% false positive rate to 85.2%. Results on a subset of data show that adding central venous pressure can significantly improve area under the receiver-operating characteristic curve from 0.646 to 0.825., Conclusion: This study validates the efficacy of deep neural networks to notably improve JET detection accuracy. We have built a performant and reliable model that can be used to create a bedside alarm that diagnoses JET, allowing for precise diagnosis of this life-threatening postoperative arrhythmia and prompt intervention. Future validation of the model in a larger cohort is needed., (© 2024 Published by Elsevier Inc. on behalf of Heart Rhythm Society.)

Background: Pediatric hypertrophic cardiomyopathy (HCM) is associated with adverse events. The contribution of diastolic dysfunction to adverse events is poorly understood. The aim of this study was to explore the association between diastolic phenotype and outcomes in pediatric patients with HCM., Methods: Children <18 years of age with diagnosed with HCM were included. Diastolic function parameters were measured from the first echocardiogram at the time of diagnosis, including Doppler flow velocities, tissue Doppler velocities, and left atrial volume and function. Using principal-component analysis, key features in echocardiographic parameters were identified. The principal components were regressed to freedom from major adverse cardiac events (MACE), defined as implantable cardioverter-defibrillator insertion, myectomy, aborted sudden cardiac death, transplantation, need for mechanical circulatory support, and death., Results: Variables that estimate left ventricular filling pressures were highly collinear and associated with MACE (hazard ratio, 0.86; 95% CI, 0.75-1.00), though this was no longer significant after controlling for left ventricular thickness and genetic variation. Left atrial size parameters adjusted for body surface area were independently associated with outcomes in the covariate-adjusted model (hazard ratio, 0.69; 95% CI, 0.5-0.94). The covariate-adjusted model had an Akaike information criterion of 213, an adjusted R 2 value of 0.78, and a concordance index of 0.82 for association with MACE., Conclusion: Echocardiographic parameters of diastolic dysfunction were associated with MACE in this population study, in combination with the severity of left ventricular hypertrophy and genetic variation. Left atrial size parameters adjusted for body surface area were independently associated with adverse events. Additional study of diastolic function parameters adjusted for patient size could facilitate the prediction of adverse events in pediatric patients with HCM., Competing Interests: Conflicts of Interest None., (Copyright © 2023 American Society of Echocardiography. Published by Elsevier Inc. All rights reserved.)

Objectives: Patients with single-ventricle physiology have a significant risk of cardiorespiratory deterioration between their first- and second-stage palliation surgeries. Detection of deterioration episodes may allow for early intervention and improved outcomes., Methods: A prospective study was executed at Nationwide Children's Hospital, Children's Hospital of Philadelphia, and Children's Hospital Colorado to collect physiologic data of subjects with single ventricle physiology during all hospitalizations between neonatal palliation and II surgeries using the Sickbay software platform (Medical Informatics Corp). Timing of cardiorespiratory deterioration events was captured via chart review. The predictive algorithm previously developed and validated at Texas Children's Hospital was applied to these data without retraining. Standard metrics such as receiver operating curve area, positive and negative likelihood ratio, and alert rates were calculated to establish clinical performance of the predictive algorithm., Results: Our cohort consisted of 58 subjects admitted to the cardiac intensive care unit and stepdown units of participating centers over 14 months. Approximately 28,991 hours of high-resolution physiologic waveform and vital sign data were collected using the Sickbay. A total of 30 cardiorespiratory deterioration events were observed. the risk index metric generated by our algorithm was found to be both sensitive and specific for detecting impending events one to two hours in advance of overt extremis (receiver operating curve = 0.927)., Conclusions: Our algorithm can provide a 1- to 2-hour advanced warning for 53.6% of all cardiorespiratory deterioration events in children with single ventricle physiology during their initial postop course as well as interstage hospitalizations after stage I palliation with only 2.5 alarms being generated per patient per day., (© 2023 The Authors.)

This paper describes computer models of three interventions used for treating refractory pulmonary hypertension (RPH). These procedures create either an atrial septal defect, a ventricular septal defect or, in the case of a Potts shunt, a patent ductus arteriosus. The aim in all three cases is to generate a right-to-left shunt, allowing for either pressure or volume unloading of the right side of the heart in the setting of right ventricular failure, while maintaining cardiac output. These shunts are created, however, at the expense of introducing de-oxygenated blood into the systemic circulation, thereby lowering the systemic arterial oxygen saturation. The models developed in this paper are based on compartmental descriptions of human hemodynamics and oxygen transport. An important parameter included in our models is the cross-sectional area of the surgically created defect. Numerical simulations are performed to compare different interventions and various shunt sizes and to assess their impact on hemodynamic variables and oxygen saturations. We also create a model for exercise and use it to study exercise tolerance in simulated pre-intervention and post-intervention RPH patients., (© The Author(s) 2022. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.)

The objective of this study is to evaluate the utility of high-frequency physiologic data during the extubation process and other clinical variables for describing the physiologic profile of extubation failure in neonates with hypoplastic left heart syndrome (HLHS) post-Norwood procedure. This is a single-center, retrospective analysis. Extubation events were collected from January 2016 until July 2021. Extubation failure was defined as the need for re-intubation within 48 h of extubation. The data included streaming heart rate, respiratory rate, blood pressure, arterial oxygen saturation, and cerebral/renal near-infrared spectroscopy (NIRS). The most recent blood laboratory results before extubation were also included. These markers, demographics, clinical characteristics, and ventilatory settings were compared between successful and failed extubations. The analysis included 311 extubations. The extubation failure rate was 10%. According to univariable analyses, failed extubations were preceded by higher respiratory rates (p = 0.029), lower end-tidal CO 2 (p = 0.009), lower pH (p = 0.043), lower serum bicarbonate (p = 0.030), and lower partial pressure of O 2 (p = 0.022). In the first 10 min after extubation, the failed events were characterized by lower arterial (p = 0.028) and cerebral NIRS (p = 0.018) saturations. Failed events were associated with persistently lower values for cerebral NIRS 2 h post-extubation (p = 0.027). In multivariable analysis, vocal cord anomaly, cerebral NIRS at 10 min post-extubation, renal NIRS at pre-extubation and post-extubation, and end-tidal CO 2 at pre-extubation remained as significant co-variables. Oximetric indices before, in the 10 min immediately after, and 2 h after extubation and vocal cords paralysis are associated with failed extubation events in patients with parallel circulation., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

This paper presents a semi-automatic method for the construction of volumetric models of the aortic valve using computed tomography angiography images. Although the aortic valve typically cannot be segmented directly from a computed tomography angiography image, the method described herein uses manually selected samples of an aortic segmentation derived from this image to inform the construction. These samples capture certain physiologic landmarks and are used to construct a volumetric valve model. As a demonstration of the capabilities of this method, valve models for 25 pediatric patients are created. A selected valve anatomy is used to perform fluid-structure interaction simulations using the immersed finite element/difference method with physiologic driving and loading conditions. Simulation results demonstrate this method creates a functional valve that opens and closes normally and generates pressure and flow waveforms that are similar to those observed clinically., (© 2022. The Author(s) under exclusive licence to Biomedical Engineering Society.)

