Surgical Simulation in Plastic Surgery: What is the Patients Perspective?
Notice bibliographique
Résumé
Title: Surgical Simulation in Plastic Surgery: What is the Patients Perspective? Research Question: In patients undergoing aesthetic plastic surgery procedures what are the impacts of pre-operative surgical simulation on satisfaction and consent? Searches: A comprehensive search of major bibliographic databases Medline (via Ovid), Embase (via Ovid), and Cochrane Library will be conducted to identify relevant studies. Databases will be searched from inception. The main search strategy will be developed on Medline. The vocabulary and syntax of the Medline strategy will be tailored and adapted to the other databases. No restrictions will be applied (e.g., language, year, status of publication). We will review the reference lists of included studies to identify any other relevant studies. Keywords and index/subject terms will be joined by Boolean operators “AND” or “OR”. Last, we will download all the retrieved citations to an EndNote library for deduplication. Search Terms: All terms utilised can be found in Table S1 (search strategy) Types of studies to be included: Prospective and retrospective studies, randomized controlled trials, cohort studies, case-series, case-control studies, and case reports will be eligible for inclusion. Systematic reviews, meta-analyses, letters to the editor, viewpoints, commentaries, abstracts not traced to full text and protocols not traced to full text will be excluded. Condition of domain being studied: Pre-operative surgical simulation as a tool for patients. This systematic review and meta-analysis will be performed in accordance with the Preferred Reporting of Systematic Review and Meta-Analysis (PRISMA) guidelines. Participants/Population: Adult (≥ 18 years old) or child (≤ 17 years old) patients undergoing surgical simulation prior to a plastic surgery procedure. Intervention(s), exposure(s): Surgical simulation in the pre-operative stage (e.g., computer simulation, augmented reality, virtual reality, artificial intelligence, 3D imaging, Crisalix, Vectra by any physical or screening tool. Comparator(s)/control: Studies which had no control group or that provided a control group (any type). Outcome(s): Type of technology utilized, Surgical Procedure, Type of surgery, Time since surgery (months), Simulation time, Revisions, Number of Rhinoplasties performed, Prior breast surgery, Preoperative simulation/Postoperative result, Similarity of simulated vs actual results, post-op management, Patient satisfaction, Complications etc. Data extraction (selection and coding): Following the removal of duplicate citations, we will transfer the EndNote library to Rayyan, an online systematic review software. Two reviewers will independently screen the titles and abstracts of all the retrieved citations against pre-specified eligibility criteria (see study eligibility above). Studies considered potentially eligible by either reviewer will proceed to full-text assessment. Any disagreements regarding study eligibility will be resolved through consensus, and when necessary, through discussion with a third reviewer. One reviewer will conduct the data extraction, with a piloted data extraction. A second reviewer will review the extracted data and report any disagreements. Discrepancies will be resolved through consensus, and when necessary, through discussion with a third reviewer. Strategy for data synthesis: We will produce summary tables which will include study and sample characteristics as well as results. Where applicable overall averages will be calculated (e.g., patient satisfaction). Analysis of subgroups or subsets: Based on the available data, we will decide if subgroup analyses are appropriate. Risk of bias (quality) assessment: Quality assessment will be performed using the Joanna Brigg’s Institute (JBI) Critical Appraisal Tools. Contact details for further information: Omar El Sewify omar.elsewify@mail.mcgill.ca Organizational affiliation of the review: McGill University Review team members and their organizational affiliations: Omar El Sewify. Laval University Dr. Andrew Gorgy. McGill University Health Centre Collaborators: Not applicable Type and method of review: Systematic review Anticipated or actual start date: January 2024 Anticipated completion date: August 2024 Funding sources/sponsors: None Conflicts of interest: None
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 | 0,024 | 0,089 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,006 | 0,004 |
| Bibliométrie | 0,004 | 0,004 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,006 | 0,008 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,004 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,012 | 0,001 |
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 ».