The impact of robot-assisted treadmill therapy on urinary incontinence rates in a child with lower limb paresis – a single case study
Bibliographic record
Abstract
Introduction Bladder incontinence is a daily challenge for spinal cord injury patients. An initial single case study showed the positive effects of robot-assisted gait training in an adult with this issue. The current study aimed to evaluate possible correlations between Lokomat®Pro treatment and incontinence in a seven-year-old boy with incomplete paraplegia at T10 caused by meningoencephalitis. Methods The study used an A-B-A-B-A-E design and observed the patient over a 17-week period. The intervention involved two 4-week blocks with the Lokomat®Pro interspersed by a wash-out phase of 3 weeks, with a final 5-week wash-out phase. Follow-up analysis included the Janda muscle function test, the 10-meter walk test (in crawling), surface sensitivity assessment, and the Patient Specific Functional Scale (PSFS) combined with the Canadian Occupational Performance Measure (COPMa-kids) at each measurement time point. The patient also received 60 min of standardised gait training daily. Results The results show a positive relationship between therapy and muscle function, with an impressive increase in bladder maximum filling volume. Furthermore, nocturnal diaper wetting disappeared under therapy, with the patient able to sleep through the night without the need for a diaper change. In addition, stool consistency returned to normal during treatment. Conclusions The therapy proved an effective treatment by reducing incontinence and positively influencing muscles. Subsequent studies, with more cases, should aim to confirm these effects.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".