Evidence map›Paper›PMID 32426637›Full record

ArticlePediatric quality & safety

The Vitals Risk Index-Retrospective Performance Analysis of an Automated and Objective Pediatric Early Warning System.

Tyler J Gorham, Steve Rust, Laura Rust, Stacy Kuehn, Jing Yang, James Shuhan Lin, Jeffrey Hoffman, Yungui Huang, Simon Lin, Richard McClead and 3 more

Abstract read
In one paragraph

Article in Pediatric quality & safety. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Tyler J GorhamAbigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio.
Steve RustAbigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio.
Laura RustNationwide Children's Hospital, Columbus, Ohio.
Stacy KuehnNationwide Children's Hospital, Columbus, Ohio.
Jing YangAbigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio.
James Shuhan LinThe Ohio State University College of Medicine, Columbus, Ohio.
Jeffrey HoffmanNationwide Children's Hospital, Columbus, Ohio.
Yungui HuangAbigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio.
Simon LinAbigail Wexner Research Institute, Nationwide Children's Hospital, Columbus, Ohio.
Richard McCleadNationwide Children's Hospital, Columbus, Ohio.
Richard BrilliNationwide Children's Hospital, Columbus, Ohio.
Ryan BodeNationwide Children's Hospital, Columbus, Ohio.
Tensing MaaNationwide Children's Hospital, Columbus, Ohio.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionPediatric in-hospital cardiac arrests and emergent transfers to the pediatric intensive care unit (ICU) represent a serious patient safety concern with associated increased morbidity and mortality. Some institutions have turned to the electronic health record and predictive analytics in search of earlier and more accurate detection of patients at risk for decompensation.

methodsObjective electronic health record data from 2011 to 2017 was utilized to develop an automated early warning system score aimed at identifying hospitalized children at risk of clinical deterioration. Five vital sign measurements and supplemental oxygen requirement data were used to build the Vitals Risk Index (VRI) model, using multivariate logistic regression. We compared the VRI to the hospital's existing early warning system, an adaptation of Monaghan's Pediatric Early Warning Score system (PEWS). The patient population included hospitalized children 18 years of age and younger while being cared for outside of the ICU. This dataset included 158 case hospitalizations (102 emergent transfers to the ICU and 56 "code blue" events) and 135,597 control hospitalizations.

resultsWhen identifying deteriorating patients 2 hours before an event, there was no significant difference between Pediatric Early Warning Score and VRI's areas under the receiver operating characteristic curve at false-positive rates ≤ 10% (pAUC

conclusionsThe VRI represents an objective, simple, and automated predictive analytics tool for identifying hospitalized pediatric patients at risk of deteriorating outside of the ICU setting.

Identifiers

PMID32426637
PMCPMC7190256

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.