FREQUENCY OF DEPRESSION IN MULTIDRUG-RESISTANT TUBERCULOSIS PATIENTS: AN EXPERIENCE FROM A TERTIARY CARE HOSPITAL
Bibliographic record
Abstract
Background: Both depression and Multi-drug resistant tuberculosis (MDRTB) are global public health problems that have a substantial impact on human health. However, depressive state among MDR-TB patients has not been well investigated in Pakistan. Objective: To find out the frequency of depression at baseline (at the time of registration) in currently diagnosed MDR-TB patients and the emergence of depression during MDR-TB treatment in registered MDR-TB patients in PMDT. Design: The longitudinal study was conducted at PMDT centre, Lady Reading Hospital Peshawar (LRH) on patients enrolled for MDR-TB treatment from 1th May 2012 to 30 August 2013. A total of 213 patients were included in this study. All newly diagnosed MDR-TB patients at the time of registration and on every follow up. Result: The total of 213 MDR-TB patients were recruited for the study. Out of 213 registered patients, 139 (65.5%) had depression at baseline. At the end of 1st quarter, only 47 (33.81%) out of 139 still had depression and at the end of 2nd quarter this number further decreased to 35 (15.10%). While the emergence of depression was 36% at the end of both 1st and 2nd quarter.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".