Objective: The purpose of this study was to describe the clinical presentation and physiologic profile of individuals with varying degrees of severity of multisystem inflammatory syndrome in children (MIS-C)., Methods: We performed a retrospective study of children diagnosed with MIS-C admitted to a single quaternary children's hospital from May 2020 to April 2021. We created an MIS-C severity score using the following parameters: hospital admission status (e.g., floor vs intensive care unit), need for inotropic or vasoactive medications, and need for mechanical ventilation. Univariate and multivariate analyses were performed to associate risk factors corresponding to the MIS-C severity score., Results: The study included 152 children who were followed for 14 days post hospital admission. A stepwise forward selection process identified seven physiologic variables associated with "severe" MIS-C according to a logistic regression. Specifically, a combination of elevated creatinine (p = 0.013), international normalized ratio (p = 0.002), brain natriuretic peptide (p = 0.001), white blood cell count (p = 0.009), ferritin (p = 0.041), respiratory rate (p = 0.047), and decreased albumin (p = 0.047) led to an excellent discrimination between mild versus severe MIS-C (AUC = 0.915)., Conclusion: This study derived a physiologic profile associated with the stratification of MIS-C severity., Impact: Based on a cohort of 152 individuals diagnosed with MIS-C, this study derived a nomenclature that stratifies the severity of MIS-C. Investigated demographic, presentational vital signs, and blood analytes associated with severity of illness. Identification of a multivariate physiologic profile that strongly associates with MIS-C severity. This model allows the care team to recognize patients likely to require a higher level of intensive care., (© 2022. The Author(s), under exclusive licence to the International Pediatric Research Foundation, Inc.)

Artificial intelligence (AI) is frequently used in non-medical fields to assist with automation and decision-making. The potential for AI in pediatric cardiology, especially in the echocardiography laboratory, is very high. There are multiple tasks AI is designed to do that could improve the quality, interpretation, and clinical application of echocardiographic data at the level of the sonographer, echocardiographer, and clinician. In this state-of-the-art review, we highlight the pertinent literature on machine learning in echocardiography and discuss its applications in the pediatric echocardiography lab with a focus on automation of the pediatric echocardiogram and the use of echo data to better understand physiology and outcomes in pediatric cardiology. We also discuss next steps in utilizing AI in pediatric echocardiography., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Nguyen, Villemain, Friedberg, Lovstakken, Rusin and Mertens.)

Objectives: To compare the clinical, laboratory, and hemodynamic parameters during hospitalization for patients with multisystem inflammatory syndrome in children (MIS-C), across the Original/Alpha and the Delta variants of severe acute respiratory syndrome coronavirus 2 infection., Design: Retrospective cohort study., Setting: Single-center quaternary children's hospital., Patients: Children with MIS-C admitted from May 2020 to February 2021(Original and Alpha variant cohort) and August 2021 to November 2021 (Delta variant cohort)., Measurements and Main Results: Continuous vital sign measurements, laboratory results, medications data, and hospital outcomes from all subjects were evaluated. Of the 134 patients (102 with Original/Alpha and 32 with Delta), median age was 9 years, 75 (56%) were male, and 61 (46%) were Hispanics. The cohort with Original/Alpha variant had more males (61% vs 41%; p = 0.036) and more respiratory/musculoskeletal symptoms on presentation compared with the Delta variant ( p < 0.05). More patients in the Original/Alpha variant cohort received mechanical ventilation (16 vs 0; p = 0.009). Median hospital length of stay (LOS) was 7 days, and ICU LOS was 3 days for the entire cohort. ICU LOS was shorter in cohort with the Delta variant compared with the Original/Alpha variant (4 vs 2 d; p = 0.001). Only one patient had cardiac arrest, two needed extracorporeal membrane oxygenation, and two needed left ventricular assist device (Impella, Danvers, MA), all in the Original/Alpha variant cohort; no mortality occurred in the entire cohort. MIS-C cohort associated with the Delta variant had lower INR, prothrombin time, WBCs, sodium, phosphorus, and potassium median values ( p < 0.05) during hospitalization compared with the Original/Alpha variants. Hemodynamic assessment showed significant tachycardia in the Original/Alpha variants cohort compared with the Delta variant cohort ( p < 0.05)., Interventions: None., Conclusions: Patients with MIS-C associated with the Delta variants had lower severity during hospitalization compared with the Original/Alpha variant. Analysis of distinct trends in clinical and laboratory parameters with future variants of concerns will allow for potential modification of treatment protocol., Competing Interests: Dr. Jain’s institution received funding from the National Institute for Child Health and Human Development (1R61HD105593). Drs. Jain, Annapragada, Muscal, Vogel, and Rusin received support for article research from the National Institutes of Health (NIH). Dr. Annapragada’s institution received funding from the NIH (R61HD105593); he received funding from Alzeca and Sensulin; he disclosed that he is the inventor on numerous patents that are either licensed to or assigned to his employer, past employers, or other entities. Drs. Muscal and Vogel disclosed the off-label product use of Anakinra. Dr. Vogel’s institution received funding from the NIH; she disclosed the off-label product use of IV immunoglobulin for multisystem inflammatory syndrome in children. Dr. Rusin received funding from Medical Informatics Corp; he disclosed that he is the cofounder and Chief Technology Officer of Medical Informatics, and he disclosed that his wife is the cofounder and Chief Executive Officer of Medical Informatics. The remaining authors have disclosed that they do not have any potential conflicts of interest., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the Society of Critical Care Medicine and the World Federation of Pediatric Intensive and Critical Care Societies.)

In this paper, we develop a pulsatile compartmental model of the Fontan circulation and use it to explore the effects of a fenestration added to this physiology. A fenestration is a shunt between the systemic and pulmonary veins that is added either at the time of Fontan conversion or at a later time for the treatment of complications. This shunt increases cardiac output and decreases systemic venous pressure. However, these hemodynamic benefits are achieved at the expense of a decrease in the arterial oxygen saturation. The model developed in this paper incorporates fenestration size as a parameter and describes both blood flow and oxygen transport. It is calibrated to clinical data from Fontan patients, and we use it to study the impact of a fenestration on several hemodynamic variables, including systemic oxygen availability, effective oxygen availability, and systemic venous pressure. In certain scenarios corresponding to high-risk Fontan physiology, we demonstrate the existence of a range of fenestration sizes in which the systemic oxygen availability remains relatively constant while the systemic venous pressure decreases., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Ahmad, Jin, Penny, Rusin, Peskin and Puelz.)

Social constructs are known risk factors for multisystem inflammatory syndrome in children. A review of 206 patients demonstrated that children who were non-Hispanic Black, over the age of 12 years or living in a disadvantaged neighborhood associated with severe multisystem inflammatory syndrome in children (intensive care unit admission, intubation and/or vasopressor use)., Competing Interests: The authors have no conflicts of interest to disclose., (Copyright © 2022 Wolters Kluwer Health, Inc. All rights reserved.)

