Evidence map›Paper›PMID 32472247›Full record

ReviewCurrent cardiology reports2020

Chest Pain Evaluation in the Emergency Department: Risk Scores and High-Sensitivity Cardiac Troponin.

Joseph Gibbs, James McCord

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current cardiology reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. The Radiologist as a Gatekeeper in Chest Pain.International journal of environmental research and public health · 2021
    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.

Joseph GibbsHeart and Vascular Institute, Henry Ford Hospital, Dearborn, MI, 48126, USA. jgibbs3@hfhs.org.
James McCordHeart and Vascular Institute, Henry Ford Hospital, Dearborn, MI, 48126, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purpose of reviewAs many as 10 million patients present annually to the emergency department in the USA with symptoms concerning for acute myocardial infarction. The use of risk scores for patients with chest pain or equivalent without ST-segment elevation on the electrocardiogram. The adaptation in the USA of high sensitivity troponin assays requires rethinking of how to best optimize troponin testing within a risk score. RECENT

findingsPatients are risk stratified using a combination of validated risk scores, biomarkers, and both noninvasive and invasive testing. The advent of high-sensitivity troponins has served to augment existing risk scores in the identification of low-risk patients for early discharge, as well as led to the introduction of new rapid rule-out protocols by which acute myocardial infarction can be excluded by biomarker evaluation more quickly. The emergence of machine learning algorithms may further enhance provider's ability to quickly diagnose or exclude myocardial infarction in the emergency department. The addition of high sensitive troponin assays to established emergency department risk scores is providing new opportunities to improve the timeliness and accuracy of the evaluation of patients presenting with a possible myocardial infarction. Utilizing the time between troponin measures as a variable combined with clinical risk factors with new algorithms may further serve to improve diagnostic accuracy.

Indexed as

Acute Coronary SyndromeBiomarkersChest PainEmergency Service, HospitalHumansProspective StudiesSensitivity and SpecificityTroponin IBiomarkersTroponin IChest painEmergency departmentHigh-sensitivity troponinRisk scores

Identifiers

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.