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Adv Ther. 2005 Jul-Aug;22(4):381-94.

Validation of an overactive bladder awareness tool for use in primary care settings.

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1
The MEDTAP Institute at United BioSource Corporation, 7101 Wisconsin Ave, Suite 600, Bethesda, Maryland 20814, USA.

Abstract

Overactive bladder (OAB)--a syndrome characterized by urinary urgency, with or without urge incontinence, urinary frequency and nocturia--is estimated to affect 10% to 20% of the US and European populations. This study was carried out to validate a patient-administered screening awareness tool to identify patients with bothersome OAB symptoms. Patients were recruited from 12 primary care and 1 gynecology practice during regularly scheduled appointments. Enrollees completed an 8-item questionnaire assessing the amount of "bother" they associated with OAB symptoms. Clinicians then asked the patients 4 questions regarding urinary frequency, urgency, nocturia, and incontinence. If the screening was positive for symptoms of OAB or if the patient provided positive responses to the urinary symptom questions, the clinician asked additional questions regarding lifestyle and coping behaviors. The clinician then diagnosed the patient, placing him or her in the "No OAB," "Possible OAB," or "Probable OAB" category. Multivariable logistic regressions controlling for age and sex were performed to assess the applicability of the tool for identifying patients with OAB. A total of 1,299 patients were enrolled, and 1,260 provided complete data. Patients were aged 51.6+/-17.0 years, 62% were female, most (89%) were Caucasian, 22% experienced urinary urgency, and 18% experienced urge incontinence. The prevalence of Probable OAB was 12%. The c-index of the model identifying patients with a diagnosis of Probable OAB was 0.96, with a sensitivity and specificity of 98.0 and 82.7. For OAB-V8 scores >or=8, the odds ratio for Probable OAB was 95.7 (95% CI: 29.3; 312.4). The OAB-V8 performed well in helping clinicians identify patients with bothersome OAB symptoms in a primary care setting and will assist clinicians in identifying patients who may benefit from treatment.

PMID:
16418145
[Indexed for MEDLINE]
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