Predicting Time to Recovery From Acute Urinary Retention in Hospitalized Patients: Development and Validation of a...

Area of Science:

• Urology
• Clinical Prediction Modeling
• Patient Outcomes

Background:

• Acute urinary retention (AUR) is a frequent complication in hospitalized individuals.
• Predicting recovery time from AUR is challenging, impacting patient management.
• Developing a reliable prediction tool is crucial for optimizing care pathways.

Purpose of the Study:

• To develop and validate a clinical prediction model for recovery from AUR within 14 days.
• To identify key predictors of successful voiding after AUR.
• To aid in risk stratification for patients experiencing AUR.

Main Methods:

• Prospective cohort study of 126 adult patients with AUR.
• Standardized voiding trials conducted every 3-4 days.
• Multivariable logistic regression analysis to determine predictors of 14-day recovery.

Main Results:

• 81.7% of patients achieved successful voiding within 14 days.
• The prediction model showed excellent discrimination (AUC=0.83).
• Key predictors included age <70, male sex, postoperative etiology, and retention volume ≤450 mL.

Conclusions:

• A validated clinical prediction model accurately identifies patients at risk for prolonged AUR.
• The model utilizes four simple bedside parameters for ease of use.
• Implementation can optimize catheter management and improve patient outcomes via risk-stratified care.