ArticleCureus2025
Technological Model to Optimize the Request for Radiological Studies.
Article in Cureus, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Inappropriate requests for imaging studies are a frequent problem in clinical practice, leading to diagnostic errors, unnecessary costs, and patient dissatisfaction. These errors often arise from insufficient dissemination of clinical guidelines, limited training of referring physicians, and variability in request formats. The result is delayed diagnoses, duplication of studies, increased radiation exposure, and inefficient use of healthcare resources. To address this issue, technological tools such as diagnostic algorithms have been proposed to support physicians in selecting the most appropriate imaging tests, especially in time-sensitive conditions. This study evaluated a diagnostic algorithm through a cross-sectional survey of 111 participants, including physicians, residents, interns, medical students, and dental professionals. The questionnaire explored perceptions of the algorithm's clinical utility, clarity, and feasibility of integration into daily workflows. Respondents consistently highlighted its capacity to improve diagnostic accuracy, expedite decision-making, and facilitate clearer communication between physicians and radiologists. Specific strengths included its applicability to abdominal emergencies and complex scenarios such as right upper quadrant pain, jaundice, pancreatitis, and trauma. At the same time, participants pointed out challenges, including difficulties in evaluating contrast safety, limited access to high-cost imaging, and the need for broader diagnostic coverage and personalization by age group. Despite these concerns, the algorithm was positively received overall and was recognized as a useful support tool for reducing inappropriate requests, enhancing diagnostic confidence, and ultimately improving patient care.
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Registered trials
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.