Question · asked by 1 review
Ultrasound during vertical distraction osteogenesis vs Placebo (no ultrasound) during vertical distraction: Distraction distance (bone gain, mm)
- Population
- Patients with vertically deficient posterior/anterior mandibular ridges needing implants
- Intervention
- Ultrasound during vertical distraction osteogenesis
- Comparison
- Placebo (no ultrasound) during vertical distraction
- Outcome
- Distraction distance (bone gain, mm)
Ultrasound during vertical distraction osteogenesis showed no clear difference in distraction distance (bone gain, mm) compared with placebo (no ultrasound) during vertical distraction; GRADE not reported.
What each review found
Include earlier review versions| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Ultrasound during vertical distraction osteogenesis vs Placebo (no ultrasound) during vertical distraction Distraction distance (bone gain, mm) · Patients with vertically deficient posterior/anterior mandibular ridges needing implants · 2 years post-loading Ultrasound during vertical distraction osteogenesis showed no clear difference in distraction distance (bone gain, mm) compared with placebo (no ultrasound) during vertical distraction; GRADE not reported. Interventions for replacing missing teeth: horizontal and vertical bone augmentation techniques for dental… (2009) · Cochrane All outcomes | Distraction distance 4.6 mm (ultrasound) vs 5.8 mm (placebo); difference 1.2 mm not statistically significant, in favour of placebo; data not shown (Schortinghuis 2008) | 1 study · 9 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Interventions for replacing missing teeth: horizontal and vertical bone augmentation techniques for dental implant treatment 2009 · Cochrane All outcomes | 2009-06 | Not listed | Not assessed |
How reviews are matched to this question
Reviews word the same question differently. Four decision models (TypeSafe's Jev, Liquid AI's d1-ultra, SubQ Snap and Baseten's Elephant) judged each wording of the population, intervention, comparator and outcome against the others; two wordings count as the same when at least three of them agree and none clearly disagrees, and findings count as this question only when all four elements match. Timing, setting and subgroup never split a question: they are shown on each finding.