Question · asked by 1 review
Professional oral care vs Usual oral care: Incidence of NHAP
- Population
- Residents of nursing homes and other long-term care facilities
- Intervention
- Professional oral care
- Comparison
- Usual oral care
- Outcome
- Incidence of NHAP
Professional oral care showed no clear difference in incidence proportion (cumulative incidence) of NHAP compared with usual oral care (low certainty).
What each review found
Current versions onlyNo studies found 0 · 0%GRADE not reported 0 · 0%Very low 0 · 0%Low 2 · 100%Moderate 0 · 0%High 0 · 0%
| Finding | Effect | Studies | GRADE certainty |
|---|---|---|---|
Professional oral care vs Usual oral care Incidence of NHAP · Residents of nursing homes and other long-term care facilities · 8-30 months Oral care measures for preventing nursing home‐acquired pneumonia (2022) · Cochrane All outcomes | Incidence of NHAP, follow-up 8-30 months, 5018 (5 studies), Low. Not pooled (individual and cluster-randomised designs, varying effect measures and follow-up). Component estimates: Bourigault HR 0.65 (0.29 to 1.46;… | 5 studies · 5018 participants | Low |
Professional oral care vs Usual oral care Incidence proportion (cumulative incidence) of NHAP · Residents of nursing homes and other long-term care facilities · 24 months Professional oral care showed no clear difference in incidence proportion (cumulative incidence) of NHAP compared with usual oral care (low certainty). Oral care measures for preventing nursing home‐acquired pneumonia (2018) · Cochrane All outcomesearlier version CD012416.PUB2, superseded | RR 0.61 [0.37, 1.01] | 1 study · 366 participants | Low |
Findings are shown side by side, never pooled across reviews.
The reviews
| Review | Searched up to | Included studies | AMSTAR 2 |
|---|---|---|---|
| Oral care measures for preventing nursing home‐acquired pneumonia 2022 · Cochrane All outcomes | 12 May 2022 | 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.