Trends of colorectal cancer surgery in 2022
Bibliographic record
Abstract
Trends of colorectal cancer surgery in 20222022 was a great year for high-quality submissions to BJS Open in the field of colorectal cancer (CRC) surgery.Layfield and associates 1 documented how changes in treatments delivered by the multidisciplinary team (MDT) over 14 years, demonstrating how implementation of CRC management based on the latest gold standards, significantly improved survival and reduced mortality in a high-volume UK institution.Of note, concerning older patients, they demonstrated the changing pattern in MDT decisions with a decreased rate of surgical intervention.Despite this reduction in surgery and oncological therapies, the survival benefit was also seen among patients aged 80 years or more, which may reflect the 'inclusion of patients who would previously have undergone surgery but lived a little longer without it' or had fatal complications after major procedures.Regarding management, in their analysis of 41 800 patients from Denmark and Yorkshire (UK), Taylor and co-authors 2 reported the application of specific policies in Denmark at a national level that resulted in a reduction in left-sided emergency resections and an increase in stenting.This resulted in conversion of potential emergency into elective resections and reduced 30-day postoperative mortality.The debate on management leads to other important topics: cost-effectiveness and correction of modifiable preoperative risk factors with protocols implemented at institutional level.In particular, a large Canadian study 3 , analysing circular stapler anastomotic rings specimens from nearly 490 CRC resections, confirmed that their routine pathologic evaluation is not useful, as no patients had cancer in the ring specimen, 5.1 per cent had benign pathological findings and patients' management was never affected by this result.Also, in another registry study including nearly 6200 patients from Sweden 4 , authors documented that the routine use of rectal washout during anterior resection did not impact the 3-year oncological outcomes, even if a reduction in local recurrence risk after the 5-year follow-up was observed.In another large Danish study 5 , authors investigated the effect of screening for modifiable high-risk factors combined with targeted interventions in CRC surgery.These consisted of a screening for anaemia, low functional capacity, and nutritional status and their implementation (iron supplementation, pre-habilitation, nutritional supplements, and consultation with a dietician) for a minimum of 4 weeks before surgery.Even when analyses were balanced for age, sex, smoking habits, stage of disease, ASA score, surgical approach, and surgical procedure, the intervention was associated with a 10.9 per cent absolute risk reduction of a complicated postoperative course, primarily due to a reduction in severe complications, highlighting what and how it's worth to correct.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".