Bipolar radiofrequency thermotherapy vs. transurethral resection of the prostate: Effect on nocturia as a result of benign prostatic obstruction
Bibliographic record
Abstract
INTRODUCTION: The purpose of this study was to investigate and compare the effects of radiofrequency thermotherapy (RF) thermotherapy and transurethral resection of the prostate (TURP) on nocturia and associated quality of life in patients diagnosed with benign prostatic obstruction (BPO) under medical treatment who have complaints of persistent nocturia. METHODS: The results of patients who underwent RF thermotherapy and TURP procedures between February 2019 and February 2022 were examined, and their three-month results were compared based on their uroflowmetry values, International Prostate Symptom Score (IPSS) values, nocturia frequency, and Nocturia Quality of Life Questionnaire scores. RESULTS: While the frequency of nocturia in the RF thermotherapy group that was 4.5±1.6 before the procedure decreased to 2.3±1.4 after the procedure (p=0.002), this value in the TURP group decreased from 5.1±2.42 to 3.9±2.1 (p=0.044). RF thermotherapy was found to be more effective than TURP (p<0.005). Significantly, more noticeable improvements were observed in most nocturia-related next-day complaints and nocturia-related concerns in the RF thermotherapy group than the TURP group. CONCLUSIONS: It was observed that RF thermotherapy had a more acceptable effect on obstructive complaints in comparison to TURP, and it could be more effective on nocturia and associated quality of life. RF ablation treatment may be offered as an appropriate option to treat nocturia complaints in suitable patients.
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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".