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Background: Urine drug testing is used by health care providers to determine a patient’s compliance to their prescribed regimen and to detect non-prescribed medications and illicit drugs. However, the cutoff levels used by clinical labs are often arbitrarily set and may not reflect the urine drug concentrations of compliant patients. Objectives: Our aim was to test the hypothesis that commonly used cutoffs for many prescribed and illicit drugs were set too high, and methods using these cutoffs may yield a considerable number of false-negative results. The goals of this study were to outline the way to analyze patient results and estimate a more appropriate cutoff, develop and validate a high sensitivity analytical method capable of quantitating drugs and metabolites at lower than the commonly used cutoffs, and determine the number of true positive results that would have been missed when using the common cutoffs. Study Design: This was a retrospective study of urine specimens submitted for urine drug testing as part of the monitoring of prescription drug compliance described in chronic opioid therapy treatment guidelines. Setting: The study was set in a clinical toxicology laboratory, using specimens submitted for routine analysis by health care providers in the normal course of business. Methods: Lognormal distributions of test results were generated and fitted with a trendline to estimate the required cutoff level necessary to capture the normal distributions of each drug for the patient population study. A validated laboratory derived liquid chromatography tandem mass spectrometry (LC-MS/MS) analysis capable of achieving the required cutoff levels was developed for each drug and/or metabolite. Results: The study shows that a lognormal distribution of patient urine test results fitted with a trendline is appropriate for estimating the required cutoff levels needed to assess medication adherence. The study showed a wide variation in the false-negative rate, ranging from 1.5% to 94.3% across a range of prescribed and illicit drugs. Limitations: The patient specimens were largely sourced from patients in either a long-term pain management program or in treatment for substance use disorder in the US. These specimens may not be representative of patients in other types of treatment or in countries with different approaches to these issues. Conclusions: The high-sensitivity method reduces false-negative results which could negatively impact patient care. Clinicians using less sensitive methods for detecting and quantifying drugs and metabolites in urine should exercise caution in assessing patient adherence using and changing the treatment plan based on those results. Key words: Urine drug testing, patient adherence, clinical toxicology, immunoassay, LC-MS, definitive drug testing, REMS, negative test results, false negative

A case in which methamphetamine use was confirmed using oral fluid analysis is described. Use of oral fluid for patient compliance testing in patients over urine is highlighted.

Cocaine is a common drug of abuse. To detect its use, a screening detection concentration for the cocaine metabolite benzoylecgonine is commonly set at 150 ng/mL and its confirmatory cut-off is set at 100 ng/mL. Studies have suggested that these cut-offs may be set too high, allowing some patients with this substance abuse problem to be missed or improperly monitored. With the advent of liquid chromatography–tandem mass spectrometry (LC–MS/MS) technology it is possible to reliably detect and quantify lower concentrations of its metabolite benzoylecgonine as part of a larger drug panel. One purpose of the study was to establish if there was a significant increase in detection of cocaine use with a ten-fold more sensitive cut-off. A very sensitive dilute and shoot assay for benzoylecgonine was developed with a lower limit of quantitation of 5 ng/mL. Validation of the 5 ng/mL cut-off was achieved by plotting all the positive cocaine observations as a frequency distribution on a logarithmic scale. The number of positive results with measurable concentrations below the typical industry 100 ng/mL cut-off level but above the high sensitivity 5 ng/mL cut-off level was observed to be 51.9% of the observed positives. The lower cut-off also allowed a re-evaluation of the window of detection after cessation of use. It was observed to be between 17 and 22 days. © 2016 Precision Diagnostics, LLC. Drug Testing and Analysis published by John Wiley & Sons, Ltd.

Drug-drug interactions are well known to have major adverse reactions. Many physicians are not aware of all the drugs their patients are taking so these interactions are not known to them. We tested more than 300,000 urine and oral fluid specimens from patients in pain treatment and substance abuse rehabilitation programs for 79 drugs and their metabolites. We used software developed by Elsevier to calculate if there was a severe drug-drug interaction for those specimens which tested positive for two potentially interacting drugs. The severe category was defined as “the use of these medications together is contraindicated, or the medications are not usually taken concurrently because the interaction may be life-threatening or may cause serious harm” We observed 1989 severe interactions. Many were not revealed to the patient’s care giver. We argue such drug-drug interactions are potentially misclassified as “opioid” deaths.

Heroin (diacetylmorphine) is made by acetylation of the 3 and 6 positions of the morphine molecule allowing it to rapidly cross the blood brain barrier. Once taken, it is rapidly de-acylated in two steps. First, the acetyl group from the 3 position is removed, forming 6-monoacetylmorphine (6-MAM). Second, the acetyl group on the 6 position is hydrolyzed, forming morphine. Although the major excreted products of heroin metabolism are morphine and morphine glucuronide, detection of heroin use is achieved by monitoring the presence of the intermediate metabolite 6-MAM in urine. The only source of this metabolite is heroin. The testing logic being that because of its short half-life there would only be minimal amounts of 6-MAM excreted. Workplace testing guidelines set the cut-off for 6-MAM at 10 ng/ml, implying that only 0.5% of the excreted morphine would be 6-MAM. Reviews of our urine samples positive for 6-MAM showed a significant number were above 1000 ng/mL. We attempted to determine the possible reason for the high 6-MAM urine concentrations.

Methamphetamine is a commonly used illegal drug and the use of the d form of methamphetamine (MAMP) can have serious implications for a patient’s treatment. Thus, correct identification of d methamphetamine is critical when releasing methamphetamine results although most reported positives are the result of illicit use, a small but significant number of MAMP positive findings can be from the use of medications that either contain or can be metabolized to MAMP. Neither common immunoassay screens nor routine mass spectral confirmatory methods can distinguish between the two forms of the drug because both forms have the same elemental composition and only differ in their orientation at the drug’s asymmetric carbon. Chromatographic chiral analysis which is a separation technique based upon the asymmetric carbon is used to resolve the drug into its enantiomeric forms. Historically, the test to differentiate the enantiomers has been time consuming requiring derivatization of the MAMP and a separate analytical system. The advent of newer chiral columns eliminates the need for derivatization and makes the analytical process simpler to automate. Federal workplace drug testing programs have established a threshold of 20% d-MAMP to distinguish between the legal and illegal use. The purpose of this study was to characterize positive MAMP results in the population of our test patients using both the derivatized and non-derivatized analytical procedures. The test population consisted of specimens collected from pain clinics and rehabilitation facilities. Of the 252,800 specimens tested between 3/28/16 and 2/3/17, we observed 11,264 specimens above our lower limit of quantitation of 50 ng/ml for methamphetamine. The average MAMP concentration was 32,530 ng/mL, while the median concentration was 27,882 ng/mL. There were 198 specimens in with 20% to 60% of the d enantiomer while 142 specimens contained greater than 99% of the l isomer. The average concentration of the d isomer value was 2074 ng/mL. The median concentration of the l isomer specimens was 166 ng/mL. However, 5 of these specimens contained MAMP concentrations greater than 20,000 ng/mL. Both methods of isomer analysis gave similar results with the d isomer measured to being 99% or greater in purity.

