CronkhiteCanada syndrome complicated with pulmonary embolism: A case report
Bibliographic record
Abstract
BACKGROUND: Cronkhite-Canada syndrome (CCS) is a rare disease, that causes gastrointestinal polyps, ectodermal abnormalities, and gastrointestinal symptoms. CCS is prone to thromboembolism, but clinical workers have not yet established a clinical consciousness of preventing thromboembolism. The present case illustrates pulmonary embolism (PE) complicated by CCS. CASE SUMMARY: A 46-year-old male patient presented with mucus, purulent, and bloody stool. Ectodermal changes included skin pigmentation, alopecia, and nail dystrophy. Colonoscopy revealed the presence of multiple polyps. After a comprehensive evaluation, the patient was diagnosed with CCS. During the disease, he was also diagnosed with pulmonary embolism, Riehl's melanosis, and intestinal flora imbalance. After symptomatic treatment with omeprazole, mesalazine, rivaroxaban, nutritional support, and regulation of intestinal flora, the patient's symptoms were significantly relieved. CONCLUSION: CCS complicated with PE was reported for the first time in China in this study. Despite the fact that CCS is extremely rare, patients with CCS should be classified as a high-risk venous thromboembolism (VTE) population, and emphasis should be placed on venous thromboembolism risk assessment and stratification, deep venous thromboembolism screening, prevention of VTE, and careful long-term follow-up.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".