Background: Junctional ectopic tachycardia (JET) is a prevalent life-threatening arrhythmia in children with congenital heart disease (CHD), with marked resemblance to normal sinus rhythm (NSR) often leading to delay in diagnosis., Objective: To develop a novel automated arrhythmia detection tool to identify JET., Methods: A single-center retrospective cohort study of children with CHD was performed. Electrocardiographic (ECG) data produced by bedside monitors is captured automatically by the Sickbay platform. Based on the detection of R and P wave peaks, 2 interpretable ECG features are calculated: P prominence median and PR interval interquartile range (IQR). These features are used as input to a simple logistic regression classification model built to distinguish JET from NSR., Results: This study analyzed a total of 64.5 physician-labeled hours consisting of 509,833 cardiac cycles (R-R intervals), from 40 patients with CHD. The extracted P prominence median feature is much smaller in JET compared to NSR, whereas the PR interval IQR feature is larger in JET compared to NSR. The area under the receiver operating characteristic curve for the unseen patient test cohort was 93%. Selecting a threshold of 0.73 results in a true-positive rate of 90% and a false-positive rate of 17%., Conclusion: This novel arrhythmia detection tool identifies JET, using 2 distinctive features of JET in ECG-the loss of a normal P wave and PR relationship-allowing for early detection and timely intervention., (© 2022 Heart Rhythm Society. Published by Elsevier Inc.)

A novel technique was used to calculate pulse pressure variation. The algorithm reliably predicted fluid responsiveness to transfusion, with a receiver operating characteristic area under the curve of 0.89. This technique may assist clinicians in the management of fluids and vasoactive medications for premature infants., (Copyright © 2021 Elsevier Inc. All rights reserved.)

Background: Patients with single-ventricle physiology have a significant risk of cardiorespiratory deterioration between their first and second stage palliation surgeries., Objectives: The objective of this study is to develop and validate a real-time computer algorithm that can automatically recognize physiological precursors of cardiorespiratory deterioration in children with single-ventricle physiology during their interstage hospitalization., Methods: A retrospective study was conducted from prospectively collected physiological data of subjects with single-ventricle physiology. Deterioration events were defined as a cardiac arrest requiring cardiopulmonary resuscitation or an unplanned intubation. Physiological metrics were derived from the electrocardiogram (heart rate, heart rate variability, ST-segment elevation, and ST-segment variability) and the photoplethysmogram (peripheral oxygen saturation and pleth variability index). A logistic regression model was trained to separate the physiological dynamics of the pre-deterioration phase from all other data generated by study subjects. Data were split 50/50 into model training and validation sets to enable independent model validation., Results: Our cohort consisted of 238 subjects admitted to the cardiac intensive care unit and stepdown units of Texas Children's Hospital over a period of 6 years. Approximately 300,000 h of high-resolution physiological waveform and vital sign data were collected using the Sickbay software platform (Medical Informatics Corp., Houston, Texas). A total of 112 cardiorespiratory deterioration events were observed. Seventy-two of the subjects experienced at least 1 deterioration event. The risk index metric generated by our optimized algorithm was found to be both sensitive and specific for detecting impending events 1 to 2 h in advance of overt extremis (receiver-operating characteristic curve area: 0.958; 95% confidence interval: 0.950 to 0.965)., Conclusions: Our algorithm can provide 1 to 2 h of advanced warning for 62% of all cardiorespiratory deterioration events in children with single-ventricle physiology during their interstage period, with only 1 alarm being generated at the bedside per patient per day., Competing Interests: Funding Support and Author Disclosures This research was supported in part by the National Institutes of Health (1R56HL131574 and 1R01HL142994) and the American Heart Association (16BGIA27490024). Dr. Rusin is a cofounder of Medical Informatics Corp.; no funding was provided by the company to support this work. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose., (Copyright © 2021 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)

The discrete empirical interpolation method (DEIM) has been shown to be a viable index-selection technique for identifying representative subsets in data. Having gained some popularity in reducing dimensionality of physical models involving differential equations, its use in subset-/pattern-identification tasks is not yet broadly known within the machine learning community. While it has much to offer as is, the DEIM algorithm is limited in that the number of selected indices cannot exceed the rank of the corresponding data matrix. Although this is not an issue for many data sets, there are cases in which the number of classes represented in a given data set is greater than the rank of the data matrix; in such cases, it is impossible for the standard DEIM algorithm to identify all classes. To overcome this issue, we present a novel extension of DEIM, called E-DEIM. With the proposed algorithm, we also provide some theoretical results for using extensions of DEIM to form the CUR matrix factorization in identifying both rows and columns to approximate the original data matrix. Results from applying variations of E-DEIM to two different data sets indicate that the presented extension can indeed allow for the identification of additional classes along with those selected by standard DEIM. In addition, comparing these results to those of some more familiar methods demonstrates that the proposed deterministic E-DEIM approach including coherence performs comparably to or better than the other evaluated methods and should be considered in future class-identification tasks., Competing Interests: Conflict of interest The only potential conflict to report is that Craig Rusin is a co-founder of Medical Informatics Corp. Medical Informatics Corp has no financial interest in this study. All other authors report no conflicts.

Background: Creatinine values are unreliable within the first weeks of life; however, creatinine is used most commonly to assess kidney function. Controversy remains surrounding the time required for neonates to clear maternal creatinine., Methods: Eligible infants had multiple creatinine lab values and were admitted to the neonatal intensive care unit (NICU). A mathematical model was fit to the lab data to estimate the filtration onset delay, creatinine filtration half-life, and steady-state creatinine concentration for each subject. Infants were grouped by gestational age (GA) [(1) 22-27, (2) >27-32, (3) >32-37, and (4) >37-42 weeks]., Results: A total of 4808 neonates with a mean GA of 34.4 ± 5 weeks and birth weight of 2.34 ± 1.1 kg were enrolled. Median (95% confidence interval) filtration onset delay for Group 1 was 4.3 (3.71, 4.89) days and was significantly different than all other groups (p < 0.001). Creatinine filtration half-life of Groups 1, 2, and 3 were significantly different from each other (p < 0.001). There was no difference in steady-state creatinine concentration among the groups., Conclusions: We quantified the observed kidney behavior in a large NICU population as a function of day of life and GA using creatinine lab results. These results can be used to interpret individual creatinine labs for infants to detect those most at risk for acute kidney injury., Impact: One of the largest cohorts of premature infants to describe the evolution of kidney development and function over their entire hospitalization. New concept introduced of the kidney filtration onset delay, the time needed for the kidney to begin clearance of creatinine, and that it can be used as an early indicator of kidney function. The smallest premature infants from 22 to 27 weeks gestation took the longest time to begin and complete maternal creatinine clearance. Clinicians can easily compare the creatinine level of their patient to the normative curves to improve understanding of kidney function at the bedside.