Background Because of the increasing volume of opiate-related overdoses, clinical testing of urine for drugs and related compounds in pain management clinics has become increasingly important. Interpreting findings of drugs present in urine specimens requires knowledge of pharmacokinetics, metabolism, drug purity, and cutoff concentrations used to report a positive result. Content This case-based mini-review provides examples of how to interpret immunoassay and quantitative confirmatory urine drug-testing results. Particular emphasis is placed on interpretation of opiate and benzodiazepine results, as these drugs have complicated metabolic profiles. Summary Both determining patient medication compliance and identifying the presence of additional drugs provides important information to the treating physician involved in managing pain. Mass spectrometry-based methods are required to identify specific drugs present and can provide important quantitative data for interpreting opiate medication compliance.

In addition to illicit methamphetamine, there are prescription and over-the-counter medications that, if ingested, may yield positive methamphetamine (MAMP) results on laboratory urine drug tests. The purpose of the study is to estimate the prevalence of medicinal and illicit MAMP in the pain population using chiral analysis to determine the relative amounts of the d and l-MAMP enantiomers. This retrospective analysis included the LC-MS/MS results and prescriber provided medication histories of 485,889 de-identified urine specimens from patients treated for pain. Two groups of 100 specimens each were subjected to chiral analysis. Group 1 contained specimens that were MAMP positive and amphetamine negative. Group 2 contained randomly selected MAMP positive specimens. The overall MAMP positivity rate of the 485,889 specimens tested was 1.6%. The prevalence of MAMP medications based on reported medications and detection of l-MAMP in Group 1 and Group 2 was 44% and 6%, respectively. These data indicate that the use of both illicit and medicinal MAMP is found in this patient population, and that medicinal use is underreported in clinical histories. Therefore, clinical laboratories should provide on request chiral analysis to aid in differentiating illicit and medicinal MAMP.

Cocaine is a common drug of abuse. To detect its use, a screening detection concentration for the cocaine metabolite benzoylecgonine is commonly set at 150 ng/mL and its confirmatory cut‐off is set at 100 ng/mL. Studies have suggested that these cut‐offs may be set too high, allowing some patients with this substance abuse problem to be missed or improperly monitored. With the advent of liquid chromatography–tandem mass spectrometry (LC–MS/MS) technology it is possible to reliably detect and quantify lower concentrations of its metabolite benzoylecgonine as part of a larger drug panel. One purpose of the study was to establish if there was a significant increase in detection of cocaine use with a ten‐fold more sensitive cut‐off. A very sensitive dilute and shoot assay for benzoylecgonine was developed with a lower limit of quantitation of 5 ng/mL. Validation of the 5 ng/mL cut‐off was achieved by plotting all the positive cocaine observations as a frequency distribution on a logarithmic scale. The number of positive results with measurable concentrations below the typical industry 100 ng/mL cut‐off level but above the high sensitivity 5 ng/mL cut‐off level was observed to be 51.9% of the observed positives. The lower cut‐off also allowed a re‐evaluation of the window of detection after cessation of use. It was observed to be between 17 and 22 days. © 2016 Precision Diagnostics, LLC. Drug Testing and Analysis published by John Wiley & Sons, Ltd.

To evaluate liquid chromatography-high-resolution mass spectrometry (LC-HR-MS) for urine toxicology screening, 29 analytes were quantitated in 152 urine specimens from patients with chronic pain using two unique mass spectrometry platforms. De-identified specimens were quantitated in April of 2011 by liquid chromatography-triple quadrupole mass spectrometry (LC-MS-MS) and by full-scan LC-HR-MS at Millennium Laboratories. Considering LC-MS-MS as the reference method, false positive results were identified in 19 specimens measured by LC-HR-MS. Application of relative retention times using deuterium labeled internal standards improved the rate of false positive detection to only five specimens, with four occurring for the same analyte. Ultra-high-resolution mass spectrometry (R = 100,000 at m/z 200) showed no improvement over high-resolution mass spectrometry (R = 10,000 at m/z 200) in the number of false positives detected. Quantitative results measured by LC-MS-MS and LC-HR-MS showed good agreement over four orders of dynamic range. This study demonstrates that LC-HR-MS is a suitable platform for toxicology screening for a pain management population and that quantitative accuracy and sensitivity are comparable to that achieved with LC-MS-MS. The specificity of LC-HR-MS is improved by the addition of deuterium labeled internal standards and the implementation of relative retention time matching.

Morphine is one of several opioids used to treat chronic pain. Because of its high abuse potential, urine drug tests can confirm "consistency with prescribed medications." Hydromorphone is a recently described minor metabolite of morphine, but few data exist on the characteristics of this metabolic pathway or the relationship of morphine and hydromorphone between and within subjects. Part I of this retrospective study shows that formation of hydromorphone from morphine is concentration-dependent and possibly saturated at high concentrations of morphine. In addition, the percentage of ultra-rapid metabolizers and poor metabolizers can be determined using the lower asymptote of a sigmoidal mathematical fit and are estimated to be 0.63 and 4.0%, respectively. Expected limits of morphine and hydromorphone (as a result of morphine metabolism) concentrations in the urine were established. Part II of this study used the metabolic ratio (hydromorphone-morphine) to determine the inter-patient and intra-patient variability in morphine metabolism to hydromorphone. Metabolic ratio values varied over a large range; 25-fold and 7-fold, respectively. The expected limits established in this study can assist in assessing the cause for possible variances in metabolism, such as drug interactions. The wide variability between and within subjects may explain unpredictable, adverse effects.

Hydrocodone in combination with acetaminophen is commonly used to control moderate pain and is metabolized by cytochrome P4502D6 to form the active metabolite, hydromorphone. The purpose of this study was to determine the metabolic relationship and variability between hydrocodone and its conversion to hydromorphone using urinary excretion data from chronic pain patients. Liquid chromatography-tandem mass spectrometry was used to quantitate hydrocodone and hydromorphone concentrations in urine specimens. The first visits of 25,200 subjects who took hydrocodone and not hydromorphone and had measurable concentrations were included in this study. The geometric mean (95% confidence index) of hydrocodone and hydromorphone urine concentrations were 1.39 (1.37-1.41) mg per gram of creatinine and 0.224 (0.221-0.227) mg per gram of creatinine, respectively. The log of creatinine-corrected hydromorphone versus the log of creatinine-corrected hydrocodone showed a positive relationship (R(2) = 0.20), with 60-fold variability between subjects. The plot of the log of the metabolic ratio ([hydromorphone] divided by [hydrocodone]) versus the log of creatinine-corrected hydrocodone had a coefficient of determination of R(2) = 0.42, with 125-fold variability between subjects. Ultra-rapid metabolizers represented 0.6% of the population, whereas 4% were poor metabolizers. Within-subject variability for the excretion of hydrocodone in urine was 23-fold, whereas between-subject variability was 134-fold. Hydrocodone and hydromorphone urine concentrations showed great variability within and between subjects.

