Uroflowmetry is a widely used diagnostic tool in both scientific research and clinical practice. It provides objective measurements of urinary flow, which are often correlated with the International Prostate Symptom Score (IPSS) to assess the severity of lower urinary tract symptoms (LUTS). However, the majority of studies on uroflowmetry have focused on the objective parameters of urinary flow and their correlation with other methods of symptom measurement. While the use of uroflowmetry curves to evaluate the normality of the exam is of great importance in clinical practice, their impact on the overall evaluation of patients is not well understood.
Therefore, the aim of this study is to evaluate the impact of uroflowmetry curve interpretation on the evaluation of patients with LUTS. By analyzing the patterns and shapes of the uroflowmetry curves, this study will investigate how they may affect the overall assessment of patients and potentially provide new insights into the diagnosis and treatment of LUTS. The findings of this study could have significant implications for the use of uroflowmetry in clinical practice and highlight the importance of interpreting uroflowmetry curves in addition to the objective parameters of urinary flow.

We collected the data used in this study as part of a broader project called "Mictional Evaluation in an African Country". We obtained 812 uroflowmetry tests and International Prostate Symptom Score (IPSS) from males in São Tomé and Príncipe aged 30 years or older, categorized by district and age. An online survey was developed using the Google Forms platform, with the collaboration of an informatics specialist, and distributed to Portuguese urologists. The survey consisted of a series of uroflowmetry curves, each of which was classified by three different urologists anonymously. The urologists were asked to classify the curve as one of the following possible types: i) bell-shaped; ii) tower-shaped; iii) restrictive pattern; iv) interrupted pattern; v) plateau-shaped. In addition, the urologists were asked to provide a classification of the degree of suspicion regarding the presence of obstruction: "Obstructed" or "Non-obstructed." The urologists had access to the objective parameters of the uroflowmetry curve, in addition to the curve itself.
Each flowmetry curve was evaluated by 3 different urologists, selected from a group of 14, anonymously, assigning a possible curve type to the curve under study: i) bell-shaped; ii) tower-shaped; iii) restrictive pattern; iv) interrupted pattern; v) plateau curve. They also assigned a classification regarding the suspicion level of obstruction: "Obstructed" and "Non-obstructed". In addition to the flowmetry curve, the urologists had access to the objective parameters of the curve.

Of the uroflowmetry exams evaluated, approximately 68% were classified as presenting a curve that was understood as non-obstructed, and 28% were classified as presenting a curve that was considered suspicious for micturition dysfunction.
In evaluating the relationship between the classification of the uroflowmetry exam and the IPSS, a statistically significant but weak correlation was found (r=0.217). This type of correlation is similar to that obtained for the relationship between the IPSS and the Qmax and Qave. The correlation between the obstructed classification and the Qmax or Qmax ≥10 ml/s was strong or very strong (r=0.798, p<0.0001). All the variables analyzed presented statistical significance.
The 2-way ANOVA test provided another approach to studying the relationship between the urologists' classification and the IPSS, using the type of curve and the presence of obstruction as factors. The obstructed or non-obstructed classification showed a statistically significant relationship (F: 15.943, p<0.0001), but the type of curve and the interaction between them did not.

The present study aimed to evaluate the impact of the interpretation of urinary flowmetry curves on their correlation with the International Prostate Symptom Score (IPSS). The results showed a statistically significant but weak correlation (r <0.3) between the classification of the flowmetry curve by urologists and the IPSS for all analyzed variables. These findings suggest that the interpretation of the urinary flowmetry curve by urologists may not add value to the correlation with the IPSS. However, caution should be exercised in interpreting these data. The correlations have similar values, and general population data were used, so it cannot be inferred what the behavior is in borderline cases, where experts usually perform better. Additionally, it should be noted that urologists always had access to the objective data of the flowmetry, namely the Qmax, which appears to be decisive in assigning the classification of obstructed.
To the best of our knowledge, this was the first study on urinary evaluation of a population that included the type of flowmetry curve and the interpretation by a urologist. These data seem to reinforce the importance of Qmax reference values in the interpretation of urinary flowmetry. However, the true correlation between the flowmetry curve and the IPSS remains unclear, particularly when objective data are concealed during its interpretation. Future studies could focus on addressing this issue by exploring the relationship between the flowmetry curve and the IPSS while hiding the objective data from the urologist, providing a better understanding of the impact of curve interpretation on the overall assessment of patients.
Overall, these results have important clinical implications, suggesting that a comprehensive interpretation of urinary flowmetry results should consider the objective parameters, such as Qmax, in addition to the curve's subjective interpretation. Furthermore, our findings highlight the need for continued research in this area, with a focus on developing more reliable and accurate diagnostic tools for urinary dysfunction, as well as on improving the standardization of the interpretation of urinary flowmetry results.

In conclusion, our study aimed to evaluate the impact of interpreting urinary flowmetry curves on the assessment of patients. We found a statistically significant but weak correlation between flowmetry classification and IPSS, indicating that the interpretation of flowmetry curves by urologists may not add value to the examination's correlation with IPSS. However, caution should be exercised when interpreting these results, as correlations have similar values, and general population data were used. The urologists always had access to the objective data of flowmetry, especially Qmax, which seems to be decisive in the obstructive classification.