A comparison of oral health-related quality of life and satisfaction among patients undergoing root canal treatment or tooth extraction – A prospective controlled cohort study
Bibliographic record
Abstract
OBJECTIVE: This study aimed to evaluate the impact of root canal treatment on Oral Health-Related Quality of Life (OHRQoL) in general dental practice and compare it with tooth extraction. Additionally, patient satisfaction following tooth-preserving treatment was assessed. MATERIAL AND METHODS: In all, 65 patients were recruited from 6 general dental clinics in Västra Götaland over 8 weeks, with 37 starting root canal treatment and 28 having extractions. Questionnaires, including Oral Health Impact Profile-14 (OHIP-14) and 9 questions assessing patient satisfaction, were administered at treatment initiation, and at 1, 6, and 12 months. The responses from both modalities were analysed using descriptive and analytical statistical methods. Results: The response rate ranged from 73.8% to 92.3%. Regarding OHRQoL, differences between the groups were few compared to baseline. However, significant improvements were observed in the extraction group at the 6- and 12-month follow-ups, in the 'total score', and the dimensions 'pain', 'discomfort', and 'handicap'. Patient satisfaction was generally high, with cost being the least satisfactory item. Pain intensity remained consistently low. CONCLUSIONS: In this prospective cohort study few differences were found between the two treatment modalities. However, significant improvements were observed in the extraction group in several dimensions. The patient satisfaction regarding root canal treatment was considered high.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".