Methadone is used to treat moderate to severe pain in patients not responsive to non-narcotic analgesics and for maintenance treatment of opioid addiction. Methadone is primarily metabolized by N-demethylation to an inactive metabolite 2-ethylidene-1,5dimethyl-3,3-diphenylpyrrolidene (EDDP) by CYP3A4 and CYP2B6. Establishing expected concentrations for metabolism of methadone to EDDP using urine excretion data may be useful for monitoring “medications” and toxicity. Urine specimens from chronic pain patients were collected during routine clinic visits. Methadone and EDDP were quantified by liquid chromatography –tandem mass spectrometry. Approximately 8,000 subjects who reported taking methadone had creatinine concentrations � 20 mg/dL, and excreted concentrations of methadone and EDDP above � 100 ng/mL were selected. The median methadone urine concentration was 3.03 mg/g cr. Ninety-five percent of the population had concentrations between 0.175 and 20.9 mg/g cr. EDDP was, on average, twice the methadone concentration. The wide variance in relationship of methadone to its metabolite was not concentration-dependent. Variability between subjects was larger than variability within subjects. As the urinary pH increased, the proportion of excreted EDDP increased, implying a preferred excretion of EDDP.

Our objective was to develop a "dilute and shoot" liquid chromatography-tandem mass spectrometry confirmatory procedure that uses full scan product ion spectra to identify drugs that are present above cutoff values as determined by isotope dilution relative to a deuterium-labeled internal standard. Deuterium-labeled internal standards are added to urine which is then diluted prior to analysis. Full scan product ion spectra were obtained in the data-dependent mode using a linear ion trap (ABI 4000 Qtrap). Identification was based on a purity fit of greater than 70. Ninety-seven urine specimens were analyzed by the method described, and results were compared to values obtained from a reference laboratory using selected reaction monitoring (SRM). The ion trap provided about 30-fold increase in signal-to-noise ratio as compared with the same instrument operated in a traditional full scan product ion mode. The assays were linear to at least 10 times the cutoff. Selecting appropriate triggers for obtaining full scan product ion spectra minimized space charging for specimens that contained high concentrations of drugs. There was 100% concordance between the full scan identification and the SRM results for identification of amphetamine, methamphetamine, benzoylecgonine, morphine, codeine, hydrocodone, and hydromorphone. The ability to "dilute and shoot" reduces the turnaround time for results. The data acquired with SRM and full scan product ion spectra provide accurate quantification and a high degree of specificity.

Background When properly selected, cutoff levels minimize the reporting of false negative and false positive test results and allow the laboratory to accurately determine the prevalence of marijuana, cocaine and methamphetamine use. Selecting the ideal cutoff requires the collection of drug excretion data for a large patient population to determine the expected range of drug concentrations. The cutoff can then be set to capture a high percentage of positives at a concentration within the dynamic range of the method. We used quantitative urine drug excretion data to calculate cutoffs needed to best determine the presence of these illicit drugs in urine. Methods This study used liquid chromatography tandem mass spectrometry (LC–MS/MS) as the analytical method. The study group was the pain patient population which is well-known to have a significant incidence of use of these illicit drugs. Frequency distributions were plotted for the creatinine normalized and raw data for all positive specimens with values greater than or equal to the method limit of quantitation. A non-parametric 2.5% estimator was applied to each data set to establish the cutoff for each drug. Results The urinary excretion data for the three drugs studied suggest cutoffs of approximately 30 ng/ml (benzoylecgonine), 10 ng/ml (carboxy-THC), and 50 ng/ml (methamphetamine) to identify 97.5% of the users of these drugs in this population. Conclusions Evaluation of urinary excretion data provides an objective method to validate the selection of cutoffs. These data provide additional support for the revised SAMHSA cutoffs which could increase the positivity rates for both benzoylecgonine and methamphetamine by 7%.

Problem statement: Patients on chronic opioid therapy are monitored to detect illicit drug use in order to deter diversion of their prescription opioids and to ensure medication adherence. The addictive potential of opioid drugs and their similar binding sites in the brain may make them potential gateway drugs for each other. Recent reports indicate that oxycodone has a high probability of leading to heroin use due to heroin’s similar effects and lower cost. This study explores the correlations between heroin abuse, prescription opioids and illicit drugs using urinary excretion data from pain patients. Approach: This retrospective analysis was conducted using a database of 148,200 urine samples from pain patients during routine drug screening at Millennium Laboratories between 2008 and 2010. Samples were tested for the presence of the heroin metabolite, 6-acetylmorphine (6-AM). All samples were analyzed and were quantified using LC-MS-MS. Microsoft® Excel 2007 and OriginPro® 8.1 were used to calculate percentages and ratios relating heroin use to opioid medications and illicit drugs. Results: Of the 446 samples positive for 6-AM, methadone was concomitantly used most frequently (26.7%) followed by cocaine (25.6%), oxycodone (24.2%), hydrocodone (16.4%), marijuana (11.6%), buprenorphine (4.9%) and methamphetamine (4.7%). The high percentage of concomitant methadone is expected because a portion of patients were likely to be on methadone maintenance therapy for heroin withdrawal. Patients on oxycodone were twice as likely to test positive for 6-AM than those on hydrocodone(0.28% versus 0.14%). Conclusions/Recommendations: Our results indicate that patients on methadone should be most closely monitored for heroin abuse due to their high proportion of concomitant use. The proportions of concomitant use were similar between oxycodone and cocaine and were both considerably higher than marijuana, a purported gateway drug for heroin. This study suggests that oxycodone may be highly correlated with heroin use. Urine samples must be assessed in the full clinical context.

Background: A significant number of chronic pain patients may use marijuana. Physicians treating those patients can benefit by knowing whether their patients using marijuana are at higher risk for using other illicit drugs such as cocaine and/or methamphetamine. Objective: Our objective was to determine whether marijuana-using chronic pain patients have a higher incidence of cocaine and/or methamphetamine use. Study Design: A retrospective study of the incidence of pain patients using marijuana and/or other illicit drugs such as methamphetamine and cocaine versus the incidence of pain patients not using marijuana but using methamphetamine and/or cocaine. Methods: Urine specimens from chronic pain patients were analyzed by LC-MS/MS to determine the co-occurrence of these abused substances. Results: In this study 21,746 urine specimens were obtained from chronic pain patients. We found a 13.0% incidence of patients positive for the acid form of Tetrahydrocannabinol (THCA). The percentage of those positive for cocaine was 4.6%, those positive for methamphetamine totaled 1.07%. Using both chi-square and a Logistic Regression analysis, we determined that there was a correlation between marijuana use and the use of other illicit drugs. The odds ratio was > 3.7 for other illicit drug use. Limitations: The study is limited in that we obtained no data as to the causal relationships of this type of drug use. Conclusions: Pain physicians should be aware that this relationship exists and marijuana-using patients are at greater risk for use of other illicit drugs although no causal relationship is implied. Increased monitoring of these patients may help minimize potential morbidity due to drug interactions as well as identify patients who may be diverting prescriptions in order to pay for illicit drugs. Key words: Marijuana, Tetrahydrocannabinol (THCA), Cocaine, Methamphetamine, Pain patients, correlation study

A "dilute and shoot" method for measuring norpropoxyphene in human urine using liquid chromatography-tandem mass spectrometry distinguishes two different metabolites of propoxyphene, norpropoxyphene (m/z 326) and a dehydrated rearrangement product (m/z 308). The metabolite formed from the rearrangement and dehydration of norpropoxyphene is excreted in human urine and also may be formed from the chemical degradation of norpropoxyphene. Previously, these two metabolites were indistinguishable by gas chromatography- mass spectrometry methods that use an alkaline extraction that converts norpropoxyphene into its rearrangement product. The degradation of norpropoxyphene presents a challenge for its analytical quantitation, and methods for circumventing these issues are presented.

