Current Status of Diagnosis and Treatment of Cap Polyposis: Insights From Chinese Studies and Comparative Analysis with Japanese Cases
Bibliographic record
Abstract
Background: Cap polyposis (CP) is a rare, non-neoplastic colorectal disorder characterized by inflammatory polyps with distinctive endoscopic and histopathological features. Although increasingly reported, particularly in East Asian populations, its etiology remains unclear, and diagnostic and treatment strategies are not well standardized. Previous studies have been limited by small sample sizes and regional focus. This review aims to systematically analyze the clinical characteristics, management, and outcomes of CP in Chinese patients, with comparative insights from Japanese cases, to improve understanding and guide clinical practice. Methods: A systematic literature search was conducted in PubMed, EMBASE, Cochrane Library, CNKI, and Wanfang databases for studies published before October 2023. Keywords included "cap polyposis" and "cap-shaped polyp". Articles were screened against predefined inclusion criteria: studies from Mainland China, pathologically confirmed CP cases, and availability of clinical and therapeutic data. Data extraction and quality assessment were performed independently by two reviewers using the Newcastle-Ottawa Scale. Results: Fourteen studies involving 57 patients were included. The most common symptoms were hematochezia (59.6%) and diarrhea (28.1%). Polyps were predominantly located in the rectum (68.4%), and 66.7% of patients had three or more polyps. Helicobacter pylori testing was positive in 57.1% of tested patients (12/21). Comparative analysis with Japanese cases revealed similar rectal predominance but suggested potential variations in gender distribution and treatment preferences. Treatments included endoscopic mucosal resection, endoscopic submucosal dissection, H. pylori eradication, and surgery. During a median follow-up of 14 months, 10 patients experienced recurrence. Conclusion: CP is a benign but easily misdiagnosed condition with a high recurrence rate. Diagnosis relies on combined endoscopic and histopathological findings. Treatment remains empirical, with H. pylori eradication beneficial in infected patients, and endoscopic resection effective for localized disease. Further multicenter studies are needed to establish standardized management protocols.
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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 | 0.011 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.003 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".