1. Predicting severe pneumonia in the emergency department: a global study of the Pediatric Emergency Research Networks (PERN)—study protocol
- Author
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Nicholas Watkins, Mark I Neuman, Todd Adam Florin, Daniel Joseph Tancredi, Lilliam Ambroggio, Fahd A Ahmad, Andrea Álvarez-Álvarez, Alberto Arrighini, Usha Avva, Elena Aquino Olivia, Uchechi Azubuine, Luisa Baron Gonzalez de Suso, Kelly R Bergmann, Stuart A Bradin, Kristen Breslin, Rosa María Calderón Checa, Maria Natali Campo Fernández, Carmen Campos-Calleja, Kerry Caperell, Pradip P Chaudhari, Jonathan Cherry, Wee-Jhong Chua, Ida Concha Murray, Thosar Deepali, Pinky-Rose Espina, Susan Fairbrother, Alexandria Farish, Daniel M Fein, Ramón Fernández Álvarez, Todd A Florin, Karen Forward, Jara Gaitero Tristán, Iker Gangoiti, Michael A Gardiner, Virginia Gómez-Barrena, Tamara Hirsch Birn, Adam Isacoff, April J Kam, Nirupama Kannikeswaran, Maria Y Kwok, Maren M Lunoe, Ryan McKee, Son H McLaren, Lianne McLean, Garth D Meckler, Erin Mills, Diana Aniela Moldovan, Andrea Mora-Capín, Viera Morales, Claudia R Morris, Nidhya Navanandan, Rebecca Oglesby, Ioannis Orfanos, Sonia Viviana Pavlicich, Astrid Pezoa Fuenzalida, Mercè Puigdomènech Fosch, Miguel Angelats Carlos Romero, Cyril Sahyoun, Frederic Samson, Nipam P Shah, Pilar Storch-de-Gracia Calvo, Tristan Turner, Muhammad Waseem, Joseph Zorc, and Sahyoun, Cyril
- Subjects
paediatric A ,Emergency Care ,Community-acquired pneumonia ,Models ,paediatric infectious disease ,Informed consent ,Prospective Studies ,Child ,Prospective cohort study ,Lung ,Pediatric ,screening and diagnosis ,Emergency Service ,ddc:618 ,immunisation ,General Medicine ,Statistical ,Health Services ,Prognosis ,Institutional review board ,Detection ,Infectious Diseases ,Pneumonia & Influenza ,Public Health and Health Services ,Medicine ,Patient Safety ,Emergency Service, Hospital ,4.2 Evaluation of markers and technologies ,medicine.medical_specialty ,Clinical Sciences ,Recursive partitioning ,paediatric infectious disease & immunisation ,paediatrics ,Hospital ,Clinical Research ,medicine ,Humans ,Models, Statistical ,Other Medical and Health Sciences ,business.industry ,Pediatric Emergency Research Networks (PERN) Pneumonia Investigators ,Infant ,Paediatrics ,Pneumonia ,Emergency department ,medicine.disease ,E and ambulatory care ,Pneumonia/diagnosis/epidemiology ,Emergency medicine ,Ordered logit ,paediatric A&E and ambulatory care ,business - Abstract
IntroductionPneumonia is a frequent and costly cause of emergency department (ED) visits and hospitalisations in children. There are no evidence-based, validated tools to assist physicians in management and disposition decisions for children presenting to the ED with community-acquired pneumonia (CAP). The objective of this study is to develop a clinical prediction model to accurately stratify children with CAP who are at risk for low, moderate and severe disease across a global network of EDs.Methods and analysisThis study is a prospective cohort study enrolling up to 4700 children with CAP at EDs at ~80 member sites of the Pediatric Emergency Research Networks (PERN; https://pern-global.com/). We will include children aged 3 months to Ethics and disseminationThis study will result in a clinical prediction model to accurately identify risk of severe disease on presentation to the ED. Ethics approval was obtained for all sites included in the study. Cincinnati Children’s Hospital Institutional Review Board (IRB) serves as the central IRB for most US sites. Informed consent will be obtained from all participants. Results will be disseminated through international conferences and peer-reviewed publications. This study overcomes limitations of prior pneumonia severity scores by allowing for broad generalisability of findings, which can be actively implemented after model development and validation.
- Published
- 2020
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