Evidence map›Paper›PMID 38796228›Full record

ReviewCritical care clinics2024

Early Warning Systems for Critical Illness Outside the Intensive Care Unit.

Katharine E Henry, Heather M Giannini

Abstract readReview
In one paragraph

Review in Critical care clinics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. [Intensive care and emergency medicine overuse and sustainability].Medizinische Klinik, Intensivmedizin und Notfallmedizin · 2025
    Review
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

2 authors.

Katharine E HenryDepartment of Computer Science, Johns Hopkins University, Malone Hall, 3400 N Charles Street, Baltimore, MD 21218, USA.
Heather M GianniniDivision of Pulmonary, Allergy and Critical Care, Hospital of the University of Pennsylvania, 5 West Gates Building, 5048, 3400 Spruce Street, Philadelphia, PA 19104, USA. Electronic address: Heather.giannini@pennmedicine.upenn.edu.

Funding

Institutional Clinical and Translational Science AwardKL2TR001879 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI MEAGHER, EMMA ANNE · 2016 to 2025
$13.7M
NCATS NIH HHS KL2 TR001879NIAID NIH HHS L30 AI172012
6 · The paper itself

Abstract

Early warning systems (EWSs) are designed and deployed to create a rapid assessment and response for patients with clinical deterioration outside the intensive care unit (ICU). These models incorporate patient-level data such as vital signs and laboratory values to detect or prevent adverse clinical events, such as vital signs and laboratories to allow detection and prevention of adverse clinical events such as cardiac arrest, intensive care transfer, or sepsis. The applicability, development, clinical utility, and general perception of EWS in clinical practice vary widely. Here, we review the field as it has grown from early vital sign-based scoring systems to contemporary multidimensional algorithms and predictive technologies for clinical decompensation outside the ICU.

Indexed as

Critical IllnessEarly Warning ScoreAlgorithmsClinical DeteriorationCritical CareHumansIntensive Care UnitsMonitoring, PhysiologicVital SignsArtificial intelligenceClinical decompensationClinical informaticsClinical predictionEarly warning systems

Identifiers

PMID38796228
PMCPMC11694888

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.