Evidence-based clinical practice guideline for the pharmacologic management of acute dental pain in children
Bibliographic record
Abstract
BACKGROUND: A guideline panel convened by the American Dental Association Council on Scientific Affairs, American Dental Association Science and Research Institute, University of Pittsburgh School of Dental Medicine, and Center for Integrative Global Oral Health at the University of Pennsylvania conducted a systematic review and meta-analyses and formulated evidence-based recommendations for the pharmacologic management of acute dental pain after 1 or more simple and surgical tooth extractions and the temporary management of toothache (that is, when definitive dental treatment not immediately available) associated with pulp and furcation or periapical diseases in children (< 12 years). TYPES OF STUDIES REVIEWED: The authors conducted a systematic review to determine the effect of analgesics and corticosteroids in managing acute dental pain. They used the Grading of Recommendations Assessment, Development and Evaluation approach to assess the certainty of the evidence and the Grading of Recommendations Assessment, Development and Evaluation Evidence to Decision framework to formulate recommendations. RESULTS: The panel formulated 7 recommendations and 5 good practice statements across conditions. There is a small beneficial net balance favoring the use of nonsteroidal anti-inflammatory drugs alone or in combination with acetaminophen compared with not providing analgesic therapy. There is no available evidence regarding the effect of corticosteroids on acute pain after surgical tooth extractions in children. CONCLUSIONS AND PRACTICAL IMPLICATIONS: Nonopioid medications, specifically nonsteroidal anti-inflammatory drugs like ibuprofen and naproxen alone or in combination with acetaminophen, are recommended for managing acute dental pain after 1 or more tooth extractions (that is, simple and surgical) and the temporary management of toothache in children (conditional recommendation, very low certainty). According to the US Food and Drug Administration, the use of codeine and tramadol in children for managing acute pain is contraindicated.
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 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 | 0.029 | 0.106 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.012 |
| Bibliometrics | 0.011 | 0.008 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.011 | 0.004 |
| Research integrity | 0.012 | 0.012 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".