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Clinicians caring for neonates with congenital heart disease encounter challenges in clinical care as these infants await surgery or are evaluated for further potential interventions. The newborn with heart disease can present with significant pathophysiologic heterogeneity and therefore requires a personalized therapeutic management plan. However, this complex field of neonatal–cardiac hemodynamics can be simplified. We explore some of these clinical quandaries and include specific sections reviewing the anatomic challenges in these patients. We propose this to serve as a primer focusing on the hemodynamics and therapeutic strategies for the preoperative neonate with systolic dysfunction, diastolic dysfunction, excessive pulmonary blood flow, obstructed pulmonary blood flow, obstructed systemic blood flow, transposition physiology, and single ventricle physiology.

Thromboembolic events post left ventricular assist devices (LVAD) implantation remain a major cause of morbidity and mortality. Mechanical thrombectomy for the treatment of pediatric intracranial thromboembolic events have been reported in LVADs, but never following HeartMate 3 (HM3) implantation. We present the case of an 8-year-old, 26.5 kg male with dilated cardiomyopathy and decompensated heart failure who presented with extensive intracranial thromboembolism in the early postoperative period following HM3 implantation and underwent successful mechanical thrombectomy with a favorable neurological outcome.

Enlarged cardiac structures, especially those on left side have the potential to cause airway compression in pediatric patients with chronic heart failure, owing to their proximity to and impact on the trachea-bronchial tree. Ventricular assist devices are effective in decompressing such hearts thereby alleviating airway problems. Aortopexy serves as an effective airway decompressive measure in cases with persistent airway compression despite effective cardiac decompression by ventricular assist devices. We report a case of 1-year-old male patient with dilated cardiomyopathy in whom airway compression persisted despite ventricular assist device implantation. Aortopexy was effective in relieving airway compression allowing for subsequent extubation and successful heart transplantation.

Accumulating evidence demonstrates the impact of bias that reflects social inequality on the performance of machine learning (ML) models in health care. Given their intended placement within healthcare decision making more broadly, ML tools require attention to adequately quantify the impact of bias and reduce its potential to exacerbate inequalities. We suggest that taking a patient safety and quality improvement approach to bias can support the quantification of bias-related effects on ML. Drawing from the ethical principles underpinning these approaches, we argue that patient safety and quality improvement lenses support the quantification of relevant performance metrics, in order to minimize harm while promoting accountability, justice, and transparency. We identify specific methods for operationalizing these principles with the goal of attending to bias to support better decision making in light of controllable and uncontrollable factors.

Background:The Single Ventricle Reconstruction Trial randomised neonates with hypoplastic left heart syndrome to a shunt strategy but otherwise retained standard of care. We aimed to describe centre-level practice variation at Fontan completion.Methods:Centre-level data are reported as median or median frequency across all centres and range of medians or frequencies across centres. Classification and regression tree analysis assessed the association of centre-level factors with length of stay and percentage of patients with prolonged pleural effusion (>7 days).Results:The median Fontan age (14 centres, 320 patients) was 3.1 years (range from 1.7 to 3.9), and the weight-for-age z-score was −0.56 (−1.35 + 0.44). Extra-cardiac Fontans were performed in 79% (4–100%) of patients at the 13 centres performing this procedure; lateral tunnels were performed in 32% (3–100%) at the 11 centres performing it. Deep hypothermic circulatory arrest (nine centres) ranged from 6 to 100%. Major complications occurred in 17% (7–33%). The length of stay was 9.5 days (9–12); 15% (6–33%) had prolonged pleural effusion. Centres with fewer patients (Conclusions:Fontan perioperative practices varied widely among study centres. Strategies to decrease the duration of pleural effusion and minimise complications may decrease the length of stay. Further research regarding deep hypothermic circulatory arrest is needed to understand its association with prolonged pleural effusion.

