Serum CA-125: biomarker of pulmonary tuberculosis activity and evaluation of response to treatment
Bibliographic record
Abstract
PURPOSE: CA-125 is a high molecular weight mucin-like glycoprotein and an ovarian cancer antigen. Elevated CA-125 levels are also seen with various other benign and malignant conditions. In this study, the ability of CA-125 to predict pulmonary tuberculosis activity was investigated. METHODS: This analytical study included 42 cases with active tuberculosis (Group 1), 35 cases with inactive tuberculosis (Group 2) and 20 healthy subjects (Group 3). CA-125 measurements were taken in all three groups. Measurements in Group 1 were repeated after completing a two month anti-tuberculosis treatment in 38 of the 42 patients. RESULTS: Mean serum CA-125 level for Group 1 was 76.48 ± 24.71 U/mL, which was significantly higher than levels in Group 2 (20.01 ± 7.89 U/mL) and Group 3 (18.32 ± 2.87 U/mL) (p < 0.001). Of the 38 patients in Group 1 who were studied both pre- and post-treatment, CA-125 levels decreased significantly: from 78.88 ± 24.72 U/mL before treatment to 22.78 ± 8.02 U/mL after treatment (p < 0.001). There was no statistically significant difference between the post-treatment values of Group 1 and either Group 2 and Group 3 values (p > 0.05). Group 2 and Group 3 levels were not significantly different (p > 0.05). The cut-off level for accurate determination of activity was 36.35 U/mL. The sensitivity at this level was 97.6% and specificity was 100%. CONCLUSION: Our findings suggest that CA-125 can be a beneficial parameter in determination of pulmonary tuberculosis activity and the evaluation of response to treatment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".