A Narrative Review of Multiinstitutional Data Registries of Pediatric Congenital Heart Disease in Pediatric Cardiac Anesthesia and Critical Care Medicine.

Congenital heart disease (CHD) is one of the most common birth anomalies. While the care of children with CHD has improved over recent decades, children with CHD who undergo general anesthesia remain at increased risk for morbidity and mortality. Electronic health record systems have enabled institutions to combine data on the management and outcomes of children with CHD in multicenter registries. The application of descriptive analytics methods to these data can improve clinicians' understanding and care of children with CHD. This narrative review covers efforts to leverage multicenter data registries relevant to pediatric cardiac anesthesia and critical care to improve the care of children with CHD.

Early prediction of clinical deterioration using data-driven machine-learning modeling of electronic health records.

OBJECTIVES: To develop and evaluate a high-dimensional, data-driven model to identify patients at high risk of clinical deterioration from routinely collected electronic health record (EHR) data. MATERIALS AND METHODS: In this single-center, retrospective cohort study, 488 patients with single-ventricle and shunt-dependent congenital heart disease <6 months old were admitted to the cardiac intensive care unit before stage 2 palliation between 2014 and 2019. Using machine-learning techniques, we developed the Intensive care Warning Index (I-WIN), which systematically assessed 1028 regularly collected EHR variables (vital signs, medications, laboratory tests, and diagnoses) to identify patients in the cardiac intensive care unit at elevated risk of clinical deterioration. An ensemble of 5 extreme gradient boosting models was developed and validated on 203 cases (130 emergent endotracheal intubations, 34 cardiac arrests requiring cardiopulmonary resuscitation, 10 extracorporeal membrane oxygenation cannulations, and 29 cardiac arrests requiring cardiopulmonary resuscitation onto extracorporeal membrane oxygenation) and 378 control periods from 446 patients. RESULTS: At 4 hours before deterioration, the model achieved an area under the receiver operating characteristic curve of 0.92 (95% confidence interval, 0.84-0.98), 0.881 sensitivity, 0.776 positive predictive value, 0.862 specificity, and 0.571 Brier skill score. Performance remained high at 8 hours before deterioration with 0.815 (0.688-0.921) area under the receiver operating characteristic curve. CONCLUSIONS: I-WIN accurately predicted deterioration events in critically-ill infants with high-risk congenital heart disease up to 8 hours before deterioration, potentially allowing clinicians to target interventions. We propose a paradigm shift from conventional expert consensus-based selection of risk factors to a data-driven, machine-learning methodology for risk prediction. With the increased availability of data capture in EHRs, I-WIN can be extended to broader applications in data-rich environments in critical care.

Use of a Risk Analytic Algorithm to Inform Weaning From Vasoactive Medication in Patients Following Pediatric Cardiac Surgery.

OBJECTIVES: Advanced clinical decision support tools, such as real-time risk analytic algorithms, show promise in assisting clinicians in making more efficient and precise decisions. These algorithms, which calculate the likelihood of a given underlying physiology or future event, have predominantly been used to identify the risk of impending clinical decompensation. There may be broader clinical applications of these models. Using the inadequate delivery of oxygen index, a U.S. Food and Drug Administration-approved risk analytic algorithm predicting the likelihood of low cardiac output state, the primary objective was to evaluate the association of inadequate delivery of oxygen index with success or failure of weaning vasoactive support in postoperative cardiac surgery patients. DESIGN: Multicenter retrospective cohort study. SETTING: Three pediatric cardiac ICUs at tertiary academic children's hospitals. PATIENTS: Infants and children greater than 2 kg and less than 12 years following cardiac surgery, who required vasoactive infusions for greater than 6 hours in the postoperative period. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Postoperative patients were identified who successfully weaned off initial vasoactive infusions (n = 2,645) versus those who failed vasoactive wean (required reinitiation of vasoactive, required mechanical circulatory support, renal replacement therapy, suffered cardiac arrest, or died) (n = 516). Inadequate delivery of oxygen index for final 6 hours of vasoactive wean was captured. Inadequate delivery of oxygen index was significantly elevated in patients with failed versus successful weans (inadequate delivery of oxygen index 11.6 [sd 19.0] vs 6.4 [sd 12.6]; p < 0.001). Mean 6-hour inadequate delivery of oxygen index greater than 50 had strongest association with failed vasoactive wean (adjusted odds ratio, 4.0; 95% CI, 2.5-6.6). In patients who failed wean, reinitiation of vasoactive support was associated with concomitant fall in inadequate delivery of oxygen index (11.1 [sd 18] vs 8.9 [sd 16]; p = 0.007). CONCLUSIONS: During the de-escalation phase of postoperative cardiac ICU management, elevation of the real-time risk analytic model, inadequate delivery of oxygen index, was associated with failure to wean off vasoactive infusions. Future studies should prospectively evaluate utility of risk analytic models as clinical decision support tools in de-escalation practices in critically ill patients.

Acute coronary artery obstruction following surgical repair of congenital heart disease.

OBJECTIVES: Acute coronary artery obstruction is a rare complication of congenital heart disease surgery but imposes a high burden of morbidity and mortality. Previous case series have described episodes in specific congenital heart lesions or surgical repairs but have not examined the complication in all-comers to congenital heart surgery. We hypothesize that shorter time from a clinically recognized postoperative sentinel event suggestive of coronary ischemia to diagnosis of coronary obstruction is associated with improved clinical outcomes. METHODS: This was a single-center, retrospective review of patients diagnosed with acute coronary artery obstruction by angiography following surgical repair of congenital heart disease between January 2000 and June 2016. RESULTS: In total, 34 patients were identified. The most common procedures associated with coronary artery obstruction were the Norwood procedure, arterial switch operation, and aortic valve repair/replacement. In total, 79% required mechanical circulatory support, 41% died, and 27% were listed for heart transplant. Patients who died or were listed for heart transplant had longer median sentinel-event-to-cardiac-catheterization time (28 [6-168] hours vs 10 [3-56] hours, P = .001), and longer median sentinel-event-to-intervention time (32 [11-350] hours vs 13 [5-59] hours, P = .003). Patients with hypoplastic left heart syndrome were at greater risk of death or transplant listing (odds ratio, 9.23, P = .03). CONCLUSIONS: Time from clinically relevant postoperative sentinel event to diagnosis of coronary artery obstruction by angiography was associated with transplant-listing-free survival. Clinicians should maintain a high index of suspicion for coronary obstruction and consider early catheterization and coronary angiography for patients in whom post-operative coronary compromise is suspected.

A Narrative Review of Analytics in Pediatric Cardiac Anesthesia and Critical Care Medicine.

Congenital heart disease (CHD) is one of the most common birth anomalies, and the care of children with CHD has improved over the past 4 decades. However, children with CHD who undergo general anesthesia remain at increased risk for morbidity and mortality. The proliferation of electronic health record systems and sophisticated patient monitors affords the opportunity to capture and analyze large amounts of CHD patient data, and the application of novel, effective analytics methods to these data can enable clinicians to enhance their care of pediatric CHD patients. This narrative review covers recent efforts to leverage analytics in pediatric cardiac anesthesia and critical care to improve the care of children with CHD.