OBJECTIVES Physiologic signals are typically measured continuously in the critical care unit, but only recorded at intermittent time intervals in the patient health record. Low frequency data collection may not accurately reflect the variability and complexity of these signals or the patient's clinical state. We aimed to characterize how increasing the temporal window size of observation from seconds to hours modifies the measured variability and complexity of basic vital signs. DESIGN Retrospective analysis of signal data acquired between April 1, 2013, and September 30, 2015. SETTING Critical care unit at The Hospital for Sick Children, Toronto. PATIENTS Seven hundred forty-seven patients less than or equal to 18 years old (63,814,869 data values), within seven diagnostic/surgical groups. INTERVENTIONS None. MEASUREMENTS AND MAIN RESULTS Measures of variability (SD and the absolute differences) and signal complexity (multiscale sample entropy and detrended fluctuation analysis [expressed as the scaling component α]) were calculated for systolic blood pressure, heart rate, and oxygen saturation. The variability of all vital signs increases as the window size increases from seconds to hours at the patient and diagnostic/surgical group level. Significant differences in the magnitude of variability for all time scales within and between groups was demonstrated (p < 0.0001). Variability correlated negatively with patient age for heart rate and oxygen saturation, but positively with systolic blood pressure. Changes in variability and complexity of heart rate and systolic blood pressure from time of admission to discharge were found. CONCLUSIONS In critically ill children, the temporal variability of physiologic signals supports higher frequency data capture, and this variability should be accounted for in models of patient state estimation.

Background No consensus exists on the optimal method to estimate resting energy expenditure (REE) in critically ill children following cardiopulmonary bypass (CPB). This study assesses the accuracy of REE estimation equations in children with congenital heart disease following CPB and tests the feasibility of using allometric scaling as an alternative energy prediction equation. Methods A retrospective analysis of a pediatric cohort following CPB (n = 107; median age 5.2 months, median weight 5.65 kg) who underwent serial measures (median 5 measurements) of REE using indirect calorimetry for 72 hours following CPB. We estimated REE using common estimation methods (Dietary Reference Intake, Harris Benedict, Schofield, World Health Organization [WHO]) as well as novel allometric equations. We compared estimated with measured REE to determine accuracy of each equation using overall discrepancy, calculated as a time‐weighted average of the absolute deviation. Results All equations incorrectly estimated REE at all time points following CPB, with overestimation error predominating. WHO had the lowest discrepancy at 10.7 ± 8.4 kcal/kg/d. The allometric equation was inferior, with an overall discrepancy of 16.9 ± 10.4. There is a strong nonlinear relationship between body surface area and measured REE in this cohort, which is a key source of estimation error using linear equations. Conclusion In a cohort of pediatric patients with congenital heart disease following CPB, no currently utilized clinical estimation equation reliably estimated REE. Allometric scaling proved inferior in estimating REE in children following CPB. Indirect calorimetry remains the ideal method of determining REE after CPB until nonlinear methods can be derived due to overestimation using linear equations.

Supplemental Digital Content is available in the text., OBJECTIVES: To characterize prearrest hemodynamic trajectories of children suffering inhospital cardiac arrest. DESIGN: Exploratory retrospective analysis of arterial blood pressure and electrocardiogram waveforms. SETTING: PICU and cardiac critical care unit in a tertiary-care children’s hospital. PATIENTS: Twenty-seven children with invasive blood pressure monitoring who suffered a total of 31 inhospital cardiac arrest events between June 2017 and June 2019. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: We assessed changes in cardiac output, systemic vascular resistance, stroke volume, and heart rate derived from arterial blood pressure waveforms using three previously described estimation methods. We observed substantial prearrest drops in cardiac output (population median declines of 65–84% depending on estimation method) in all patients in the 10 minutes preceding inhospital cardiac arrest. Most patients’ mean arterial blood pressure also decreased, but this was not universal. We identified three hemodynamic patterns preceding inhospital cardiac arrest: subacute pulseless arrest (n = 18), acute pulseless arrest (n = 7), and bradycardic arrest (n = 6). Acute pulseless arrest events decompensated within seconds, whereas bradycardic and subacute pulseless arrest events deteriorated over several minutes. In the subacute and acute pulseless arrest groups, decreases in cardiac output were primarily due to declines in stroke volume, whereas in the bradycardic group, the decreases were primarily due to declines in heart rate. CONCLUSIONS: Critically ill children exhibit distinct physiologic behaviors prior to inhospital cardiac arrest. All events showed substantial declines in cardiac output shortly before inhospital cardiac arrest. We describe three distinct prearrest patterns with varying rates of decline and varying contributions of heart rate and stroke volume changes to the fall in cardiac output. Our findings suggest that monitoring changes in arterial blood pressure waveform-derived heart rate, pulse pressure, cardiac output, and systemic vascular resistance estimates could improve early detection of inhospital cardiac arrest by up to several minutes. Further study is necessary to verify the patterns witnessed in our cohort as a step toward patient rather than provider-centered definitions of inhospital cardiac arrest.

