Immunohistochemistry and real-time Polymerase Chain Reaction: importance in the diagnosis of intestinal tuberculosis in a Peruvian population
Bibliographic record
Abstract
INTRODUCTION: The diagnosis of intestinal tuberculosis is challenging even nowadays. This study aims to report the positivity rates of new diagnostic methods such as immunohistochemistry and Real-Time Polymerase Chain Reaction in patients with intestinal tuberculosis, as well as describe the pathological and endoscopic features of intestinal tuberculosis in our population. METHODS: This was a retrospective observational study conducted in patients diagnosed with intestinal tuberculosis, between 2010 to 2023 from the Hospital Nacional Daniel Alcides Carrion and a Private Pathology Center, both located in Peru. Clinical data was obtained, histologic features were independently re-evaluated by three pathologists; and immunohistochemistry and real-time Polymerase Chain Reaction evaluation were performed. The 33 patients with intestinal tuberculosis who fulfilled the inclusion criteria were recruited. RESULTS: Immunohistochemistry was positive in 90.9% of cases, while real-time Polymerase Chain Reaction was positive in 38.7%. The ileocecal region was the most affected area (33.3%), and the most frequent endoscopic appearance was an ulcer (63.6%). Most of the granulomas were composed solely of epithelioid histiocytes (75.8%). Crypt architectural disarray was the second most frequent histologic finding (78.8%) after granulomas, but most of them were mild. CONCLUSION: Since immunohistochemistry does not require an intact cell wall, it demonstrates higher sensitivity compared to Ziehl-Neelsen staining. Therefore, it could be helpful for the diagnosis of paucibacillary tuberculosis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".