The Actual Prevalence of Symptoms in Pancreatic Cystic Neoplasms: A Prospective Propensity Matched Cohort Analysis
Bibliographic record
Abstract
BACKGROUND: The prevalence of symptoms in pancreatic cystic neoplasms (PCNs) is mainly based on retrospective surgical series. The aim of this study is to describe the actual prevalence of symptoms in PCNs under surveillance. METHODS: Patients with PCNs under surveillance observed from 2015 to 2017 were submitted to magnetic resonance imaging (MRI) and a specific interview. An identical survey was carried out on a control population matched for age, sex, and comorbidities in which any pancreatic disease was excluded by MRI. RESULTS: Two groups of 184 individuals were compared. Patients with PCNs have a similar prevalence of abdominal pain when compared to controls (35.2 vs. 28.8, p = 0.2). PCNs in the distal pancreas experienced a significantly increased prevalence of abdominal pain (42.3 vs. 28.8%, p = 0.04), whereas size and presumed connection with the ductal system did not affect the prevalence of abdominal pain. PCNs associated with abdominal pain did not differ in terms of clinical and radiological features from asymptomatic ones. CONCLUSION: Patients with PCNs under surveillance have a similar prevalence of abdominal pain when compared to a matched population of controls. Abdominal pain might not correlate with radiological signs of malignancy.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".