Leprosy with type 1 reaction in a patient from Ontario, Canada without recent travel misdiagnosed as vasculitic neuropathy: a case report
Bibliographic record
Abstract
BACKGROUND: Leprosy is rare within non-endemic countries such as Canada, where cases are almost exclusively imported from endemic regions, often presenting after an incubation period of as many as 20 years. Due to its rarity and prolonged incubation period, diagnosis is often delayed, which may result in neurologic impairment prior to the initiation of treatment. In this report we describe a case that is novel in its incubation period, which is the longest reported to-date and may have contributed to diagnostic delay. The case also uniquely demonstrates the challenges of distinguishing leprosy reactions from new rheumatologic manifestations in a patient with established autoimmune disease. CASE PRESENTATION: We describe an 84-year-old male patient with rheumatoid arthritis on methotrexate and hydroxychloroquine, with no travel history outside Canada for 56 years, who presented in 2019 with new-onset paresthesias and rash. His paresthesias persisted despite a short course of prednisone, and his rash recurred after initial improvement. He underwent skin biopsy in May 2021, which eventually led to the diagnosis of leprosy. He was diagnosed with type 1 reaction and was started on rifampin, dapsone, clofazimine and prednisone, with which his rash resolved but his neurologic impairment remained. CONCLUSION: This case report serves to highlight the potential for leprosy to present after markedly prolonged incubation periods. This is especially relevant in non-endemic countries that is home to an aging demographic of individuals who migrated decades ago from endemic countries. The importance of this concept is emphasized by the persistent neurologic impairment suffered by our case due to untreated type 1 reaction. We also demonstrate the necessity of skin biopsy in distinguishing this diagnosis from other autoimmune mimics in a patient with known autoimmune disease.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".