Age Is an Important Risk Factor for Onset and Sequelae of Reversal Reactions in Vietnamese Patients with Leprosy
Bibliographic record
Abstract
BACKGROUND: Reversal, or type 1, leprosy reactions (T1Rs) are acute immune episodes that occur in skin and/or nerves and are the leading cause of neurological impairment in patients with leprosy. T1Rs occur mainly in patients with borderline or multibacillary leprosy, but little is known about additional risk factors. METHODS: We enrolled 337 Vietnamese patients with leprosy in our study, including 169 subjects who presented with T1Rs and 168 subjects with no history of T1Rs. A multivariate analysis was used to determine risk factors for T1R occurrence, time to T1R onset after leprosy diagnosis, and T1R sequelae after treatment. RESULTS: Prevalence of T1Rs was estimated to be 29.1%. Multivariate analysis identified 3 clinical features of leprosy associated with T1R occurrence. Borderline leprosy subtype (odds ratio, 6.3 [95% confidence interval, 2.9-13.7] vs. polar subtypes) was the major risk factor; 2 other risk factors were positive bacillary index and presence of > 5 skin lesions. In addition, age at leprosy diagnosis was a strong independent risk factor for T1Rs (odds ratio, 2.4 [95% confidence interval, 1.3-4.4] for patients aged > or = 15 years old vs. < 15 years old). We observed that T1Rs with neuritis occurred significantly earlier than pure skin-related T1Rs. Sequelae were present in 45.1% of patients who experienced T1Rs after treatment. The presence of a motor or sensory deficit at T1R onset was an independent risk factor for sequelae, as was the age at diagnosis of leprosy (odds ratio, 4.4 [95% confidence interval, 1.7-11.6] for patients > or = 20 years old vs. < 20 years old). CONCLUSION: In addition to specific clinical features of leprosy, age is an important risk factor for both T1R occurrence and sequelae after treatment for T1Rs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".