Identification of Risk Factors in Patients with Recurrent Cystitis May Improve Individualized Management

Background/Objectives: Management of acute episodes of lower urinary tract infection (LUTI) depends on whether they are sporadic or recurrent. We aimed to define factors that differentiate patients with acute sporadic cystitis (AC) from those with recurrent cystitis (RC) and thereby improve individualized care. Methods: We performed a post hoc analysis of prospectively collected data from the multinational GPIU.COM study. Female patients with an acute LUTI episode completed the Acute Cystitis Symptom Score (ACSS) and underwent a routine clinical and laboratory evaluation, including a physical examination, ultrasonography, urinalysis, and urine culture and antimicrobial susceptibility testing. Risk factors for recurrence were evaluated using the Lower Urinary Tract Infection Recurrence Risk (LUTIRE) nomogram and the ORENUC classification. Statistical analysis followed a robust stepwise approach. Significant variables were assessed by relative risk (RR), and logistic regression was used to estimate odds ratios (ORs). Model performance was evaluated using the area under the curve (AUC), the Hosmer–Lemeshow test, variance inflation factor (VIF), and bootstrap sampling. Results: A total of 106 women were included (AC n = 50; RC n = 56). Patients with RC more frequently presented with a history of constipation, a severe impact of symptoms on daily activities, multiple uropathogens, and trace proteinuria. Pyuria was inversely associated with RC. Logistic regression identified chronic constipation, severe impact of symptoms on daily activities, and multiple uropathogens as independent predictors of RC. Three predictive models showed consistent discrimination between AC and RC (AUC = 0.80, 0.82, and 0.84). Conclusions: AC and RC showed notable differences in certain symptom profiles, quality of life, urinalysis, and microbiological findings. Combining high-value predictors from LUTIRE and ORENUC into a comprehensive prognostic algorithm could improve assessment of recurrence risk. A refined classification of LUTIs with recurrence grading is warranted to guide decision-making and prevention strategies.