Evidence map›Paper›PMID 39638911›Full record

ArticleEmergency radiology2025

Radiology resident proficiency in identifying misplaced lines, tubes, and devices: a simulation-based study using WIDI SIM.

Alexandria Iakovidis, Kevin Pierre, Abheek Raviprasad, Isabella Carvalho, Alina Zankevich, Roberta Slater, Christopher Sistrom, Otgonbayar Batmunh, Priya Sharma, Anthony Mancuso and 1 more

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Article in Emergency radiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

11 authors.

Alexandria IakovidisUniversity of Florida, Gainesville, USA. a.iakovidis@ufl.edu.
Kevin PierreUniversity of Florida, Gainesville, USA. kpierre150@ufl.edu.
Abheek RaviprasadUniversity of Florida, Gainesville, USA.
Isabella CarvalhoUniversity of Florida, Gainesville, USA.
Alina ZankevichUniversity of Florida, Gainesville, USA.
Roberta SlaterUniversity of Florida, Gainesville, USA.
Christopher SistromUniversity of Florida, Gainesville, USA.
Otgonbayar BatmunhUniversity of Florida, Gainesville, USA.
Priya SharmaUniversity of Florida, Gainesville, USA.
Anthony MancusoUniversity of Florida, Gainesville, USA.
Dhanashree RajderkarUniversity of Florida, Gainesville, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccurate placement of medical devices is crucial in critical care to prevent severe complications. This study aims to evaluate radiology residents' proficiency in identifying four specific critical misplacements of medical devices using the Wisdom in Diagnostic Imaging Simulation (WIDI SIM).

methodsA retrospective analysis was conducted on 1,102 responses from radiology residents who participated in the WIDI SIM between 2010 and 2022. The majority were first- and second-year residents from multiple institutions. The simulation presented four specific cases featuring misplacements of an endotracheal tube in the esophagus, an intrauterine device embedded in the myometrium, a peripherally inserted central catheter in the right internal jugular vein, and an umbilical venous catheter in the splenic vein. Residents provided free-text interpretations scored on a 0-10 scale by subspecialty radiologists. Errors were categorized as observational (failure to identify misplacement) or interpretive (misinterpretation of identified misplacement). Statistical analyses were performed using Kruskal-Wallis and Dunn's multiple comparisons tests.

resultsAcross all cases, residents' average scores did not meet the acceptable standard of 7 points. Observational errors were predominant, indicating a failure to recognize these specific device misplacements. Effective report rates were low: 58% for the endotracheal tube case, 35% for the intrauterine device, 19% for the peripherally inserted central catheter, and 25% for the umbilical venous catheter. Significant performance improvements were observed between first- and second-year residents in three of the four cases (p-values ranging from < 0.0001 to 0.0238), but overall proficiency remained suboptimal even among senior residents.

conclusionThis study reveals gaps in radiology residents' ability to identify these specific misplaced lines, tubes, and devices accurately. The consistent pattern of underperformance, primarily due to observational errors, suggests a need for targeted educational interventions to improve resident proficiency in this aspect of emergency radiology.

Indexed as

Clinical CompetenceDiagnostic ErrorsInternship and ResidencyRadiologySimulation TrainingCatheterization, Central VenousFemaleHumansIntubation, IntratrachealMaleRetrospective StudiesDevice-Related ComplicationsDiagnostic AccuracyDiagnostic ImagingMedical ErrorsPatient SafetyQuality ImprovementRadiologyRadiology Resident EducationResident EducationSimulation Training

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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.