In children who suffer out of hospital cardiac arrest, targeted hypothermia at 33.0 C confers no benefit when compared to targeted normothermia at 36.8 C. Level of evidence: 2B (RCT with wide CIs)Appraised by: Andrew Claxton Citation: Moler FW, Silverstein FS, Holubkov R and the THAPCA Trial Investigators. Therapeutic hypothermia after out-of-hospital cardiac arrest in children. N Eng

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.

BACKGROUND-Targeted temperature management is recommended for comatose adults and children after out-of-hospital cardiac arrest; however, data on temperature management after inhospital cardiac arrest are limited.

Liver transplantation in the pediatric patient is a durable procedure that provides excellent long-term survival. Although there have been overall improvements in patient outcome with increased experience, the effect is most pronounced for patients younger than 1 year of age. Retransplantation, although effective in a meaningful number of patients, continues to carry a progressive decrement in survival with the number of allografts performed. Use of living-related and in situ split-liver allografts has dramatically reduced waiting times for small children and has improved patient survival.