ODP578 Utility of the ACR-TIRADS Score – A Survey of Primary Care Providers
Notice bibliographique
Résumé
Abstract Background The American College of Radiology – Thyroid Imaging Reporting and Data System (ACR-TIRADS) score is an ultrasound-based tool used to assess the risk of malignancy in thyroid nodules. Despite evidence supporting its efficacy, the use of this score in clinical practice has not yet been reported. Since primary care providers commonly identify and manage thyroid nodules, we aimed to determine 1) current diagnostic approach to thyroid nodules and 2) perceived utility of ACR-TIRADS in Canadian primary care providers. Methods We conducted a cross-sectional survey study with family medicine physicians and nurse practitioners working in Canada. The 23-question survey was developed and distributed electronically on Qualtrics using convenience sampling from August 31 2021 to January 3, 2022. Sociodemographic and other quantitative questions using Likert scales were analyzed using descriptive statistics; Likert scale responses were analyzed as proportion of individuals who agreed or strongly agreed. Qualitative data from free text answers was assessed using content analysis. Results One hundred and four primary care providers responded to our survey. Of these, 90 (87%) completed the entire survey and were included. Fifty-six percent were female, 58% were aged <40 years, and 48% were in practice for five or fewer years. In terms of management of thyroid nodules, only 47% were confident in their ability to risk-stratify. Ninety-four percent of participants risk-stratified using imaging characteristics, but only 57% of respondents reported using a risk stratification tool. Despite 64% percent of participants agreeing with being familiar with the ACR-TIRADS score, only 28% used this scoring system, and 80% of participants had a desire to learn more about it. Only 68% of physicians believed the score was present on ultrasound reports, and <5% requested it on reports themselves. After being shown a diagram demonstrating the ACR-TIRADS scoring system, 93% thought that the ACR-TIRADS score was useful. Of the 31 (34%) participants who were not initially familiar with the score, 61% would use the ACR-TIRADS score more, and 77% would ask radiology to report the ACR-TIRADS score more often. In terms of qualitative data, respondents believed educational tools and increased reporting by radiologists would increase use of ACR-TIRADS. Conclusion In this Canadian survey study, the majority of respondents were not confident with risk stratification of thyroid nodules, and only half used a risk stratification tool. With education, almost all participants thought ACR-TIRADS was useful, and most participants would use it more often. Further interventions to educate primary care providers regarding the ACR-TIRADS score may help enhance its uptake and improve systematic management of thyroid nodules. Presentation: No date and time listed
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 | 0,003 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».