Determination of patient quality of life following severe acute pancreatitis.
Bibliographic record
Abstract
BACKGROUND: Severe acute pancreatitis results in significant morbidity and mortality. Clinical experience suggests a significantly reduced quality of life for patients, but few studies exist to confirm this experience. We sought to objectively demonstrate patient quality of life after severe acute pancreatitis. METHODS: Forty-two patients were assessed 24-36 months after an episode of severe acute pancreatitis. Patients completed the English Standard Short Form 36 survey (SF-36) and a questionnaire about pancreatic function to assess both their health-related quality of life and symptoms of pancreatic dysfunction. RESULTS: Compared with the general Canadian population, survivors of severe acute pancreatitis had significantly reduced SF-36 scores. There is also a significant correlation between the Ranson score at presentation and the SF-36 Physical Composite Score at time of follow-up (rho = -0.47, p = 0.03). Seventy-six percent of patients had ongoing symptoms suggestive of pancreatic dysfunction. These included abdominal pain, diarrhea, unintentional weight loss, new onset of diabetes mellitus and the need for regular pancreatic enzyme supplementation. CONCLUSIONS: Survivors of severe acute pancreatitis had a reduced quality of life compared with healthy controls. Higher Ranson scores at presentation may predict which patients are more likely to have poorer outcomes in the first few years of their recovery.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".