INFLUENCES OF POSTERIOR TEETH'S PAIN INTENSITY AND DURATION ON THE INCIDENCE AND CHARACTERISTICS OF OROFACIAL PAIN
Bibliographic record
Abstract
: Background: referred pain from toothache may obscure accurate identification of the offending tooth. For example, in the presence of pulpal pathology, patients may complain not only of pain in the offending tooth, but they may also report widely pain in other orofacial structure. Objectives: this study examined the influence of posterior toothache intensity, quality and duration on the incidence and characteristics of referred orofacial pain. Patients and Methods: In this cross – sectional study, 462 subjects with posterior toothache were recruited randomly from patients referred to the faculty of dentistry. After clinical and radiographic examination, the patients were asked to complete a questionnaire consisting of a numerical rating scale for pain intensity and chose verbal descriptors from McGill questionnaire to describe the quality of their pain. Data were analyzed using chi-square test, fisher exact test and Mann-Whitney test. Result: There was significant differences in intensity, quality and duration of toothache and orofacial referred pain (P<0.05). Conclusion: These results indicate that there is a positive correlation between referral pain and intensity, quality and duration of toothache.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".