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Patient-level factors related to cardiac arrest in the pediatric cardiac population are well understood but may be unmodifiable. The impact of cardiac ICU organizational and personnel factors on cardiac arrest rates and outcomes remains unknown. We sought to better understand the association between these potentially modifiable organizational and personnel factors on cardiac arrest prevention and rescue.Retrospective analysis of the Pediatric Cardiac Critical Care Consortium registry.Pediatric cardiac ICUs.All cardiac ICU admissions were evaluated for cardiac arrest and survival outcomes.None.Successful prevention was defined as the proportion of admissions with no cardiac arrest (inverse of cardiac arrest incidence). Rescue was the proportion of patients surviving to cardiac ICU discharge after cardiac arrest. Cardiac ICU organizational and personnel factors were captured via site questionnaires. The associations between organizational and personnel factors and prevention/rescue were analyzed using Fine-Gray and multinomial regression, respectively, accounting for clustering within hospitals. We analyzed 54,521 cardiac ICU admissions (29 hospitals) with 1,398 cardiac arrest events (2.5%) between August 1, 2014, and March 5, 2019. For both surgical and medical admissions, lower average daily cardiac ICU occupancy was associated with better cardiac arrest prevention. Better rescue for medical admissions was observed for higher registered nursing hours per patient day and lower proportions of "part time" cardiac ICU physician staff (6 service weeks/yr). Increased registered nurse experience was associated with better rescue for surgical admissions. Increased proportion of critical care certified nurses, full-time intensivists with critical care fellowship training, dedicated respiratory therapists, quality/safety resources, and annual cardiac ICU admission volume were not associated with improved prevention or rescue.Our multi-institutional analysis identified cardiac ICU bed occupancy, registered nurse experience, and physician staffing as potentially important factors associated with cardiac arrest prevention and rescue. Recognizing the limitations of measuring these variables cross-sectionally, additional studies are needed to further investigate these organizational and personnel factors, their interrelationships, and how hospitals can modify structure to improve cardiac arrest outcomes.

BACKGROUND: Hospitals are increasingly likely to implement clinical informatics tools to improve quality of care, necessitating rigorous approaches to evaluate effectiveness. We leveraged a multi-institutional data repository and applied causal inference methods to assess implementation of a commercial data visualization software in our pediatric cardiac intensive care unit. METHODS: Natural experiment in the University of Michigan (UM) Cardiac Intensive Care Unit pre and postimplementation of data visualization software analyzed within the Pediatric Cardiac Critical Care Consortium clinical registry; we identified N=21 control hospitals that contributed contemporaneous registry data during the study period. We used the platform during multiple daily rounds to visualize clinical data trends. We evaluated outcomes—case-mix adjusted postoperative mortality, cardiac arrest and unplanned readmission rates, and postoperative length of stay—most likely impacted by this change. There were no quality improvement initiatives focused specifically on these outcomes nor any organizational changes at UM in either era. We performed a difference-in-differences analysis to compare changes in UM outcomes to those at control hospitals across the pre versus postimplementation eras. RESULTS: We compared 1436 pre versus 779 postimplementation admissions at UM to 19 854 (pre) versus 14 160 (post) at controls. Admission characteristics were similar between eras. Postimplementation at UM we observed relative reductions in cardiac arrests among medical admissions, unplanned readmissions, and postoperative length of stay by −14%, −41%, and −18%, respectively. The difference-in-differences estimate for each outcome was statistically significant ( P CONCLUSIONS: Clinical registries provide opportunities to thoroughly evaluate implementation of new informatics tools at single institutions. Borrowing strength from multi-institutional data and drawing ideas from causal inference, our analysis solidified greater belief in the effectiveness of this software across our institution.