Geoffrey Berlyne, whom we honor in this Festschrift, has contributed much to the modern understanding of diseases of the kidney, and of the clinical and metabolic disorders that occur in acute and chronic renal failure. The Festschrift highlights the many areas of his contributions. It is important to note that underlying them all is astute clinical observation, incisive analysis and reasoning, a breadth of approach, experimentation that facilitated understanding of the relevant clinical issues, and an unusual clarity of exposition in the literature. As author, editor, and teacher, Geoffrey Berlyne has brought this clarity of approach to a generation in nephrology. The following analysis of clinical data from a working dialysis unit, rendering care to a predominantly underprivileged patient population, is presented in the hope that it throws light on everyday problems in nephrology in a manner similar to that in which Geoffrey has guided the nephrology community.

The predominantly human sequence, high-affinity anticocaine monoclonal antibody (mAb) 2E2 was cleared slowly from mouse blood by a first-order process with an elimination t 1/2 of 8.1 days. Infused 2E2 also produced a dramatic dose-dependent increase in plasma cocaine concentrations and a concomitant decrease in the brain cocaine concentrations produced by an i.v. injection of cocaine HCl (0.56 mg/kg). At the highest dose of 2E2 tested (3:1, mAb/drug), cocaine was not detectable in the brain. Pharmacokinetic studies showed that the normal disappearance of cocaine from plasma was described by a two-compartment pharmacokinetic model with distribution t 1/2α and terminal elimination t 1/2β values of 1.9 and 26.1 min, respectively. In the presence of an equimolar dose of mAb 2E2, there was a 26-fold increase in the area under the plasma cocaine concentration-time curve (AUC) relative to the AUC in the absence of 2E2. Consequently, 2E2 decreased the volume of distribution of cocaine from 6.0 to 0.20 l/kg, which approximated that of 2E2 (0.28 l/kg). However, cocaine was still rapidly cleared from plasma, and its elimination was now described by a single-compartment model with an elimination t 1/2 of 17 min. Importantly, 2E2 also produced a 4.5-fold (78%) decrease in the cocaine AUC in the brain. Therefore, the effect of 2E2 on plasma and brain cocaine concentrations was predominantly caused by a change in the distribution of cocaine with negligible effects on its rate of clearance. These data support the concept of immunotherapy for drug abuse.

Background: The purpose of this study was to determine whether coenzyme Q10 (CoQ) concentrations and redox status are associated with components of the metabolic syndrome. Methods: This is a cross-sectional survey of 223 adults (28–78 years), who were drawn from the ongoing Princeton Follow-up Study in greater Cincinnati. Individuals were assessed for measures of fatness, blood pressure, glucose, lipid profiles, C-reactive protein (CRP), reduced CoQ (ubiquinol), oxidized CoQ (ubiquinone), total CoQ and CoQ redox ratio (ubiquinol/ubiquinone). Results: After adjusting for age, sex and race, we found that total CoQ, ubiquinol and CRP levels are significantly increased in metabolic syndrome. Comparison of minimal risk and high-risk metabolic syndrome groups indicates an increased CoQ redox ratio in the high risk group (p

Reference intervals serve as the basis of laboratory testing and aid the physician in differentiating between the healthy and diseased patient. Standard methods for determining the reference interval are to define and obtain a healthy population of at least 120 individuals and use nonparametric estimates of the 95% reference interval. This method is less accurate if the group size is significantly less and does not allow for exclusion of outliers. In order to overcome these limitations many authors in the current literature report reference intervals after arbitrary truncation of the data or use inappropriate parametric calculations. We argue that the use of outlier removal and robust estimators, with or without transformation to normality, address the shortcomings of the standard method and eliminate the need for employing less valid methods.To test these methods of analysis well-defined test groups are required. In a few studies physician-determined health status is provided for each subject along with commonly measured analytes. The NHANES and Fernald studies provide such groups. With such data it is possible to show the range of effects on the reference interval width by including a known non-healthy subgroup. With the NHANES data the effect ranged from negligible to a 30% increase in reference interval width. We found that use of outlier detection with the robust estimator yielded reference intervals that were closer to those of the true healthy group.Another issue is one of demographics. That is, whether or not one should derive separate reference intervals for different demographic groups, e.g., males and females. The standard mathematical test for deriving separate reference intervals is due to Harris and Boyd. Using the NHANES data we examined 33 analytes for each of three ethnic groups (separated by genders). We used the Harris and Boyd procedure and observed that it was necessary to derive separate reference intervals for approximately 30% of the comparisons. The most notable analytes were glucose and gamma GT.The methods used by most laboratories have similar precision, identical units, are linearly related (often on a 1:1 basis) and correlate well with each other. As a result the only difference is the method bias. By using the reference interval width, this bias is eliminated. We argue that the log ratio of the reference interval widths is a good estimate of the variability between groups.

Objective: To describe the differences between mass spectrometry technologies and compare and contrast them with immunoassay techniques of urine drug testing (UDT). Highlight the potential importance of the differences among these technologies for clinicians so as to allow them make decisions in their use in patient care. Methods: Review of mass spectrometry techniques, including gas chromatography, liquid chromatography, and time-of-flight techniques. Results: The potential clinical implications of these technologies stemming from their scope and accuracy are presented. Significance: UDT is an important clinical tool, though there are differences in technology and testing processes with important implications for clinical decision making. It is crucial, therefore, that clinicians have an understanding of the technologies behind the tests they order, so that their interpretation and use of results are based on an understanding of the strengths and weaknesses of the technologies used.

