Pain in chronic pancreatitis: assessment and relief through treatment.
Bibliographic record
Abstract
AIM: To assess two scores of pain used in chronic pancreatitis, to analyse the morphological factors identified by imaging techniques and the extrinsic factors involved in causing pain and in pain evolution during treatment. PATIENTS AND METHODS: Pain was assessed by means of a unidimensional numeric scale and a multidimensional Mc Gill score in 50 patients with chronic pancreatitis. We prospectively followed up 28 patients over a period of 17 months. RESULTS: Pain assessment by means of the two scores was statistically comparable. The multidimensional score correlated with the presence of Wirsung stenoses in the univariate analysis and with Wirsung stenoses and their diameter in the multivariate one. The smokers had a smaller rate of pain relief during the treatment. In cases with more morphological changes of severe chronic pancreatitis, pain relief was lower than in cases with fewer changes. CONCLUSIONS: The McGill score is more appropriate for the quantitative assessment of pain. Smoking reduces the chances of pain relief under treatment. Duct stenoses and Wirsung diameter have the best correlation with pain intensity. The severe chronic pancreatitis changes are negative predictive factors for pain relief under treatment
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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 | 0.000 |
| 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) | 0.001 | 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".