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Enregistrement W4207054574 · doi:10.33976/iugns.30.1/2022/2

Initial Experience of the Training Centre of Minimally Invasive Surgery at Ahli Arab Hospital in Gaza

2022· article· en· W4207054574 sur OpenAlexaboutno aff

Notice bibliographique

RevueIUG Journal of Natural Studies · 2022
Typearticle
Langueen
DomaineMedicine
ThématiqueSurgical Simulation and Training
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésTrainerLaparoscopic surgeryCurriculumInvasive surgeryTraining systemMedicineTraining (meteorology)Virtual realityPhysical therapyMedical educationSurgerySimulationMedical physicsLaparoscopyPsychologyComputer scienceArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Background: Minimally Invasive Surgery (MIS) training outside operation room is still done by simulation in different training centers worldwide. Strong validity of such a training was evidenced using either the physical simulator (trainer box) or a biological model or a virtual reality (VR) or an animal model. Currently MIS is rapidly spreading worldwide in different surgical centers depending on the fact that MIS training is an essential prerequisite for any surgeon even with a vast experience in open surgery. A well-structured proficiency-based curriculum is essential to provide training for individuals who need to acquire MIS skills. Aim: To prove the efficiency and accuracy of training laparoscopic skills on combination of physical simulator as the dry module to be scored by a modified McGill Inanimate System for Training and Evaluation of Laparoscopic Skills (MISTELS) scoring system and on laparoscopic simulator as the wet module (Full Turkey model) using the Global Operative Assessment of Laparoscopic Surgery (GOALS) scoring items. Methods: One hundred and thirty-nine surgeons of different surgical specialties, age and experience levels (during the period from July 2018 to July 2019) were subjected to this curriculum-based training. All trainees received the basic cognitive knowledge in groups of fifteen to eighteen. In the hands on training each group is divided into three subgroups to fit the available six fundamental laparoscopic surgery (FLS) training boxes. Trainees are monitored by at two mentored per trainer in the different FLS skills and tasks. A modified (MISTELS) was used to score the five Fundamental Laparoscopic Surgery (FLS) skills and tasks that are the standard of the Society of American Gastroenterology Endoscopic Surgery (SAGES). Modifications entail the scoring time to be in minutes rather than in seconds. Some extra-activities were added to the first three skills/tasks. A score sheet was designed for each task considering both the scoring time and penalties. In Wet lab, not only the five tasks were repeated but also a complementary skill such as Veress needle insertion, port insertion and camera manipulation together with dissection e.g. intracorporeally in cholecystectomy were provided through a full Turkey model on a laparoscopic simulator. Trainees’ performance was measured with integration of cognitive knowledge post-testing, score in the modified MISTEL in dry lab and by the Global Operative Assessment of Laparoscopic Surgery (GOALS) scoring in wet laboratory. The mean of total score of the trainee before training was 35.28 while after training was 82.59 but Cronbach’s Alpha value in the pre and post testing scored 0.778 and 0.799 respectively Results: Majority of trainees showed improvement in all measured domains in different stations. In cognitive knowledge the mean score difference between the pre and post testing was 50.1and 72.14 respectively. This is statistically significant as shown in the student T-test value of 19.13. This indicates that the trainees are having some knowledge but definitely refined and improved on post testing. In Dry Lab there is a dramatic improvement in the post testing compared to pretests where there was a clear statistical significance of a P value of 0.01 in all the five skills and tasks between the pre and post test of each. In wet Lab the Global Operative Assessment of Laparoscopic Surgery (GOALS) scoring system Which is used to assess skill of surgeons in clinical settings in OR is used to simulate clinical sessions on a Full Turkey Model on laparoscopic simulator set. GOALS scoring in Full Turkey model proves its feasibility and efficiency in most trainees where Mean score was 84.1, The Median 84.0, and the Std = 5.38. Construct validity of this triad methodology of cognitive knowledge, dry lab and wet lab of full Turkey model is evident among different trainees of different groups with no florid significance of different surgeons in relation scores achieved and age group proving validity of this type of training. There is no statistical differences between age group and the final score of overall training the mean average of the trainees ages less than 35 years old was 81.2% followed by the trainees above 45 years old 79.7% with very simple difference in mean with trainees aged between 35 years old to 45 years old 79.6%. Conclusion: MIS training integrating a triad of training modules of MIS cognitive knowledge, traditional physical box trainer and a biological wet lab on a full Turkey model is fairly feasible and effective in the acquisition of fundamental laparoscopic skills and tasks. Global Operative Assessment of Laparoscopic Skills (GOALS) can be a valid tool to assess trainees outside operation room.

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: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,033
Score d'incertitude au seuil0,239

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
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 Opus0,071
Tête enseignante GPT0,332
Écart entre enseignants0,261 · 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'étudeObservationnel
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

Citations0
Publié2022
Routes d'admission1
Résumé présentoui

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