Healing Outcomes Following the Treatment of Molars Using Different Root Canal Disinfection Methods: A Prospective Cohort Study
Bibliographic record
Abstract
INTRODUCTION: To address the shortage of clinical outcome studies on contemporary root canal disinfection methods, this prospective cohort study assessed healing of apical periodontitis (AP) after use of the GentleWave (GW) system or Ultrasonic Activation (UA) combined with negative pressure irrigation (NPI). METHODS: Maxillary and mandibular molars with AP (n = 230) were treated with either GW or UA + NPI. A board-certified endodontist performed all procedures following standardized protocols. Patients with follow-up assessments available (n = 177) had radiographs assessed independently by 2 blinded endodontists who assigned a periapical index (PAI) score before and after treatment. The mean time between these assessments was 14.9 months. After excluding extractions, our statistical analyses first compared the numbers of positive and negative outcomes between GW (n = 85) and UA + NPI (n = 85) groups using strict (healed - PAI ≤2) and loose criteria (healing - decreased PAI >2). An ANOVA assessed if treatment type affected healing rates (PAI scores). RESULTS: Following treatment and adopting the strict success criteria, 70.6% of cases in the GW group were successful, compared to 72.9% in the UA + NPI group. Under the loose criteria, 83.5% were successful in the GW group compared to 87.1% in the UA + NPI group. No significant differences were found between the groups adopting either criterion. There was also no effect of treatment type (GW vs UA + NPI) on healing rates (PAI scores). The follow up time after treatment did not impact these findings. CONCLUSIONS: Within the limitations of this study, the GW system and UA + NPI were equally effective in promoting AP healing, suggesting both methods are viable options for root canal disinfection. Further research is needed to optimize protocol strategies and improve clinical outcomes.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".