Effect of non-steroidal anti-inflammatory drugs on fracture healing in children: A systematic review
Bibliographic record
Abstract
BACKGROUND: Non-steroidal anti-inflammatory drugs (NSAIDs) are among the most commonly prescribed medications in the United States. Although they are safe and effective means of analgesia for children with broken bones, there is considerable variation in their clinical use due to persistent concerns about their potentially adverse effect on fracture healing. AIM: To assess whether NSAID exposure is a risk factor for fracture nonunion in children. METHODS: We systematically reviewed the literature reporting the effect of NSAIDs on bone healing. We included all clinical studies that reported on adverse bone healing complications in children with respect to NSAID exposure. The outcomes of interest were delayed union or nonunion. Study quality was assessed using the Newcastle-Ottawa scale for non-randomized studies. A final table was constructed summarizing the available evidence. RESULTS: A total of 120 articles were identified and screened, of which 6 articles were included for final review. Nonunion in children is extremely rare; among the studies included, there were 2011 nonunions among 238822 fractures (0.84%). None of the included studies documented an increased risk of nonunion or delayed bone healing in those children who are treated with NSAIDs in the immediate post-injury or peri-operative time period. Additionally, children are likely to take these medications for only a few days after injury or surgery, further decreasing their risk of adverse side-effects. CONCLUSION: This systematic review suggests that NSAIDS can be safely prescribed to pediatric orthopaedic patients absent other contraindications without concern for increased risk of fracture non-union or delayed bone healing. Additional prospective studies are needed focusing on higher risk fractures and elective orthopaedic procedures such as osteotomies and spinal fusion.
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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 | 0.005 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".