Transient unilateral oculomotor and trigeminal nerve palsy following intranasal local anesthetic infiltration: a case report
Bibliographic record
Abstract
Background: Complications from in-office inferior turbinate (IT) and septal swell body coblation typically include pain, congestion, and bleeding. However, rare cases of cranial nerve palsies from local anesthetic infiltration can occur. We present a rare case of an oculomotor nerve palsy and palsies of the ophthalmic (V1) and maxillary (V2) branches of the trigeminal nerve following intranasal local anesthetic infiltration prior to coblation, a complication not previously documented in the literature. Awareness of such rare and transient complications can help surgeons and clinicians avoid unnecessary interventions and better counsel patients. Case Description: A 75-year-old female with a one-year history of recalcitrant bilateral nasal obstruction underwent an in-office primary bilateral coblation of the ITs and septal swell bodies. Four percent lidocaine-soaked neuropatties were applied over the ITs and septal swell bodies, followed by infiltration with 0.25% bupivacaine hydrochloride with 1:200,000 epinephrine. Shortly after infiltration, the patient developed left-sided ptosis and was unable to adduct the left eye, causing diplopia. Additionally, the patient reported paresthesia in the V1 and V2 dermatomes. All symptoms resolved within 15 minutes. At the 6-week post-procedure visit, there was no sustained diplopia, left eye ptosis, or facial paresthesia. These symptoms also remained absent at the six-month post-procedure visit. Conclusions: Although relatively low-risk, surgeons should be aware of potential cranial nerve complications associated with intranasal anesthetic administration. Recognizing the benign and reversible nature of such presentations may help avoid unnecessary diagnostic workups, reduce patient distress, and reinforce best practices such as aspiration prior to infiltration and slow injection techniques.
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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 | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".