Sensitivity, Specificity, Negative and Positive Predictive Values of Adenosine Deaminase in Patients of Tubercular and Non-Tubercular Serosal Effusion in India
Bibliographic record
Abstract
BACKGROUND: In India, tuberculosis is an endemic disease. Delay in diagnosis results in poor prognosis and fast spread of the disease. The objective of the present study is to look for an effective and acceptable diagnostic test, which may be helpful to initiate early treatment to improve prognosis and reduce spread. METHODS: Three hundred and thirty patients with pleural, ascitic, meningeal and synovial effusion were selected and divided depending upon the etiology and the involvement of serosal membranes. Serosal aspirated fluid was subjected to biochemical tests and adenosine deaminase estimation. Cutoff taken is above 40 for pleural, peritoneal or synovial fluid and above 10 for CSF. RESULTS: In cases of pulmonary and extra-pulmonary disease, sensitivity was 92.80% and 94.29%; specificity 90.00% and 92.16%; positive predictive value 92.86% and 89.00%; and negative predictive value 90.00% and 95.92% respectively. CONCLUSIONS: Adenosine deaminase estimation is not only a fairly sensitive and specific test (more than 90%), helpful in differentiating tubercular from non-tubercular etiology both in pulmonary and extra-pulmonary disease, but is also simple, inexpensive and rapid. For this reason this test may help in early diagnosis, improve the prognosis and reduce spread of disease and sequlae. KEYWORDS: Adenosine deaminase; Serosal effusion; Tubercular; Non-tubercular; Pulmonary; Extra-pulmonary.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".