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A model for predicting motor urge urinary incontinence.

M Gray¹, R McClain, M Peruggia

¹Department of Urology and School of Nursing at the University of Virginia, Charlottesville 22908, USA.

Nursing Research

|April 17, 2001

Summary

A new model accurately diagnoses motor urge urinary incontinence (UI) using key symptoms, age, and gender. This simplified tool aids routine evaluations, improving upon traditional methods for urge and mixed UI diagnosis.

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Area of Science:

Urology
Gynecology
Geriatrics

Background:

Historical interviews show limited accuracy for diagnosing urge or mixed urinary incontinence (UI).
Stress UI diagnosis is more accurate with interviews compared to urge or mixed UI.

Purpose of the Study:

To develop an optimal diagnostic model for motor urge UI.
To create a simplified clinical instrument for diagnosing motor urge UI during routine evaluations.

Main Methods:

An optimal model was built using symptoms, age, gender, neurologic history, and urodynamic parameters.
A simplified model incorporated readily available factors like symptoms, age, and gender.
An instrument was developed from the simplified model for clinical use.

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Main Results:

The optimal model achieved a 91% accuracy rate for diagnosing motor urge UI.
A simplified model demonstrated strong performance with R2 of 0.85 and adjusted R2 of 0.84.
Clinical diagnosis agreement was high for stress UI (93%) but lower for urge (63%) and mixed UI (35%).

Conclusions:

Age, gender, and key symptoms (frequency, nocturia, urgency) form an accurate model for motor urge UI.
The developed instrument offers a clinically useful method for diagnosing motor urge UI.
Further research is needed to validate the instrument's reliability and clinical utility.