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Enregistrement W2317788471 · doi:10.5603/cj.2014.0009

Generation iUltrasound: Bedside diagnostic imaging with Hand-Held Cardiac Ultrasound

2014· article· en· W2317788471 sur OpenAlex

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Notice bibliographique

RevueCardiology Journal · 2014
Typearticle
Langueen
DomaineMedicine
ThématiqueUltrasound in Clinical Applications
Établissements canadiensQueen's University
Organismes subventionnairesnon disponible
Mots-clésMedicineCardiologyCardiac imagingInternal medicineUltrasoundCardiac UltrasoundUltrasound imagingRadiology

Résumé

récupéré en direct d'OpenAlex

In the early nineteenth century, an enquiring physician rolled up a notebook and placed it upon the chest of a young woman in order to hear her heart and understand its rhythmic beating more clearly. Thus began the teaching of a new approach to ‘les maladies cardiologiques’ [1]. Two-hundred years later this tube remains the cornerstone of the cardiac physical exam; an object evocative of our profession (Figs. 1, 2). As clinical educators, are we ready for a change in diagnostic technology? Whether we are or not, the availability of small, portable Hand-Held Cardiac Ultrasound (HHCU) devices portends a tidal change in diagnostic ability with important implications to the physical exam and point-of-care diagnosis (Fig. 3). We are now tasked with establishing the capabilities and limitations of these new medical devices in the hands of various users. Some consensus is emerging: studies have shown that these devices are a valuable tool for augmenting the diagnostic value of the standard physical exam and even novel learners can be taught to identify specific cardiac pathologies using HHCU [2–4]. However it is now clearly recognized that bedside examination with HHCU is not to be considered a substitute for a comprehensive or limited echocardiogram, and with the current technology these machines are only suited to performing focused cardiac ultrasound examinations, even when used by expert sonographers [5]. Within the practice of focused cardiac ultrasound, the image acquisition and interpretation skills of the user are the major factors determining the efficacy of these devices as a mechanism for improving the diagnostic power of a standard cardiac exam [6]. Further research into the development and implementation of HHCU training is warranted. The Cardiovascular Imaging Network at Queen’s (CINQ) has sought to gain experience in developing a critical framework for teaching HHCU skills in new learners. Our group is led by expert Level III trained echocardiographers with expertise in medical education. Our work has been presented at several conferences across Canada and the USA [2, 7] and we lead the Canadian National Working Group on HHCU Education. We recently advanced this work by conducting a preliminary study in 10 senior internal medical residents demonstrating that HHCU improved clinical management of patients in the Emergency Department and improved the confidence of these physicians in their assessment of patients referred for cardiology assessment [8]. Although this exciting preliminary work shows feasibility of a formal HHCU training program for residents, careful further study is required to investigate the optimal method of delivering this integrative skill. Acquisition of HHCU skill is becoming recognized as an emerging essential competency, however, currently medical residency has objectives set by the Royal College which do not incorporate these specific skills. Thus, additional training of this complex integrative skill requires recognition of the current time and resource constraints placed upon learners and educators. To address these challenges, we developed rich electronic modules in coordination with our Information Technology experts at Queen’s School of Medicine, and worked with our Simulation Laboratory to acquire and develop a state-of-the-art cardiac ultrasound simulation program. In addition to the lecture based curriculum developed by expert educators in our laboratory, we developed resources available for delivering HHCU programming in post-graduate training. We now intend to look at various combinations of these resources to determine the optimal method of delivering HHCU skill to internal medicine trainees during their busy residency. COMMENTARIES Cardiology Journal 2014, Vol. 21, No. 1, pp. 98–99 DOI: 10.5603/CJ.2014.0009 Copyright © 2014 Via Medica ISSN 1897–5593

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,005
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,106
Score d'incertitude au seuil0,756

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,005
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0010,001
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,025
Tête enseignante GPT0,302
Écart entre enseignants0,277 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle