Diagnostic nomogram to differentiate between epididymal tuberculosis and bacterial epididymitis

We developed and validated a diagnostic nomogram for differentiating epididymal tuberculosis (TB) from bacterial epididymitis.

In this retrospective study, we developed a prediction model based on demographics and clinical characteristics. Eligible patients were randomly divided into derivation and validation cohorts (ratio 7:3). Univariate and multivariate regression analyses were used to filter variables and select predictors. Multivariate logistic regression was used to construct the nomogram. Concordance index (C-index), calibration plots, and decision curves analysis (DCA) were used to assess the discrimination, calibration, and clinical usefulness of the nomogram.

We included 147 patients (epididymal TB, 93; bacterial epididymitis, 54). The derivation cohort included 66 patients with epididymal TB and 38 with bacterial epididymitis; the validation cohort included 27 patients with epididymal TB and 16 with bacterial epididymitis. One regression model was built from three differential variables: body mass index, purified protein derivative, and chronic infection. Accordingly, one nomogram was developed. The model had good discrimination and calibration. C-indexes of the derivation and validation cohorts were 0.89 and 0.98 (95% confidence intervals, 0.83-0.95 and 0.94-1.01), respectively. DCA showed that the proposed nomogram was useful for differentiation.

The nomogram can differentiate between epididymal TB and bacterial epididymitis.