Objective: To propose a new method to estimate pulse pressure variability (PPV) in the arterial blood pressure waveform., Methods: Traditional techniques of calculating PPV using peak finding have a fundamental flaw that prevents them from accurately resolving PPV for small tidal volumes, limiting the use of PPV to only mechanical ventilated patients. The improved method described here addresses this limitation using Fourier analysis of an oscillatory signal that exhibits a time-varying modulation of its amplitude. The analysis reveals a constraint on the spectral representation that must be satisfied for any oscillatory signal that exhibits a time-varying modulation of its amplitude. This intrinsic mathematical structure is taken advantage of in order to improve the robustness of the algorithm., Results: The applicability of the method is tested using synthetic data and 100 h of physiologic data collected from patients admitted to Texas Children's Hospital., Significance and Conclusion: The proposed method accurately recovers values of PPV at signal-to-noise ratios six times smaller than the traditional method. This is a significant advance for the potential use of PPV to recognize fluid responsiveness during low tidal volume ventilation or spontaneous breathing for which the signal-to-noise ratio is expected to be small., Competing Interests: Declaration of Competing Interest Dr. Rusin declares that he has a conflict with Medical Informatics Corp. Medical Informatics Corp did not financially support this work. All other authors have no conflicts of interest.

Aldosterone-producing zona glomerulosa (zG) cells of the adrenal gland arrange in distinct multi-cellular rosettes that provide a structural framework for adrenal cortex morphogenesis and plasticity. Whether this cyto-architecture also plays functional roles in signaling remains unexplored. To determine if structure informs function, we generated mice with zG-specific expression of GCaMP3 and imaged zG cells within their native rosette structure. Here we demonstrate that within the rosette, angiotensin II evokes periodic Ca v 3-dependent calcium events that form bursts that are stereotypic in form. Our data reveal a critical role for angiotensin II in regulating burst occurrence, and a multifunctional role for the rosette structure in activity-prolongation and coordination. Combined our data define the calcium burst as the fundamental unit of zG layer activity evoked by angiotensin II and highlight a novel role for the rosette as a facilitator of cell communication.

Background: Cerebrovascular critical closing pressure (CrCP) is the arterial blood pressure (ABP) at which cerebral blood flow ceases. Preterm ABP is low and close to CrCP. The diastolic closing margin (diastolic ABP minus CrCP) has been associated with intraventricular hemorrhage in preterm infants. CrCP is estimated from middle cerebral artery cerebral blood flow velocity (CBFV) and ABP waveforms. However, these estimations have not been validated due to a lack of gold standard. Direct observation of the CrCP in preterm infants with hypotension is an opportunity to validate synchronously estimated CrCP., Methods: ABP and CBFV tracings were obtained from 24 extremely low birth weight infants. Recordings where diastolic CBFV was zero were identified. The gold standard CrCP was delineated using piecewise regression of ABP and CBFV values paired by rank ordering and then estimated using a published formula. The measured and estimated values were compared using linear regression and Bland-Altman analysis., Results: Linear regression showed a high degree of correlation between measured and calculated CrCP (r 2  = 0.93)., Conclusions: This is the first study to validate a calculated CrCP by comparing it to direct measurements of CrCP from preterm infants when ABP is lower than CrCP.

Objectives: Acetaminophen is ubiquitously used as antipyretic/analgesic administered IV to patients undergoing surgery and to critically ill patients when enteral routes are not possible. Widely believed to be safe and free of adverse side effects, concerns have developed in adult literature regarding the association of IV acetaminophen and transient hypotension. We hypothesize that there are hemodynamic effects after IV acetaminophen in the PICU and assess the prevalence of such in a large pediatric cardiovascular ICU population using high-fidelity data., Design: Observational study analyzing an enormous set of continuous physiologic data including millions of beat to beat blood pressures surrounding medication administration., Setting: Quaternary pediatric cardiovascular ICU between January 1, 2013, and November 13, 2017., Patients: All patients less than or equal to 18 years old who received IV acetaminophen. Mechanical support devices excluded., Interventions: None., Measurements and Main Results: Physiologic vital sign data were analyzed in 5-minute intervals starting 60 minutes before through 180 minutes after completion. Hypotension defined as mean arterial pressure -15% from baseline and relative hypotension defined -10%. Only doses where patients received no other medications, including vasopressors, within the previous hour were included. t test and a correlation matrix were used to eliminate correlated factors before a logistic regression analysis was performed. Six-hundred eight patients received 777 IV acetaminophen doses. Median age was 8.8 months (interquartile range, 2-62 mo) with a dose of 12.5 mg/kg (interquartile range, 10-15 mg/kg). Data were normalized for age and reference values. One in 20 doses (5%) were associated with hypotension, and one in five (20%) associated with relative hypotension. Univariate analysis revealed hypotension associated with age, baseline mean arterial pressure, and skin temperature (p = 0.05, 0.01, and 0.09). Logistic regression revealed mean arterial pressure (p = 0.01) and age (p = 0.05) remained predictive for hypotension., Conclusions: In isolation of other medication, a hemodynamic response to IV acetaminophen has a higher prevalence in critically ill children with cardiac disease than previously thought and justifies controlled studies in the perioperative and critical care setting. The added impact on individual patient hemodynamics and physiologic instability will require further study.

Mortality or severe disability affects the majority of patients after severe traumatic brain injury (TBI). Adherence to the brain trauma foundation guidelines has overall improved outcomes; however, traditional as well as novel interventions towards intracranial hypertension and secondary brain injury have come under scrutiny after series of negative randomized controlled trials. In fact, it would not be unfair to say there has been no single major breakthrough in the management of severe TBI in the last two decades. One plausible hypothesis for the aforementioned failures is that by the time treatment is initiated for neuroprotection, or physiologic optimization, irreversible brain injury has already set in. We, and others, have recently developed predictive models based on machine learning from continuous time series of intracranial pressure and partial brain tissue oxygenation. These models provide accurate predictions of physiologic crises events in a timely fashion, offering the opportunity for an earlier application of targeted interventions. In this article, we review the rationale for prediction, discuss available predictive models with examples, and offer suggestions for their future prospective testing in conjunction with preventive clinical algorithms. This article is part of the Special Issue entitled "Novel Treatments for Traumatic Brain Injury"., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Background: Arrhythmias are common in the pediatric population. In patients unable to take oral medications or in need of acute therapy, options of intravenous (IV) antiarrhythmic medications are limited. Recently IV sotalol has become readily available, but experience in children is limited., Objective: The purpose of this study was to describe our initial experience with the use of IV sotalol in the pediatric population., Methods: A retrospective study of all pediatric patients receiving IV sotalol was performed. Patient demographic characteristics, presence of congenital heart disease, arrhythmia type, efficacy of IV sotalol use, and adverse effects were evaluated., Results: A total of 47 patients (26 (55%) male and 24 (51%) with congenital heart disease) received IV sotalol at a median age of 2.05 years (interquartile range 0.07-10.03 years) and a median weight of 12.8 kg (interquartile range 3.8-34.2 kg), and 13 (28%) received IV sotalol in the acute postoperative setting. Supraventricular arrhythmias occurred in 40 patients (85%) and ventricular tachycardia in 7 (15%). Among 24 patients receiving IV sotalol for an active arrhythmia, acute termination was achieved in 21 (88%). Twenty-three patients received IV sotalol as maintenance therapy for recurrent arrhythmias owing to inability to take oral antiarrhythmic medications; 19 (83%) were controlled with sotalol monotherapy. No patient required discontinuation of IV sotalol secondary to adverse effects, proarrhythmia, or QT prolongation., Conclusion: IV sotalol is an effective antiarrhythmic option for pediatric patients and may be an excellent agent for acute termination of active arrhythmias. It was well tolerated, with no patient requiring discontinuation secondary to adverse effects., (Copyright © 2018 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

