Clinical diagnostic criteria for suspected ileocaecal tuberculosis.
Bibliographic record
Abstract
BACKGROUND: Ileocecal Tuberculosis (TB) is difficult to diagnose clinically as getting histological specimens means resorting to surgery, which is often hazardous and complicated in sick, anemic and emaciated patients with malabsortion syndrome. The present study was undertaken as an attempt to devise clinical criteria for diagnosis of ileocecal TB without resorting to invasive surgery. METHODS: 52 patients with suspected ileocecal TB were assigned pre-determined criteria based on clinical signs, symptoms and simple laboratory investigations. Criteria for exclusion were also devised; patients were followed up for an average of 1.1 years. Clinical response was assessed by complete resolution of symptoms and signs within 3 months. RESULTS: All 52 patients completed the study and all became symptom free within 3 months of treatment. All patients gained a minimal of 2 kg over 6 weeks and 32 patients gained more than 10% of body weight within 3 months; the difference in mean weights before and after 3 months treatment was highly significant (p < 0.001). CONCLUSIONS: In patients with suspected ileocecal tuberculosis, predetermined clinical criteria can be readily applied for early diagnosis, without resorting to surgery and with excellent clinical response.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".