Serotonin Toxicity Associated with Concomitant Use of Linezolid
Bibliographic record
Abstract
OBJECTIVE: To report 2 cases of serotonin toxicity (ST) associated with concomitant use of linezolid and serotonergic drugs and review previously published case reports. CASE SUMMARIES: Case 1. A 38-year-old white female with cystic fibrosis treated with venlafaxine 300 mg/day for one year was prescribed linezolid 600 mg intravenously every 12 hours for treatment of methicillin-resistant Staphylococcus aureus (MRSA) pulmonary infection. She displayed symptoms of ST 8 days after the introduction of linezolid. The venlafaxine dosage was decreased to 150 mg/day, and symptoms gradually abated over 36 hours. Case 2. A 37-year-old male with multiple myeloma received citalopram 40 mg/day and trazodone 150 mg/day for anxiety-related disorders. Linezolid treatment with 600 mg orally twice daily was instituted for MRSA cellulitis. The following day, the patient developed anxiety, panic attacks, tremors, tachycardia, and hypertension that persisted throughout linezolid treatment. Symptoms finally waned 5 days after linezolid treatment was stopped. DISCUSSION: The symptoms observed in our patients were consistent with Sternbach's criteria for ST. A review of published case reports showed a short time to onset of symptoms following the introduction of linezolid, generally within 1-3 days. Also of note is the use of relatively high dosages of serotonergic drugs. Use of the Naranjo probability scale indicated a possible relationship between the use of linezolid and the occurrence of ST in both cases. CONCLUSIONS: Clinicians should pay special attention to patients treated with serotonergic drugs, especially those receiving dosages in the higher end of the normal range who are prescribed linezolid, and consider tapering or reducing the dosage of serotonergic drugs for the duration of antibiotic therapy.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".