Urine analysis of 3,4-methylenedioxypyrovalerone in opioid-dependent patients by gas chromatography-mass spectrometry.

A gas chromatography-mass spectrometry (GCMS) procedure was developed for the quantitative analysis of the new designer drug methylenedioxypyrovalerone (MDPV) in urine together with the common stimulants amphetamine, methamphetamine, and methylenedioxymethamphetamine (MDMA). The procedure involved electron ionization (EI) GCMS in the selected ion monitoring (SIM) mode after liquid-liquid extraction with toluene and derivatization with heptafluorobutyric acid anhydride. All MDPV findings were confirmed by positive chemical ionization GCMS in SIM mode. Positive chemical ionization-GCMS allowed the protonated molecule M+H+ m/z 276 to be used as a target ion with 3 abundant fragments as qualifier ions. By electron ionization-GCMS, the limit of quantification (LOQ) for MDPV was 0.02 mg/L; and for amphetamine, methamphetamine, and MDMA, the LOQ was 0.05 mg/L. The method was applied to monitoring urine samples from opioid-dependent patients undergoing opioid substitution treatment. Nine of the 34 urine samples (26%) analyzed were MDPV positive by the GCMS procedure. The positive samples were obtained from 2 female and 7 male patients with a mean age of 31 years. The median (range) MDPV concentration was 0.16 mg/L (0.04-3.9 mg/L) based on the 7 samples for which a numeric value was obtained, whereas the concentration was below the LOQ but above the limit of detection in 2 samples. The method revealed amphetamine in approximately 40% of the cases, and there was no statistical difference between the MDPV-positive and MDPV-negative groups. Urine amphetamine concentrations were on average 10 times higher than those of MDPV. The opioid-dependent patients used MDPV mainly as a substitute for amphetamine, judging from the laboratory findings of this study and the information from our patients.

Quantification of a methadone metabolite (EDDP) in urine: assessment of compliance.

OBJECTIVE: To investigate the possibility of utilizing the ratio of the methadone metabolite, 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP), to urine creatinine to develop a regression model that would predict drug adherence in patients prescribed methadone for either pain management or drug addiction. DESIGN: Retrospective study. SETTING: Marshfield Clinic-Lakeland Center, one of 41 regional centers that make up Marshfield Clinic, a large, private, multi-specialty healthcare institution in central Wisconsin. PARTICIPANTS: Patients receiving methadone treatment for substance abuse or chronic pain. Group 1 was an initial pilot group consisting of 7 patients who were followed for a 4-month period. Group 2 consisted of 33 patients who were followed over a 28-month period. METHODS: Age, gender, weight, height, methadone dosage, quantitative urine creatinine and EDDP levels, reported compliance/non-compliance, and relevant clinical cofactors were retrospectively abstracted from the patients' medical records. Log-log regression analyses were used to model EDDP and the EDDP/creatinine ratio from urine screening results as functions of methadone dose, and in the larger cohort (group 2), body size, gender and age. The coefficient of determination adjusted for the number of predictor terms (R(adj)(2)) was reported as a measure of model fit. RESULTS: For group 1 data, there was a significant positive relation (P<0.001) but also substantial variability (R(adj)(2) = 0.49). Adjustment for creatinine through the EDDP/creatinine ratio provided a tighter relation (R(adj)(2) = 0.95). Similarly, for group 2 data, there was a significant positive relation (P=0.001) and substantial variability (R(adj)(2) = 0.53). Adjustment for creatinine through EDDP/creatinine ratios provided a substantially stronger relation (R(adj)(2) = 0.73). Gender and age showed no evidence of association with the EDDP/creatinine ratio (P=0.60 and P=0.51, respectively). Body size was significant in the model, both when measured by body surface area and by lean body weight, and improved the prediction when added to our model (R(adj)(2) = 0.80). CONCLUSION: For the first time, urine analyses may be used to monitor methadone over- or under-use in a clinical setting, regardless of the state of patient hydration or the manipulation of a sample by addition of another substance, such as bleach, soap, or even methadone, which could render an appropriate sample inappropriate or an inappropriate sample appropriate. A similar approach may prove useful for other drug treatments, allowing for more accurate monitoring of commonly abused prescription medications.