Association Between Persistent Hypothermia After Cardiopulmonary Bypass in Neonates and Odds of Serious Complications.

Importance: Persistent hypothermia after cardiopulmonary bypass (CPB) in neonates with congenital heart defects (CHD) has been historically considered benign despite lack of evidence on its prognostic significance.

Objectives: Examine associations between the magnitude and pattern of unintentional postoperative hypothermia and odds of complications in neonates with CHD undergoing CPB.

Design: Retrospective cohort study.

Engaging Multidisciplinary Clinical Users in the Design of an Artificial Intelligence-Powered Graphical User Interface for Intensive Care Unit Instability Decision Support.

Background: Critical instability forecast and treatment can be optimized by artificial intelligence (AI)-enabled clinical decision support. It is important that the user-facing display of AI output facilitates clinical thinking and workflow for all disciplines involved in bedside care.

Objectives: Our objective is to engage multidisciplinary users (physicians, nurse practitioners, physician assistants) in the development of a graphical user interface (GUI) to present an AI-derived risk score.

Machine learning for ECG diagnosis and risk stratification of occlusion myocardial infarction.

Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting electrocardiogram (ECG) are increasing in numbers. These patients have a poor prognosis and would benefit from immediate reperfusion therapy, but, currently, there are no accurate tools to identify them during initial triage. Here we report, to our knowledge, the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI.

Developmental care pathway for hospitalised infants with CHD: on behalf of the Cardiac Newborn Neuroprotective Network, a Special Interest Group of the Cardiac Neurodevelopmental Outcome Collaborative.

Infants and children born with CHD are at significant risk for neurodevelopmental delays and abnormalities. Individualised developmental care is widely recognised as best practice to support early neurodevelopment for medically fragile infants born premature or requiring surgical intervention after birth. However, wide variability in clinical practice is consistently demonstrated in units caring for infants with CHD.

Machine Learning for the ECG Diagnosis and Risk Stratification of Occlusion Myocardial Infarction at First Medical Contact.

Patients with occlusion myocardial infarction (OMI) and no ST-elevation on presenting ECG are increasing in numbers. These patients have a poor prognosis and would benefit from immediate reperfusion therapy, but we currently have no accurate tools to identify them during initial triage. Herein, we report the first observational cohort study to develop machine learning models for the ECG diagnosis of OMI.

Engaging clinicians early during the development of a graphical user display of an intelligent alerting system at the bedside.

Background: Artificial Intelligence (AI) is increasingly used to support bedside clinical decisions, but information must be presented in usable ways within workflow. Graphical User Interfaces (GUI) are front-facing presentations for communicating AI outputs, but clinicians are not routinely invited to participate in their design, hindering AI solution potential.

Purpose: To inform early user-engaged design of a GUI prototype aimed at predicting future Cardiorespiratory Insufficiency (CRI) by exploring clinician methods for identifying at-risk patients, previous experience with implementing new technologies into clinical workflow, and user perspectives on GUI screen changes.

Your neighborhood matters: A machine-learning approach to the geospatial and social determinants of health in 9-1-1 activated chest pain.

Healthcare disparities in the initial management of patients with acute coronary syndrome (ACS) exist. Yet, the complexity of interactions between demographic, social, economic, and geospatial determinants of health hinders incorporating such predictors in existing risk stratification models. We sought to explore a machine-learning-based approach to study the complex interactions between the geospatial and social determinants of health to explain disparities in ACS likelihood in an urban community.

The role of machine learning applications in diagnosing and assessing critical and non-critical CHD: a scoping review.

Machine learning uses historical data to make predictions about new data. It has been frequently applied in healthcare to optimise diagnostic classification through discovery of hidden patterns in data that may not be obvious to clinicians. Congenital Heart Defect (CHD) machine learning research entails one of the most promising clinical applications, in which timely and accurate diagnosis is essential.

Performance and limitations of automated ECG interpretation statements in patients with suspected acute coronary syndrome.

