Evidence map›Paper›PMID 35959233›Full record

ArticleJournal of multidisciplinary healthcare2022

Paramedic Ability in Interpreting Electrocardiogram with ST-segment Elevation Myocardial Infarction (STEMI) in Saudi Arabia.

Abdullah A Alrumayh, Abdullah M Mubarak, Abdulkarim A Almazrua, Musab Z Alharthi, Deem F Alatef, Turki B Albacker, Fahad M Samarkandy, Yousef M Alsofayan, Muath Alobaida

Open access · goldAbstract read
In one paragraph

Article in Journal of multidisciplinary healthcare, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. 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

9 authors at 4 institutions in 1 country.

Abdullah A AlrumayhDepartment of Basic Sciences, Prince Sultan Bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.ORCID 0000-0002-9538-2202
Abdullah M MubarakDepartment of Basic Sciences, Prince Sultan Bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.ORCID 0000-0002-6920-6272
Abdulkarim A AlmazruaDepartment of Aviation and Marine, Prince Sultan Bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.
Musab Z AlharthiDepartment of Accident and Trauma, Prince Sultan Bin AbdulazizCollege for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.
Deem F AlatefDepartment of Emergency Medical Services and Disaster Management, King Saud Medical City, Riyadh, Saudi Arabia.
Turki B AlbackerDepartment of Cardiac Sciences, College of Medicine, King Saud University, Riyadh, Saudi Arabia.
Fahad M SamarkandyDepartment of Operational Affairs, Saudi Red Crescent Authority, Riyadh, Saudi Arabia.
Yousef M AlsofayanExecutive Directorate of Medical Affairs, Saudi Red Crescent Authority, Riyadh, Saudi Arabia.ORCID 0000-0001-7028-7930
Muath AlobaidaDepartment of Basic Sciences, Prince Sultan Bin Abdulaziz College for Emergency Medical Services, King Saud University, Riyadh, Saudi Arabia.ORCID 0000-0003-1257-1428
King Saud bin Abdulaziz University for Health Sciences · SAKing Saud Medical City · SAKing Saud University · SASaudi Arabian Monetary Authority · SA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: To evaluate paramedic ability in recognizing 12-lead Electrocardiogram (ECG) with ST-segment Elevation myocardial infarction (STEMI) in Saudi Arabia. Methods: This is a quantitative exploratory cross-sectional study using an electronic survey of paramedics was conducted between June and September 2021. The survey included demographics, educational and clinical experiences, and multiple 12-lead ECG strip questions to assess participants' ability to recognize STEMI. We reported the overall sensitivity, specificity, and correct proportions with 95% Confidence Intervals (CI). Results: Eighty-four paramedics completed the survey, and 65% of them were between 24 and 29 years old, with a median, of three years of field experience. Overall sensitivity and specificity were 58.39% (95% CI, 50.4% to 66.1%) and 29.01% (95% CI, 25.15% to 33.1%), respectively. In total, 67.1% correctly identified inferior STEMI, whereas only 50% correctly identified lateral STEMI. Both STEMIs were correctly identified by 41%, and the majority misinterpreted STEMI mimics (ECG rhythms with similar ECG morphology to STEMI). The proportion who correctly recognized left bundle branch block was 14.8%, pericarditis was 10.9%, and ventricular pacing was 1.4%. However, almost third of participants correctly identified right bundle branch block (32.9%) and left ventricle hypertrophy (30.7%). Overall, there was no correlation between the correct ECG interpretation of STEMIs and educational and clinical experiences. Conclusion: Paramedics were able to identify STEMI events in prehospital settings with moderate sensitivity and low specificity with limited ability to differentiate between STEMI and STEMI mimics. Therefore, additional training in ECG interpretation could improve their clinical decision-making, and to ensure that proper care and treatment is provided. Further research on a large, representative sample of paramedics across the country could provide more definitive evidence to establish a greater degree of accuracy in detecting STEMI in prehospital settings.

Indexed as

electrocardiogramemergency medical servicesmyocardial infarctionparamedicST segment elevation myocardial infarction

Identifiers

PMID35959233
PMCPMC9359379
OpenAlexW4289705212

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.