Artificial intelligence in the neonatal intensive care unit: the time is now.

Artificial intelligence (AI) has the potential to revolutionize the neonatal intensive care unit (NICU) care by leveraging the large-scale, high-dimensional data that are generated by NICU patients. There is an emerging recognition that the confluence of technological progress, commercialization pathways, and rich data sets provides a unique opportunity for AI to make a lasting impact on the NICU. In this perspective article, we discuss four broad categories of AI applications in the NICU: imaging interpretation, prediction modeling of electronic health record data, integration of real-time monitoring data, and documentation and billing. By enhancing decision-making, streamlining processes, and improving patient outcomes, AI holds the potential to transform the quality of care for vulnerable newborns, making the excitement surrounding AI advancements well-founded and the potential for significant positive change stronger than ever before.

Comparison of pulmonary congestion severity using artificial intelligence-assisted scoring versus clinical experts: A secondary analysis of BLUSHED-AHF.

AIM: Acute decompensated heart failure (ADHF) is the leading cause of cardiovascular hospitalizations in the United States. Detecting B-lines through lung ultrasound (LUS) can enhance clinicians' prognostic and diagnostic capabilities. Artificial intelligence/machine learning (AI/ML)-based automated guidance systems may allow novice users to apply LUS to clinical care. We investigated whether an AI/ML automated LUS congestion score correlates with expert's interpretations of B-line quantification from an external patient dataset. METHODS AND RESULTS: This was a secondary analysis from the BLUSHED-AHF study which investigated the effect of LUS-guided therapy on patients with ADHF. In BLUSHED-AHF, LUS was performed and B-lines were quantified by ultrasound operators. Two experts then separately quantified the number of B-lines per ultrasound video clip recorded. Here, an AI/ML-based lung congestion score (LCS) was calculated for all LUS clips from BLUSHED-AHF. Spearman correlation was computed between LCS and counts from each of the original three raters. A total of 3858 LUS clips were analysed on 130 patients. The LCS demonstrated good agreement with the two experts' B-line quantification score (r = 0.894, 0.882). Both experts' B-line quantification scores had significantly better agreement with the LCS than they did with the ultrasound operator's score (p < 0.005, p < 0.001). CONCLUSION: Artificial intelligence/machine learning-based LCS correlated with expert-level B-line quantification. Future studies are needed to determine whether automated tools may assist novice users in LUS interpretation.

Training pathways and careers for neonatologists interested in cardiovascular care.

Neonatologists and neonatal-perinatal trainees continue to be invested in the cardiovascular care of the newborn, many focusing their careers in this area of expertise. Multiple formalized structured and non-structured training pathways have evolved for neonatologists caring for infants with congenital heart disease and other cardiovascular pathologies. Furthermore, the evolution of neonatal hemodynamic science over the past decade has also spawned a formal training pathway in hemodynamics consultation to enhance standard of care and guide the management of infants at risk for cardiovascular compromise. Neonatologists have also chosen to expand upon on their neonatology training with clinical and research exposure to enhance their roles in neonatal cardiovascular care, including fetal care consultation, delivery room management, and perioperative cardiac intensive care consultation. To provide insight and career guidance to interested neonatal trainees and early career physicians, this perspective article highlights several different pathways in the care of neonates with cardiovascular disease.

Cardiac mechanics in infants with Down syndrome in the early neonatal period.

OBJECTIVE: The objective of this study is to test whether myocardial performance is impaired over the first week of age in infants with Down syndrome (DS) without congenital heart disease (CHD). STUDY DESIGN: A prospective cohort study of 20 infants with DS without CHD and 17 healthy term infants comparing echocardiographic measures of left (LV) and right (RV) ventricular function and pulmonary hypertension (PH) on days 1, 2, and 5-7. RESULTS: Indices of PH were higher in the DS group over the study period. Infants with DS had larger RV and smaller LV dimensions. Fractional area change and RV longitudinal strain values were lower in the DS group. LV shear strain values were lower in infants with DS driven by a lack of basal rotation. CONCLUSION: Infants with DS without CHD and echocardiographic evidence of PH during the early neonatal period demonstrate reduced RV systolic function with impaired LV rotational mechanics, reflective of the ventricular interdependence.

