To develop a simplified clinical risk score integrating urethral pressure profilometry through the Prostatic Plateau Area (PPA) and maximum flow rate (Qmax) during uroflowmetry to identify men with a high probability of bladder outflow obstruction.

This original cross-sectional study included men who underwent urodynamics and urethral pressure profilometry (UPP) between July 2022 and October 2025 in a tertiary centre. Patients with neurogenic lower urinary tract dysfunction, or prior prostate or urethral surgery were excluded. Bladder outlflow obstruction was defined according to the Bladder Outlet Obstruction Index (BOOI). A BOOI >40 was used to define obstruction. PPA was calculated as the product of prostatic plateau pressure (PPP) and functional length (FL). FL was defined as the distance from the onset of the urethral pressure profile to the midpoint of the maximum urethral closure pressure (MUCP) peak. Continuous variables (e.g., Age, Qmax, PPA) were summarized according to distribution and compared across BOOI categories using Welch’s-ANOVA and Games–Howell tests, while categorical variables (e.g., BCI categories) were analyzed using Chi-square test. A multivariable logistic regression model was constructed with BOOI >40 as the dependent variable and PPA and Qmax as independent predictors. The events-per-variable ratio was 58.5. A simplified score was derived from the regression coefficients. Discrimination was assessed using the area under the ROC curve. Internal validation was performed using 2000 bootstrap resamples to estimate optimism-corrected discrimination. Model calibration was evaluated using calibration intercept and slope. Risk categories were defined using percentile-based stratification (25th and 75th percentiles) and rounded to practical thresholds. Data was stored in Microsoft Excel and analyzed using Jamovi statistical software (version 2.3.28). Artificial intelligence tools were used to support aspects of data organization and statistical workflow structuring in Jamovi.

A total of 266 men were included, of whom 117 (44%) were classified as obstructed. PPA showed a moderate positive association with BOOI, whereas Qmax demonstrated a moderate inverse association (both p < 0.001). The simplified score (S = PPA − 10×Qmax) achieved an AUC of 0.755, comparable to the multivariable logistic regression model. Internal validation yielded an optimism-corrected AUC of 0.754. Calibration analysis demonstrated good agreement between predicted and observed probabilities (intercept −0.066; slope 0.978). Compared with the low-risk group, the odds of BOO increased across risk categories, reaching OR 3.29 (95% CI 1.6–6.7) and OR 18.1 (95% CI 7.8–42.1) in the intermediate- and high-risk groups, respectively. The high-risk threshold (>85) demonstrated high specificity (89.9%) and positive predictive value (PPV) (78.6%). The low-risk group (≤ −25) included 83.1% of patients without BOO, indicating a low probability of obstruction within this category.

The simplified score preserves the discriminative performance of the multivariable logistic model while enabling clinically practical risk stratification. The high-risk threshold prioritizes specificity and PPV, supporting its potential role as a rule-in criterion.

This internally validated score provides clinically meaningful discrimination for identifying patients with BOO. While pressure–flow studies remains the gold standard for diagnosis, this index may serve as a supportive tool in scenarios where an adequate study cannot be obtained, such as in patients inability to void. It is not intended to replace conventional multi-channel urodynamic evaluation, but rather to complement clinical decision-making in selected contexts. Nevertheless, prospective studies and external validation are required before considering its implementation in clinical practice.

Continence 19S (2026) 102624
DOI: 10.1016/j.cont.2026.102624