Background : The proportion of reduced coenzyme Q 10 (Q 10 H 2 ) in total coenzyme Q 10 (TQ 10 ), referred to as the Q 10 H 2 :TQ 10 ratio, may be used as a possible marker of in vivo oxidative stress. However, the ranges for Q 10 H 2 :TQ 10 ratio from previous reports are quite variable. Sample handling and preparation appear to have a profound effect on the stability of Q 10 H 2 . Methods : Paired tests were used to estimate TQ 10 , Q 10 H 2 , oxidized coenzyme Q 10 (Q 10 ), and Q 10 H 2 :TQ 10 ratio in patient samples collected in vacutainers containing heparin or EDTA. Sample tubes were immediately placed on ice and promptly centrifuged. After harvesting plasma, 100 μl of plasma was extracted with 1-propanol and centrifuged. The supernatant was injected directly into a high-performance liquid chromatography (HPLC) system. Results : Significantly higher values ( p =0.0015) of TQ 10 , Q 10 H 2 , and Q 10 H 2 :TQ 10 ratio were noted in heparinized plasma as compared to EDTA plasma; Q 10 concentrations were lower in heparinized plasma. When vacutainers containing specimen were opened and kept refrigerated, the Q 10 H 2 :TQ 10 ratios in heparinized samples were stable over 7 h with variation 10 H 2 in closed heparin vacutainers kept refrigerated was stable up to 24 h. Conclusions : Our results indicate that the heparinized plasma is superior to the EDTA plasma in all measurements for coenzyme Q 10 .

Background: The term drug screen is a misnomer since it implies screening for all drugs, which is not possible. Current practice is to limit the testing to the examination of serum for several drugs such as ethanol, acetaminophen, salicylate, and of urine for several specific drugs or classes of drugs. In the emergency setting the screen should be performed in less than one hour. Controversies continue to exist regarding the value of urine drug testing in the medical setting. The reasons for these include the drugs involved, the sample, the methods utilized to perform the tests, and the level of understanding of the physician using the data, all of which are closely related to the other. Methods: Current automated methods provide rapid results demanded in emergency situations, but are often designed for, or adapted from, workplace testing and are not necessarily optimized for clinical applications. Furthermore, the use of these methods without consideration of the frequency in which the drugs are found in a given area is not cost-effective. The laboratory must understand the limitations of the assays used and provide this information to the physician. Additionally, the laboratory and the physicians using the data must cooperate to determine which drugs are appropriate and necessary to measure for their institution and clinical setting. In doing so it should be remembered that for many drugs, the sample, urine, contains the end product(s) of drug metabolism, not the parent drug. Furthermore, it is necessary to understand the pharmacokinetic parameters of the drug of interest when interpreting data. Finally, while testing for some drugs may not appear cost-effective, the prevention or reduction of morbidity and mortality may offset any laboratory costs. Conclusions: While the literature is replete with studies concerning new methods and a few regarding physician understanding, there are none that we could find that thoroughly, objectively, and fully addressed the issues of utility and cost-effectiveness.

Background: Improvement in reference interval estimation using a new outlier detection technique, even with a physician-determined healthy sample, is examined. The effect of including physician-determined nonhealthy individuals in the sample is evaluated. Methods: Traditional data transformation coupled with robust and exploratory outlier detection methodology were used in conjunction with various reference interval determination techniques. A simulation study was used to examine the effects of outliers on known reference intervals. Physician-defined healthy groups with and without nonhealthy individuals were compared on real data. Results: With 5% outliers in simulated samples, the described outlier detection techniques had narrower reference intervals. Application of the technique to real data provided reference intervals that were, on average, 10% narrower than those obtained when outlier detection was not used. Only 1.6% of the samples were identified as outliers and removed from reference interval determination in both the healthy and combined samples. Conclusions: Even in healthy samples, outliers may exist. Combining traditional and robust statistical techniques provide a good method of identifying outliers in a reference interval setting. Laboratories in general do not have a well-defined healthy group from which to compute reference intervals. The effect of nonhealthy individuals in the computation increases reference interval width by ∼10%. However, there is a large deviation among analytes.

Background: The percentage of reduced coenzyme Q10 (CoQ10H2) in total coenzyme Q10 (TQ10) is decreased in plasma of patients with prematurity, hyperlipidemia, and liver disease. CoQ10H2 is, however, easily oxidized and difficult to measure, and therefore reliable quantification of plasma CoQ10H2 is of clinical importance.Methods: Venous blood was collected into evacuated tubes containing heparin, which were immediately placed on ice and promptly centrifuged at 4 °C. The plasma was harvested and stored in screw-top polypropylene tubes at −80 °C until analysis. After extraction with 1-propanol and centrifugation, the supernatant was injected directly into an HPLC system with coulometric detection.Results: The in-line reduction procedure permitted transformation of CoQ10 into CoQ10H2 and avoided artifactual oxidation of CoQ10H2. The electrochemical reduction yielded 99% CoQ10H2. Only 100 μL of plasma was required to simultaneously measure CoQ10H2 and CoQ10 over an analytical range of 10 μg/L to 4 mg/L. Intra- and interassay CVs for CoQ10 in human plasma were 1.2–4.9% across this range. Analytical recoveries were 95.8–101.0%. The percentage of CoQ10H2 in TQ10 was ∼96% in apparently healthy individuals. The method allowed analysis of up to 40 samples within an 8-h period.Conclusions: This optimized method for CoQ10H2 analysis provides rapid and precise results with the potential for high throughput. This method is specific and sufficiently sensitive for use in both clinical and research laboratories.

Urine drug monitoring is used by physicians treating chronic pain patients with opioid therapy. Patients are tested in part to insure that they are not taking other drugs. Therefore, the finding of codeine in a patient who is only prescribed morphine has clinical implications. Morphine preparations are known to have small amounts of codeine as an impurity estimated to be about 0.04%. In a population of 535 pain patients prescribed morphine, Kadian, MS Contin, and/or Avinza, the investigators observed 24 samples that contained codeine20 ng/mL. Fifteen of the 24 contained codeine20 and50 ng/mL. Of the 9 samples that were50 ng/mL, 7 had high levels of codeine (indicating codeine use), 1 was from a patient who had a prescription for codeine, and 1 was also positive for 6-acetylmorphine, indicating heroin use. A control group of 680 patients taking oxycodone was negative for codeine. The finding of codeine was ascribed to the manufacturing process of the morphine medications. Clinicians and laboratories testing urine for drugs should be aware of this possibility.

The current study addresses the distribution of low concentrations of excreted drugs in the pain patient population in an effort to establish a more rational set of cutoffs for this cohort. To wit, 19 analytes in approximately 8000 urine specimens from pain patients were measured using liquid chromatography tandem mass spectroscopy (LC-MS/MS) methodology. The lower limits of quantitation for the LC-MS/MS were set as the nominal cutoffs for the determination of positive and negative results. The measured concentrations were compared with the Substance Abuse & Mental Health Services Administration (SAMHSA) nominal immunoassay cutoffs, and a subset of "missed samples" was identified for each of the 19 analytes. This "missed samples" subset contained all samples that measured above the LC MS/MS cutoff for a given analyte but below the SAMHSA immunoassay cutoff. The number of "missed samples" divided by the total number of samples measured positive by the LC-MS/MS method defines the percentage of this population that would have been found falsely negative if a prescreen by immunoassay using SAMHSA cutoffs had been conducted. For example, 69% of the specimens that were positive for hydromorphone by LC-MS/MS would have been falsely scored as negative by immunoassay.

