Use of a device that applies external kneading-like force on the abdomen for treatment of constipation
Bibliographic record
Abstract
AIM: To evaluate the efficacy of a recently developed device that applies kneading-like motion on the abdomen in improving constipation in elderly long-term care patients. METHODS: Thirty constipated elderly patients were randomly selected from two nursing homes. They were instructed to use the device once daily for 20 min. Rate of bowel movements, volume and consistency of stool and the use of laxantia were all recorded during a 3-wk baseline period and for 12-wk treatment period. Colonic transit time (CTT) was measured in 13 patients by radiopaque markers during the baseline and at the end of treatment. RESULTS: Bowel movement rate (BM/week) increased from 1.4±0.4 BM/wk during baseline to 3.9±0.8 BM/wk during treatment (P5.0×10-7). Stool amount that was low in 30 patients during baseline increased in 21 patients at the end of the study period (x2 = 19.048-P= 1.3×10-5). Stool consistency,that was hard in 25 patients and soft in 5 patients during baseline, ameliorated in 23 patients at the end of the study (only 2 patients referred hard stool) (x2 = 21.043-P= 4.0×10-6). The mean baseline CTT measured was 92.3±32.3 h at baseline and decreased to 49.4±31.3 h during the study period (P = 0.000208). No side effects were observed during the study period. CONCLUSION: External mechanical vibration of the abdomen reduced CTT and helped to relieve severe constipation in elderly constipated 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".