EUS‐guided Celiac Plexus Neurolysis for Pain in Pancreatic Cancer
Bibliographic record
Abstract
Over 80% of pancreas cancer (PC) patients experience pain, of which 50% require narcotics as part of the armamentarium for pain alleviation. Although surgical splanchnicectomy has been performed, celiac plexus neurolysis (CPN), which involves injecting a neurolytic agent (e.g. absolute alcohol, phenol) around and/or into the celiac ganglia to destroy these neural networks, has surfaced as the favored strategy. CPN can be accomplished intraoperatively, percutaneously (PQ-CPN), and guided by endoscopic ultrasound (EUS-CPN). Historically, EUS-CPN has been used as salvage therapy after the downward spiral of increasing pain and narcotic use. Subsequently, a systematic review of additional studies found a significant pain reduction at weeks 2, 4, 8, and 12 with a mean difference in pain score of –4.26, –4.21, –4.13, and –4.28, respectively. This is consistent with a meta-analysis which showed pain reduction in 80% of patients following EUS-CPN for pancreatic cancer.
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.
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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.004 | 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".