Objective: To evaluate the association between the Mucosal Contact Index (MCI), a novel imaging-based parameter reflecting stone-mucosa interaction, and postoperative fever/SIRS after retrograde intrarenal surgery, and to compare its predictive performance with systemic inflammatory markers. Methods: This retrospective study included 666 patients undergoing RIRS for upper urinary tract stones. Patients with preoperative infection, malignancy, or missing CT data were excluded. Mucosal Contact Index was calculated on non-contrast CT using a 2-dimensional planimetric method on the axial slice with the largest stone cross-section, defined as the ratio of mucosal contact length to total stone circumference. The primary outcome was postoperative fever/SIRS. Logistic regression analyses were performed, and predictive performance was evaluated using ROC analysis. Internal validation was conducted with bootstrap resampling. Results: Postoperative fever/SIRS occurred in 53 patients (8.0%). MCI was significantly higher in patients who developed postoperative fever/SIRS (p < 0.001). In univariate analysis, age, multiple stones, stone volume, preoperative double-J stent, and MCI were associated with postoperative fever/SIRS. MCI demonstrated the highest discriminative performance, with an area under the curve (AUC)=0.811, outperforming inflammatory markers (NLR, PLR, LMR). The optimal cutoff was 0.157. In multivariable analysis, age (adjusted OR=1.06, p < 0.001), multiple stones (OR=3.95, p = 0.001), stone volume (OR=1.04 per 100 mm³, p = 0.029), preoperative DJ stent (OR=2.64, p = 0.026), and MCI as a continuous variable (OR=1.087 per 0.01-unit increase, p < 0.001) remained independent predictors. The model showed good discrimination (AUC=0.874), with an optimism-corrected AUC of 0.863 on internal validation. Conclusion: MCI is a strong and independent predictor of postoperative fever/SIRS in patients with negative preoperative urine cultures undergoing RIRS, outperforming systemic inflammatory markers. As a preoperative imaging-based parameter, it may improve risk stratification in this selected population. External validation in broader patient cohorts is warranted.
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Çoban et al. (2026) studied this question.
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