Development of a Core Outcome Set in Endodontics (COS-ENDO): Part 1 – General Methods for Developing COS-ENDO for Studies of Nonsurgical Root Canal Treatment, Retreatment, Surgical Endodontics, Vital Pulp Therapy, Apexification, and Regenerative Endodontics in Permanent Teeth
Bibliographic record
Abstract
INTRODUCTION: Methodological heterogeneity and reporting bias complicate interpreting endodontic outcomes. Supported by the American Association of Endodontists and its Foundation, this study developed the Core Outcome Set in Endodontics (COS-ENDO) to standardize reporting for studies of nonsurgical root canal treatment/retreatment, surgical endodontics, vital pulp therapy, apexification, and regenerative endodontics. This article, the first in a 5-part series, outlines the methods for developing COS-ENDO, with detailed findings for each treatment presented in subsequent parts. METHODS: Outcomes were identified through scoping reviews, a qualitative study with patients, and a web-based survey of American Association of Endodontists practicing members. In a 2-round Delphi survey, clinicians, patients, and researchers rated outcomes on a 9-point scale. Ratings were assessed against consensus criteria, and a virtual meeting finalized COS-ENDO. RESULTS: Of the 97 invited participants to round 1, 77 (79%) registered and 73 (95%) completed the survey, including 24 academicians/researchers, 26 clinicians, and 23 patients (or their caregivers/parents). They rated 64 outcomes, totaling 182 occurrences across treatments: 39 for nonsurgical root canal treatment/retreatment, 46 for surgical endodontics, 46 for vital pulp therapy, and 51 for apexification/regenerative endodontics. The outcomes that achieved consensus for inclusion and those lacking consensus (either for inclusion or exclusion) advanced to round 2 for rerating by 70 participants. During the final consensus meeting, 16 participants discussed the outcomes and finalized the COS-ENDO. CONCLUSION: COS-ENDO is an important step toward standardizing outcome reporting in endodontics. Its implementation will ensure consistent reporting, enhancing research utility and evidence synthesis. Further efforts are needed to establish optimal measurement methods.
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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 | 0.446 | 0.456 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.004 | 0.012 |
| Bibliometrics | 0.021 | 0.017 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".