Root canal re-treatment with gutta percha - which techniques influence success?
Bibliographic record
Abstract
Abstract Objective A systematic review and meta-analysis of the literature was carried out assessing the success rate of root canal retreatment using gutta percha. Data sources Four of the largest databases were used to identify existing literature with no date or language restrictions. PubMed, Cochrane, ScienceDirect, Scopus and other additional sources were searched. Grey literature was also reviewed. Study selection Two authors, with Master’s degrees in endodontics and with extensive university teaching experience, were selected to screen the databases to identify suitable studies. In case the authors were not able to agree during the study selection process, a third investigator was consulted. Specific inclusion and exclusion criteria were outlined and adhered to in the study selection. Two randomised controlled trials, seven single arm prospective studies and one single arm ambispective study published before the 10th of December 2022 were included. These studies evaluated the success of root canal re-treatment, obturated with gutta percha with at least a 1-year follow-up. Nine of the studies were published between 1998 and 2022. Seven studies were conducted in Europe, one in North America and one in Asia. Data extraction and synthesis Standard Cochrane methods to assess interval validity were used. Risk of bias in individual studies was assessed using The Newcastle-Ottawa quality assessment scale (NOS) for single-arm studies, and the Cochrane risk of bias tool (RoB2) was used for randomised controlled trials. Outcome measures were standardised as either success or failure of root canal retreatment. Success was classified into 2 different criteria: Strict criteria = absence of clinical signs and symptoms and radiographically normal periodontal ligament space; and Loose criteria = absence of clinical signs and symptoms and absence or reduction of apical radiolucency in the control radiograph. Statistical analysis was undertaken using R software and the Freeman-Turkey transformation was performed. Results were visualised using forest plots. Heterogeneity between studies was measured using the Cochrane Q test and I2 values. Results Whilst following strict criteria, the success rate of non-surgical root canal retreatment obturated with gutta percha was 71% for 1–3 years follow-up (95% CI, 0.66–0.77) and 77% for 4–5 years follow-up (95% CI, 0.67–0.86). Heterogeneity was moderate (I2 = 61.4) and low (I2 = 0.0), respectively. Factors reducing the success rate of root canal re-retreatment under the strict criteria were older patients, mandibular teeth, molar teeth, the presence of a peri-apical radiolucency, teeth with a previous radiolucency, large peri-apical radiolucency’s, higher initial periapical index scores and multiple visit-retreatments. Following the loose criteria, the success rate of non-surgical root canal re-treatment obturated with gutta percha was 87% for 1–3 years follow-up (95% CI, 0.79–0.93) with significant heterogeneity across the studies (I2 = 88.5%). Factors influencing the success rate under the loose criteria were large periapical lesions >5 mm and higher initial periapical index (PAI) scores. Conclusions Non-surgical root canal retreatment results in favourable outcomes. However, there are several factors which can result in a lower success rate: the presence and size of a periapical radiolucency, a higher initial PAI score, multiple-visit retreatments, and the size and position of the tooth.
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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 | 0.037 | 0.075 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.029 | 0.050 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".