Can Baseline Electromyography Predict Response to Biofeedback for Anorectal Disorder? A Long-Term Follow-Up Study
Bibliographic record
Abstract
BACKGROUND: Biofeedback has been recommended for the treatment of anorectal disorders, especially constipation and fecal incontinence (FI). The objective of this study was to assess the long-term efficacy of biofeedback and evaluate baseline electromyography (EMG) as a predictor for maintenance of long-term improvement. METHODS: A retrospective chart review was performed on randomly selected patients who underwent biofeedback between the years 1990 and 2000. Clinical characteristics, including EMG values at baseline (resting and contraction) as well as EMG after exercises, were collected. Patients were contacted and were classified as "improved" if they had self-reported symptomatic improvement and "not-improved" if their symptoms were unchanged or worsened. RESULTS: A total of 41 subjects were included. Majority (85.4%) were female, the mean age was 48.95 ± 15.46 (range 22 - 77 years) and the median follow-up was 4 years (range 4 - 5 years). Constipation was the primary indication for biofeedback in 27/41 (65.9%), FI in 9/41 (22%) and "other" in 5/41 (12.1%). Within constipation, 55.6% reported long-term improvement as compared to 66.7% of FI and 80% of the other patients. There was borderline difference in the baseline EMG (3.11 ± 1.85 µV, improved, and 7.41 ± 11.01 µV, not improved, P = 0.06) but no significant difference in post-exercise resting (3.13 ± 3.21 µV, improved, and 4.28 ± 3.63 µV, not improved, P = 0.33) and contraction EMG between the two groups. CONCLUSIONS: Biofeedback is an important treatment tool in anorectal disorders. Over 50% of our subjects maintained their improvement 4 - 5 years after completing biofeedback therapy. A lower resting baseline EMG showed a trend of association with improvement in the long term.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".