As part of the PhysioNet/Computing in Cardiology Challenge 2020, we developed a model for multilabel classification of 12-lead electrocardiogram (ECG) data according to specified cardiac abnormalities. Our team, LaussenLabs, developed a novel classifier pipeline with 6 core features (1) the addition of r-peak, p-wave, and t-wave features that were input into the model along with the 12-lead data, (2) data augmentation, (3) competition metric hacking, (4) modified WaveNet architecture, (5) Sigmoid threshold tuning, and (6) model stacking. Our approach received a score of 0.63 using 6-fold cross-validation on the full training data. Unfortunately, our model was unable to run on the test dataset due to time constraints, therefore, our model's final test score is undetermined.

It is no longer a hypothetical worry that artificial intelligence - more specifically, machine learning (ML) - can propagate the effects of pernicious bias in healthcare. To address these problems, some have proposed the development of 'algorithmic fairness' solutions. The primary goal of these solutions is to constrain the effect of pernicious bias with respect to a given outcome of interest as a function of one's protected identity (i.e., characteristics generally protected by civil or human rights legislation. The technical limitations of these solutions have been well-characterized. Ethically, the problematic implication - of developers, potentially, and end users - is that by virtue of algorithmic fairness solutions a model can be rendered 'objective' (i.e., free from the influence of pernicious bias). The ostensible neutrality of these solutions may unintentionally prompt new consequences for vulnerable groups by obscuring downstream problems due to the persistence of real-world bias. The main epistemic limitation of algorithmic fairness is that it assumes the relationship between the extent of bias's impact on a given health outcome and one's protected identity is mathematically quantifiable. The reality is that social and structural factors confluence in complex and unknown ways to produce health inequalities. Some of these are biologic in nature, and differences like these are directly relevant to predicting a health event and should be incorporated into the model's design. Others are reflective of prejudice, lack of access to healthcare, or implicit bias. Sometimes, there may be a combination. With respect to any specific task, it is difficult to untangle the complex relationships between potentially influential factors and which ones are 'fair' and which are not to inform their inclusion or mitigation in the model's design.

After pediatric heart operations, we sought to determine the incidence of unplanned cardiac reinterventions during the same hospitalization, assess risk factors for these reinterventions, and explore associations between reinterventions and outcomes. We hypothesized that younger patients undergoing more complex operations would be at greater risk for unplanned cardiac reinterventions and that operative mortality and postoperative length of stay (PLOS) would be greater in patients who undergo reintervention than in those who do not.Patients aged 18 years or younger in The Society of Thoracic Surgeons Congenital Heart Surgery Database (January 2010 to June 2015) were included. We used multivariable regression to evaluate risk factors for unplanned cardiac reintervention (operation or therapeutic catheterization) and associations of reintervention with operative mortality and PLOS.Of 84,404 patients (117 centers), 21% were neonates and 36% infants. An unplanned cardiac reintervention was performed in 5.4% of patients, including 11.8% of neonates, 5.2% of infants, and 2.8% of children. Independent risk factors for unplanned reintervention included presence of noncardiac anomalies/genetic syndromes, nonwhite race, younger age, lower weight among neonates and infants, prior cardiothoracic operations, preoperative mechanical ventilation, other Society of Thoracic Surgeons preoperative risk factors, and higher Society of Thoracic Surgeons-European Association for Cardiothoracic Surgery Mortality Category (adjusted p0.001 for all). Unplanned reintervention was a risk factor for operative mortality (adjusted odds ratio, 5.3; 95% confidence interval, 4.8 to 5.8; p0.001) and longer PLOS (adjusted relative risk, 2.3; 95% confidence interval, 2.2 to 2.4; p0.001).Unplanned cardiac reinterventions are not rare, particularly in neonates, and are independently associated with operative mortality and increased PLOS. Patients at greater risk may be identified preoperatively, presenting opportunities for quality improvement.

