Objectives: The objective of this study was to determine the prevalence of ICU delirium in children less than 18 years old that underwent cardiac surgery within the last 30 days. The secondary aim of the study was to identify risk factors associated with ICU delirium in postoperative pediatric cardiac surgical patients. Design: A 1-day, multicenter point-prevalence study of delirium in pediatric postoperative cardiac surgery patients. Setting: Twenty-seven pediatric cardiac and general critical care units caring for postoperative pediatric cardiac surgery patients in North America. Patients: All children less than 18 years old hospitalized in the cardiac critical care units at 06:00 on a randomly selected, study day. Interventions: Eligible children were screened for delirium using the Cornell Assessment of Pediatric Delirium by the study team in collaboration with the bedside nurse. Measurement and Main Results: Overall, 181 patients were enrolled and 40% (n = 73) screened positive for delirium. There were no statistically significant differences in patient demographic information, severity of defect or surgical procedure, past medical history, or postoperative day between patients screening positive or negative for delirium. Our bivariate analysis found those patients screening positive had a longer duration of mechanical ventilation (12.8 vs 5.1 d; p = 0.02); required more vasoactive support (55% vs 26%; p = 0.0009); and had a higher number of invasive catheters (4 vs 3 catheters; p = 0.001). Delirium-positive patients received more total opioid exposure (1.80 vs 0.36 mg/kg/d of morphine equivalents; p < 0.001), did not have an ambulation or physical therapy schedule (p = 0.02), had not been out of bed in the previous 24 hours (p < 0.0002), and parents were not at the bedside at time of data collection (p = 0.008). In the mixed-effects logistic regression analysis of modifiable risk factors, the following variables were associated with a positive delirium screen: 1) pain score, per point increase (odds ratio, 1.3; 1.06–1.60); 2) total opioid exposure, per mg/kg/d increase (odds ratio, 1.35; 1.06–1.73); 3) SBS less than 0 (odds ratio, 4.01; 1.21–13.27); 4) pain medication or sedative administered in the previous 4 hours (odds ratio, 3.49; 1.32–9.28); 5) no progressive physical therapy or ambulation schedule in their medical record (odds ratio, 4.40; 1.41–13.68); and 6) parents not at bedside at time of data collection (odds ratio, 2.31; 1.01–5.31). Conclusions: We found delirium to be a common problem after cardiac surgery with several important modifiable risk factors.

Intensive care units (ICUs) provide care for critically-ill patients who require constant monitoring and the availability of specialized equipment and personnel. In this environment, a high volume of information and a high degree of uncertainty present a burden to clinicians. In specialized cohorts, such as pediatric patients with congenital heart defects (CHDs), this burden is exacerbated by increased complexity, the inadequacy of existing decision support aids, and the limited and decreasing availability of highly-specialized clinicians. Among CHD patients, infants with single ventricle (SV) physiology are one of the most complex and severely-ill sub-populations. While SV mortality rates have dropped, patient deterioration may happen unexpectedly in the period before patients undergo stage-2 palliative surgery. Even in expert hands, critical and potentially catastrophic events (CEs), such as cardiopulmonary resuscitation (CPR), emergent endotracheal intubation (EEI), or extracorporeal membrane oxygenation (ECMO) are common in SV patients, and may negatively impact morbidity, mortality, and hospital length of stay. There is a clinical need of predictive tools that help intensivists assess and forecast the advent of CEs in SV infants. Although ubiquitous, widely adopted ICU severity-of-illness scores or early warning systems (EWS), e.g., PRISM and PIM, have not met this need. They are often v developed for general ICU use and do not generalize well to specialized populations. Furthermore, most EWS are developed for prediction of patient mortality. Among SV patients, however, death is semi-elective. On the other hand, prediction of CEs may help clinicians improve patient care by anticipating the advent of patient deterioration. In this dissertation, we aimed to develop and validate predictive models that achieve early and accurate prediction of CEs in infants with SV physiology. Such models may provide early and actionable information to clinicians and may be used to perform clinical interventions aimed at preventing CEs, and to reducing morbidity, mortality, and healthcare costs. We assert that our work is significant in that it addresses an unmet clinical need by achieving state-of-the-art, early prediction of patient deterioration in a challenging and vulnerable population. vi TABLE OF CONTENTS

No abstract

Background The Intensive Care Unit Complexity Assessment and Monitoring to Ensure Optimal Outcomes (ICU CAMEO III) acuity tool measures patient acuity in terms of the complexity of nursing cognitive workload. Objective To validate the ICU CAMEO III acuity tool in US children’s hospitals. Methods Using a convenience sample, 9 sites enrolled children admitted to pediatric intensive care units (ICUs). Descriptive statistics were used to summarize patient, nursing, and unit characteristics. Concurrent validity was evaluated by correlating the ICU CAMEO III with the Therapeutic Intervention Scoring System-Children (TISS-C) and the Pediatric Risk of Mortality III (PRISM III). Results Patients (N = 840) were enrolled from 15 units (7 cardiac and 8 mixed pediatric ICUs). The mean number of ICU beds was 23 (range, 12-34). Among the patients, 512 (61%) were diagnosed with cardiac and 328 (39%) with noncardiac conditions; 463 patients (55.1%) were admitted for medical reasons, and 377 patients (44.9%) were surgical. The ICU CAMEO III median score was 99 (range, 59-163). The ICU CAMEO complexity classification was determined for all 840 patients: 60 (7.1%) with level I complexity; 183 (21.8%) with level II; 201 (23.9%), level III; 267 (31.8%), level IV; and 129 (15.4%), level V. Strong correlation was found between ICU CAMEO III and both TISS-C (ρ = .822, P &lt; .001) and PRISM III (ρ = .607, P &lt; .001) scores, and between the CAMEO complexity classifications and the PRISM III categories (ρ = .575, P = .001). Conclusion The ICU CAMEO III acuity tool and CAMEO complexity classifications are valid measures of patient acuity and nursing cognitive workload compared with PRISM III and TISS-C in academic children’s hospitals.