Clinical prediction rules for the diagnosis of neuritis in leprosy

Background: Diagnosing neuritis in leprosy patients with neuropathic pain or chronic neuropathy remains challenging since no specific laboratory or neurophysiological marker is available. Methods: In a cross-sectional study developed at a leprosy outpatient clinic in Rio de Janeiro, RJ, Brazil, 54 individuals complaining of neural pain (single or multiple sites) were classified into two groups ("neuropathic pain"or"neuritis") by a neurological specialist in leprosy based on anamnesis together with clinical and electrophysiological examinations. A neurologist, blind to the pain diagnoses, interviewed and examined the participants using a standardized form that included clinical predictors, pain features, and neurological symptoms. The association between the clinical predictors and pain classifications was evaluated via the Pearson Chi-Square or Fisher's exact test (p <0.05). Results: Six clinical algorithms were generated to evaluate sensitivity and specificity, with 95% confidence intervals, for clinical predictors statistically associated with neuritis. The most conclusive clinical algorithm was: pain onset at any time during the previous 90 days, or in association with the initiation of neurological symptoms during the prior 30-day period, necessarily associated with the worsening of pain upon movement and nerve palpation, with 94% of specificity and 35% of sensitivity. Conclusion: This algorithm could help physicians confirm neuritis in leprosy patients with neural pain, particularly in primary health care units with no access to neurologists or electrophysiological tests.