OBJECTIVES Define the distributions of heart rate and intraarterial blood pressure in children at admission to an ICU based on admission diagnosis and examine trends in these physiologic signs over 72 hours from admission (or to discharge if earlier). DESIGN A retrospective analysis of continuously acquired signals. SETTING A quaternary and primary referral children's hospital with a general PICU and cardiac critical care unit. PATIENTS One thousand two hundred eighty-nine patients less than 18 years old were analyzed. Data from individual patient admissions were divided into 19 groups by primary admission diagnosis or surgical procedure. INTERVENTIONS None. MEASUREMENT AND MAIN RESULTS Distributions at admission are dependent on patient age and admission diagnosis (p < 10(-6)). Heart rate decreases over time, whereas arterial blood pressure is relatively stable, with differences seen in the directions and magnitude of these trends when analyzed by diagnosis group (p < 10(-6)). Multiple linear regression analysis shows that patient age, diagnosis group, and physiologic vital sign value at admission explain 50-63% of the variation observed for that physiologic signal at 72 hours (or at discharge if earlier) with admission value having the greatest influence. Furthermore, the variance of either heart rate or arterial blood pressure for the individual patient is smaller than the variance measured at the level of the group of patients with the same diagnosis. CONCLUSIONS This is the first study reporting distributions of continuously measured physiologic variables and trends in their behavior according to admission diagnosis in critically ill children. Differences detected between and within diagnostic groups may aid in earlier recognition of outliers as well as allowing refinement of patient monitoring strategies.

Introduction Non-sustained ventricular tachycardia (NSVT), defined by ventricular tachycardia lasting less than 30 seconds, is common in patients with left ventricular assist devices (LVADs)​. Ventricular tachy-arrhythmias (VAs) such as sustained ventricular tachycardia (VT) and ventricular fibrillation (VF) are uncommon but carry a significant risk of morbidity and death. Case Report A 16-year-old male underwent continuous flow LVAD implantation after presenting with end stage heart failure due to dilated cardiomyopathy. Prior to LVAD, he had an increasing burden of NSVT, which improved post-LVAD insertion. On post-op day 11, he developed palpitations related to sinus tachycardia and monomorphic NSVT. He remained conscious with clinical signs of adequate peripheral perfusion. The VAD flows fell from 5.2 L/min to 1.9 L/min secondary to the effects of the VA on the right ventricle (RV). The VAs then deteriorated into sustained polymorphic VT followed by VF (Image 1). He continued to answer questions appropriately but complained of dizziness and visual changes. Medical management included lidocaine, calcium, magnesium, amiodarone, and epinephrine for RV support. In addition, he received 4 defibrillations, the last of which successfully converted him to sinus rhythm. He did not require chest compressions and maintained adequate cardiac output throughout. He underwent cardiac catheterization which confirmed normal coronary arteries and enabled optimization of LVAD settings. He was discharged home 15 days later on LVAD support, with amiodarone, metoprolol and a home automated external defibrillator. He remains well 10 months later with no further events. Summary VF, a potentially life-threatening arrhythmia, was remarkably well tolerated in a teenager on LVAD support despite some evidence of RV compromise. This case highlights the importance of improved risk stratification of NSVTs in the LVAD population to establish the need for anti-arrhythmic medication or implantable cardioverter-defibrillator.

