Cognitive biases in pediatric cardiac care.

Medical practitioners are entrusted with the pivotal task of making optimal decisions in healthcare delivery. Despite rigorous training, our confidence in reasoning can fail when faced with pressures, uncertainties, urgencies, difficulties, and occasional errors. Day-to-day decisions rely on swift, intuitive cognitive processes known as heuristic or type 1 decision-making, which, while efficient in most scenarios, harbor inherent vulnerabilities leading to systematic errors.

Quantitative Prediction of Right Ventricular Size and Function From the ECG.

Background: Right ventricular ejection fraction (RVEF) and end-diastolic volume (RVEDV) are not readily assessed through traditional modalities. Deep learning-enabled ECG analysis for estimation of right ventricular (RV) size or function is unexplored.

Methods And Results: We trained a deep learning-ECG model to predict RV dilation (RVEDV >120 mL/m), RV dysfunction (RVEF ≤40%), and numerical RVEDV and RVEF from a 12-lead ECG paired with reference-standard cardiac magnetic resonance imaging volumetric measurements in UK Biobank (UKBB; n=42 938).

E-Health: A Game Changer in Fetal and Neonatal Cardiology?

Technological advancements have greatly impacted the healthcare industry, including the integration of e-health in pediatric cardiology. The use of telemedicine, mobile health applications, and electronic health records have demonstrated a significant potential to improve patient outcomes, reduce healthcare costs, and enhance the quality of care. Telemedicine provides a useful tool for remote clinics, follow-up visits, and monitoring for infants with congenital heart disease, while mobile health applications enhance patient and parents' education, medication compliance, and in some instances, remote monitoring of vital signs.

Neighborhood Childhood Opportunity, Race/Ethnicity, and Surgical Outcomes in Children With Congenital Heart Disease.

Background: Racial and ethnic disparities in outcomes for children with congenital heart disease (CHD) coexist with disparities in educational, environmental, and economic opportunity.

Objectives: We sought to determine the associations between childhood opportunity, race/ethnicity, and pediatric CHD surgery outcomes.

Methods: Pediatric Health Information System encounters aged <18 years from 2016 to 2022 with International Classification of Diseases-10th edition codes for CHD and cardiac surgery were linked to ZIP code-level Childhood Opportunity Index (COI), a score of neighborhood educational, environmental, and socioeconomic conditions.