Determination of Gabapentin in Plasma by Liquid Chromatography with Fluorescence Detection after Solid-Phase Extraction with a C18 Column
Bibliographic record
Abstract
Gabapentin (Neurontin®), one of the relatively new antiepileptic drugs, has a novel mechanism of action that is not fully understood. Gabapentin has been shown to increase γ-aminobutyric acid concentrations in the brain of epilepsy patients (1)(2). There is an approximate linear relationship between dose and plasma concentrations. A therapeutic range of 2–20 mg/L has been commonly accepted (2), although a higher minimum concentration of 6 mg/L has also been suggested (1). Various analytical methods have been used for the determination of gabapentin in plasma, with liquid chromatography being the most commonly used approach in clinical laboratories. Gabapentin does not have a natural chromophore; therefore, it must be derivatized to be detected spectrophotometrically or fluorometrically unless detected by mass spectrometry (3). Gabapentin has been derivatized with 2,4,6-trinitrobenzenesulfonic acid for photometric detection (4)(5). Several approaches have been described for the preparation of fluorescent derivatives. Garcia et al. (6) derivatized gabapentin with fluorescamine for determination by capillary electrophoresis. However, the preparation of o -phthalaldehyde (OPA) derivatives of gabapentin has been the most popular and practical approach for liquid chromatographic determinations (7)(8)(9)(10)(11)(12). In all of these procedures, plasma proteins are precipitated by different reagents and the resulting supernatant is treated with the derivatizing reagent. As a result, all endogenous amino compounds produce fluorescent derivatives, which produce very large solvent peaks, decreasing the sensitivity and increasing the length of the chromatographic run times. These procedures have another limitation in that the OPA derivatives must be injected almost immediately after preparation because …
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".