Evidence map›Paper›PMID 31343475›Full record

ArticleCritical care medicine2019

Characteristics of Rapid Response Calls in the United States: An Analysis of the First 402,023 Adult Cases From the Get With the Guidelines Resuscitation-Medical Emergency Team Registry.

Patrick G Lyons, Dana P Edelson, Kyle A Carey, Nicole M Twu, Paul S Chan, Mary Ann Peberdy, Amy Praestgaard, Matthew M Churpek, American Heart Association’s Get With the Guidelines – Resuscitation Investigators

Abstract readMulticenter Study
In one paragraph

Article in Critical care medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
–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

23 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Observational
  7. Article
  8. Article
  9. Article
  10. Ten Steps Toward Improving In-Hospital Cardiac Arrest Quality of Care and Outcomes.Circulation. Cardiovascular quality and outcomes · 2023
    Review
  11. Nightmare on CIL Street: A Simulation Series to Increase Confidence and Skill in Responding to Clinical Emergencies.Federal practitioner : for the health care professionals of the VA, DoD, and PHS · 2023
    Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Long term survival following a medical emergency team call at an Australian regional hospital.Critical care and resuscitation : journal of the Australasian Academy of Critical Care Medicine · 2022
    Article
  19. Article
  20. Observational
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Patrick G LyonsDepartment of Medicine, Washington University School of Medicine, St. Louis, MO.
Dana P EdelsonDepartment of Medicine, University of Chicago, Chicago, IL.
Kyle A CareyDepartment of Medicine, University of Chicago, Chicago, IL.
Nicole M TwuDepartment of Medicine, University of Chicago, Chicago, IL.
Paul S ChanDepartment of Internal Medicine, Mid America Heart Institute at St. Luke's Hospital, University of Missouri-Kansas City, Kansas City, MO.
Mary Ann PeberdyDepartments of Internal Medicine and Emergency Medicine, Virginia Commonwealth University, Richmond, VA.
Amy PraestgaardDepartment Center for Clinical Epidemiology and Biostatistics, University of Pennsylvania School of Medicine, Philadelphia, PA.
Matthew M ChurpekDepartment of Medicine, University of Chicago, Chicago, IL.
American Heart Association’s Get With the Guidelines – Resuscitation Investigators

Funding

PRINCIPLES IN PULMONARY RESEARCHT32HL007317 · NHLBI · WASHINGTON UNIVERSITY · PI Steven Brody, Michael J Holtzman · 1985 to 2026
$16.1M
Hospital Enhancement of Resuscitation Outcomes for In-Hospital Cardiac Arrest (HER01HL123980 · NHLBI · SAINT LUKE'S HOSPITAL · PI CHAN, PAUL SHEUNG-YAN, NALLAMOTHU, BRAHMAJEE K · 2014 to 2018
$2.7M
Sepsis Early Prediction and Subphenotype Illumination Study (SEPSIS)R01GM123193 · NIGMS · UNIVERSITY OF WISCONSIN-MADISON · PI CHURPEK, MATTHEW MICHAEL · 2017 to 2021
$1.9M
Predicting In-hospital Cardiac Arrest Using Electronic Health Record DataK08HL121080 · NHLBI · UNIVERSITY OF CHICAGO · PI CHURPEK, MATTHEW MICHAEL · 2014 to 2018
$751k
NHLBI NIH HHS K08 HL121080NHLBI NIH HHS R01 HL123980NHLBI NIH HHS T32 HL007317NIGMS NIH HHS R01 GM123193
6 · The paper itself

Abstract

objectivesTo characterize the rapid response team activations, and the patients receiving them, in the American Heart Association-sponsored Get With The Guidelines Resuscitation-Medical Emergency Team cohort between 2005 and 2015.

designRetrospective multicenter cohort study.

settingThree hundred sixty U.S. hospitals. PATIENTS: Consecutive adult patients experiencing rapid response team activation.

interventionsRapid response team activation. MEASUREMENTS AND MAIN

resultsThe cohort included 402,023 rapid response team activations from 347,401 unique healthcare encounters. Respiratory triggers (38.0%) and cardiac triggers (37.4%) were most common. The most frequent interventions-pulse oximetry (66.5%), other monitoring (59.6%), and supplemental oxygen (62.0%)-were noninvasive. Fluids were the most common medication ordered (19.3%), but new antibiotic orders were rare (1.2%). More than 10% of rapid response teams resulted in code status changes. Hospital mortality was over 14% and increased with subsequent rapid response activations.

conclusionsAlthough patients requiring rapid response team activation have high inpatient mortality, most rapid response team activations involve relatively few interventions, which may limit these teams' ability to improve patient outcomes.

Indexed as

Emergency Service, HospitalRegistriesAgedCohort StudiesFemaleHospital Rapid Response TeamHumansMaleMiddle AgedPractice Guidelines as TopicResuscitationRetrospective StudiesUnited States

Identifiers

PMID31343475
PMCPMC7189351

What OpenQuestion holds

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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.