Perioperative use of non‐steroidal anti‐inflammatory drugs might impair dental implant osseointegration
Bibliographic record
Abstract
OBJECTIVE: To appraise whether adverse biological events following oral implant placement may be associated with perioperative use of non-steroidal anti-inflammatory drugs (NSAIDs). METHODS: All patients treated in a university faculty postgraduate dental clinic between 1979 and 2012 that had experienced a failing and surgically removed dental implant (292 implants in 168 patients) were contacted to solicit additional information about their present dental and medical status and frequency of current and past use of NSAIDs. Potential associations between perioperative NSAIDs use and the occurrence of adverse biological events were explored by the use of 2 × 2 tables and two-tailed Fisher's exact tests. RESULTS: One hundred and four patients with initially 468 implants had experienced 238 implant failures, of which 197 were due to failing osseointegration (42%). Sixty of the participants, initially with 273 implants, had used NSAIDs perioperatively and experienced 44% implant failures, versus 38% in the non-NSAID cohort. The NSAID cohort experienced 3.2 times more cases of radiographic bone loss greater than 30% of the vertical height of their remaining implants and 1.9 times more cases of cluster failures, defined as failure of 50% or more of the implant(s) placed. CONCLUSIONS: Notwithstanding that a retrospective study design is open to potential bias, the current data indicate that dental implant osseointegration may be affected negatively by an inhibitory effect of NSAIDs on bone healing in vulnerable patients. Future and better clinical studies than the current should be designed to appraise more precisely the potential effects of NSAIDs on implant osseointegration in study populations that are not limited by stringent medical inclusion and exclusion criteria.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".