Pediatr Crit Care Me
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Pediatr Crit Care Me · Feb 2021
Observational StudyAdmission Psychosocial Characteristics of Critically Ill Children and Acute Stress.
Children are at increased risk for developing acute stress and post-traumatic stress following admission to the PICU. The primary objective of this investigation was to explore the prehospitalization psychosocial characteristics of children admitted to the PICU and their association with acute stress. ⋯ The current investigation is a novel evaluation of the prehospitalization psychosocial characteristics of children admitted to a PICU. The children enrolled reported high rates of acute stress, which was associated with a history of post-traumatic stress and worsened quality of life. The relation with post-traumatic stress is consistent with prior research into complex post-traumatic stress disorder and increases concerns about long-term psychosocial outcomes. Our data advance understanding of the factors contributing to acute stress during hospitalizations and may add to recognizing the importance of models integrating psychosocial support.
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Pediatr Crit Care Me · Feb 2021
The Association of Laboratory Test Abnormalities With Mortality Risk in Pediatric Intensive Care.
To determine the bivariable associations between abnormalities of 28 common laboratory tests and hospital mortality and determine how mortality risks changes when the ranges are evaluated in the context of commonly used laboratory test panels. ⋯ The relative importance of laboratory test ranges vary widely, with some ranges strongly associated with mortality and others strongly associated with survival. When evaluated in the context of test panels rather than isolated tests, the mortality odds ratios for the test ranges decreased but generally remained significant as risk was distributed among the components of the test panels. These data are useful to develop critical values for children in ICUs, to identify risk factors previously underappreciated, for education and training, and for future risk score development.
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Pediatr Crit Care Me · Feb 2021
Observational StudySpillover of Early Extubation Practices From the Pediatric Heart Network Collaborative Learning Study.
The Pediatric Heart Network Collaborative Learning Study used collaborative learning strategies to implement a clinical practice guideline that increased rates of early extubation after infant repair of tetralogy of Fallot and coarctation of the aorta. We assessed early extubation rates for infants undergoing cardiac surgeries not targeted by the clinical practice guideline to determine whether changes in extubation practices spilled over to care of other infants. ⋯ We observed spillover of extubation practices promoted by the Collaborative Learning Study clinical practice guideline to lower complexity operations not included in the original study that was sustainable 1 year after study completion, though this effect differed across sites and operation subtypes. No changes in postoperative extubation outcomes following higher complexity surgeries were seen. The significant variation in outcomes by site suggests that center-specific factors may have influenced spillover of clinical practice guideline practices.
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Pediatr Crit Care Me · Feb 2021
Machine Learning to Predict Cardiac Death Within 1 Hour After Terminal Extubation.
Accurate prediction of time to death after withdrawal of life-sustaining therapies may improve counseling for families and help identify candidates for organ donation after cardiac death. The study objectives were to: 1) train a long short-term memory model to predict cardiac death within 1 hour after terminal extubation, 2) calculate the positive predictive value of the model and the number needed to alert among potential organ donors, and 3) examine associations between time to cardiac death and the patient's characteristics and physiologic variables using Cox regression. ⋯ Our long short-term memory model accurately predicted whether a child will die within 1 hour of terminal extubation and may improve counseling for families. Our model can identify potential candidates for donation after cardiac death while minimizing unnecessarily prepared operating rooms.