Assessment of early wound healing, pain experience, life quality and related influenced factors during periodontal surgery: a cross-sectional study
Bibliographic record
Abstract
Abstract Background This cross-sectional study was to assess the early wound healing, pain experience, life quality, surgical satisfaction and the related factors during periodontal surgery. Methods 369 enrolled patients undergoing periodontal surgery completed the questionnaire before (baseline) and after operation immediately (phase I), on the day of suture removal (phase II) and one month later (phase III). The Early Wound Healing Score (EHS), short-form-McGill-Pain-Questionnaire (SF-MPQ) and tooth hypersensitivity visual analogue scales (VAS), oral-health-related-quality-of-life measure (OHQoL-UK) and surgical satisfaction VAS were detected and analysed. Results The EHS was 8.41 ± 2.74 and influenced by disease severity and surgical factors. SF-MPQ, pain intensity and OHQoL-UK were significantly increased in phase I and decreased later. The tooth sensitivity decreased significantly after periodontal surgery. Psychological factors positively related with these scores during periodontal surgery. Besides, disease severity and surgical factors were contributed in baseline or in phase I/II/III. Surgical acceptance and re-operation willing were continuously decreased after surgery and related to various and complicated factors. Conclusions EHS was good after periodontal surgery and related to disease severity and surgical factors. Pain experience and life quality were deteriorating in phase I but significantly improved later, which were influenced by disease severity, psychological and surgical factors. All these scores related to the surgical satisfaction. Trial registration: This cross-sectional study article reported the results without any intervention on human participants and all the experimental procedures involving human in this study were approved by the Ethics Committee of West China college of stomatology, Sichuan University (WCHSIRB-D-2020-284).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".