Introduction This is a case of a 16-year-old male with ccTGA who underwent systemic RVAD (HeartMate III) implantation for severe systemic RV dysfunction. Case Report Based on suboptimal transesophageal (TEE) and epicardial ECHO imaging, the inflow cannula was to be placed anterior and lateral to the true apex of the systemic RV. The ventriculotomy created by a coring device overrode into the ventricular septum and was hidden underneath the inflow cannula ring (Fig 1A). After VAD support was initiated, patient became severely hypoxic with a PO2 of 45-50 mmHg. CPB was re-initiated and the inflow cannula was removed, revealing a large iatrogenic VSD at the cannula insertion point. VSD was closed by bovine pericardial patch and the ventriculotomy was extended laterally to relocate the VAD sewing ring (Fig 1B). After CPB was weaned again, patient initially remained cyanotic and imaging identified possible tiny VSD patch leak with right to left shunting as a potential cause of hypoxia. Pursuing residual VSD closure was deemed unsafe. Rescue nitric oxide (NO) infusion dramatically corrected the desaturation. Summary Iatrogenic VSD in the setting of systemic RVAD causes significant hypoxia but can be effectively repaired by patch closure. Determining the favourable positioning of the inflow cannula in ccTGA is a technical challenge. Using a combination of TEE and epicardial ECHO offers superior guidance for cannula insertion, but can still be inadequate in preventing iatrogenic injury. Furthermore, even small residual VSDs or septal suture holes can be a source of hemodynamically significant right to left shunting due to the high negative pressure from the inflow cannula. In these situations, medical optimization may be the solution. Rationale for the remarkable effect of NO in our case is somewhat unclear, but perhaps explained by improved ventricular ejection and decompression from the subpulmonary LV. Figure 1. ECHO of A) iatrogenic VSD hidden by sewing ring and B) RV after VSD patch closure and lateral repositioning of inflow cannula.=

Background Palliative procedures performed before the Fontan procedure may require ligation of the subclavian arteries, thereby affecting flow to the vertebral arteries. In adults with functionally univentricular heart disease, the implications of altered brainstem vascular anatomy for perioperative management of failing Fontan circulation are not known. Methods We identified abnormal posterior circulation anatomy in an adult patient with failing Fontan circulation who experienced a brainstem stroke after Fontan conversion. We then changed our clinical practice to include detailed preoperative neurologic evaluation of adults with univentricular heart disease and failing Fontan circulation. Here, we report the clinical and neuroimaging findings in 5 consecutive patients before and after this change in practice. Results Five patients ages 28 to 42 years had Fontan procedures performed in childhood, and underwent either Fontan conversion or cardiac transplantation. Patient 1 experienced an episode of decreased cerebral perfusion pressure on postoperative day 3, and experienced an ischemic brainstem stroke causing transient locked-in syndrome. A change in practice was made, and patients 2, 3, and 4 were evaluated preoperatively by the neurocritical care service. These patients then had higher target blood pressures perioperatively and no neurologic injury. Patient 5 was evaluated for symptoms consistent with subclavian steal. Neuroimaging in 3 patients was abnormal, with atrophic vertebral arteries, an occluded vertebral artery, and retrograde perfusion of a vertebral artery. Conclusions In adults with failing Fontan circulation there is a potential for neurologic complications as a result of venous congestion with elevated central venous pressures, and aberrant posterior circulation. The patient's history and brain imaging may be used to identify at-risk patients and to tailor perioperative management during Fontan conversion or heart transplantation to mitigate the risk for brainstem ischemia.

