Is there a role for growth status in distinguishing gallbladder adenomas from cholesterol polyps? – A retrospective study based on 520 cholecystectomy patients
Bibliographic record
Abstract
Gallbladder adenomas have cancerous potential and occur in 4–8.9% of gallbladder polyps. The growth status (size progression and growth rate during follow-up) of polyps and their effectiveness for predicting adenomas are poorly defined. Herein, we compared adenomas and cholesterol polyps based on the growth status and evaluated the reported risk factors in predicting neoplasm. We enrolled 520 patients who underwent preoperative ultrasonic follow-up more than 6 months with post-cholecystectomy pathologically confirmed gallbladder polyps. The patients were classified into adenoma and cholesterol polyp groups. Growth status, clinical characteristics, laboratory data, ultrasonic findings were reviewed and compared between the groups. Seventy-nine adenomas and 441 cholesterol polyps were analyzed. The mean diameter of adenomas (cholesterol polyps) was 7.24 ± 4.36 mm (6.23 ± 2.88 mm) in the initial and 12.06 ± 4.61 mm (10.05 ± 2.95 mm) in the preoperative examination. The median size progression (range) of polyps in the cholesterol polyps [3 (0, 22)] mm was smaller than that in adenomas [4 (0, 21)] mm (p = .075). The mean growth rate of adenomas (1.07 ± 1.33 mm/6 months) was slightly faster than in cholesterol polyps (0.83 ± 1.04 mm/6 months) (p = .338). The indicators significantly associated with adenomas were age >49.5 years, lack of gallbladder polyps/cholelithiasis family history, polyp size >11.5 mm and solitary polyp (p = .005, p = .027, p = .001, and p = .021, respectively). Growth status was not a valuable modality to distinguishing gallbladder adenomas from cholesterol polyps. Risk factors such as age, polyp size, and solitary polyp were effective in predicting adenomas.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".