A systematic review of full economic evaluations of robotic-assisted surgery in thoracic and abdominopelvic procedures
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
This study aims to conduct a systematic review of full economic analyses of robotic-assisted surgery (RAS) in adults' thoracic and abdominopelvic indications. Authors used Medline, EMBASE, and PubMed to conduct a systematic review following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines. Fully published economic articles in English were included. Methodology and reporting quality were assessed using standardized tools. Majority of studies (28/33) were on oncology procedures. Radical prostatectomy was the most reported procedure (16/33). Twenty-eight studies used quality-adjusted life years, and five used complication rates as outcomes. Nine used primary and 24 studies used secondary data. All studies used modeling. In 81% of studies (27/33), RAS was cost-effective or potentially cost-effective compared to comparator procedures, including radical prostatectomy, nephrectomy, and cystectomy. Societal perspective, longer-term time-horizon, and larger volumes favored RAS. Cost-drivers were length of stay and equipment cost. From societal and payer perspectives, robotic-assisted surgery is a cost-effective strategy for thoracic and abdominopelvic procedures.Clinical trial registration This study is a systematic review with no intervention, not a clinical trial.
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 | 0.011 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.014 | 0.003 |
| Bibliometrics | 0.003 | 0.001 |
| 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 it