We propose a new methodology for the estimation of reference intervals for data sets with small numbers of observations or for those with substantial numbers of outliers. We propose a prediction interval that uses robust estimates of location and scale. The SAS software can be readily modified to do these calculations. We compared four reference interval procedures (nonparametric, transformed, robust with a nonparametric lower limit, and transformed robust) for sample sizes of 20, 40, 60, 80, 100, and 120 from χ2 distributions of 1, 4, 7, and 10 df. χ2 distributions were chosen because they simulate the skewness of distributions often found in clinical chemistry populations. We used the root mean square error as the measure of performance and used computer simulation to calculate this measure. The robust estimator showed the best performance for small sample sizes. As the sample size increased, the performance values converged. The robust method for calculating upper reference interval values yields reasonable results. In two examples using real data for haptoglobin and glucose, the robust estimator provides slightly smaller upper reference limits than the other procedures. Lastly, the robust estimator was compared with the other procedures in a population where 5% of the values were multiplied by a factor of 5. The reference intervals were calculated with and without outlier detection. In this case, the robust approach consistently yielded upper reference interval values that were closer to those of the true underlying distributions. We propose that robust statistical analysis can be of great use for determinations of reference intervals from limited or possibly unreliable data.

Background: Laboratory urine drug testing of patients on chronic opioid therapy requires providing a large test menu of medications commonly prescribed for this population as well as metabolites and illicit substances. It has been shown that liquid chromatography-tandem mass spectrometry (LC-MS/MS) is the preferred method to analyze urine specimens for these substances. Purpose of the study: To describe the challenges and some of the techniques to validate the analytical procedures used to identify and quantify these medications and substances. Methods: Using data obtained from testing over one million specimens, the authors developed a proposed test menu. Potential isobaric interferences were established by using literature references. A list of potentially interfering medications was obtained by using the proposed test menu and the most commonly prescribed medications. Finally, criteria were designed to detect possible carryover. Results: The LC-MS/MS instrumentation eliminated all potential interferences and provided quantitative data over the test range needed to monitor these patients. Carryover could be eliminated by setting the carryover thresholds for each analyte. Conclusions: Reference laboratories utilizing LC-MS/MS technology to conduct urine drug testing for pain clinicians should employ specific techniques described in this study to develop an optimal test menu and validate procedures that include isolating retention times for isobaric compounds, identifying interfering substances including impurities in medicinal and illicit substance preparations, monitoring ion suppression, and avoiding carryover.

Liver transplantation is an accepted therapy for end-stage liver disease. After allografting, a variety of clinical problems may require laboratory involvement for accurate and timely diagnosis and intervention. Critical factors in the choice of a laboratory test menu to support a transplant program include turnaround times that support clinical decisionmaking, real diagnostic value, and real value for money. Particular clinical problems, whose early presentation must be anticipated, include graft ischemia, primary nonfunction, and hepatic artery thrombosis. Acute rejection is common at 5–10 days posttransplantation, the principal target being the biliary tree. Longer-term problems are associated with the therapeutic drug measurement of cyclosporin A and, increasingly, tacrolimus (FK506); the side effects of immunosuppressant therapy also require monitoring. A successful liver transplant program can be adequately supported with a simple battery of automated tests that are cheap, fast, and available at all times.

The object of this study was to evaluate the metabolism of oxycodone to oxymorphone in a pain patient population using a quantitative liquid chromatography-tandem mass spectrometry analysis of 32,656 urine specimens obtained from pain patients between March 2008 and Feb 2010. The observed excretion was modeled using logarithmic transformation and approximated a Gaussian distribution. Oxycodone excretion into urine had a geometric mean of 1.93 mg/g of creatinine and oxymorphone had a value of 0.41 mg/g of creatinine. Increasing concentrations of oxycodone correlated with a smaller proportion of oxymorphone excretion suggesting saturation of oxycodone metabolism. Urine samples containing oxycodone without oxymorphone allowed an estimation of the proportion of poor metabolizers (2.4 ± 2.1%) in the population. A similar analysis of samples containing oxymorphone without oxycodone gave an estimate of the proportion of ultra-rapid metabolizers (1.8 ± 1.1%) in the population. Samples with concentrations of oxycodone above 10 mg/g of creatinine showed a sub-population of subjects with metabolic ratios roughly 100-fold less than the linear predictive model in this study. This study describes typical ranges for oxycodone and oxymorphone in urine, and showed that it is possible to identify fast or slow metabolizers who may be at risk for adverse events.

Background. Traditionally, urine drug screens have only been concerned with positive or negative results. Those results provide physicians treating patients for pain with chronic opioid therapy with information about medication compliance, use of nonprescribed medications, and use of illicit drugs. However, the analysis of urine for drugs offers additional information that, when compiled and accurately interpreted, may also be of great value to these doctors. Purpose: The aim of this article was to discuss the interpretation of urine drug tests and their application to pain physician practices. Method. We utilized a selection of recent articles on urine drug screening applicable to the pain patient population. Results and Conclusions. The article provides pertinent information about interpretation of urine drug testing, which is separated into six categories: which drugs and metabolites to test for; which analytical cutoffs to use; pain medication metabolism; identification of alcohol use; determination of patient compliance; and which patient groups to consider for more frequent testing.

Background Effective urine drug testing requires an understanding of the stability of medications, metabolites and other substances excreted in the urine matrix. When the testing results do not fit the clinical picture, physicians frequently request repeat testing of the original specimen in order to corroborate the results. We determined the stability in urine of various medications, metabolites, and illicit substances commonly requested for testing by physicians treating patients with pain and pain-related disorders. Methods Quantitative analyses of urine specimens were performed using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Two replicates at a high and low concentration were analyzed at time 0, and after 2, 3 and 6 months following storage at + 4 °C and − 20 °C. At each time interval, the percent difference from time 0 for each analyte was calculated and averaged for each storage condition. Results For the majority of medications, the percent differences were within 20% of the original measurement for all 3 storage conditions. All were within 30% of the original measurement after 2, 3 and 6 months in all storage conditions, except for 7-amino-clonazepam, and carboxy-tetrahydrocannabinol. Conclusions The findings from the current study confirm that the majority of medications, metabolites, and illicit substances commonly requested for testing by physicians treating patients with pain and pain-related disorders are stable within 20% of the original concentration when stored refrigerated or frozen for up to 6 months. Thus, delayed testing, repeat testing, and add-on testing of urine specimens can yield reliable results for up to 6 months following the urine collection date.

