Effect of Low‐Intensity Pulsed Ultrasound on Distraction Osteogenesis Treatment Time
Bibliographic record
Abstract
OBJECTIVES: The objectives of this systematic review with a meta-analysis were to critically analyze the available scientific literature regarding the effects of low-intensity pulsed ultrasound (US) on stimulating bone regeneration and bone maturation during distraction osteogenesis in humans and to determine whether the stimulatory effect of low-intensity pulsed US can effectively reduce the associated treatment time. METHODS: Studies were considered for inclusion if they were randomized clinical trials that examined the effect of low-intensity pulsed US on distraction osteogenesis compared to conventional distraction osteogenesis. The primary outcome was reduced treatment time. Study selection, risk of bias assessment, and data extraction were performed in duplicate. A random-effects meta-analysis model was used when more than 3 trials were eligible for a quantitative analysis and considering the expected differences in interventions and measurement tools. RESULTS: Five randomized clinical trials, with a moderate to high risk of bias, met the eligibility criteria. Four trials examining tibial distraction osteogenesis in 118 patients were combined in a meta-analysis. A statistically significant difference for reduced treatment time between distraction osteogenesis with low-intensity pulsed US and standard distraction osteogenesis was evident (mean difference, -15.236 d/cm; random-effects 95% confidence interval, -19.902 to -10.569 d/cm; P < .0001). As for the mandible, only 1 clinical trial was available, which showed no significant effect of low-intensity pulsed US therapy on distraction osteogenesis. CONCLUSIONS: Current available evidence suggests that low-intensity pulsed US therapy may provide a reduction in the overall treatment time for tibial distraction osteogenesis. However, this conclusion should be considered with caution, given the moderate to high risk of bias in the included randomized clinical trials.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 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 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".