Management of Acute Contrast Reactions—Understanding Radiologists' Preparedness and the Efficacy of Simulation-Based Training in Canada
Notice bibliographique
Résumé
PURPOSE: Acute radiologic emergencies, primarily severe contrast reactions, are rare but life-threatening events. Given a generalized paucity of formalized or mandated training, studies have shown that radiologists and trainees perform poorly when acutely managing such events. Moreover, skill base, knowledge, and comfort levels precipitously decline over time given the infrequent occurrence of these events during one's daily practice. The primary aim of this study was to assess radiologists' preparedness for managing acute radiologic emergencies and to determine the efficacy of a high-fidelity simulation based training model in an effort to provide a rationale for similar programs to be implemented on a provincial or national level. METHODS: This was a prospective, observational study of radiology residents and attending radiologists throughout the province who were recruited to attend a full-day simulation-based course presenting various cases of acute radiologic emergencies. Participant demographics were collected at the time of commencement of the workshop. Course materials were disseminated 4 weeks prior to the workshop, and a 17-question knowledge quiz was administered before and after the workshop. Likert-type questionnaires were also distributed to survey comfort levels and equipment familiarity. The knowledge quiz and questionnaire were redistributed at 3- and 6-month intervals for acquisition of follow-up data. RESULTS: A total of 14 attending radiologists and 7 residents attended the workshop, with all participants completing the preworkshop questionnaire and 90.5% (19 of 21) completing the post-workshop questionnaire. Participants' principle locations of practice were as follows: academic institutions (50%), community hospitals (36.9%), and private clinics (13.1%). A significant increase in knowledge was demonstrated, with average scores of 10 out of 17 (59%) and 14.5 out of 17 (85%) (P < .001) before and after the workshop, respectively. A significant increase in participants' comfort levels in recognizing acute anaphylactic reactions (3.5; 4.7, P < .001), commencing initial management for acute radiologic emergencies (3.3; 5.0, P < .001), and administering the correct dose for anaphylactic reactions (2.5; 4.8, P < .001) was also demonstrated. Moreover, participants became increasingly familiar with the contents and equipment found within contrast reaction kits (2.8; 3.8, P < .01). Repeat evaluations at 3 and 6 months found an average knowledge test score of 13.8 out of 17 (81%) and 10.8 out of 17 (64%), respectively. Comfort levels were also reassessed in recognizing acute anaphylactic reactions (4.5; 4.1), commencing initial management (4.0; 3.9) and administering the correct dose of medication (4.0; 3.7) at 3- and 6-month intervals. CONCLUSIONS: Acute radiologic emergencies are rare but life-threatening events that require rapid diagnosis and treatment to mitigate associated morbidity and mortality. Simulation-based workshops are a highly efficacious training model to increase knowledge, comfort levels, and equipment familiarity for radiologists and trainees alike; however, retraining at regular intervals is required.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,016 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,002 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».