Investigating the effect of tamsulosin on the measurement of bladder wall thickness and International Prostate Symptom Score in benign prostatic hyperplasia
Bibliographic record
Abstract
Introduction: According to previous studies, aging, gender, bladder volume and pathological states, such as bladder outflow obstruction, affect bladder wall thickness (BWT). The aim of this study was to evaluate the correlation between BWT and the International Prostatic Symptom Score (IPSS) in patients with benign prostatic hyperplasia (BPH) before and after tamsulosin treatment.Methods: In this study, 60 BPH patients were included. After obtaining informed consent, data were gathered using questionnaires to determine IPSS. After that, prostate-specific antigen was measured and a clinical examination, including a digital rectal examination, was performed for all patients. BWT was determined by transabdominal ultrasound. Finally, all patients were treated with tamsulosin (0.4 mg/day) for 2 months. After completing treatment, the IPSS and BWT were measured again and compared with the initial findings.Results: In total, 44 patients completed treatment. Patients aged 61.7 ± 9.2 years old. The mean ± standard deviation of IPSS and BWT were 14.6 ± 5.0 and 5.36 ± 1.28 mm before treatment, while they significantly (p < 0.0001) decreased to 8.2 ± 4.7 and 4.69 ± 1.23 mm, respectively, after treatment. Chi-square test showed that the decrease in BWT was significantly correlated with the improvement in IPSS (p = 0.002; r = 0.449).Conclusion: After treatment with tamsulosin, patients experienced a reduction in their BWT which was significantly correlated with improvement in their IPSS. We conclude that transabdominal evaluation of BWT could be included in the follow-up assessment in BPH.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".