Pulmonary arterial hypertension (PAH) is a complex disease involving increased resistance in the pulmonary arteries and subsequent right ventricular (RV) remodeling. Ventricular-arterial interactions are fundamental to PAH pathophysiology but are rarely captured in computational models. It is important to identify metrics that capture and quantify these interactions to inform our understanding of this disease as well as potentially facilitate patient stratification. Towards this end, we developed and calibrated two multi-scale high-resolution closed-loop computational models using open-source software: a high-resolution arterial model implemented using CRIMSON, and a high-resolution ventricular model implemented using FEniCS. Models were constructed with clinical data including non-invasive imaging and invasive hemodynamic measurements from a cohort of pediatric PAH patients. A contribution of this work is the discussion of inconsistencies in anatomical and hemodynamic data routinely acquired in PAH patients. We proposed and implemented strategies to mitigate these inconsistencies, and subsequently use this data to inform and calibrate computational models of the ventricles and large arteries. Computational models based on adjusted clinical data were calibrated until the simulated results for the high-resolution arterial models matched within 10% of adjusted data consisting of pressure and flow, whereas the high-resolution ventricular models were calibrated until simulation results matched adjusted data of volume and pressure waveforms within 10%. A statistical analysis was performed to correlate numerous data-derived and model-derived metrics with clinically assessed disease severity. Several model-derived metrics were strongly correlated with clinically assessed disease severity, suggesting that computational models may aid in assessing PAH severity.

INTRODUCTION The right ventricular infundibular sparing approach (RVIS) to the repair of tetralogy of Fallot (TOF) avoids a full-thickness ventricular incision, typically utilized in the transinfundibular (TI) method. METHODS We performed a retrospective, age-matched cohort study of patients who underwent RVIS at Texas Children's Hospital or TI at Children's Hospital Medical Center in Nebraska and subsequently underwent cardiac magnetic resonance imaging (CMR). We compared right ventricular end-diastolic and systolic volumes indexed to body surface area (RVEDVi and RVESVi) and right ventricular ejection fraction (RVEF) as primary endpoints. Secondary endpoints were indexed left ventricular diastolic and systolic volume (LVEDVi and LVESVi), left ventricular ejection fraction (LVEF), right ventricular (RV) sinus ejection fraction (EF) and RV outflow tract EF (RVOT EF). RESULTS Seventy-nine patients were included in the analysis; 40 underwent RVIS and 39 underwent TI repair. None of the patients in the TI repair group had an initial palliation with a systemic to pulmonary arterial shunt compared to seven (18%) in the RVIS group (P

The objectives of this review are (I) to describe the challenges associated with monitoring patients in the pediatric cardiac intensive care unit (PCICU) and (II) to discuss the use of innovative statistical and artificial intelligence (AI) software programs to attempt to predict significant clinical events. Patients cared for in the PCICU are clinically fragile and at risk for fatal decompensation. Current monitoring modalities are often ineffective, sometimes inaccurate, and fail to detect a deteriorating clinical status in a timely manner. Predictive models created by AI and machine learning may lead to earlier detection of patients at risk for clinical decompensation and thereby improve care for critically ill pediatric cardiac patients.

Coronary spasm during coronary angiography for vasculopathy in children can be prevented by the intracoronary administration of nitroglycerin. We reviewed the anesthesia and catheterization reports and charts for pediatric transplant recipients who underwent angiography from 2005 through 2010. Correlation analysis was used to study the relation of post-injection systolic blood pressure (SBP) to nitroglycerin dose. Forty-one angiographic evaluations were performed on 25 patients (13 male and 12 female). Mean age was 9.9 ± 3.2 years (range, 3.3–16.1 yr). The mean total dose of nitroglycerin was 2.93 ± 1.60 µg/kg (range, 1–8 µg/kg). There was a significant drop between the baseline SBP (mean, 106 ± 21.6 mmHg) and the lowest mean SBP before nitroglycerin administration (78 ± 13.2, P

Software that aggregates and displays real-time physiologic data in the pediatric cardiac intensive care unit (CICU) holds promise to advance clinical care. We assessed multiple CICU outcomes at our institution before and after implementation of a commercial software platform and compared these