Accelerating access to quality TB care for pediatric TB cases through better diagnostic strategy in four major cities of India
Bibliographic record
Abstract
BACKGROUND: Diagnosis of TB in children is challenging, and is largely based on positive history of contact with a TB case, clinical and radiological findings, often without microbiological confirmation. Diagnostic efforts are also undermined by challenges in specimen collection and the limited availability of high sensitivity, rapid diagnostic tests that can be applied with a quick turnaround time. The current project was undertaken in four major cities of India to address TB diagnostic challenges in pediatric population, by offering free of cost Xpert testing to pediatric presumptive TB cases, thereby paving the way for better TB care. METHODS: A high throughput lab was established in each of the four project cities, and linked to various health care providers across the city through rapid specimen transportation and electronic reporting linkages. Free Xpert testing was offered to all pediatric (0-14 years) presumptive TB cases (both pulmonary and extra-pulmonary) seeking care at public and private health facilities. RESULTS: The current project enrolled 42,238 pediatric presumptive TB cases from April, 2014 to June, 2016. A total of 3,340 (7.91%, CI 7.65-8.17) bacteriologically confirmed TB cases were detected, of which 295 (8.83%, CI 7.9-9.86) were rifampicin-resistant. The level of rifampicin resistance in the project cohort was high. Overall Xpert yielded a high proportion of valid results and TB detection rates were more than three-fold higher than smear microscopy. The project provided same-day testing and early availability of results led to rapid treatment initiation and success rates and very low rates of treatment failure and loss to follow-up. CONCLUSION: The current project demonstrated the feasibility of rolling out rapid and upfront Xpert testing for pediatric presumptive TB cases through a single Xpert lab per city in an efficient manner. Rapid turnaround testing time facilitated prompt and appropriate treatment initiation. These results suggest that the upfront Xpert assay is a promising solution to address TB diagnosis in children. The high levels of rifampicin resistance detected in presumptive pediatric TB patients tested under the project are a major cause of concern from a public health perspective which underscores the need to further prioritize upfront Xpert access to this vulnerable population.
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.
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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".