MétaCan
Menu
Retour à la cohorte
Enregistrement W2912529759 · doi:10.7759/cureus.3991

Development of an Anatomical Silicone Model for Simulation-based Medical Training of Obstetric Anal Sphincter Injury Repair in Bangladesh

2019· article· en· W2912529759 sur OpenAlexafffundabout
Christine Goudie, Atamjit Gill, Jessica Shanahan, Andrew Furey, Adam Dubrowski

Notice bibliographique

RevueCureus · 2019
Typearticle
Langueen
DomaineMedicine
ThématiquePelvic and Acetabular Injuries
Établissements canadiensMemorial University of Newfoundland
Organismes subventionnairesAtlantic Canada Opportunities Agency
Mots-clésMedicineAnal sphincterSimulation trainingSphincterSurgerySimulation

Résumé

récupéré en direct d'OpenAlex

Advancing global healthcare in developing countries has traditionally been an area of interest for many North American medical organizations, as they strive to improve patient outcomes by helping to control disease and death-related illnesses. Women's healthcare in developing countries, in particular, presents a unique set of complexities, revealing high maternal mortality statistics surrounding pregnancy, labor, and childbirth, which is often tied to home births without medically trained attendants. In September 2018, Team Broken Earth, a Canadian-based outreach initiative, hosted a three-day women's healthcare course in Dhaka, Bangladesh, which included simulation-based training stations, for the purpose of advancing clinical skills and education in regards to local labor and delivery. The training stations included the prevention of shoulder dystocia, helping babies breathe, the application of uterine compression sutures, and the repair of obstetric anal sphincter injuries (OASIS). The OASIS management station provided an opportunity to practice anal sphincter repair on anatomically accurate silicone models, which was a focus of the training course due to the high frequency of such injuries in rural Bangladesh. Evaluation surveys were supplied to workshop participants to capture their feedback about the use of the OASIS models and their efficacy as a training tool in Bangladesh. Overall, the models were considered superior as compared to pre-existing training methods, which traditionally involve textbook education and hands-on learning in emergency birthing scenarios by non-medically trained attendants. Two minor iterative improvements were suggested during the Team Broken Earth workshops in Dhaka, Bangladesh, with regards to improving the models for future use: (a) the ethnicity coloring of the models should be more inclusive, especially when delivering training in international countries, and (b) future silicone models should include the addition of mesh across the bottom layer to ensure participants fingers did not rupture the enclosed vaginal canal while suturing. The purpose of this technical report is to determine the efficacy of a silicone OASIS model, developed for practicing high-risk laceration repair that can occur during childbirth, which presents in higher frequency in developing countries, such as Bangladesh, due to the number of rural at-home deliveries. The original study in this series involved the investigation of silicone perineal repair models focusing on first- and second-degree lacerations, which were used at the Remote and Rural Conference in St. John's, Newfoundland, in April 2018. The facilitators distributed the first iteration of the models to conference participants and collected participant feedback, which concluded that several improvements were required to enhance the models for medical training purposes. With the iterative revisions complete, the model is now under further validation testing to determine its efficacy within simulation-based medical education (SBME) and clinical skill maintenance. This technical report is the second in the series and includes the most recent third and fourth-degree silicone models as well as all suggested improvements from previous clinical feedback.

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 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)0,000
score de la tête « metaresearch » (Gemma)0,001
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,868
Score d'incertitude au seuil0,400

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
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 Opus0,037
Tête enseignante GPT0,326
Écart entre enseignants0,289 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations10
Publié2019
Routes d'admission3
Résumé présentoui

Explorer davantage

Même revueCureusMême sujetPelvic and Acetabular InjuriesTravaux en français237 207