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Spontaneous uroflowmetry in prostatism.

K M Jensen, R C Bruskewitz, P Iversen

    Urology
    |October 1, 1984
    PubMed
    Summary
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    Uroflowmetry, a test for urinary flow rate, did not predict surgical outcomes for men with prostatism. Maximum flow rate showed weak correlations and did not differentiate patient success after transurethral resection of the prostate.

    Area of Science:

    • Urology
    • Urodynamics
    • Surgical Outcomes

    Background:

    • Prostatism frequently requires surgical intervention.
    • Uroflowmetry is a common urodynamic screening tool for patient selection.
    • The predictive value of uroflowmetry for surgical success in prostatism remains debated.

    Purpose of the Study:

    • To evaluate the role of spontaneous uroflowmetry in selecting patients with prostatism for surgery.
    • To assess the correlation between maximum flow rate and clinical outcomes post-transurethral resection of the prostate (TURP).

    Main Methods:

    • Prospective study of 53 patients undergoing TURP.
    • Patients selected for surgery based on non-urodynamic data.
    • Preoperative and postoperative extensive urodynamic testing, including uroflowmetry.

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  • Correlation analysis between maximum flow rate and symptom scores, pressure variables, and urethral resistance.

    • Main Results:

    • A weak correlation was observed between maximum flow rate and symptom scores, pressure variables, and minimum urethral resistance.
    • Classifying patients into high, medium, and low maximum flow rate groups did not identify subgroups with less favorable surgical outcomes.
    • Patients with higher maximum flow rates experienced similar outcomes to those with lower flow rates post-TURP.

    Conclusions:

    • Spontaneous uroflowmetry demonstrated a limited role in the preoperative evaluation of patients with prostatism.
    • Non-urodynamic factors appear to be as effective as uroflowmetry in predicting surgical success for prostatism.
    • Further research may be needed to refine predictive models for TURP outcomes.