Delays in diagnosis and treatment of pulmonary tuberculosis in India: a systematic review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: To systematically review Indian literature on delays in tuberculosis (TB) diagnosis and treatment. METHODS: We searched multiple sources for studies on delays in patients with pulmonary TB and those with chest symptoms. Studies were included if numeric data on any delay were reported. Patient delay was defined as the interval between onset of symptoms and the patient's first contact with a health care provider. Diagnostic delay was defined as the interval between the first consultation with a health care provider and diagnosis. Treatment delay was defined as the interval between diagnosis and initiation of anti-tuberculosis treatment. Total delay was defined as time interval from the onset of symptoms until treatment initiation. RESULTS: Among 541 potential citations identified, 23 studies met the inclusion criteria. Included studies used a variety of definitions for onset of symptoms and delays. Median estimates of patient, diagnostic and treatment delay were respectively 18.4 (IQR 14.3-27.0), 31.0 (IQR 24.5-35.4) and 2.5 days (IQR 1.9-3.6) for patients with TB and those with chest symptoms combined. The median total delay was 55.3 days (IQR 46.5-61.5). About 48% of all patients first consulted private providers; an average of 2.7 health care providers were consulted before diagnosis. Number and type of provider first consulted were the most important risk factors for delay. CONCLUSIONS: These findings underscore the need to develop novel strategies for reducing patient and diagnostic delays and engaging first-contact health care providers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| 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) | 0.000 | 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 it