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.

Exceptionally high initial seizure threshold in a catatonic patient treated with electroconvulsive therapy.

OBJECTIVES: Seizure threshold in electroconvulsive therapy (ECT) is generally defined as the smallest electrical stimulus dose that produces a generalized seizure of at least 25 to 30 seconds on electroencephalography. Seizure thresholds vary considerably among patients, and some patients have an exceptionally high initial seizure threshold. We describe a patient with catatonia who showed an initial seizure threshold exceeding 500 milliCoulombs. The literature was searched for other reports on this phenomenon. METHODS: A systematic review was conducted using MedLine from 1966 to January 2008 and PsychINFO (2007), cross-referencing ECT and (excessively high) seizure threshold, as well as standard works on ECT. The literature was scrutinized for reports on high initial seizure threshold and associated demographic and clinical characteristics. RESULTS: Besides our patient, 6 articles were found reporting on 9 severely depressed, mostly elderly patients (aged 45-85 years; 5 males, 2 females; 2 persons with unknown sex) with excessive initial seizure thresholds ranging from 335 to 896 milliCoulombs (mC), and most with cardiovascular compromise. Strategies to lower seizure thresholds in ECT included manipulation of stimulus parameters, adjustment of anesthetics, and augmentation with proconvulsant agents. CONCLUSIONS: Because reports on exceptionally high initial seizure thresholds in ECT are rare, no definite conclusions can be drawn regarding its possible risk factors and management. However, since high initial seizure thresholds can complicate ECT, it is clinically important to further investigate this phenomenon.

Model for the breakup of a tuft of fibers.

A simple model for the forces acting on a single fiber as it is withdrawn from a tangled fiber assembly is proposed. Particular emphasis is placed on understanding the dynamics of the reptating fiber with respect to the entanglement of fibers within the tuft. The resulting two-parameter model captures the qualitative features of experimental simulation. The model is extended to describe the breakup of a tuft. The results show good agreement with experiment and indicate where a tuft is most likely to fracture based on the density of fiber endpoints.

Quantification of oxycodone and morphine analytes in urine: Assessment of adherence.

OBJECTIVE: To use urine drug testing (UDT) results and other covariates to develop a model for the assessment of opioid medication prescription adherence. DESIGN: Retrospective study. SETTING: The Pain Management Clinic at one center of a large, private, multispecialty healthcare system (consisting of 52 regional centers) in northcentral and western Wisconsin. PARTICIPANTS: Seven hundred thirty-three Pain Management Clinic patients with an opioid prescription and UDT between June 1, 2007 and May 17, 2010. UDT results were available for 2,615 individual drug screens from 2,364 urine samples. INTERVENTION: Patient characteristics, drug dosage, quantitative urine creatinine and drug/analyte levels, and reported adherence/nonadherence were abstracted from the electronic medical record. MAIN OUTCOME MEASURES: Adherence was categorized for all UDT results using an objective set of criteria. Drug adherence was modeled excluding samples for clinically observed adherence issues, detection of illicit substances, diagnosed addictive disorders, and/or metabolic reasons. RESULTS: Considerable variability was observed for primary urine analytes, even among those prescribed the same dose and believed to be adherent and free of confounding medical issues. For all medications evaluated, only urine creatinine contributed significantly (p < 0.0001) to predictive models of adherence based on dose alone. Simulated underuse and review of identified overuse and underuse suggest that this model could provide useful adherence information. CONCLUSION: Predictive models based on urine analyte levels and clinical covariates, particularly urine creatinine, may be clinically useful for assessing opioid adherence. Future work should evaluate whether genetics or other factors can improve predictive accuracy of these models.

Random genetic drift determines the level of mutant mtDNA in human primary oocytes.

We measured the proportion of mutant mtDNA (mutation load) in 82 primary oocytes from a woman who harbored the A3243G mtDNA mutation. The frequency distribution of mutation load indicates that random drift is the principal mechanism that determines the level of mutant mtDNA within individual oocytes.