Development of a Nomogram Predicting the Infection Stones in Kidney for Better Clinical Management: A Retrospective...

Area of Science:

• Urology
• Nephrology
• Medical Diagnostics

Background:

• Infection stones pose a significant challenge in kidney stone management, complicating treatment and increasing recurrence risk.
• Accurate prediction of infection stones preoperatively is crucial for optimizing perioperative care and postoperative prevention strategies.

Purpose of the Study:

• To develop and validate the first comprehensive nomogram for predicting infection stones prior to treatment.
• To identify key clinical and laboratory predictors of infection stones in patients undergoing stone removal procedures.

Main Methods:

• Retrospective analysis of 461 patients who underwent mini-percutaneous nephrolithotomy or flexible ureteroscopy.
• Multivariable logistic regression was used to identify significant predictors of infection stones.
• A predictive nomogram was constructed based on the identified factors.

Main Results:

• 100 out of 461 patients (21.70%) had infection stones.
• Predictors for infection stones included female sex, recurrent kidney stones, larger stone burden, high Hounsfield Units (HU), positive preoperative bladder urine culture (PBUC), positive urine leukocyte esterase (ULE), specific urine pH, and positive urine turbidity.
• The established nomogram demonstrated utility in identifying patients at risk for infection stones.

Conclusions:

• The developed nomogram is a valuable tool for predicting infection stones in kidney stone patients.
• Identifying these predictors allows for tailored perioperative management and enhanced postoperative prevention of infection stones.
• This model aids clinicians in better managing patients with or at risk of developing infection stones.