Objective Storage of physiological waveform data for retrospective analysis presents significant challenges. Resultant data can be very large, and therefore becomes expensive to store and complicated to manage. Traditional database approaches are not appropriate for large scale storage of physiological waveforms. Our goal was to apply modern time series compression and indexing techniques to the problem of physiological waveform storage and retrieval. Approach We deployed a vendor-agnostic data collection system and developed domain-specific compression approaches that allowed long term storage of physiological waveform data and other associated clinical and medical device data. The database (called AtriumDB) also facilitates rapid retrieval of retrospective data for high-performance computing and machine learning applications. Main results A prototype system has been recording data in a 42-bed pediatric critical care unit at The Hospital for Sick Children in Toronto, Ontario since February 2016. As of December 2019, the database contains over 720,000 patient-hours of data collected from over 5300 patients, all with complete waveform capture. One year of full resolution physiological waveform storage from this 42-bed unit can be losslessly compressed and stored in less than 300 GB of disk space. Retrospective data can be delivered to analytical applications at a rate of up to 50 million time-value pairs per second. Significance Stored data are not pre-processed or filtered. Having access to a large retrospective dataset with realistic artefacts lends itself to the process of anomaly discovery and understanding. Retrospective data can be replayed to simulate a realistic streaming data environment where analytical tools can be rapidly tested at scale.

IntroductionDiagnostic errors cause significant patient harm and increase costs. Data characterising such errors in the paediatric cardiac intensive care population are limited. We sought to understand the perceived frequency and types of diagnostic errors in the paediatric cardiac ICU.MethodsPaediatric cardiac ICU practitioners including attending and trainee physicians, nurse practitioners, physician assistants, and registered nurses at three North American tertiary cardiac centres were surveyed between October 2014 and January 2015.ResultsThe response rate was 46% (N=200). Most respondents (81%) perceived that diagnostic errors harm patients more than five times per year. More than half (65%) reported that errors permanently harm patients, and up to 18% perceived that diagnostic errors contributed to death or severe permanent harm more than five times per year. Medication side effects and psychiatric conditions were thought to be most commonly misdiagnosed. Physician groups also ranked pulmonary overcirculation and viral illness to be commonly misdiagnosed as bacterial illness. Inadequate care coordination, data assessment, and high clinician workload were cited as contributory factors. Delayed diagnostic studies and interventions related to the severity of the patient’s condition were thought to be the most commonly reported process breakdowns. All surveyed groups ranked improving teamwork and feedback pathways as strategies to explore for preventing future diagnostic errors.ConclusionsPaediatric cardiac intensive care practitioners perceive that diagnostic errors causing permanent harm are common and associated more with systematic and process breakdowns than with cognitive limitations.

Patients with critical congenital heart disease are exposed to significant lifetime morbidity and mortality. Prenatal diagnosis can provide opportunities for anticipatory co-management of patients between palliative subspecialists and the cardiac care team. The benefits of palliative care include support for longitudinal decision-making and avoidance of interventions not consistent with family goals. Effectively counseling families requires an up-to-date understanding of outcomes and knowledge of provider biases. Patient-proxy reported quality of life (QOL) is highly variable in this population and healthcare providers need to be aware of limitations in their own subjective assessment of QOL.

The approach to sepsis in a global setting can appear challenging at first, complicated by differences in infectious etiologies, limitations in resources, variability in treatment and prevention strategies, controversies in application of clinical trial results, public health policy, and variation in cultural norms. In reality, however, the basic approach to sepsis in any context follows core principles within the practice of emergency medicine and critical care. Here, we discuss pediatric sepsis from a global health perspective and review simple strategies to reduce morbidity and mortality.

