Literature DB >> 28292743

'The Score Matters': wide variations in predictive performance of 18 paediatric track and trigger systems.

Susan M Chapman1,2,3, Jo Wray2,4, Kate Oulton2,4, Christina Pagel5,6, Samiran Ray6,7, Mark J Peters6,7.   

Abstract

OBJECTIVE: To compare the predictive performance of 18 paediatric early warning systems (PEWS) in predicting critical deterioration.
DESIGN: Retrospective case-controlled study. PEWS values were calculated from existing clinical data, and the area under the receiver operator characteristic curve (AUROC) compared.
SETTING: UK tertiary referral children's hospital. PATIENTS: Patients without a 'do not attempt resuscitation' order admitted between 1 January 2011 and 31 December 2012. All patients on paediatric wards who suffered a critical deterioration event were designated 'cases' and matched with a control closest in age who was present on the same ward at the same time. MAIN OUTCOME MEASURES: Respiratory and/or cardiac arrest, unplanned transfer to paediatric intensive care and/or unexpected death.
RESULTS: 12 'scoring' and 6 'trigger' systems were suitable for comparative analysis. 297 case events in 224 patients were available for analysis. 244 control patients were identified for the 311 events. Three PEWS demonstrated better overall predictive performance with an AUROC of 0.87 or greater. Comparing each system with the highest performing PEWS with Bonferroni's correction for multiple comparisons resulted in statistically significant differences for 13 systems. Trigger systems performed worse than scoring systems, occupying the six lowest places in the AUROC rankings.
CONCLUSIONS: There is considerable variation in the performance of published PEWS, and as such the choice of PEWS has the potential to be clinically important. Trigger-based systems performed poorly overall, but it remains unclear what factors determine optimum performance. More complex systems did not necessarily demonstrate improved performance. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Entities:  

Keywords:  Intensive Care; Monitoring; Resuscitation

Mesh:

Year:  2017        PMID: 28292743     DOI: 10.1136/archdischild-2016-311088

Source DB:  PubMed          Journal:  Arch Dis Child        ISSN: 0003-9888            Impact factor:   3.791


  21 in total

1.  Priorities for Pediatric Patient Safety Research.

Authors:  James M Hoffman; Nicholas J Keeling; Christopher B Forrest; Heather L Tubbs-Cooley; Erin Moore; Emily Oehler; Stephanie Wilson; Elisabeth Schainker; Kathleen E Walsh
Journal:  Pediatrics       Date:  2019-02       Impact factor: 7.124

2.  Surviving sepsis campaign international guidelines for the management of septic shock and sepsis-associated organ dysfunction in children.

Authors:  Scott L Weiss; Mark J Peters; Waleed Alhazzani; Michael S D Agus; Heidi R Flori; David P Inwald; Simon Nadel; Luregn J Schlapbach; Robert C Tasker; Andrew C Argent; Joe Brierley; Joseph Carcillo; Enitan D Carrol; Christopher L Carroll; Ira M Cheifetz; Karen Choong; Jeffry J Cies; Andrea T Cruz; Daniele De Luca; Akash Deep; Saul N Faust; Claudio Flauzino De Oliveira; Mark W Hall; Paul Ishimine; Etienne Javouhey; Koen F M Joosten; Poonam Joshi; Oliver Karam; Martin C J Kneyber; Joris Lemson; Graeme MacLaren; Nilesh M Mehta; Morten Hylander Møller; Christopher J L Newth; Trung C Nguyen; Akira Nishisaki; Mark E Nunnally; Margaret M Parker; Raina M Paul; Adrienne G Randolph; Suchitra Ranjit; Lewis H Romer; Halden F Scott; Lyvonne N Tume; Judy T Verger; Eric A Williams; Joshua Wolf; Hector R Wong; Jerry J Zimmerman; Niranjan Kissoon; Pierre Tissieres
Journal:  Intensive Care Med       Date:  2020-02       Impact factor: 17.440

3.  Remote Pediatric Critical Care Telephone Consultations: Quality and Outcomes.

Authors:  Janice A Tijssen; Michael R Miller; Christopher S Parshuram
Journal:  J Pediatr Intensive Care       Date:  2019-02-25

4.  Consensus on patient cases for hospitalised children with a high paediatric track and trigger tool score that raises no mounting concern: a Delphi process study.

Authors:  Claus Sixtus Jensen; Hanne Vebert Olesen; Hans Kirkegaard; Marianne Lisby
Journal:  BMJ Paediatr Open       Date:  2022-07

5.  Development and External Validation of a Machine Learning Model for Prediction of Potential Transfer to the PICU.

Authors:  Anoop Mayampurath; L Nelson Sanchez-Pinto; Emma Hegermiller; Amarachi Erondu; Kyle Carey; Priti Jani; Robert Gibbons; Dana Edelson; Matthew M Churpek
Journal:  Pediatr Crit Care Med       Date:  2022-04-21       Impact factor: 3.971

6.  Accuracy of a Modified qSOFA Score for Predicting Critical Care Admission in Febrile Children.

Authors:  Sam T Romaine; Jessica Potter; Aakash Khanijau; Rachel J McGalliard; Jemma L Wright; Gerri Sefton; Simon Leigh; Karl Edwardson; Philip Johnston; Anne Kerr; Luregn J Schlapbach; Philip Pallmann; Enitan D Carrol
Journal:  Pediatrics       Date:  2020-10       Impact factor: 7.124

7.  Prognostic accuracy of age-adapted SOFA, SIRS, PELOD-2, and qSOFA for in-hospital mortality among children with suspected infection admitted to the intensive care unit.

Authors:  Luregn J Schlapbach; Lahn Straney; Rinaldo Bellomo; Graeme MacLaren; David Pilcher
Journal:  Intensive Care Med       Date:  2017-12-19       Impact factor: 17.440

8.  Validity and effectiveness of paediatric early warning systems and track and trigger tools for identifying and reducing clinical deterioration in hospitalised children: a systematic review.

Authors:  Rob Trubey; Chao Huang; Fiona V Lugg-Widger; Kerenza Hood; Davina Allen; Dawn Edwards; David Lacy; Amy Lloyd; Mala Mann; Brendan Mason; Alison Oliver; Damian Roland; Gerri Sefton; Richard Skone; Emma Thomas-Jones; Lyvonne N Tume; Colin Powell
Journal:  BMJ Open       Date:  2019-05-05       Impact factor: 2.692

9.  A Vital Sign-Based Model to Predict Clinical Deterioration in Hospitalized Children.

Authors:  Anoop Mayampurath; Priti Jani; Yangyang Dai; Robert Gibbons; Dana Edelson; Matthew M Churpek
Journal:  Pediatr Crit Care Med       Date:  2020-09       Impact factor: 3.971

10.  A clinical prediction model to identify patients at high risk of hemodynamic instability in the pediatric intensive care unit.

Authors:  Cristhian Potes; Bryan Conroy; Minnan Xu-Wilson; Christopher Newth; David Inwald; Joseph Frassica
Journal:  Crit Care       Date:  2017-11-20       Impact factor: 9.097

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