BS SO02 - A systematic review to summarise and appraise the reporting of surgical innovation: A case study in robotic Roux-en-Y gastric bypass
Bibliographic record
Abstract
Abstract Background Robotic Roux-en-Y gastric bypass (RRYGB) is an innovative alternative to the laparoscopic approach, however its clinical benefits are uncertain. The Idea, Development, Exploration, Assessment and Long-term follow-up (IDEAL) framework was developed to improve the evaluation of surgical innovations alongside their adoption into clinical practice. Studies investigating the benefits of RRYGB have been published, however the reporting quality and robustness of literature has not been assessed. The aim of this systematic review was to summarise and appraise the reporting of RRYGB as a case study of a surgical innovation in relation to the IDEAL framework. Method Systematic searches for primary studies evaluating totally RRYGB were undertaken. Their IDEAL stages were determined using a standardised algorithm. Information pertaining to study characteristics, governance/ethical factors, patient selection, demographics, surgeon expertise/training, technique description and outcomes were extracted. A narrative summary was formulated, with descriptive statistics and data arranged chronologically. All methodology was done in accordance with PRISMA guidance. Results Fourty-seven studies published between 2005-2024 were included: case report (n=1), case series (n=11), non-randomised comparative (n=28) and retrospective analysis of registry databases (n=7). IDEAL stages were assigned as follows: stage 1 (n=1), stage 2a (n=6), stage 2b (n=40), stage 3 (n=0), stage 4 (n=0). There was a lack of sequential progression through IDEAL stages as time progressed since the inception of RRYGB. There was incomplete and inconsistent reporting of governance, ethics, patient selection criteria, surgeon expertise/training and technique description. Outcomes were heterogenous and rarely corresponded to progress through the IDEAL model of surgical innovation. Conclusion Reporting of RRYGB literature correlated poorly with IDEAL recommendations. This indicates poor reporting quality of available literature, impeding the ability for surgeons to draw meaningful conclusions from available evidence. This also complicates patients’ ability to take part in shared decision-making and give informed consent. Future studies should report findings in a structured way using IDEAL guidance or a similar reporting standard. This will ensure future research is transparent, robustly designed, prospective, uses COSs and follows an ethos of incremental learning. This may reduce research waste and the premature adoption of surgical innovations, ensuring their safe introduction into clinical practice.
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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 | 0.020 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.008 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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; a candidate call from one teacher head, not a consensus.
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".