Neuropathic Pain After Dental Implant Surgery: Literature Review and Proposed Algorithm for Medicosurgical Treatment
Bibliographic record
Abstract
The objective of this study is to establish an algorithm for the medicosurgical treatment of dental implant-induced neuropathic pain. The methodology was based on the good practice guidelines from the French National Authority for Health: the data were searched on the Medline database. A working group has drawn up a first draft of professional recommendations corresponding to a set of qualitative summaries. Consecutive drafts were amended by the members of an interdisciplinary reading committee. A total of 91 publications were screened, of which 26 were selected to establish the recommendations: 1 randomized clinical trial, 3 controlled cohort studies, 13 case series, and 9 case reports. In the event of the occurrence of post-implant neuropathic pain, a thorough radiological assessment by at least a panoramic radiograph (orthopantomogram) or especially a cone-beam computerized tomography scan is recommended to ensure that the tip of the implant is placed more than 4 mm from the anterior loop of the mental nerve for an anterior implant and 2 mm from the inferior alveolar nerve for a posterior implant. Very early administration of high-dose steroids, possibly associated with partial unscrewing or full removal of the implant preferably within the first 36-48 hours after placement, is recommended. A combined pharmacological therapy (anticonvulsants, antidepressants) could minimize the risk of pain chronicization. If a nerve lesion occurs in the context of dental implant surgery, treatment should be initiated within the first 36-48 hours after implant placement, including partial or full removal of the implant and early pharmacological treatment.
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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 | 0.002 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".