• Nadir Yehya, Michael O Harhay, Margaret J Klein, Steven L Shein, Byron E Piñeres-Olave, Ledys Izquierdo, Anil Sapru, Guillaume Emeriaud, Philip C Spinella, Heidi R Flori, Mary K Dahmer, Aline B Maddux, Yolanda M Lopez-Fernandez, Bereketeab Haileselassie, Deyin Doreen Hsing, Ranjit S Chima, Amanda B Hassinger, Stacey L Valentine, Courtney M Rowan, Kneyber Martin C J MCJ Department of Pediatrics, Division of Pediatric Critical Care Medicine, Beatrix Children's Hospital and University of Groningen, Groningen, The Net, Lincoln S Smith, Robinder G Khemani, Neal J Thomas, and Pediatric Acute Respiratory Distress Syndrome Incidence and Epidemiology (PARDIE) V1 Investigators and the Pediatric Acute Lung Injury and Sepsis Investigators (PALISI) Network.
• Department of Anesthesiology and Critical Care Medicine, Children's Hospital of Philadelphia and University of Pennsylvania, Philadelphia, PA.
• Crit. Care Med. 2020 Jun 1; 48 (6): e514-e522.

ObjectivesPediatric 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.DesignLeveraging 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.SettingThe derivation cohort represented 100 centers worldwide; the validation cohort was from Children's Hospital of Philadelphia.PatientsThere were 624 and 640 subjects in the derivation and validation cohorts, respectively.InterventionsNone.Measurements And Main ResultsThe 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.ConclusionsWe 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.

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