Do Preoperative Transfusions Impact Prognosis in Moderate to Severe Anaemic Surgical Patients with Colon Cancer?
Bibliographic record
Abstract
(1) Background: Anaemia is a common finding in patients with colon cancer and is commonly corrected by blood transfusion prior to surgery. However, the prognostic role of perioperative transfusions is still debated. The aim of the present study was to investigate the role of preoperative anaemia and preoperative blood transfusion in influencing the prognosis in colon cancer. (2) Patients and Methods: Patients undergoing elective surgery for colon cancer at a tertiary referral university hospital between January 2010 and December 2018 were included in a retrospective review of a prospectively collected database. Univariate and regression analyses were performed to identify the prognostic role of preoperative anaemia and preoperative transfusions in this homogeneous cohort of patients. (3) Results: A total of 780 patients were included in the final analysis. The estimated five-year overall survival rate was significantly worse in the anaemic group (83.8% in non-anaemic patients, 60.6% in mild anaemic patients, 61.3% in moderate anaemic patients and 58.4% in severe anaemic patients; log-rank < 0.001 vs. non-anaemic patients). Anaemic status was found to be an independent adverse prognostic factor (hazard ratio (HR): 1.46; 95% confidence interval (CI): 1.02-2.07) during multivariate analysis. Among moderate to severe anaemic patients, no significant association was found between preoperative transfusions and the risk of mortality or recurrence. (4) Conclusions: Preoperative anaemia, regardless of its severity, and not preoperative blood transfusion, was independently associated with a worse prognosis after surgery in patients with colonic cancer.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".