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Predicting Mortality in Children With Pediatric Acute Respiratory Distress Syndrome: A Pediatric Acute Respiratory Distress Syndrome Incidence and Epidemiology Study
- Source :
- Critical Care Medicine, Critical Care Medicine, 48(6), E514-E522. LIPPINCOTT WILLIAMS & WILKINS
- Publication Year :
- 2020
- Publisher :
- Ovid Technologies (Wolters Kluwer Health), 2020.
-
Abstract
- Supplemental Digital Content is available in the text.<br />Objectives: Pediatric acute respiratory distress syndrome is heterogeneous, with a paucity of risk stratification tools to assist with trial design. We aimed to develop and validate mortality prediction models for patients with pediatric acute respiratory distress syndrome. Design: Leveraging additional data collection from a preplanned ancillary study (Version 1) of the multinational Pediatric Acute Respiratory Distress syndrome Incidence and Epidemiology study, we identified predictors of mortality. Separate models were built for the entire Version 1 cohort, for the cohort excluding neurologic deaths, for intubated subjects, and for intubated subjects excluding neurologic deaths. Models were externally validated in a cohort of intubated pediatric acute respiratory distress syndrome patients from the Children’s Hospital of Philadelphia. Setting: The derivation cohort represented 100 centers worldwide; the validation cohort was from Children’s Hospital of Philadelphia. Patients: There were 624 and 640 subjects in the derivation and validation cohorts, respectively. Interventions: None. Measurements and Main Results: The model for the full cohort included immunocompromised status, Pediatric Logistic Organ Dysfunction 2 score, day 0 vasopressor-inotrope score and fluid balance, and Pao2/Fio2 6 hours after pediatric acute respiratory distress syndrome onset. This model had good discrimination (area under the receiver operating characteristic curve 0.82), calibration, and internal validation. Models excluding neurologic deaths, for intubated subjects, and for intubated subjects excluding neurologic deaths also demonstrated good discrimination (all area under the receiver operating characteristic curve ≥ 0.84) and calibration. In the validation cohort, models for intubated pediatric acute respiratory distress syndrome (including and excluding neurologic deaths) had excellent discrimination (both area under the receiver operating characteristic curve ≥ 0.85), but poor calibration. After revision, the model for all intubated subjects remained miscalibrated, whereas the model excluding neurologic deaths showed perfect calibration. Mortality models also stratified ventilator-free days at 28 days in both derivation and validation cohorts. Conclusions: We describe predictive models for mortality in pediatric acute respiratory distress syndrome using readily available variables from day 0 of pediatric acute respiratory distress syndrome which outperform severity of illness scores and which demonstrate utility for composite outcomes such as ventilator-free days. Models can assist with risk stratification for clinical trials.
- Subjects :
- medicine.medical_specialty
Pediatrics
Adolescent
risk stratification
Intensive Care Units, Pediatric
pediatric acute respiratory distress syndrome
Critical Care and Intensive Care Medicine
Sensitivity and Specificity
Severity of Illness Index
Immunocompromised Host
03 medical and health sciences
0302 clinical medicine
Epidemiology
Severity of illness
Intubation, Intratracheal
Humans
Medicine
Derivation
Child
Respiratory Distress Syndrome
ventilator-free days
Receiver operating characteristic
business.industry
Incidence
Incidence (epidemiology)
Organ dysfunction
Online Clinical Investigations
030208 emergency & critical care medicine
prediction
Water-Electrolyte Balance
Prognosis
Respiration, Artificial
mortality
Clinical trial
ROC Curve
030228 respiratory system
Child, Preschool
Cohort
ComputingMethodologies_DOCUMENTANDTEXTPROCESSING
medicine.symptom
business
Subjects
Details
- ISSN :
- 00903493
- Volume :
- 48
- Database :
- OpenAIRE
- Journal :
- Critical Care Medicine
- Accession number :
- edsair.doi.dedup.....da9b81712d57dd3704373303610e73e1