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Record W7161955239 · doi:10.82308/34543

Radiation Impact on Endodontic-Treated Teeth in Head-Neck Cancer Patients

2024· dissertation· en· W7161955239 on OpenAlexaboutno aff
Elahe Akbari

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldMedicine
TopicOral health in cancer treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAsymptomaticCancerRoot canalHead and neck cancerRadiographyMedical recordOsteoradionecrosis

Abstract

fetched live from OpenAlex

Background: To date, uncertainty persists regarding the necessity of additional treatment for head and neck cancer (HNC) patients with prior root canal treatments. These patients may be clinically asymptomatic but exhibit specific radiographic risk factors. The dilemma arises as to whether such individuals should undergo further intervention before undergoing radiation therapy (RT). This uncertainty is compounded by the potential for oral complications, spanning from mucosal to bone tissue impairments, and the compromised immune systems commonly observed in patients undergoing RT. However, there is a notable scarcity of studies investigating the effects of RT on asymptomatic root canal-treated teeth in HNC patients with defects.Objective: This prospective observational cohort study in Montreal, Canada, aims to describe the impact of RT on asymptomatic root canal-treated teeth in HNC patients with periapical radiolucency (PARL), underfilled and overfilled canals, widened periodontal ligaments (PDL), and defective coronal seals.Methods: The records of 956 patients diagnosed with Head and neck cancer who underwent RT between 2018 and 2022 were retrospectively reviewed. Among them, 286 patients who had comprehensive dental, medical, and radiographic records were identified, and within this subset 122 had undergone at least one root canal treatment. Demographic information, cancer diagnosis, treatment details, pre-RT dental records, radiographs, and all dental records during RT follow-up were thoroughly reviewed. Ultimately,18 patients met the specific inclusion criteria. The assessment involved utilizing updated radiographs (periapical and panoramic) alongside comprehensive dental examinations to detect any symptomatic or radiographic changes in root canal-treated teeth with specific defects.Results: A total of 18 patients were included in the study, comprising 61% females and 39% males. Among the patients, 50 root canal-treated teeth with defects were identified. Of these teeth, 24 exhibited short root canal filling lengths, one tooth had an overfilled root canal filling length, 41 displayed poor-quality root canal treatments, 11 had defective coronal restorations, 13 exhibited periapical radiolucency (PARL), and 15 showed widened periodontal ligament (PDL) prior to radiotherapy (RT). The median follow-up period post-RT was 15 months. Clinical manifestations included defective restorations in 16% of teeth and mobility in 16% of teeth. Notably, teeth with clinical signs received significantly higher radiation doses (43.04 vs. 10.75 Gy). Evaluation of periapical radiographs comparing pre- and post-RT X-rays indicated stability despite observed clinical variations.Conclusion: Despite factors predisposing to root canal treatment failure, the dental conditions remained unexpectedly stable, suggesting resilience in the face of RT-induced changes in the duration of the study

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.069
Threshold uncertainty score0.138

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.023
GPT teacher head0.419
Teacher spread0.396 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations0
Published2024
Admission routes1
Has abstractyes

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