Evidence map›Paper›PMID 35593355›Full record

ArticleCurrent cardiology reviews2022

Recent Updates and Technological Developments in Evaluating Cardiac Syncope in the Emergency Department.

Utkarsh Ojha, James Ayathamattam, Kenneth Okonkwo, Innocent Ogunmwonyi

Open access · greenAbstract read
In one paragraph

Article in Current cardiology reviews, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.2field-weighted citation impact, top 50% of its field
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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

4 authors at 3 institutions in 1 country.

Utkarsh OjhaDepartment of Cardiology, Royal Brompton & Harefield Hospitals, England, UK.
James AyathamattamDepartment of Medicine, Royal Lancaster Infirmary, Lancaster, United Kingdom.
Kenneth OkonkwoDepartment of Medicine, Royal Lancaster Infirmary, Lancaster, United Kingdom.
Innocent OgunmwonyiDepartment of Medicine, Darent Valley Hospital, Dartford, England, UK.
Royal Lancaster Infirmary · GBDarent Valley Hospital · GBHarefield Hospital · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Syncope is a commonly encountered problem in the emergency department (ED), accounting for approximately 3% of presenting complaints. Clinical assessment of syncope can be challenging due to the diverse range of conditions that can precipitate the symptom. Annual mortality for patients presenting with syncope ranges from 0-12%, and if the syncope is secondary to a cardiac cause, then this figure rises to 18-33%. In ED, it is paramount to accurately identify those presenting with syncope, especially patients with an underlying cardiac aetiology, initiate appropriate management, and refer them for further investigations. In 2018, the European Society of Cardiology (ESC) updated its guidelines with regard to diagnosing and managing patients with syncope. We highlight recent developments and considerations in various components of the workup, such as history, physical examination, investigations, risk stratification, and novel biomarkers, since the establishment of the 2018 ESC guidelines. We further discuss the emerging role of artificial intelligence in diagnosing cardiac syncope and postulate how wearable technology may transform evaluating cardiac syncope in ED.

Indexed as

Artificial IntelligenceCardiologyEmergency Service, HospitalHumansSyncopearrhythmiaartificial intelligenceCardiac syncopeemergency departmentnon-traumatictechnology

Identifiers

PMID35593355
PMCPMC9893151
OpenAlexW4224211536

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.