The success of an atrioventricular septal defect repair depends largely on the function of the left atrioventricular valve. Given the exposure of this valve to systemic pressures, postoperative haemodynamic management has been of interest, though practices are variable.

A single-centre, retrospective study of infants less than 1 year of age admitted to the paediatric cardiac ICU following atrioventricular septal defect repair between January 2022 and May 2025 was conducted. Utilising high-fidelity physiologic data, the primary aim of this study was to characterise haemodynamics in the first 48 h of progression of left atrioventricular valve regurgitation after complete repair. Regurgitation data was collected from echocardiograms. Generalised estimation equation modelling was done to help further isolate the association of worsening left atrioventricular valve regurgitation with haemodynamic variables.

Among twenty-eight patients, nine (32%) exhibited worsening left atrioventricular valve regurgitation. Haemodynamic parameters significantly correlated with worse left atrioventricular valve regurgitation were increased mean arterial blood pressure, increased blood pressure variability, and decreased cerebral and renal near-infrared spectroscopy. Of note, blood pressure variability had a greater association with worsening left atrioventricular valve regurgitation when compared to absolute mean arterial blood pressure.

In infants recovering from atrioventricular septal defect repair, early postoperative haemodynamic alterations, in particular mean arterial blood pressure variability, are associated with worse left atrioventricular valve function. A high cardiac output, low systemic vascular resistance state with minimal blood pressure variability appears optimal to decrease impact on the left atrioventricular valve.

Non-code dose boluses of epinephrine are utilised in critically ill paediatric patients during periods of hemodynamic deterioration, often with the hopes of preventing a cardiac arrest. Data regarding the physiologic effects of these administrations are limited. The primary aim of this study was to use high-fidelity physiologic data to characterise the effects of intravenous non-code dose bolus epinephrine.

Paediatric patients in the cardiac ICU who received non-code dose bolus epinephrine were identified. Those who received fluid boluses or chest compressions within 2 minutes of bolus epinephrine were excluded. Autoregressive integrated moving average analyses with exogenous variables were conducted to characterise the time-dependent changes in hemodynamic indices. Cluster analyses were then conducted to determine patterns in hemodynamic changes associated with bolus epinephrine.

A total of 71 non-code dose bolus epinephrine administrations were included in the final analyses. Heart rate, blood pressure, and renal near infrared spectroscopy all demonstrated statistically significant changes after bolus epinephrine administration. Peak change in each was 40%, 52%, and 9%, respectively, with peaks occurring between 60 seconds and 120 seconds after administration. Three response-based clusters were identified.

Non-code dose bolus epinephrine is associated with a significant increase in heart rate, blood pressure, and systemic oxygen delivery. Cluster analysis using the peak change identified distinct clinical clusters.

Physiologic data streaming and aggregation platforms such as Sickbay® and Etiometry are becoming increasingly used in the paediatric acute care setting. As these platforms gain popularity in clinical settings, there has been a parallel growth in scholarly interest. The primary aim of this study is to characterise research productivity utilising high-fidelity physiologic streaming data with Sickbay® or Etiometry in the acute care paediatric setting.

A systematic review of the literature was conducted to identify paediatric publications using data from Sickbay® or Etiometry. The resulting publications were reviewed to characterise them and identify trends in these publications.

A total of 41 papers have been published over 9 years using either platform. This involved 179 authors across 21 institutions. Most studies utilised Sickbay®, involved cardiac patients, were single-centre, and did not utilise machine learning or artificial intelligence methods. The number of publications has been significantly increasing over the past 9 years, and the average number of citations for each publication was 7.9.

A total of 41 papers have been published over 9 years using Sickbay® or Etiometry data in the paediatric setting. Although the majority of these are single-centre and pertain to cardiac patients, growth in publication volume suggests growing utilisation of high-fidelity physiologic data beyond clinical applications. Multicentre efforts may help increase the number of centres that can do such work and help drive improvements in clinical care.