In Response to ‘Intravenous Lipid Emulsion Given to Volunteers Does Not Affect Symptoms of Lidocaine Brain Toxicity’
Bibliographic record
Abstract
Dear Editor,We read with interest the recent report 1 assessing the treatment of human neurological toxicity due to lidocaine with intravenous lipid emulsion. We would like to voice a few concerns regarding the study. The toxicity and treatment assessed in this study were mostly subjective symptoms. We are concerned that the patients were not truly blinded as lipid administration is associated with a distinct burning sensation during infusion and patients are likely to notice a rapid, high-volume injection. The efficacy of blinding would have been greatly supported had the authors asked study participants which treatment they believe they had received. Additionally, details regarding the interpretation of the EEGs and the degree of blinding for this assessment were not mentioned. Furthermore, the dose of lidocaine given in this study was only 1 mg/kg, a therapeutic dose in which no symptoms of toxicity are typically expected. Although patients did report subjective symptoms, all patients recovered within 5 min. of lidocaine injection. Using a longer acting, and more lipophilic, local anaesthetic might have shown more of a difference in antidotal activity. The clinical utility of this study is further limited because of the pre-treatment model of intravenous lipid emulsion administration prior to toxin administration. However, this could have been mitigated by attempting to show an escalated dose requirement to develop toxicity. We commend the authors on assessing intravenous lipid emulsion as a therapy for drug-induced neurotoxicity, an adverse effect uncommonly studied. We look forward to seeing the authors’ future work on this subject. The authors report no conflicts of interest. None. All authors had a role in writing the letter.
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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 | 0.004 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.014 | 0.013 |
| Insufficient payload (model declined to judge) | 0.003 | 0.003 |
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".