Background: The 12‑lead ECG plays an important role in triaging patients with symptomatic coronary artery disease, making automated ECG interpretation statements of "Acute MI" or "Acute Ischemia" crucial, especially during prehospital transport when access to physician interpretation of the ECG is limited. However, it remains unknown how automated interpretation statements correspond to adjudicated clinical outcomes during hospitalization. We sought to evaluate the diagnostic performance of prehospital automated interpretation statements to four well-defined clinical outcomes of interest: confirmed ST- segment elevation myocardial infarction (STEMI); presence of actionable coronary culprit lesions, myocardial necrosis, or any acute coronary syndrome (ACS).

Novel ECG features and machine learning to optimize culprit lesion detection in patients with suspected acute coronary syndrome.

Background: Novel temporal-spatial features of the 12‑lead ECG can conceptually optimize culprit lesions' detection beyond that of classical ST amplitude measurements. We sought to develop a data-driven approach for ECG feature selection to build a clinically relevant algorithm for real-time detection of culprit lesion.

Methods: This was a prospective observational cohort study of chest pain patients transported by emergency medical services to three tertiary care hospitals in the US.

Holding and Mobility of Pediatric Patients With Transthoracic Intracardiac Catheters.

Background: Nursing care of pediatric patients after cardiac surgery consists of close hemodynamic monitoring, often through transthoracic intracardiac catheters, requiring patients to remain on bed rest and limiting holding and mobility.

Objectives: The primary aim of this quality improvement project was to determine the feasibility of safely mobilizing pediatric patients with transthoracic intracardiac catheters out of bed. Once feasibility was established, the secondary aim was to increase the number of days such patients were out of bed.

Nursing Practice With Transthoracic Intracardiac Catheters in Children: International Benchmarking Study.

Background: Transthoracic intracardiac catheters are central catheters placed in the operating room at the conclusion of cardiac surgery for infants and children. Complications associated with these catheters (eg, bleeding, migration, premature removal, infection, leakage, and lack of function) have been described. However, no researchers have addressed the nursing management of these catheters in the intensive care unit, including catheter dressing and securement, mobilization of patients, and flushing the catheters, or the impact of these interventions on patients' outcomes.

Quality Over Quantity: Standardization of Pediatric HeartWare Ventricular Assist Device Dressing Changes.

Pediatric patients are unique both in their diagnosis and clinical presentation before implantation of a ventricular assist device (VAD) and in their driveline site characteristics post-implant. There is limited evidence in scholarly literature that describes complications of pediatric VAD driveline sites or approaches by which to manage them. The Cardiac Center at The Children's Hospital of Philadelphia (CHOP) follows a standard of care for HeartWare VAD (HVAD) dressing changes in the inpatient setting with the goal of transitioning patients to weekly dressing changes by the time they are discharged to home.

Reducing Ischemic Injury From Indwelling Peripheral Arterial Catheters in a Pediatric Cardiac ICU: A Quality Improvement Initiative.

Objectives: To reduce the number of ischemic arterial catheter injuries in children with congenital or acquired heart disease.

Design: This is a quality improvement study with pre- and postintervention groups.

Setting: University-affiliated pediatric cardiac center in a quaternary care freestanding children's hospital.

Just-in-Time Training for High-Risk Low-Volume Therapies: An Approach to Ensure Patient Safety.

High-risk low-volume therapies are those therapies that are practiced infrequently and yet carry an increased risk to patients because of their complexity. Staff nurses are required to competently manage these therapies to treat patients' unique needs and optimize outcomes; however, maintaining competence is challenging. This article describes implementation of Just-in-Time Training, which requires validation of minimum competency of bedside nurses managing high-risk low-volume therapies through direct observation of a return-demonstration competency checklist.

Implementation of a screening, brief intervention, and referral to treatment program using the electronic medical record in a pediatric trauma center.

The purpose of this project was to develop and implement a consistent process for (1) screening adolescents by history for alcohol and substance abuse and (2) providing a motivational interview for change and appropriate referrals as needed. In the 18 months since we implemented the program, 534 patients were eligible for screening. Of these, 442 actually underwent screening and of these, 32 screened positive, thus receiving a brief intervention by social work and referral for further treatment.