Bayesian adaptive trial design in acute heart failure syndromes: moving beyond the mega trial.

Over the last 2 decades, early treatment for patients presenting with acute heart failure syndromes (AHFS) has changed very little. Despite strikingly different underlying disease pathophysiology, presenting signs and symptoms, and precipitants of AHFS, most patients are treated in a homogeneous manner with intravenous loop diuretics. Inhospital studies of new therapies have produced disappointingly neutral results at best. Patients continue to be enrolled in trials long after initial therapy, at a time when vital signs have improved, symptoms have changed, and initiating pathophysiologic processes, such as myocardial and renal injury, have already begun. The "one-size-fits-all" approach to inhospital AHFS trials have been recognized as one potential contributor to the disappointing trial results seen to date. Studies designed to tailor the therapeutic approach to ascertain which treatment modalities are most effective depending on patient phenotypes have not been previously conducted in AHFS because this objective is not traditional in clinical trial design. Utilizing Bayesian adaptive designs in trials of early AHFS provides an opportunity to personalize therapy within the constraints of clinical research. Bayesian adaptive design is increasingly recognized as an efficient method for obtaining valid clinical trial results. At its core, this approach uses existing information at the time of trial initiation, combined with data accumulating during the trial, to identify treatments most beneficial for specific patient subgroups. Based on accumulating evidence, the study then "adapts" its focus to critical differences between treatments within patient subgroups. Bayesian adaptive design is ideally suited for investigating complex, heterogeneous conditions such as AHFS and affords investigators the ability to study multiple treatment approaches and therapies in multiple patient phenotypes within a single trial, while maintaining a reasonable overall sample size. Identifying specific treatment approaches that safely improve symptoms and facilitate early discharge in patients who traditionally are admitted, often for prolonged periods of time, are necessary if we aim to reverse the disappointing trend in clinical trial results. In this study, AHFS clinical researchers and biostatisticians with expertise and experience in designing "personalized medicine" trials describe the development of a Bayesian adaptive design for an emergency department-based AHFS trial.

National Heart, Lung, and Blood Institute working group on emergency department management of acute heart failure: research challenges and opportunities.

This paper details the substance and recommendations arising from a meeting convened by the National Heart, Lung, and Blood Institute in August 2009, to assess the challenges and opportunities of emergency department management of acute heart failure syndrome (AHFS). The assembled faculty represented a large cross section of medical professionals spanning the medical management continuum of patients presenting with acute heart failure and included heart failure cardiologists, emergency physicians, laboratory medicine specialists, nurses, and bench scientists. Their recommendations include proposals regarding the design and conduct of emergency department-based clinical trials, suggestions regarding the development of improved methods for early detection and monitoring of AHFS, and potential needs for expanding translational and applied AHFS focused research and biotechnology. We anticipate that this review will serve as a starting point for future investigations across the spectrum of funding sources.

Evaluation and management of moderate to severe pediatric head trauma.

UNLABELLED: A case of pediatric head trauma is presented with a detailed discussion of current concepts in evaluation and treatment. Management of the moderate to severe head-injured child is reviewed, and best practices for emergency department treatment are discussed. BACKGROUND: Pediatric head trauma is a common and potentially devastating injury. Thorough knowledge of the clinical evaluation and treatment will assist the emergency physician in providing optimal care. DISCUSSION: Using a case-based scenario, the initial management strategies along with rationale evidence-based treatments are reviewed. CONCLUSIONS: Computed tomography scan is the diagnostic test of choice for the moderate to severe head-injured pediatric patient. Several unique scales to describe and prognosticate the head injury are discussed, although currently, the Glasgow Coma Scale is still the most commonly accepted one. Similar to the adult patient, avoidance of hypotension and hypoxia are key to decreasing mortality. Etomidate and succinylcholine remain the choice of medications for intubation. Hyperventilation should be avoided.