A Scoping Review of Four Decades of Outcomes in Nonsurgical Root Canal Treatment, Nonsurgical Retreatment, and Apexification Studies: Part 3—A Proposed Framework for Standardized Data Collection and Reporting of Endodontic Outcome Studies
Bibliographic record
Abstract
INTRODUCTION: Despite initiatives to standardize and improve reporting of rapidly growing endodontic outcome research studies, issues related to missing and ambiguous information are still of great concern. In this article, we propose a framework for standardized data collection and a compiled checklist for reporting of various study designs on endodontic outcome. METHODS: A comprehensive search was carried out to locate randomized controlled trials, cohorts, case-control studies, or case series of >100 patients that reported on endodontic outcomes. We reviewed these articles to develop a Data Collection Template and compiled a checklist for reporting of future endodontic outcome research. RESULTS: Out of 354 eligible articles previously reported in our scoping review on endodontic outcome studies, 109 articles were selected and screened for study variables or levels of categorization. Our complied Data Collection Template was developed in 19 domains to highlight important demographic, preoperative, intraoperative, and postoperative variables. Because of the specific needs for endodontic outcome literature, we also proposed a compiled checklist (consisting of 4 main domains) to facilitate the reporting of various study designs on endodontic outcome studies. This checklist included simple descriptions of the required items and examples on reporting from published endodontic studies. CONCLUSIONS: By facilitating the collection and reporting of relevant research data by investigators in private practice and academia, we hope that the proposed Data Collection Template and reporting guideline can highlight the importance of standardization among clinicians and researchers while producing valid scientific information that will support evidence-based treatment decisions.
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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 | 0.374 | 0.497 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.012 | 0.015 |
| Bibliometrics | 0.111 | 0.079 |
| Science and technology studies | 0.007 | 0.009 |
| Scholarly communication | 0.017 | 0.024 |
| Open science | 0.008 | 0.014 |
| Research integrity | 0.009 | 0.007 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".