Comparison of Water Flosser and Interdental Brush on Reduction of Gingival Bleeding and Plaque: A Randomized Controlled Pilot Study.
Bibliographic record
Abstract
OBJECTIVES: The purpose of this randomized, two-week, single blind, two-group parallel pilot study was to compare the reduction in gingival bleeding and plaque in subjects using a water flosser or interdental brush, each combined with a manual toothbrush. METHODS: Twenty-eight subjects completed the study. Subjects were randomly assigned to one of two groups: Waterpik® Water Flosser (WF) plus manual toothbrush or interdental brushes (IDBs) plus a manual toothbrush. Bleeding on probing (BOP) was measured at six sites and reported for whole mouth, lingual, facial, and interproximal areas. Plaque data were measured using the Rustogi Modification of the Navy Plaque Index (RMNPI) and were reported for whole mouth, approximal, marginal, facial, and lingual areas. Subjects received verbal and written instructions on the use of their interdental product and demonstrated proficiency prior to starting the study. RESULTS: There were no differences between the groups for BOP or RMNPI at baseline. Both groups demonstrated a significant reduction in BOP and RMNPI for all regions and areas measured from baseline to two weeks. The WF was more effective than the IDBs for BOP whole mouth (56%), facial (44%), approximal whole mouth (53%), and approximal facial (41%). Post hoc power analysis showed that the sample size was not adequate to detect a significant difference between groups for lingual and marginal assessments for BOP or any area for RMNPI. CONCLUSIONS: The Waterpik Water Flosser is more effective than IDBs for reducing gingival bleeding over two weeks.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".