Differentiating Intestinal Tuberculosis From Crohn's Disease: A Diagnostic Challenge
Bibliographic record
Abstract
With the changing epidemiology of Crohn's disease (CD) and intestinal tuberculosis (ITB), we are in an era where the difficulty facing physicians in discriminating between the two diseases has increased, and the morbidity and mortality resulting from a delayed diagnosis or misdiagnosis is considerably high. In this article, we examine the changing trends in the epidemiology of CD and ITB, in addition to clinical features that aid in the differentiation of both diseases. The value of various laboratory, serological, and the tuberculin skin tests are reviewed as well. The use of an interferon-gamma-release assay, QuantiFERON-TB Gold, in the workup of these patients and its value in populations where the bacillus Calmette-Guérin vaccine is still administered is discussed. Different radiological, endoscopic, and pathological similarities and features that can aid the clinician in reaching a rapid diagnosis are reviewed as well. The association between mycobacteria and CD, the concerns with the practice of antituberculosis medication trials in areas where tuberculosis (TB) is endemic, as well as extrapulmonary TB induced by the use of antitumor necrosis factor-alpha agents are delineated in this article. Furthermore, we propose an algorithm for the investigation of patients in whom the differential diagnosis encompasses CD and ITB.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".