Background: Almost one million prematurely born infants die annually from respiratory insufficiency, predominantly in countries with limited access to respiratory support for neonates. The primary hypothesis tested in the present study was that a modified device for bubble nasal continuous positive airway pressure (Bn-CPAP) would provide lower work of spontaneous breathing, estimated by esophageal pressure-rate products., Methods: Infants born <32 weeks gestation and stable on Bn-CPAP with FiO2 <0.30 were studied within 72 h following delivery. Esophageal pressures during spontaneous breathing were measured during 2 h on standard Bn-CPAP, then 2 h with Bn-CPAP using a modified bubble device presently termed Seattle-PAP, which produces a different pattern of pressure fluctuations and which provided greater respiratory support in preclinical studies, then 2 h on standard Bn-CPAP., Results: All 40 infants enrolled completed the study and follow-up through 36 wks post menstrual age or hospital discharge, whichever came first. No infants were on supplemental oxygen at completion of follow-up. No infants developed pneumothoraces or nasal trauma, and no adverse events attributed to the study were observed. Pressure-rate products on the two devices were not different, but effort of breathing, assessed by areas under esophageal pressure-time curves, was lower with Seattle-PAP than with standard Bn-CPAP., Conclusion: Use of Seattle-PAP to implement Bn-CPAP lowers the effort of breathing exerted even by relatively healthy spontaneously breathing premature neonates. Whether the lower effort of breathing observed with Seattle-PAP translates to improvements in neonatal mortality or morbidity will need to be determined by studies in appropriate patient populations.

Introduction Haemodynamically unstable patients can experience potentially hazardous changes in vital signs related to the exchange of depleted syringes of epinephrine to full syringes. The purpose was to determine the measured effects of epinephrine syringe exchanges on the magnitude, duration, and frequency of haemodynamic disturbances in the hour after an exchange event (study) relative to the hours before (control). Materials and methods Beat-to-beat vital signs recorded every 2 seconds from bedside monitors for patients admitted to the paediatric cardiovascular ICU of Texas Children's Hospital were collected between 1 January, 2013 and 30 June, 2015. Epinephrine syringe exchanges without dose/flow change were obtained from electronic records. Time, magnitude, and duration of changes in systolic blood pressure and heart rate were characterised using Matlab. Significant haemodynamic events were identified and compared with control data., Results: In all, 1042 syringe exchange events were found and 850 (81.6%) had uncorrupted data for analysis. A total of 744 (87.5%) exchanges had at least 1 associated haemodynamic perturbation including 2958 systolic blood pressure and 1747 heart-rate changes. Heart-rate perturbations occurred 37% before exchange and 63% after exchange, and 37% of systolic blood pressure perturbations happened before syringe exchange, whereas 63% occurred after syringe exchange with significant differences found in systolic blood pressure frequency (p<0.001), duration (p<0.001), and amplitude (p<0.001) compared with control data., Conclusions: This novel data collection and signal processing analysis showed a significant increase in frequency, duration, and magnitude of systolic blood pressure perturbations surrounding epinephrine syringe exchange events.

In this paper, we use the CUR matrix factorization as a means of dimension reduction to identify important subsequences in electrocardiogram (ECG) time series. As opposed to other factorizations typically used in dimension reduction that characterize data in terms of abstract representatives (for example, an orthogonal basis), the CUR factorization describes the data in terms of actual instances within the original data set. Therefore, the CUR characterization can be directly related back to the clinical setting. We apply CUR to a synthetic ECG data set as well as to data from the MIT-BIH Arrhythmia, MGH-MF, and Incart databases using the discrete empirical interpolation method (DEIM) and an incremental QR factorization. In doing so, we demonstrate that CUR is able to identify beat morphologies that are representative of the data set, including rare-occurring beat events, providing a robust summarization of the ECG data. We also see that using CUR-selected beats to label the remaining unselected beats via 1-nearest neighbor classification produces results comparable to those presented in other works. While the electrocardiogram is of particular interest here, this work demonstrates the utility of CUR in detecting representative subsequences in quasiperiodic physiological time series., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Understanding cerebral blood flow dynamics is crucial for the care of patients at risk of poor cerebral perfusion. We describe an effective model of cerebral hemodynamics designed to reveal important macroscopic features of cerebral blood flow without having to resolve the detailed microvasculature of the brain. Based on principles of fluid and elastic dynamics and vascular pressure-reactivity, the model quantifies the physical means by which the vasculature executes autoregulatory reflexes. We demonstrate that the frequency response of the proposed model matches experimental measurements and explains the influence of mechanical factors on the autoregulatory performance. Analysis of the model indicates the existence of an optimal mean arterial pressure which minimizes the sensitivity of the flow to changes in perfusion pressure across the frequency spectrum of physiological oscillations. We highlight the simplicity of the model and its potential to improve monitoring of brain perfusion via real-time computational simulations of cerebro- and cardio-vascular interventions., (Copyright © 2017 Elsevier Inc. All rights reserved.)

We formulate and study a new mathematical model of pulmonary hypertension. Based on principles of fluid and elastic dynamics, we introduce a model that quantifies the stiffening of pulmonary vasculature (arteries and arterioles) to reproduce the hemodynamics of the pulmonary system, including physiologically consistent dependence between compliance and resistance. This pulmonary model is embedded in a closed-loop network of the major vessels in the body, approximated as one-dimensional elastic tubes, and zero-dimensional models for the heart and other organs. Increasingly severe pulmonary hypertension is modeled in the context of two extreme scenarios: (1) no cardiac compensation and (2) compensation to achieve constant cardiac output. Simulations from the computational model are used to estimate cardiac workload, as well as pressure and flow traces at several locations. We also quantify the sensitivity of several diagnostic indicators to the progression of pulmonary arterial stiffening. Simulation results indicate that pulmonary pulse pressure, pulmonary vascular compliance, pulmonary RC time, luminal distensibility of the pulmonary artery, and pulmonary vascular impedance are much better suited to detect the early stages of pulmonary hypertension than mean pulmonary arterial pressure and pulmonary vascular resistance, which are conventionally employed as diagnostic indicators for this disease.

