Possibilities of objectivization of pelvic floor muscle exercises in patients with urine leakage after delivery.
Bibliographic record
Abstract
BACKGROUND: Examination of pelvic floor muscle function is very important before starting exercises in patients with urine leakage and other pelvic floor dysfunctions. Perineometer and palpation examination is currently being used. A new trend in physiotherapy is the ultrasound examination of pelvic floor muscles. The examination can be performed by abdominal approach or perineal approach. We evaluate 2D and 3/4D images of pelvic floor muscles. METHODS: The International Consultation on Incontinence Questionnaire Urinary Incontinence Short Form (ICIQ-UI SF). OAB-q - overactive bladder questionnaire - short form. The Urinary Incontinence Quality of Life scale (I-QoL) - self-assessment scale for assessing the quality of life of patients with urinary incontinence. Adjusted Oxford scale to assess pelvic floor muscle strength. PERFECT scheme by Laycock and Jerwood. Pelvic floor examination by perineometer (Peritron-Ontario, L4V, Canada). Pelvic floor examination by 2D and 3/4D ultrasound examination (Volunson-i BT 11 Console, VCI volume contrast imaging software, (GE Healthcare Austria GmbH & Co OG, Zipf, Austria, RAB4-8-RS 3D/4D 4-8 MHz probe). High intensity exercise of pelvic floor muscles with stabilization elements. CONCLUSION: The effect of pelvic floor muscle training was objectively proved by the above mentioned objectivization methods with subjective improvement of quality of life. There was also a significant effect of education in USG exercise.
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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 | 0.001 | 0.002 |
| 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) | 0.005 | 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".