Management Of Post‐Treatment Endodontic Disease: A Current Concept Of Case Selection
Bibliographic record
Abstract
Over 30% of root filled teeth in the population present with endodontic infective disease, which has either persisted or emerged after treatment. Management of these "failed" cases is a challenge to the clinician, at the levels of diagnosis, case selection, communication and decision, and that is even before techniques are considered. Diagnosis should differentiate between endodontic and other aetiologies, and focus on the site of infection. Case selection should be based on how best to control the infection, but also on the benefit-risk balance of the alternative treatment modalities, the attitudes of the patient and the capability of the clinician. All of the above must be communicated to the patient, who then should make the informed decision regarding the selected treatment. This article discusses the treatment rationale, diagnosis, case selection and communication related to post-treatment endodontic disease.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".