Interindividual and Intraindividual Variation of Methylphenidate Concentrations in Serum and Saliva of Patients With Attention-Deficit/Hyperactivity Disorder
Bibliographic record
Abstract
BACKGROUND: Therapeutic drug monitoring is becoming increasingly important in psychiatric therapy, especially in children. However, for several reasons, it cannot yet be implemented as a daily routine in clinical or outpatient settings. To evaluate new, noninvasive procedures, blood and saliva (oral fluid) samples were collected from patients with attention-deficit/hyperactivity disorder (ADHD) who were also being administered methylphenidate (MPH). The study's main purposes were to correlate MPH concentrations in serum and saliva between subjects and to analyze intraindividual variation of serum concentration. METHODS: Thirty-six patients with ADHD (27 children and 9 adults) on MPH medication were included for drug analysis. MPH and its major metabolite ritalinic acid were quantified using liquid chromatography-tandem mass spectrometry measurements. The following correlations were investigated: (1) between drug concentrations in serum and saliva, and (2) between pH value and saliva to serum concentration ratio. Furthermore, the mean intraindividual MPH-concentration fluctuation in saliva under constant frame conditions was analyzed. RESULTS: After quantification, MPH concentrations were approximately 5 times higher in the saliva than in the serum, whereas the concentrations of ritalinic acid were much lower in saliva. We found significant correlations between concentrations of MPH in serum and saliva (r = 0.51, P < 0.05). Saliva MPH measures, compared with serum, were pH-dependent (r = -0.56, P < 0.01). Daily coefficient of variance of saliva concentration in children taking constant medication was 27.3% (11%-42%), whereas the coefficient of variance for the ratio of saliva to serum was 122% (2%-2060%). CONCLUSIONS: Our data indicate that the interindividual variation in saliva to serum concentrations is rather high, whereas the intraindividual variation is fairly low, as already shown in the literature for repeated citalopram serum measurements. Saliva may well serve as an alternative matrix for therapeutic drug monitoring of MPH in patients with ADHD, especially for follow-up examinations. Future research should focus on analyzing the relationship between drug levels in saliva and clinical effects as well as on understanding the mechanisms that generate saliva drug concentrations. These are essential steps before potential clinical use.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".