The incidences of bleeding and thrombosis are high during ECMO support. Laboratory sampling is a major contributor to transfusion during ECMO. Strategies to reduce the daily risk of bleeding and thrombosis, and different thresholds for transfusion, may be appropriate subjects of future trials to improve outcomes of children requiring this supportive therapy.

Objective To create a functional status outcome measure for large outcome studies that is well defined, quantitative, sufficiently rapid, reliable, minimally dependent on subjective assessments, and applicable to hospitalized pediatric patients across a wide spectrum of ages and inpatient environments. Patients and Methods The Functional Status Scale (FSS) was developed by a multidisciplinary consensus process. Domains of functioning included mental status, sensory, communication, motor, feeding, and respiratory categorized from normal (1) to very severe dysfunction (5). The Adaptive Behavior Assessment System (ABAS) II established construct validity and calibration within domains. Seven institutions provided pediatric intensive care unit (PICU) patients within 24 hours of PICU discharge, high-risk non-PICU patients within 24 hours of admission, and technology-dependent children. Primary care nurses completed the ABAS II based on patient’s functioning when the FSS was completed. Patients from 10% of the study days were used to evaluate inter-rater reliability. Data were randomly split into estimation and validation sets. Statistical analyses included Pearson correlations, construct validity, linear regression analysis, receiver operating characteristic (ROC) curve analysis for discriminant validity, and the intraclass correlation for inter-rater reliability. Results A total of 836 children with a mean FSS of 10.3 (standard deviation 4.4) were studied. Eighteen percent had the minimum possible FSS = 6, 44% had FSS ≥ 10, 14% had a FSS ≥ 15, and 6% had FSS scores ≥ 20. Each FSS domain was associated with mean ABAS II (p<.0001). Cells in each domain were collapsed and reweighted, which improved correlations with ABAS II from −0.58 to −0.62 in the estimation sample, and −0.60 to −0.63 in the validation sample (p<0.001 for improvements). Discrimination was very good for moderate and severe dysfunction (ABAS II categories) and improved with FSS weighting (area under the ROC curve > 0.8). Intraclass correlations of original and weighted total FSS were 0.95 and 0.94 respectively. Conclusions The FSS met our objectives and is well suited for large outcome studies.

Objectives Severity of illness measures have long been used in pediatric critical care. The Pediatric Risk of Mortality is a physiologically based score used to quantify physiologic status, and when combined with other independent variables, it can compute expected mortality risk and expected morbidity risk. Although the physiologic ranges for the Pediatric Risk of Mortality variables have not changed, recent Pediatric Risk of Mortality data collection improvements have been made to adapt to new practice patterns, minimize bias, and reduce potential sources of error. These include changing the outcome to hospital survival/death for the first PICU admission only, shortening the data collection period and altering the Pediatric Risk of Mortality data collection period for patients admitted for “optimizing” care before cardiac surgery or interventional catheterization. This analysis incorporates those changes, assesses the potential for Pediatric Risk of Mortality physiologic variable subcategories to improve score performance, and recalibrates the Pediatric Risk of Mortality score, placing the algorithms (Pediatric Risk of Mortality IV) in the public domain. Design Prospective cohort study from December 4, 2011, to April 7, 2013. Measurements and Main Results Among 10,078 admissions, the unadjusted mortality rate was 2.7% (site range, 1.3–5.0%). Data were divided into derivation (75%) and validation (25%) sets. The new Pediatric Risk of Mortality prediction algorithm (Pediatric Risk of Mortality IV) includes the same Pediatric Risk of Mortality physiologic variable ranges with the subcategories of neurologic and nonneurologic Pediatric Risk of Mortality scores, age, admission source, cardiopulmonary arrest within 24 hours before admission, cancer, and low-risk systems of primary dysfunction. The area under the receiver operating characteristic curve for the development and validation sets was 0.88 ± 0.013 and 0.90 ± 0.018, respectively. The Hosmer-Lemeshow goodness of fit statistics indicated adequate model fit for both the development (p = 0.39) and validation (p = 0.50) sets. Conclusions The new Pediatric Risk of Mortality data collection methods include significant improvements that minimize the potential for bias and errors, and the new Pediatric Risk of Mortality IV algorithm for survival and death has excellent prediction performance.