Background/purpose: The purpose of this study was to develop a computational algorithm that would predict the need for ECMO in neonates with congenital diaphragmatic hernia (CDH)., Methods: CDH patients from August 2010 to 2016 were enrolled in a study to continuously measure cerebral tissue oxygen saturation (cStO2) of left and right cerebral hemispheres. NIRS devices utilized were FORE-SIGHT, CASMED and INVOS 5100, Somanetics. Using MATLAB©, a data randomization function was used to deidentify and blindly group patient's data files as follows: 12 for the computational model development phase (6 ECMO and 6 non-ECMO) and the remaining patients for the validation phase., Results: Of the 56 CDH patients enrolled, 22 (39%) required ECMO. During development of the algorithm, a difference between right and left hemispheric cerebral oxygenation via NIRS (ΔHCO) was noted in CDH patients that required ECMO. Using ROC analysis, a ΔHCO cutoff >10% was predictive of needing ECMO (AUC: 0.92; sensitivity: 85%; and specificity: 100%). The algorithm predicted need for ECMO within the first 12h of life and at least 6h prior to the clinical decision for ECMO with 88% sensitivity and 100% specificity., Conclusion: This computational algorithm of cerebral NIRS predicts the need for ECMO in neonates with CDH., Level of Evidence: II., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Fontan patients may undergo additional surgical modifications to mitigate complications like protein-losing enteropathy, liver cirrhosis, and other issues in their splanchnic circulation. Recent case reports show promise for several types of modifications, but the subtle effects of these surgeries on the circulation are not well understood. In this paper, we employ mathematical modeling of blood flow to systematically quantify the impact of these surgical changes on extracardiac Fontan hemodynamics. We investigate two modifications: (1) the fenestrated Fontan and (2) the Fontan with hepatic vein exclusion. Closed-loop hemodynamic models are used, which consist of one-dimensional networks for the major vessels and zero-dimensional models for the heart and organ beds. Numerical results suggest the hepatic vein exclusion has the greatest overall impact on the hemodynamics, followed by the largest sized fenestration. In particular, the hepatic vein exclusion drastically lowers portal venous pressure while the fenestration decreases pulmonary artery pressure. Both modifications increase flow to the intestines, a finding consistent with their utility in clinical practice for combating complications in the splanchnic circulation., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

One-dimensional blood flow models take the general form of nonlinear hyperbolic systems but differ in their formulation. One class of models considers the physically conserved quantities of mass and momentum, while another class describes mass and velocity. Further, the averaging process employed in the model derivation requires the specification of the axial velocity profile; this choice differentiates models within each class. Discrepancies among differing models have yet to be investigated. In this paper, we comment on some theoretical differences among models and systematically compare them for physiologically relevant vessel parameters, network topology, and boundary data. In particular, the effect of the velocity profile is investigated in the cases of both smooth and discontinuous solutions, and a recommendation for a physiological model is provided. The models are discretized by a class of Runge-Kutta discontinuous Galerkin methods.

Objective: We evaluated ST-segment monitoring to detect clinical decompensation in infants with single ventricle anatomy. We proposed a signal processing algorithm for ST-segment instability and hypothesized that instability is associated with cardiopulmonary arrests., Design: Retrospective, observational study., Setting: Tertiary children's hospital 21-bed cardiovascular ICU and 36-bed step-down unit., Patients: Twenty single ventricle infants who received stage 1 palliation surgery between January 2013 and January 2014. Twenty rapid response events resulting in cardiopulmonary arrests (arrest group) were recorded in 13 subjects, and nine subjects had no interstage cardiopulmonary arrest (control group)., Interventions: None., Measurements and Main Results: Arrest data were collected over the 4-hour time window prior to cardiopulmonary arrest. Control data were collected from subjects with no interstage arrest using the 4-hour time window prior to cardiovascular ICU discharge. A paired subgroup analysis was performed comparing subject 4-hour windows prior to arrest (prearrest group) with 4-hour windows prior to discharge (postarrest group). Raw values of ST segments were compared between groups. A 3D ST-segment vector was created using three quasi-orthogonal leads (II, aVL, and V5). Magnitude and instability of this continuous vector were compared between groups. There was no significant difference in mean unprocessed ST-segment values in the arrest and control groups. Utilizing signal processing, there was an increase in the ST-vector magnitude (p = 0.02) and instability (p = 0.008) in the arrest group. In the paired subgroup analysis, there was an increase in the ST-vector magnitude (p = 0.05) and instability (p = 0.05) in the prearrest state compared with the postarrest state prior to discharge., Conclusions: In single ventricle patients, increased ST instability and magnitude were associated with rapid response events that required intervention for cardiopulmonary arrest, whereas conventional ST-segment monitoring did not differentiate an arrest from control state.

Objectives: To develop computer algorithms that can recognize physiologic patterns in traumatic brain injury patients that occur in advance of intracranial pressure and partial brain tissue oxygenation crises. The automated early detection of crisis precursors can provide clinicians with time to intervene in order to prevent or mitigate secondary brain injury., Design: A retrospective study was conducted from prospectively collected physiologic data. intracranial pressure, and partial brain tissue oxygenation crisis events were defined as intracranial pressure of greater than or equal to 20 mm Hg lasting at least 15 minutes and partial brain tissue oxygenation value of less than 10 mm Hg for at least 10 minutes, respectively. The physiologic data preceding each crisis event were used to identify precursors associated with crisis onset. Multivariate classification models were applied to recorded data in 30-minute epochs of time to predict crises between 15 and 360 minutes in the future., Setting: The neurosurgical unit of Ben Taub Hospital (Houston, TX)., Subjects: Our cohort consisted of 817 subjects with severe traumatic brain injury., Measurements and Main Results: Our algorithm can predict the onset of intracranial pressure crises with 30-minute advance warning with an area under the receiver operating characteristic curve of 0.86 using only intracranial pressure measurements and time since last crisis. An analogous algorithm can predict the start of partial brain tissue oxygenation crises with 30-minute advanced warning with an area under the receiver operating characteristic curve of 0.91., Conclusions: Our algorithms provide accurate and timely predictions of intracranial hypertension and tissue hypoxia crises in patients with severe traumatic brain injury. Almost all of the information needed to predict the onset of these events is contained within the signal of interest and the time since last crisis.

While survival of children with complex congenital heart defects has improved in recent years, roughly half suffer neurological deficits suspected to be related to cerebral ischemia. Here we report the first demonstration of optical diffuse correlation spectroscopy (DCS) for continuous and non-invasive monitoring of cerebral microvascular blood flow during complex human neonatal or cardiac surgery. Comparison between DCS and Doppler ultrasound flow measurements during deep hypothermia, circulatory arrest, and rewarming were in good agreement. Looking forward, DCS instrumentation, alone and with NIRS, could provide access to flow and metabolic biomarkers needed by clinicians to adjust neuroprotective therapy during surgery.

