Adjunctive antimicrobial photodynamic therapy (aPDT) applied after submucosal instrumentation (SI) vs Submucosal instrumentation (SI) alone, or SI plus placebo/sham aPDT: Change in probing pocket depth (PPD)
- Population
- Adults (> 18 years) with peri-implant mucositis, receiving active treatment
- Intervention
- Adjunctive antimicrobial photodynamic therapy (aPDT) applied after submucosal instrumentation (SI)
- Comparison
- Submucosal instrumentation (SI) alone, or SI plus placebo/sham aPDT
- Outcome
- Change in probing pocket depth (PPD)
Adjunctive antimicrobial photodynamic therapy (aPDT) applied after… showed no clear difference in change in probing depth (PD/PPD) compared with submucosal instrumentation (SI) alone, or SI plus placebo/sham aPDT; GRADE not reported.
What each review found
Current versions only| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Adjunctive antimicrobial photodynamic therapy (aPDT) applied after submucosal instrumentation (SI) vs Submucosal instrumentation (SI) alone, or SI plus placebo/sham aPDT Change in probing depth (PD/PPD) · Adults (> 18 years) with peri-implant mucositis, receiving active treatment · 3 months (change from baseline) Adjunctive antimicrobial photodynamic therapy (aPDT) applied after… showed no clear difference in change in probing depth (PD/PPD) compared with submucosal instrumentation (SI) alone, or SI plus placebo/sham aPDT; GRADE not reported. Adjunctive antimicrobial photodynamic therapy for treating periodontal and peri‐implant diseases (2024) · Cochrane All outcomes | MD -0.10 [-0.57, 0.37] | 1 study · 38 participants | GRADE not reported |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Adjunctive antimicrobial photodynamic therapy for treating periodontal and peri‐implant diseases 2024 · Cochrane All outcomes | 2024-02 | 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.