Background: Physicians treating patients for chronic pain have limited means of determining whether a person is taking their medications as prescribed and are not taking extra medication. Complicating patient treatment regimens is the fact that pain physicians’ prescribing practices may come under scrutiny by the Drug Enforcement Agency and other licensing agencies. If questioned, doctors can be hard-pressed to substantiate that their particular practices meet the established standard of care. It would be helpful to establish that their patients adhere to medications when compared with other practices. Previous studies show that urinary excretion data transformed by mathematical models can produce a reliable range of expected values for pain medications and may be useful to help resolve the aforementioned issues.Purpose of the study: To provide comparative urinary excretion information data on three commonly prescribed opioid medications (morphine, hydrocodone, and oxycodone).Methods: This retrospective study involved quantitative analysis of 300,000 urine specimens for three test drugs using previously described methods. The results were analyzed as percent frequency distributions and logarithmic functions.Results: The authors established a creatinine-normalized range of urinary concentration values for each drug. Results for two practices were compared with the meta-findings, providing quantitative evidence of overall standard of care prescription practice by that physician.Conclusions: Expected urinary drug excretion values for morphine, hydrocodone, and oxycodone can potentially benefit pain physicians by showing that they are within the expected standard of care, helping to establish patient compliance, and identifying patients whose metabolism of these drugs may put them at risk.

Background: Patients on chronic opioid therapy are often closely monitored to identify prescribed or nonprescribed medications and/or illicit substances and to identify medication use that may lead to adverse events. Monitoring is typically performed using a combination of clinical tools and assessment methods that often include patient medication histories, risk assessments, and medication monitoring with urine testing. The chronic pain population may be prescribed an average of three to five medications for pain and associated symptoms. In addition to prescribed therapies, this patient population often takes non-prescribed medications and/or illicit substances. Medication monitoring with Urine Drug Testing (UDT), particularly when performed using mass spectrometry, provides accurate information about medications and illicit substances present in the urine. Purpose of the study: To use LC-MS/MS analyses to describe the variety of medications and metabolites observed in urine specimens from individuals on opioid therapy. Methods: Analytical procedures were developed using LC-MS/MS that could detect and differentiate between various opioids and their metabolites, other medications commonly prescribed for pain, and certain illicit substances. This retrospective analysis used approximately 340,000 de-identified specimens tested between November 2011 and February 2012 at Millennium Laboratories. Data was sorted to determine frequency of detection and concentrations of the excreted drugs and metabolites. Results: The most frequently observed medications were hydrocodone and oxycodone, and their metabolites. The next most frequently observed medication was the benzodiazepine class followed by gabapentin, buprenorphine, and morphine. Additionally, illicit substances were detected in 15% of specimens; the most common illicit substances were cannabinoids and cocaine. Conclusions: Urine drug testing, using LC-MS/MS technology with validated cutoff values for each analyte, provides objective data for providers to use when assessing medication use, potential drug-drug interactions, potential adverse events, and possible diversion. Specific identification of both the medication or substance and the associated metabolites allows for informed interpretation of UDT results. Understanding the medications and illicit substances found in UDT specimens from the pain population helps providers optimize medication monitoring for the best possible plan for pain management.

The clinical chemist desiring to set up appropriate reference intervals must consider race or ethnicity as a possible factor on which to subdivide an interval. The effect of ethnicity on various analyte values has not been systematically studied (1)(2). The advent of National Health and Nutrition Examination Survey (NHANES) data (3) has made it possible to determine the effect of ethnicity on reference interval estimation and whether separate reference intervals should be derived for each ethnic group. The Third National Health and Nutrition Examination Survey (NHANES III) contains data for 33 994 persons ages 2 months and older who participated in the survey. Clinical chemistry measurements were made on several analytes, and health status was determined by a physician. In this report, we will use only individuals with the “Excellent”rating of health status as recommended by the IFCC (4) and NCCLS (5). The issue of whether to use separate reference intervals has been addressed by Harris and Boyd (6). Their recommendation, which is used by the NCCLS (5), is that two groups should be combined into a single group unless their means and/or SDs exceed appropriate predetermined thresholds. By treating the known healthy individuals as a “gold standard”, the effect of the addition of ethnicity on these estimators will be examined. We used a previously described outlier detection scheme (7) to reduce the effect of atypical observations on these estimators. The NHANES population was obtained from NHANES 3x Ver. 1.21 (3). The data are the result of a complex survey design involving stratification and clustering that yielded individual weights for each observation. However, for our purposes in this report, we will treat the individuals as coming from a random sample, i.e., individual weights …

Background Concomitant use of opioids and benzodiazepines can result in significant untoward effects. Point of care (POC) urine testing devices are commonly used tools to monitor patient use of medications. These useful devices are relatively inexpensive and yield immediate results that can be acted upon at the time of the appointment, although numerous limitations have been identified for specific medications or medication classes. We established the diagnostic accuracy of a commonly used POC testing method for benzodiazepines. Methods One thousand patients, from a single interventional pain practice receiving opioid therapy provided urine specimens as part of the usual practice of monitoring consistency with prescribed medications. These de-identified urine specimens were tested using LC-MS/MS and the results were compared using the standard calculations for sensitivity, specificity, and predicted value. Five specimens were excluded from the study because the prescribed flurazepam could not be confirmed by LC-MS/MS (the LC-MS/MS instrumentation was not set to identify flurazepam), resulting in 995 specimens. Results Point of care assays yielded false negative results for patients prescribed benzodiazepines nearly 20% of the time (98 out of 498 patients). The point of care cup often failed to produce positive results for persons who were shown by LC-MS/MS to be taking lorazepam or clonazepam. Although only 26 out of 498 patients (5%) were prescribed ≥ 2 benzodiazepines, 73 out of 498 patients (15%) were found to be positive for that drug class. Conclusions POC immunoassay for benzodiazepines could fail to provide accurate information regarding patient specific medication use. The false positive and false negative rates of the immunoassay were particularly high for clonazepam and lorazepam. Further testing of patient specimens using more accurate methods such as LC-MS/MS is necessary to provide definitive data that can assist in clinical decision making, and potentially protect these patients from untoward effects, morbidity and mortality.

To determine the degree of ethanol absorption and the resultant formation and urinary excretion of its conjugated metabolites following intensive use of high ethanol content mouthwash, 10 subjects gargled with Listerine(®) antiseptic 4 times daily for 3¼ days. First morning void urine specimens were collected on each of the four study days and post-gargle specimens were collected at 2, 4, and 6 h after the final gargle of the study. Urine ethanol, ethyl glucuronide (EtG), ethyl sulfate (EtS), and creatinine were measured. Ethanol was below the positive threshold of 20 mg/dL in all of the urine specimens. EtG was undetectable in all pre-study urine specimens, but two pre-study specimens had detectable EtS (6 and 82 ng/mL; 16 and 83 μg/g creatinine). Only one specimen contained detectable EtG (173 ng/mL; 117 μg/g creatinine). EtS was detected in the urine of seven study subjects, but was not detected in the single specimen that had detectable EtG. The maximum EtS concentrations were 104 ng/mL and 112 μg/g creatinine (in different subjects). Three subjects produced a total of eight (non-baseline) urinary EtS concentrations above 50 ng/mL or 50 μg/g creatinine and three EtS concentrations exceeding 100 ng/mL or 100 μg/g creatinine. In patients being monitored for ethanol use by urinary EtG and EtS concentrations, currently accepted EtG and EtS cutoffs of 500 ng/mL are adequate to distinguish between ethanol consumption and four times daily use of high ethanol content mouthwash.

