Challenges and potential solutions to the evaluation, monitoring, and regulation of surgical innovations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: As it may be argued that many surgical interventions provide obvious patient benefits, formal, staged assessment of the efficacy and safety of surgical procedures has historically been and remains uncommon. The majority of innovative surgical procedures have therefore often been developed based on anatomical and pathophysiological principles in an attempt to better manage clinical problems. MAIN BODY: In this manuscript, we sought to review and contrast the models for pharmaceutical and surgical innovation in North America, including their stages of development and methods of evaluation, monitoring, and regulation. We also aimed to review the present structure of academic surgery, the role of methodological experts and funding in conducting surgical research, and the current system of regulation of innovative surgical procedures. Finally, we highlight the influence that evidence and surgical history, education, training, and culture have on elective and emergency surgical decision-making. The above discussion is used to support the argument that the model used for assessment of innovative pharmaceuticals cannot be applied to that for evaluating surgical innovations. It is also used to support our position that although the evaluation and monitoring of innovative surgical procedures requires a rigorous, fit-for-purpose, and formal system of assessment to protect patient safety and prevent unexpected adverse health outcomes, it will only succeed if it is supported and championed by surgical practice leaders and respects surgical history, education, training, and culture. CONCLUSION: We conclude the above debate by providing a recommended approach to the evaluation, monitoring, and regulation of surgical innovations, which we hope may be used as a guide for all stakeholders involved in interpreting and/or conducting future surgical research.
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.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it