The influence of pain catastrophising on the experience of persistent pain/discomfort following non‐surgical root canal treatment
Bibliographic record
Abstract
Aims To (i) determine the prevalence and influence of pain catastrophising on pain/discomfort experience associated with teeth demonstrating periapical healing following non‐surgical root canal treatment (NSRCT); (ii) investigate common descriptors for characterising the pain/discomfort sensation. Methodology A total of 198 patients (264 teeth) were examined clinically and radiographically 5–14 months after completion of NSRCT. All the radiographs were assessed by one observer and 33% were additionally examined independently by a pre‐calibrated second observer. Each tooth was classified into complete, incomplete, uncertain healing and failed to heal groups. Detailed pain histories were obtained using the Short Form of the McGill Pain Questionnaire. The pain catastrophising score for each case was determined using the Pain Catastrophising Scale (PCS) questionnaire. Cohen's kappa coefficients were calculated to assess intra‐ and inter‐observer agreement on radiographic examination. Multiple logistic regression models were employed to investigate the association between prevalence of pain/discomfort and pain catastrophising as well as other potential influencing factors. Clustering effects within patients were adjusted using robust standard error. Results In total, 25% (n = 62/249) of teeth showing signs of periapical healing were associated with pain/discomfort on review. The most commonly used descriptors for the pain/discomfort sensation were ‘Sensitivity’, ‘aching’, ‘tender’ and ‘throbbing’. Intra‐ and inter‐observer agreements were substantial (0.8 and 0.6, respectively). The PCS score had no significant association with pain/discomfort experience after NSRCT (OR = 1.3, 95% CI 0.3, 1.1). Significant factors affecting the prevalence of pain/discomfort included: history of chronic pain (OR = 3.5, 95% CI 1.5, 8.4); pre‐operative vital pulp (OR = 5.2, 95% CI 1.5, 18.1); presence of pre‐operative pain (OR = 2.9, 95% CI 1.1, 8.1); presence of a pre‐operative crack (OR = 2.5, 95% CI 1.0, 6.3); and size of pre‐operative periapical lesion (OR = 0.85, 95% CI 0.77, 0.95). Conclusions Twenty‐five per cent of teeth showing signs of periapical healing had pain/discomfort characterised by typical descriptors; with five significant predicting factors. Pain catastrophising did not predict the occurrence of post‐operative pain/discomfort. Further monitoring of the clinical course of prevalent pain/discomfort associated with periapical healing should inform future decision‐making on further management.
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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 | 0.002 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".