Challenging diagnosis of amebiasis in a non-endemic region: a clinical case
Bibliographic record
Abstract
In Russia, amebiasis is sporadically registered mainly in the southern regions. An endemic area is the Republic of Dagestan. We describe a clinical case, which illustrates challenges in the diagnosis of amebial colitis related to low awareness of physicians of parasitic diseases in non-endemic regions. A 38-year old female patient living in Moscow was initially misdiagnosed with Crohn's disease. Erosive and ulcerative colonic lesions found at colonoscopy were interpreted by a gastroenterologist as symptoms of an inflammatory bowel disease. No differential diagnosis with infections and parasitic diseases was performed. Long (2 years) persistence of symptoms despite treatment with 5-aminosalicylic agents for suspected Crohn's disease, absence of any significant laboratory abnormalities and no history of travelling to Asian countries were the reason for subsequent additional diagnostic work-up. After the patient was finally diagnosed with intestinal amebiasis, she was treated with metronidazole with some positive effect of decreased abdominal bloating and bowel growling. At the control colonoscopy, there was a positive trend seen in colonic mucosa, with healing of ulcers without any scarring. No protozoan cysts were any more found in her feces. According to the recommendations, the patient is regularly seen by a specialist in infectious diseases and a gastroenterologist. Expansion of amebiasis outside endemic regions points to the necessity to perform a wider diagnostic work-up in cases of mucosal lesions found at colonoscopy.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| 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".