The Assessment of Patient-Reported Outcomes in the Medical Management of Patients With Benign Prostatic Hyperplasia
Bibliographic record
Abstract
Background Benign prostatic hyperplasia (BPH) is a prevalent condition that a large portion of the male population develops with aging, in which the prostate gland enlarges and results in urinary symptoms. Objective The objective of this article is to assess patient-reported outcomes (PRO) of medical management of benign prostate hyperplasia in terms of international prostate symptoms score (IPSS), BPH impact index (BPHII), and treatment satisfaction score (TSS). Methods This descriptive study included 114 patients who received medical management for BPH during the period 5th May 2021 till 30th December 2023, at the Department of Urology, Institute of Kidney Disease Peshawar. Patient-reported outcomes were measured in terms of IPSS, BPHII, and TSS. Readings were recorded at the start of treatment and at three months of treatment and then compared. Data was analyzed using SPSS v.25 (IBM Inc., Armonk, New York). Results The mean age of the patients was 64.33 ± 6.12 years. The mean prostate size was 77.35 ± 12.83 ml. Overall mean pre-treatment and post-treatment IPSS was 24.82 ± 4.90 versus 15.57 ± 5.15, respectively (p-value 0.00). Mean pre-treatment and post-treatment BPHII were 11.98 ± 1.02 and 7.12 ± 2.46, respectively (p-value 0.000). The overall mean treatment satisfaction score was 6.89 ± 1.44. Conclusion Medical management improved symptomatology in BPH patients. This study is a step in the direction of the development of larger and longer-term PRO studies in BPH management.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".