A systemic review of the utility of antituberculosis therapy for presumed tuberculous uveitis
Bibliographic record
Abstract
BACKGROUND: Uveitis presumed to be secondary to Mycobacterium tuberculosis is a rare but potentially blinding condition. Difficulty in making an accurate diagnosis and the low incidence of TB uveitis (TBU) contribute to the lack of evidence regarding the best management of this condition. This systematic review aims to analyse existing research to provide a summary of the literature regarding the utility of TB therapy for the management of TBU. METHODS: This systematic review was prospectively registered on PROSPERO (PROSPERO 2021 CRD42021273379). We searched Medline, Embase and Central databases, and the search was done on 20th June 2023 with an updated literature search. RESULTS: We included 55 studies and found that the heterogeneity in the methodology of these studies precluded metanalysis, and a narrative analysis was undertaken. Risk of bias analysis was undertaken using the Newcastle-Ottawa scale. CONCLUSIONS: Key findings of this systematic review include multiple systemic biases in the available evidence, and general lack of control for confounding variables. This results in many unanswered questions regarding the utility of TB therapy for TBU and reinforces the need for more data in this area.
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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 | 0.006 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".