In children with fulminant myocarditis (FM), we sought to describe presenting characteristics and clinical outcomes, and identify risk factors for cardiac arrest and mechanical circulatory support (MCS). A retrospective review of patients with FM admitted at our institution between January 1, 2004, and June 31, 2015, was performed. We compared characteristics and outcomes of FM patients who received cardiopulmonary resuscitation (CPR) and/or were placed on MCS (CPR/MCS group) to those who did not develop these outcomes (Control group). There were 28 patients who met criteria for FM. Median age was 1.2 years (1 day–17 years). Recovery of myocardial function occurred in 13 patients (46%); 6 (21%) had chronic ventricular dysfunction, 6 (21%) underwent heart transplantation, and 3 (11%) died prior to hospital discharge (including one death following heart transplant). Of the 28 FM patients, 13 (46%) developed cardiac arrest (n = 11) and/or received MCS (n = 8). When compared to controls, patients in the CPR/MCS group had a higher peak b-type natriuretic peptide (BNP) levels (p = 0.03) and peak inotropic scores (p = 0.02). No significant differences were found between groups in demographics; chest radiograph, electrocardiogram, or echocardiogram findings; or initial laboratory values including BNP, troponin, C-reactive protein, lactate, and creatinine (p > 0.05 for all). Children with FM are at high risk of cardiovascular collapse leading to the use of CPR or MCS. Aside from peak BNP levels and inotropic scores, the most presenting characteristics were not helpful for predicting these outcomes. FM patients should ideally receive care in centers that provide emergent MCS.

This paper presents a detailed overview of our submission to the 2017 Physionet Challenge where competitors were asked to build a model to classify a single lead ECG waveform as either normal sinus rhythm, atrial fibrillation, other rhythm, or noisy. A step-by-step machine learning pipeline was assembled, which included signal conditioning, R-peak detection and filtering, and feature extraction. A suite of over 300 features, falling into one of three main feature groups; template features, RRI features, and full waveform features, were extracted from each waveform and an XGBoost, tree-based, gradient boosting classifier was used as the machine learning algorithm. The model produced a cross-validation F1 score of 0.8245, a hidden sub-test score of 0.82, and a hidden test score of 0.8125. The score breakdown for each class (normal sinus rhythm, atrial fibrillation, other rhythm, and noisy) was as follows: F1, NRS = 0.9024, F1, AF = 0.8156, F1, OR = 0.7194, F1, Noise = 0.5705.

This review offers a critical-care perspective on the pathophysiology, monitoring, and management of acute heart failure syndromes in children. An in-depth understanding of the cardiovascular physiological disturbances in this population of patients is essential to correctly interpret clinical signs, symptoms and monitoring data, and to implement appropriate therapies. In this regard, the myocardial force–velocity relationship, the Frank–Starling mechanism, and pressure–volume loops are discussed. A variety of monitoring modalities are used to provide insight into the haemodynamic state, clinical trajectory, and response to treatment. Critical-care treatment of acute heart failure is based on the fundamental principles of optimising the delivery of oxygen and minimising metabolic demands. The former may be achieved by optimising systemic arterial oxygen content and the variables that determine cardiac output: heart rate and rhythm, preload, afterload, and contractility. Metabolic demands may be decreased by a number of ways including positive pressure ventilation, temperature control, and sedation. Mechanical circulatory support should be considered for refractory cases. In the near future, monitoring modalities may be improved by the capture and analysis of complex clinical data such as pressure waveforms and heart rate variability. Using predictive modelling and streaming analytics, these data may then be used to develop automated, real-time clinical decision support tools. Given the barriers to conducting multi-centre trials in this population of patients, the thoughtful analysis of data from multi-centre clinical registries and administrative databases will also likely have an impact on clinical practice.

Pediatric cardiac surgery patients commonly suffer from alterations in vascular tone in the early post-operative period. Pharmacologic manipulation of systemic vascular resistance (SVR) can be complex in a variety of special patient situations including extremes of age, presence of left sided valvar lesions and the use of mechanical circulatory support. Familiarity with how these special circumstances alter SVR and the response to pharmacologic intervention will allow for tailored therapy and hopefully, optimized outcomes. This article addresses the eighth topic of the special issue entitled "Pharmacologic strategies with afterload reduction in low cardiac output syndrome after pediatric cardiac surgery".

Errors in diagnosis cause significant harm and increase costs. Data characterizing such errors in pediatric cardiac intensive care units (PCICU) are limited. An anonymous, 23-item survey was sent to 432 PCICU practitioners (physicians, nurse practitioners, physician assistants and nurses) at 3