Background: Clinical laboratories are required to establish reference intervals for all the analytes tested, and these are provided along with the test results. In contrast, laboratories testing for pain medications use cutoffs established by the manufacturers of immunoassay reagents. These cutoffs may be inappropriate for monitoring patients being treated for chronic pain with opioid therapy because the cutoffs are set too high.Purpose of the study: To use quantitative urine drug excretion data determined by liquid chromatography-tandem mass spectrometry analysis to calculate cutoffs needed to best determine patient compliance with prescribed medications.Methods: Two methods of calculation were used to estimate cutoffs. First, all positive results for each drug or drug metabolite were ranked from highest to lowest. The lowest value was one-half of the lower limit of quantitation. A nonparametric 2.5 percent estimator was used to establish each cutoff. Second, positive results were normalized using creatinine values, resulting in the excretion being expressed as nanograms of excreted drug per gram of creatinine. A nonparametric 2.5 percent estimator was used to establish the cutoff.Results: Cutoffs established using these calculations included at least 97.5 percent of the data for the drugs: 7-aminoclonazepam, α-hydroxalprazolam, buprenorphine, carisoprodol, hydrocodone, hydromorphone, meperidine, meprobamate, methadone, morphine, oxycodone, oxymorphone, propoxyphene, and tramadol gave cutoffs near the lower limit of quantitation. One exception was with the drug codeine, where the lower limit could not be identified.Conclusions: These cutoffs were significantly lower than those suggested by many immunoassay manufacturers and better identify patient compliance in a representative population of pain patients. The limitation of the study is that only values one-half of our lowest calibrator were used. By using population values, laboratories can establish appropriate cutoffs for best monitoring pain patient medication compliance.

Background: A major concern of physicians treating pain patients with chronic opioid therapy and similar drugs is determining whether the patients are also using illicit drugs. This is commonly determined by urine drug testing (UDT). However, there are few studies on whether or not monitoring patients by this technique decreases illicit drug use. Objective: To determine if the presence of illicit drugs decreases over a number of physician visits where UDT was performed. Method: The method involved a retrospective study of tests for the illicit drugs marijuana, cocaine, methamphetamine, ecstacy (MDMA) phencyclidine (PCP) and the heroin metabolite, 6-acetylmorphine as confirmed by Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS). A database of 150,000 patient visits was examined for the presence of any of these 6 drugs. Results: A total of 87,000 patients were initially tested. The number of patients who were repeatedly tested decreased over time. The percentage of patients positive for any of these illicit drugs decreased from 23% to 9% after 14 visits where UDT was performed. When graphed there was a trend to decreasing use. The Spearman correlation = -0.88, P < 0.0001. The major illicit drug was marijuana. When this was removed from the analysis, there was an even greater correlation with decreased illicit drug use. Spearman correlation = -0.92 (P < 0.0001) using a weighted correlation. Limitation: Patients continuing to use illicit drugs might be dismissed from practices thus biasing the study towards illicit drug avoidance. Conclusion: Continued UDT might decrease illicit drug use among pain patients. Key words: Pain patients, UDT, urine drug testing, LC-MS/MS, illicit drugs, decrease drug use

To assess the degree of ethanol absorption and subsequent formation of urinary ethyl glucuronide (EtG) and ethyl sulfate (EtS) following sustained application of hand sanitizer, 11 volunteers cleansed their hands with Purell(™) hand sanitizer (62% ethanol) every 5 min for 10 h on three consecutive days. Urine specimens were obtained at the beginning and end of each day of the study, and on the morning of the fourth day. Urinary creatinine, ethanol, EtG, and EtS concentrations were measured. EtG was undetectable in all pre-study urine specimens, but two pre-study specimens had detectable EtS (73 and 37 ng/mL). None of the pre-study specimens had detectable ethanol. The maximum EtG and EtS concentrations over the course of the study were 2001 and 84 ng/mL, respectively, and nearly all EtG- and EtS-positive urine specimens were collected at the conclusion of the individual study days. Only two specimens had detectable EtG at the beginning of any study day (96 and 139 ng/mL), and only one specimen had detectable EtS at the beginning of a study day (64 ng/mL), in addition to the two with detectable EtS prior to the study. Creatinine-adjusted maximum EtG and EtS concentrations were 1998 and 94 μg/g creatinine, respectively. In patients being monitored for ethanol use by urinary EtG concentrations, currently accepted EtG cutoffs do not distinguish between ethanol consumption and incidental exposures, particularly when urine specimens are obtained shortly after sustained use of ethanolcontaining hand sanitizer. Our data suggest that EtS may be an important complementary biomarker in distinguishing ethanol consumption from dermal exposure.

Accurate and early diagnosis of the cause of renal transplant dysfunction is important in successful patient management. Controversy exists as to whether a cyclosporine-specific or -nonspecific method is more predictive of clinical events. In an attempt to answer this question, all episodes of acute renal dysfunction were reviewed in 322 stable renal transplant recipients over a 20-month period. To diagnose the cause of each episode of renal dysfunction, an analysis was made of patient demographics; weight; serum creatinine; cyclosporine dose; cyclosporine level, using a specific method--high-performance liquid chromatography (HPLC)--and a nonspecific method--fluorescent polarization immunoassay (FPIA); changes in cyclosporine dose; renal biopsy; and response to any therapeutic intervention. There were 138 patients, who developed 279 episodes of renal dysfunction. Causes of renal dysfunction were cyclosporine-related (n = 103), acute rejection (n = 63), extracellular fluid volume depletion (n = 27), other (n = 59), and unknown (n = 27). The mean HPLC cyclosporine level was significantly different in patients with acute cyclosporine toxicity (p < 0.001) and patients with acute rejection (p < 0.001) when compared to those with stable renal function; the mean FPIA cyclosporine levels were not significantly different between the three groups. However, a larger percentage of patients with rejection were subtherapeutic when measured by HPLC, while a higher proportion of patients with nephrotoxicity were above the therapeutic range measured by FPIA.(ABSTRACT TRUNCATED AT 250 WORDS)

In this enzyme assay for kinetic measurement of alkaline phosphatase (EC 3.1.3.1) activity in human serum by flow injection analysis with electrochemical detection (FIA-EC), the substrate phenyl phosphate is enzymatically hydrolyzed and the phenol produced is quantified by FIA-EC. The standard curve is linear over the range 40 to 500 U/l, and the predicted linearity is up to 1000 U/l. The CV is 5% over the range of the assay. Correlation with the Sclavo Diagnostics nitrophenyl phosphate spectrophotometric technique gave an r of 0.98. This new technique requires as little as 1 μl of serum. The FIA-EC method is not subject to interference by hemolysis, icteria, or lipemia or by electroactive substances such as urate, ascorbate, or acetaminophen. Sensitive measurements free from spectrophotometric interferences are thus possible.