OBJECTIVE. We sought to inform decision-making for children and families by describing what is known and remains unknown about the impact of childhood critical illness and injury on families. This report also was designed as a tool for research planning and design so that meaningful studies are performed and duplication is avoided.DESIGN. After a national scholarship competition and the identification of 3 medical student summer scholars, a literature search was conducted by using the National Library of Medicine and a PubMed keyword search system at the National Institutes of Health.RESULTS. A total of 115 reports were reviewed and assigned to the 5 following categories characterizing the impact of pediatric critical illness/injury on families: stressors, needs, specific domains (psychological, physical, social), coping, and interventions. The reports reviewed indicate that pediatric critical illness and injury is stressful for the entire family. The effects on parents, siblings, and marital cohesion were variably described. Needs of family members (eg, rest, nutrition, communication) were identified as being unmet in many studies. Permanent impact on siblings and marital relationships has been considered detrimental, but these conclusions are not adequately quantified in presently available studies. Reviewed reports minimally investigated cultural diversity, effects on fathers versus mothers, siblings, socioeconomic status, and financial burden. Studies were often anecdotal and included small sample sizes. Methodologic limitations were numerous and varied and seriously narrowed the significance of the studies we reviewed. The reports that we evaluated were largely limited to those of Englishspeaking families, white people, and married mothers.CONCLUSIONS. Future research should use more rigorous methods in the measurement of impact of childhood critical illness and injury on families. Families of critically ill and injured children would benefit from the practitioners of pediatric critical care acquiring enhanced knowledge and sensitivity about famliy communication and dynamics.www.pediatrics.org/cgi

Objective Changes in technology and increased reports of successful extracorporeal life support (ECLS) use in patient populations such as influenza, cardiac arrest and adults are leading to expansion of ECLS. Major limitations to ECLS expansion remain bleeding and thrombosis. These complications are the most frequent causes of death and morbidity. As a pilot project to provide baseline data for a detailed evaluation of bleeding and thrombosis in the current era, ECLS patients were analyzed from eight centers in the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) Collaborative Pediatric Critical Care Research Network (CPCCRN). Study design Retrospective analysis of patients (<19 years) reported to the ELSO (Extracorporeal Life Support Organization registry from eight CPCCRN centers between 2005 and 2011. Subjects The study cohort consisted of 2036 patients [13% with congenital diaphragmatic hernia (CDH)]. Interventions none Main results In the cohort of non-CDH patients (n=1773), bleeding occurred in 38% of patients while thrombosis was noted in 31%. Bleeding and thrombosis were associated with a decreased survival by 40% (RR: 0.59; 95%CI: 0.53, 0.66) and 33% (OR 0.67; 95%CI: 0.60, 0.74). Longer duration of ECLS and use of venoarterial cannulation were also associated with increased risk of bleeding and/or thrombotic complications and lower survival. The most common bleeding events included surgical site bleeding (17%; n=306), cannulation site bleeding (14%; n=256), and intracranial hemorrhage (11%; n=192). Common thrombotic events were clots in the circuit (15%; n=274) and the oxygenator (12%; n=212), and hemolysis (plasma free hemoglobin>50 mg/dL) (10%; n=177). Among patients with CDH, bleeding and thrombosis occurred in, respectively, 45% (n=118) and 60% (n=159), Bleeding events were associated with reduced survival (RR 0.62; 95%CI: 0.46, 0.86) although thrombotic events were not (RR 0.92; 95%CI: 0.67, 1.26). Conclusions Bleeding and thrombosis remain common complications in patients undergoing ECLS. Further research to reduce or eliminate bleeding and thrombosis is indicated to help improve patient outcome.