Evidence map›Paper›PMID 33419909›Full record

ArticleBMJ open2021

Study protocol for a prospective, double-blinded, observational study investigating the diagnostic accuracy of an app-based diagnostic health care application in an emergency room setting: the eRadaR trial.

S Fatima Faqar-Uz-Zaman, Natalie Filmann, Dora Mahkovic, Michael von Wagner, Charlotte Detemble, Ulf Kippke, Ursula Marschall, Luxia Anantharajah, Philipp Baumartz, Paula Sobotta and 2 more

Abstract readClinical Trial Protocol
In one paragraph

Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Trial
  2. Trial
  3. Review
  4. Article
  5. Review
  6. 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

12 authors.

S Fatima Faqar-Uz-ZamanDepartment for General, Visceral and Transplant Surgery, Hospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Germany SaraFatima.Faqar-Uz-Zaman@kgu.de.ORCID 0000-0002-9017-1641
Natalie FilmannInstitute of Biostatistics and Mathematical Modeling, Goethe-University, Frankfurt/Main, Frankfurt, Germany.
Dora MahkovicLjubljana Central Medical School, Ljubljana, Slovenia.
Michael von WagnerGoethe University Frankfurt, Frankfurt am Main, Hessen, Germany.
Charlotte DetembleHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.
Ulf KippkeHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.
Ursula MarschallBARMER, Wuppertal, Germany.
Luxia AnantharajahHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.
Philipp BaumartzHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.
Paula SobottaHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.
Wolf O BechsteinHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.
Andreas A SchnitzbauerHospital of the Goethe University Frankfurt Surgery Centre, Frankfurt am Main, Hessen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionOccurrence of inaccurate or delayed diagnoses is a significant concern in patient care, particularly in emergency medicine, where decision making is often constrained by high throughput and inaccurate admission diagnoses. Artificial intelligence-based diagnostic decision support system have been developed to enhance clinical performance by suggesting differential diagnoses to a given case, based on an integrated medical knowledge base and machine learning techniques. The purpose of the study is to evaluate the diagnostic accuracy of Ada, an app-based diagnostic tool and the impact on patient outcome. METHODS AND ANALYSIS: The eRadaR trial is a prospective, double-blinded study with patients presenting to the emergency room (ER) with abdominal pain. At initial contact in the ER, a structured interview will be performed using the Ada-App and both, patients and attending physicians, will be blinded to the proposed diagnosis lists until trial completion. Throughout the study, clinical data relating to diagnostic findings and types of therapy will be obtained and the follow-up until day 90 will comprise occurrence of complications and overall survival of patients. The primary efficacy of the trial is defined by the percentage of correct diagnoses suggested by Ada compared with the final discharge diagnosis. Further, accuracy and timing of diagnosis will be compared with decision making of classical doctor-patient interaction. Secondary objectives are complications, length of hospital stay and overall survival. ETHICS AND DISSEMINATION: Ethical approval was received by the independent ethics committee (IEC) of the Goethe-University Frankfurt on 9 April 2020 including the patient information material and informed consent form. All protocol amendments must be reported to and adapted by the IEC. The results from this study will be submitted to peer-reviewed journals and reported at suitable national and international meetings. TRIAL REGISTRATION NUMBER: DRKS00019098.

Indexed as

COVID-19Mobile ApplicationsArtificial IntelligenceDelivery of Health CareEmergency Service, HospitalHumansObservational Studies as TopicProspective StudiesRandomized Controlled Trials as TopicSARS-CoV-2accident & emergency medicineadult gastroenterologyadult surgery

Identifiers

PMID33419909
PMCPMC7798704

What OpenQuestion holds

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Registered trials

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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.