Evidence map›Paper›PMID 29705886›Full record

ArticleInternal and emergency medicine2018

Media messaging in diagnosis of acute CXR pathology: an interobserver study among residents.

Guy S Handelman, Ailin C Rogers, Zafir Babiker, Michael J Lee, Morgan P McMonagle

Abstract read
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In one paragraph

Article in Internal and emergency medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Diagnostic accuracy and reliability of smartphone captured radiologic images communicated via WhatsApp®.African journal of emergency medicine : Revue africaine de la medecine d'urgence · 2022
    Article
  3. 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

5 authors.

Guy S HandelmanDepartment of Radiology, Royal Victoria Hospital, Grosvenor Road, Belfast, BT12 6BA, UK.ORCID http://orcid.org/0000-0003-4275-783X
Ailin C RogersDepartment of Surgery, Beaumont Hospital, Dublin, Ireland.
Zafir BabikerDepartment of Radiology, University Hospital Waterford, Waterford, Ireland.
Michael J LeeDepartment of Radiology, Beaumont Hospital, Dublin, Ireland.
Morgan P McMonagleDepartment of Vascular Surgery, University Hospital Waterford, Waterford, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The objectives of the study were to determine whether diagnostic accuracy and reliability by on-call teams is affected by communicating chest radiograph (CXR) images via instant messaging on smartphones in comparison to viewing on a workstation. 12 residents viewed 100 CXR images each with a 24% positive rate for significant or acute findings sent to their phones via a popular instant messaging application and reported their findings if any. After an interval of 42 days they viewed the original DICOM images on personal computers and again reported their findings. There were no statistically significant differences in accuracy, agreement, sensitivity, specificity, positive predictive value or negative predictive value between desktop workstation viewed images and images sent via the mobile application. Media messaging is a useful adjunct for quick second opinions on radiological images, without significant decay in diagnostic accuracy. If technical, ethical and legal issues are addressed, it could be incorporated into practice as a useful adjunct.

Indexed as

AdultClinical CompetenceFemaleHumansMaleMobile ApplicationsPathologyRadiographyReproducibility of ResultsTeleradiologyText MessagingThoraxEthics, medicalLiability, legalMobile applicationsNear miss, healthcare, chest X-rayTeleradiology

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.