Erythema Induratum and Tuberculosis-Associated Ocular Inflammation in Low Tuberculosis Incidence Setting: 11-Year Retrospective Case Review With Prospective Clinical Follow-Up in Alberta, Canada
Bibliographic record
Abstract
Background. Erythema induratum (EI)—nodular vasculitis associated with Mycobacterium tuberculosis (TB)—and tuberculosis-associated ocular inflammation (TB-AOI) represent uncommon manifestations of TB in low incidence countries. Both entities are diagnosed indirectly and neither has standardized therapy. Methods. Retrospective review of EI and TB-AOI cases managed in a provincial TB program between 1 January 2004 and 31 December 2014. Prospective phone-based follow-up pursued for those who received anti-tuberculosis therapy (ATT). TB-AOI diagnosis was based on referring ophthalmologist's assessment and positive TB testing (IGRA/TST). EI cases were referred following dermatologist assessment and met clinical or pathologic criteria along with positive TB testing. Results. Twenty-two EI and 21 TB-AOI cases were managed over the study period, 10 and 11, respectively, were reached for phone-based follow-up. The majority of EI and TB-AOI cases were female and immigrated from TB high-burden countries. Mean ages at time of diagnosis were 44.3 and 39 years (IQR 8.25 and 18) for EI and TB-AOI cases, respectively. Mean duration of symptoms prior to diagnosis were 3.1 and 1.8 years (IQR 2 and 2.1) for EI and TB-AOI cases, respectively. Amongst 17 EI cases that underwent biopsy, granulomatous inflammation was the most common finding (88%) followed by panniculitis (59%), necrobiosis (53%) and vasculitis (47%). ATT was initiated in 41 (95%) cases with 36 (88%) completing therapy. 14 different ATT regimes were used for a mean duration of 5.8 months (range 1–9). ATT related side effects occurred in 52% of EI and 35% of TB-AOI cases of which 18% and 19%, respectively, resulted in therapy cessation. Clinical resolution was documented in 70% of EI cases at a mean clinical follow-up of 7.3 months (range 0–48); however, only 50% of EI and 18% of TB-AOI patients reported sustained resolution of symptoms on phone-based follow-up at mean post treatment periods of 4.5 and 3.8 years (IQR 3.8 and 4), respectively. Conclusion. In this cohort, EI and TB-AOI represented uncommon presentations receiving highly variable therapy with high rates of ATT side effects. Fewer than half of patients contacted on follow-up reported durable resolution of symptoms. Disclosures. All authors: No reported disclosures.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".