Abstract
Urge urinary incontinence (UUI) poses diagnostic challenges due to subjective assessments and limited biomarkers. This study aims to enhance accuracy by integrating skin sympathetic nerve activity (SKNA) with urine biomarkers. A prospective analysis included 36 UUI and 36 non-UUI participants. All participants underwent measurements of SKNA and evaluations of nine urine biomarkers, both with and without urinary creatinine correction. Logistic regression and support vector machine with L1 penalty were applied to SKNA and urine biomarker measurements. Six-fold stratified cross-validation ensuring equitable distribution of UUI positive and negative samples was adopted. Nonzero model weights were extracted to identify most relevant biomarkers. Elevated SKNA and calibrated urine biomarkers were observed in UUI participants. Calibrated urinary biomarkers alone achieves better accuracy than using raw biomarkers. Integration of SKNA and calibrated biomarkers demonstrated superior diagnostic performance for UUI (AUC = 0.80 ± 0.07; sensitivity = 0.72, specificity = 0.83) compared to using SKNA alone, raw or calibrated urine biomarkers alone, and alternative combinations. Baseline SKNA, calibrated MCP-1, MIP-1β, and IP-10 emerged as promising biomarkers. In conclusion, combining SKNA and urinary creatinine-normalized biomarkers yielded the highest diagnostic accuracy for UUI. This study proposes an innovative diagnostic algorithm, advancing UUI diagnostics by integrating autonomic function parameters and urine biomarker analysis.