Objective: To determine whether the diastolic closing margin (DCM), defined as diastolic blood pressure minus critical closing pressure, is associated with the development of early severe intraventricular hemorrhage (IVH)., Study Design: A reanalysis of prospectively collected data was conducted. Premature infants (gestational age 23-31 weeks) receiving mechanical ventilation (n = 185) had ∼1-hour continuous recordings of umbilical arterial blood pressure, middle cerebral artery cerebral blood flow velocity, and PaCO2 during the first week of life. Models using multivariate generalized linear regression and purposeful selection were used to determine associations with severe IVH., Results: Severe IVH (grades 3-4) was observed in 14.6% of the infants. Irrespective of the model used, Apgar score at 5 minutes and DCM were significantly associated with severe IVH. A clinically relevant 5-mm Hg increase in DCM was associated with a 1.83- to 1.89-fold increased odds of developing severe IVH., Conclusion: Elevated DCM was associated with severe IVH, consistent with previous animal data showing that IVH is associated with hyperperfusion. Measurement of DCM may be more useful than blood pressure in defining cerebral perfusion in premature infants., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Objectives: Sudden death is common in patients with hypoplastic left heart syndrome and comparable lesions with parallel systemic and pulmonary circulation from a common ventricular chamber. It is hypothesized that unforeseen acute deterioration is preceded by subtle changes in physiologic dynamics before overt clinical extremis. Our objective was to develop a computer algorithm to automatically recognize precursors to deterioration in real-time, providing an early warning to care staff., Methods: Continuous high-resolution physiologic recordings were obtained from 25 children with parallel systemic and pulmonary circulation who were admitted to the cardiovascular intensive care unit of Texas Children's Hospital between their early neonatal palliation and stage 2 surgical palliation. Instances of cardiorespiratory deterioration (defined as the need for cardiopulmonary resuscitation or endotracheal intubation) were found via a chart review. A classification algorithm was applied to both primary and derived parameters that were significantly associated with deterioration. The algorithm was optimized to discriminate predeterioration physiology from stable physiology., Results: Twenty cardiorespiratory deterioration events were identified in 13 of the 25 infants. The resulting algorithm was both sensitive and specific for detecting impending events, 1 to 2 hours in advance of overt extremis (receiver operating characteristic area = 0.91, 95% confidence interval = 0.88-0.94)., Conclusions: Automated, intelligent analysis of standard physiologic data in real-time can detect signs of clinical deterioration too subtle for the clinician to observe without the aid of a computer. This metric may serve as an early warning indicator of critical deterioration in patients with parallel systemic and pulmonary circulation., (Copyright © 2016 The American Association for Thoracic Surgery. Published by Elsevier Inc. All rights reserved.)

Background/purpose: The aim of this study was to create a computational simulator to serve as an early alert system for cerebral hypoxemia prior to the onset of clinical symptoms., Methods: Neonates with congenital diaphragmatic hernia (Jan 2010-Dec 2014) were recruited to collect continuous measurements of cerebral tissue oxygen saturation (cStO2) using a near-infrared spectroscopy (NIRS) device (FORE-SIGHT®, CASMED). Clinicians were blinded to NIRS data and treated infants based on pre-established clinical protocols. Charts were reviewed retrospectively to identify clinical events of hypoxemia (spontaneous, sustained decrease in preductal SpO2<85% leading to ventilator changes). We developed a computational algorithm that determined baseline values, variability and event data for each patient., Results: Twenty-three of 36 patients enrolled met data criteria. The algorithm anticipated an event at least 15 minutes prior to the event in 77% of cases, with an average pre-event detection of 47 minutes (range 16-122 minutes). Post-event StO2 (SpO2<85%) was determined to be 63.7% ± 11.7. In this computational model, the sensitivity to distinguish low states of cerebral perfusion was 94% with a specificity of 96%., Conclusion: We have developed a computational algorithm with an early warning system that has the potential of being translated into a real-time clinical interface that may improve management of neonates., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Premature infants are at risk of vascular neurological insults. Hypotension and hypertension are considered injurious, but neither condition is defined with consensus. Critical closing pressure (CrCP) is the arterial blood pressure (ABP) at which cerebral blood flow ceases. CrCP may serve to define subject-specific low or high ABP. Our objective was to quantify CrCP as a function of gestational age (GA). One hundred eighty-six premature infants with a GA range of 23-33 weeks, were monitored with umbilical artery catheters and transcranial Doppler insonation of middle cerebral artery flow velocity (FV) for 1-h sessions over the first week of life. CrCP was calculated using an impedance model derivation with Doppler-based estimations of cerebrovascular resistance and compliance. CrCP increased significantly with GA (r = 0.47; slope = 1.4 mmHg/week gestation), an association that persisted with multivariate analysis (p < 0.001). Higher diastolic ABP and higher GA were associated with increased CrCP (p <0.001 for both). CrCP increases significantly at the end of the second and beginning of the third trimester. The low CrCP observed in premature infants may explain their ability to tolerate low ABP without global cerebral infarct or hemorrhage.

Our objective was to quantify cerebrovascular autoregulation as a function of gestational age (GA) and across the phases of the cardiac cycle. One hundred eighty-six premature infants, with a GA range of 23-33 weeks, were monitored using umbilical artery catheters and transcranial Doppler insonation of middle cerebral artery flow velocity (FV) for 1-h sessions over the first week of life. Autoregulation was quantified as a moving correlation coefficient between systolic arterial blood pressure (ABP) and systolic FV (Sx); mean ABP and mean FV (Mx); diastolic ABP and diastolic FV (Dx). Autoregulation was compared across GAs for each aspect of the cardiac cycle. Systolic FV was pressure-passive in infants with the lowest GA, and Sx decreased with increased GA (r = -0.3; p < 0.001). By contrast, Dx was elevated in all subjects, and showed minimal change with increased GA (r = -0.06; p = 0.05). Multivariate analysis confirmed that GA (p < 0.001) and the "closing margin" (p < 0.01) were associated with Sx. Premature infants have low and almost always pressure-passive diastolic cerebral blood FV. Conversely, the regulation of systolic cerebral blood FV by autoregulation was manifested in this cohort at a GA of between 23 and 33 weeks.

Premature infants are at an increased risk of intraventricular hemorrhage (IVH). The roles of hypotension and hyperemia are still debated. Critical closing pressure (CrCP) is the arterial blood pressure (ABP) at which cerebral blood flow (CBF) ceases. When diastolic ABP is equal to CrCP, CBF occurs only during systole. The difference between diastolic ABP and CrCP is the diastolic closing margin (DCM). We hypothesized that a low DCM was associated with IVH. One hundred eighty-six premature infants, with a gestational age (GA) range of 23-33 weeks, were monitored with umbilical artery catheters and transcranial Doppler insonation of middle cerebral artery flow velocity for 1-h sessions over the first week of life. CrCP was calculated linearly and using an impedance model. A multivariate generalized linear regression model was used to determine associations with severe IVH (grades 3-4). An elevated DCM by either method was associated with IVH (p < 0.0001 for the linear method; p < 0.001 for the impedance model). Lower 5-min Apgar scores, elevated mean CBF velocity, and lower mean ABP were also associated with IVH (p < 0.0001). Elevated DCM, not low DCM, was associated with severe IVH in this cohort.

Mathematical modeling at the level of the full cardiovascular system requires the numerical approximation of solutions to a one-dimensional nonlinear hyperbolic system describing flow in a single vessel. This model is often simulated by computationally intensive methods like finite elements and discontinuous Galerkin, while some recent applications require more efficient approaches (e.g. for real-time clinical decision support, phenomena occurring over multiple cardiac cycles, iterative solutions to optimization/inverse problems, and uncertainty quantification). Further, the high speed of pressure waves in blood vessels greatly restricts the time step needed for stability in explicit schemes. We address both cost and stability by presenting an efficient and unconditionally stable method for approximating solutions to diagonal nonlinear hyperbolic systems. Theoretical analysis of the algorithm is given along with a comparison of our method to a discontinuous Galerkin implementation. Lastly, we demonstrate the utility of the proposed method by implementing it on small and large arterial networks of vessels whose elastic and geometrical parameters are physiologically relevant.

