Cost-effectiveness of current approaches in rectal surgery
Bibliographic record
Abstract
Colorectal cancer is ranked as the fourth malignant cause of mortality. With the tremendous revolution in the modern medical techniques, minimally invasive approaches have been incorporated into rectal surgery. The effectiveness of surgical procedures is usually measured by a combination of qualitative (quality of life) and quantitative (years of life) measures, while the costs should reflect the use of different resources that were involved in delivering the medical care and they are affected by several factors, including length of hospital stay. In this review, we provide an insight into the cost-effectiveness of the different types of rectal surgeries in order to present a systematic approach for future preferences. A comprehensive literature review using Medline (via PUBMED), Embase and Cochrane Central Register of clinical trials (via clinical trial.org) was performed. Minimally invasive rectal surgeries have considerable cost-effective properties that outweigh those of the open techniques in terms of earlier return to bowel function, lower morbidity rates, reduced pain, shorter length of hospital stay and the overall patients' quality of life although there was no difference in long-term oncological and survival outcomes. The paucity of currently available long-term oncologic, quality of life, and economic outcomes may limit an adequate comparison of robotic surgeries to other surgical techniques. It is therefore recommended to conduct focused studies to help balance the cost/benefit factors along with other technical considerations aimed at reducing the cost of robotic systems with subsequent improvement of their cost-effectiveness.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 source (direct Gemma or distilled Codex), 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".