Falsely Elevated Vancomycin Concentrations in a Patient Not Receiving Vancomycin
Bibliographic record
Abstract
Therapeutic drug monitoring (TDM) of vancomycin is commonly performed using immunoassays. This case describes falsely elevated vancomycin serum concentrations, possibly secondary to endogenous protein interference. Vancomycin was prescribed for a patient with a suspected septic knee. A blood sample for TDM was inadvertently collected before the first dose. The reported concentration was 36.1 mg/L using the Roche Modular P analyzer and remained high over the next 48 hours and 8 months later in the absence of vancomycin therapy. Vancomycin was undetectable in the patient sample by liquid chromatography-tandem mass spectrometry. The sample was subsequently investigated for endogenous protein interference. The responsible interference was removed by polyethylene glycol precipitation and heat inactivation. Four alternative immunoassays with varying test principles measured vancomycin concentrations ranging from undetectable to 108 mg/L. A glucose-6-phosphate dehydrogenase detection method was common to the two immunoassays exhibiting the greatest interference. To our knowledge, this is the first report of falsely elevated vancomycin concentrations on the Roche Modular P analyzer. Immunoassays are generally robust in facilitating TDM but are susceptible to cross-reactivity. Assay interference should be considered and laboratory professionals contacted when vancomycin levels do not correlate with clinical expectations.
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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 | 0.001 | 0.010 |
| 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".