Efficacy and Safety of HIFU in Improving Bladder Control in Women with Urinary Incontinence
Bibliographic record
Abstract
Introduction: Urinary incontinence is a common gynecological issue, affecting millions of women worldwide due to the weakening of pelvic floor muscles. Aims & Objectives: To evaluate the efficacy and safety of High-Intensity Focused Ultrasound (HIFU) for strengthening pelvic floor muscles and improving bladder control in women with urinary incontinence. Place and Duration of Study: The study was conducted at CMH Multan from April 2023 to May 2024 in collaboration with the gynecology and urology departments. Material & Methods: The current non-randomized trial included 100 females diagnosed with urinary incontinence and aged ?35 years through non-probability convenience sampling. This study adopted a unique HIFU treatment consisting of weekly 20-minute sessions over 8 consecutive weeks. The primary outcome was a change in urinary incontinence symptoms measured by the International Consultation on Incontinence Questionnaire-Urinary Incontinence Short Form (ICIQ-UI SF) score. Secondary outcomes included a reduction in incontinence episodes, bladder control parameters (maximum bladder capacity and detrusor pressure), strengthening pelvic floor (perineometry, digital palpation), life quality (I-QOL and PFDI-20), and adverse events. Descriptive statistics were expressed using SPSS version 23.0, as mean ± SD or frequency/percentages to check the mean difference across the two groups, t-test was applied. A p-value of <0.05 was considered statistically significant. Results: The HIFU group showed a significant decrease in ICIQ-UI SF scores (-6 ± 2) compared to the non-HIFU group (-2 ± 1, p < 0.001). HIFU participants experienced a greater decrease in incontinence episodes (10 ± 3 vs. 4 ± 2, p< 0.001) and improvements in bladder control and muscle strength. Participants undergoing HIFU demonstrated a significant rise in the I-QOL score (p < 0.01), with 80% reporting subjective improvement. The HIFU group also experienced minimal adverse effects and the results were significant. P<0.05. Conclusion: HIFU is an effective, safe, and non-invasive treatment for urinary incontinence, significantly improving symptoms, bladder control, muscle strength, and life quality while offering minimum to no adverse effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.003 | 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".