Background: Premature infants are at risk of vascular neurologic insults. Hypotension and hypertension are considered injurious, but neither condition is defined with consensus. Cerebrovascular critical closing pressure (CrCP) is the arterial blood pressure (ABP) at which cerebral blood flow (CBF) ceases. CrCP may serve to define subject-specific low or high ABP. Our objective was to determine the ontogeny of CrCP., Methods: Premature infants (n = 179) with gestational age (GA) from 23-31 wk had recordings of ABP and middle cerebral artery flow velocity twice daily for 3 d and then daily for the duration of the first week of life. All infants received mechanical ventilation. CrCP was calculated using an impedance-model derivation with Doppler-based estimations of cerebrovascular resistance and compliance. The association between GA and CrCP was determined in a multivariate analysis., Results: The median (interquartile range) CrCP for the cohort was 22 mm Hg (19-25 mm Hg). CrCP increased significantly with GA (r = 0.6; slope = 1.4 mm Hg/wk gestation), an association that persisted with multivariate analysis (P < 0.0001)., Conclusion: CrCP increased significantly from 23 to 31 wk gestation. The low CrCP observed in very premature infants may explain their ability to tolerate low ABP without global cerebral infarct or hemorrhage.

In this article we derive applicable expressions for the macroscopic compliance and resistance of microvascular networks. This work yields a lumped-parameter model to describe the hemodynamics of capillary beds. Our derivation takes into account the multiscale nature of capillary networks, the influence of blood volume and pressure on the effective resistance and compliance, as well as, the nonlinear interdependence between these two properties. As a result, we obtain a simple and useful model to study hypotensive and hypertensive phenomena. We include two implementations of our theory: (i) pulmonary hypertension where the flow resistance is predicted as a function of pulmonary vascular tone. We derive from first-principles the inverse proportional relation between resistance and compliance of the pulmonary tree, which explains why the RC factor remains nearly constant across a population with increasing severity of pulmonary hypertension. (ii) The critical closing pressure in pulmonary hypotension where the flow rate dramatically decreases due to the partial collapse of the capillary bed. In both cases, the results from our proposed model compare accurately with experimental data., (Copyright © 2015 Elsevier Inc. All rights reserved.)

Objective: To quantify cerebrovascular autoregulation as a function of gestational age (GA) and across the phases of the cardiac cycle., Study Design: The present study is a hypothesis-generating re-analysis of previously published data. Premature infants (n=179) with a GA range of 23 to 33 weeks were monitored with umbilical artery catheters and transcranial Doppler insonation of the middle cerebral artery for 1-h sessions over the first week of life. Autoregulation was quantified by three methods, as a moving correlation coefficient between: (1) systolic arterial blood pressure (ABP) and systolic cerebral blood flow (CBF) velocity (Sx); (2) mean ABP and mean CBF velocity (Mx); and (3) diastolic ABP and diastolic CBF velocity (Dx). Comparisons of individual and cohort cerebrovascular pressure autoregulation were made across GA for each aspect of the cardiac cycle., Results: Systolic, mean and diastolic ABP increased with GA (r=0.3, 0.4 and 0.4; P<0.0001). Systolic CBF velocity was pressure-passive in infants with the lowest GA, and Sx decreased with advancing GA (r=-0.3; P<0.001), indicating increased capacity for cerebral autoregulation during systole during development. By contrast, Dx was elevated, indicating dysautoregulation, in all subjects and showed minimal change with advancing GA (r=-0.06; P=0.05). Multivariate analysis confirmed that both GA (P<0.001) and 'effective cerebral perfusion pressure' (ABP minus critical closing pressure (CrCP); P<0.01) were associated with Sx., Conclusion: Premature infants have low and usually pressure-passive diastolic CBF velocity. By contrast, the regulation of systolic CBF velocity by pressure autoregulation developed in this cohort between 23 and 33 weeks GA. Elevated effective cerebral perfusion pressure derived from the CrCP was associated with dysautoregulation.

Objective: In 2006 the apnea of prematurity (AOP) consensus group identified inaccurate counting of apnea episodes as a major barrier to progress in AOP research. We compare nursing records of AOP to events detected by a clinically validated computer algorithm that detects apnea from standard bedside monitors., Study Design: Waveform, vital sign, and alarm data were collected continuously from all very low-birth-weight infants admitted over a 25-month period, analyzed for central apnea, bradycardia, and desaturation (ABD) events, and compared with nursing documentation collected from charts. Our algorithm defined apnea as > 10 seconds if accompanied by bradycardia and desaturation., Results: Of the 3,019 nurse-recorded events, only 68% had any algorithm-detected ABD event. Of the 5,275 algorithm-detected prolonged apnea events > 30 seconds, only 26% had nurse-recorded documentation within 1 hour. Monitor alarms sounded in only 74% of events of algorithm-detected prolonged apnea events > 10 seconds. There were 8,190,418 monitor alarms of any description throughout the neonatal intensive care unit during the 747 days analyzed, or one alarm every 2 to 3 minutes per nurse., Conclusion: An automated computer algorithm for continuous ABD quantitation is a far more reliable tool than the medical record to address the important research questions identified by the 2006 AOP consensus group., (Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.)

Background: Analysis and modeling of data monitoring vital signs and waveforms in patients in a surgical/trauma intensive care unit (STICU) may allow for early identification and treatment of patients with evolving respiratory failure., Methods: Between February 2011 and March 2012, data of vital signs and waveforms for STICU patients were collected. Every-15-minute calculations (n = 172,326) of means and standard deviations of heart rate (HR), respiratory rate (RR), pulse-oxygen saturation (SpO2), cross-correlation coefficients, and cross-sample entropy for HR-RR, RR-SpO2, and HR-SpO2, and cardiorespiratory coupling were calculated. Urgent intubations were recorded. Univariate analyses were performed for the periods <24 and ≥24 hours before intubation. Multivariate predictive models for the risk of unplanned intubation were developed and validated internally by subsequent sample and bootstrapping techniques., Results: Fifty unplanned intubations (41 patients) were identified from 798 STICU patients. The optimal multivariate predictive model (HR, RR, and SpO2 means, and RR-SpO2 correlation coefficient) had a receiving operating characteristic (ROC) area of 0.770 (95% confidence interval [CI], 0.712-0.841). For this model, relative risks of intubation in the next 24 hours for the lowest and highest quintiles were 0.20 and 2.95, respectively (15-fold increase, baseline risk 1.46%). Adding age and days since previous extubation to this model increased ROC area to 0.865 (95 % CI, 0.821-0.910)., Conclusion: Among STICU patients, a multivariate model predicted increases in risk of intubation in the following 24 hours based on vital sign data available currently on bedside monitors. Further refinement could allow for earlier detection of respiratory decompensation and intervention to decrease preventable morbidity and mortality in surgical/trauma patients., (Copyright © 2013 Mosby, Inc. All rights reserved.)