HIPEC + EPIC versus HIPEC‐alone: Differences in major complications following cytoreduction surgery for peritoneal malignancy
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
INTRODUCTION: Peritoneal metastases (PM) can be treated with cytoreduction surgery (CRS) with intraoperative heated intraperitoneal chemotherapy (HIPEC) plus or minus early postoperative intraperitoneal chemotherapy (EPIC). HIPEC + EPIC may be associated with more complications than HIPEC alone. METHODS: A prospective database of consecutive patients undergoing CRS + HIPEC ± EPIC at the University of Calgary between February 2000 and May 2011 was reviewed. Patient, tumor, and perioperative variables included peritoneal cancer index (PCI), completeness of cytoreduction (CCR) score, HIPEC ± EPIC type, and grade III/IV complications. RESULTS: 198 patients had a CCR score of 0/1 and received: (1) HIPEC mitomycin C + EPIC 5-fluorouracil for 5 days (n = 85; February 2000-January 2008); or (2) HIPEC oxaliplatin with IV 5-fluorouracil + no EPIC (n = 113; February 2008-May 2011). Clinicodemographics were similar except PCI was higher in the HIPEC-alone group (mean PCI 22 vs. 17; P = 0.02). The rate of grade III/IV complications was higher in the HIPEC + EPIC group (44.7% vs. 31.0%; P = 0.05). On multivariate logistic regression only HIPEC + EPIC and PCI > 26 were associated with an increased rate of complications. CONCLUSION: In patients with PM, the use of EPIC, in combination with CRS and HIPEC, is associated with an increased rate of complications. Surgeons should consider using HIPEC only (without EPIC).
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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