Evidence map›Paper›PMID 40057691›Full record

ArticleBMC cardiovascular disorders2025

Design and Evaluation of ACAFiB-APP, a clinical decision support system for anticoagulant considerations in patients with atrial fibrillation.

Ramin Ansari, Sorayya Rezayi, Ali Asghar Safaei, Reza Mollazadeh, Eisa Rezaei, Mahboobeh Khabaz Mafinejad, Soha Namazi, Keyhan Mohammadi

Abstract readEvaluation Study
In one paragraph

Article in BMC cardiovascular disorders, 2025. 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
–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

2 citing papers in PubMed.

  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

8 authors.

Ramin AnsariDepartment of Clinical Pharmacy, School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.
Sorayya RezayiDepartment of Health Information Management, School of Management and Medical Informatics, Tabriz University of Medical Sciences, Tabriz, Iran.
Ali Asghar SafaeiDepartment of Medical Informatics, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
Reza MollazadehDepartment of Cardiology, School of Medicine, Imam Khomeini Hospital Complex, Tehran University of Medical Sciences, Tehran, Iran.
Eisa RezaeiDepartment of Medical Education, Virtual University of Medical Sciences, Tehran, Iran.
Mahboobeh Khabaz MafinejadDepartment of Medical Education, Health Professions Education Research Center, Education Development Center, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Soha NamaziDepartment of Clinical Pharmacy, School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran.
Keyhan MohammadiDepartment of Clinical Pharmacy, School of Pharmacy, Tehran University of Medical Sciences, Tehran, Iran. keyhanmohammadi72@yahoo.com.ORCID 0000-0002-7699-8538

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPatients with atrial fibrillation are at risk for various complications, including thromboembolic events. This study involves developing and evaluating a Clinical Decision Support System (CDSS) to select appropriate anticoagulant drug, considering comorbidities, laboratory data, and concurrent medications. The system is based on a streamlined interpretation of the most recent globally accepted clinical guidelines.

methodsPrimarily a semi-structured interview regarding the challenges in the field of thromboprophylaxis for AF and clinical pharmacists and cardiologists' needs in practice was conducted. Then the required data were extracted from the latest guidelines and confirmed by the expert panel. Using Microsoft Visio software each scenario and its corresponding rules were modeled. Dart programming language, the Flutter framework, and the Visual Studio editor were used to develop the application. Finally, the uMARS questionnaire was used to evaluate the application quality.

resultsThe selection of the anticoagulants was reported to be the most challenging domain by 78.6% of the participants in the interview. According to the designed algorithms, the application was developed using Asp.net with the Microsoft SQL Server database platform. This CDSS is called ACAFiB-APP, which stands for Anticoagulant in AF Application. The user goes through various calculators and obtains the required data, moreover, the user will choose one or more comorbidities/clinical scenarios. Finally, ACAFiB-APP will represent the proper anticoagulant options with dosing and related considerations. All of the sections in the uMARS questionnaire received acceptable scores.

conclusionsThe CDSS will facilitate the informed selection of anticoagulants for complicated AF cases by considering the patient clinical scenario. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

AnticoagulantsAtrial FibrillationDecision Support Systems, ClinicalDecision Support TechniquesThromboembolismClinical Decision-MakingHumansPatient SelectionRisk AssessmentRisk FactorsSoftware DesignAnticoagulantsAnticoagulantAtrial fibrillationClinical decision support systemDigital health

Identifiers

PMID40057691
PMCPMC11889798

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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.