Surgical Simulation in Plastic Surgery: What is the Patients Perspective?
Bibliographic record
Abstract
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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".