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Psychiatric and non-psychiatric drugs causing false positive amphetamines urine test in psychiatric patients: a pharmacovigilance analysis using FAERS
Abstract
Introduction
Immunoassay urine drug screen (UDS) is frequently used in clinical practice for initial screening process, being generally available, fast, and inexpensive. Exposure to widely prescribed drugs might determine false positive UDS amphetamines, leading to diagnostic issues, wrong therapeutic choices, impairment of physician-patient relationship and legal implications.
Areas covered
To summarize and comment on a comprehensive list of compounds responsible for UDS false positive for amphetamines, we conducted a literature review on PubMed along with a comparison with Real World Data from the Food and Drug Administration Adverse Event Reporting System (FAERS) database analysis between 2010 and 2022. Forty-four articles and 125 Individual Case Safety Reports (ICSR) involving false positive amphetamine UDS in psychiatric patients were retrieved in FAERS.
Expert opinion
False positive results were described in literature for antidepressants, atomoxetine and methylphenidate, antipsychotics, but also for non-psychiatric drugs of common use, like labetalol, fenofibrate and metformin. Immunoassays method is usually responsible for false positive results and in most cases mass spectrometry (MS) do not eventually confirm the UDS positivity. Physicians should be aware of immunoassays’ limitations and when turning to a confirmatory test. Any new cross-reaction should be reported to pharmacovigilance activities.
... Thus, identifying and managing the most critical side effects encourages patients to take medications regularly and adhere to the course of treatment. This situation increases treatment compliance and may positively affect treatment outcomes [10]. Therefore, priority should be given to the more important ones, among these side effects. ...
... Stomach Ailments (STLM) [2] Respiratory Ailments (RRLM) [4] Psychological side effects (PYDD) [7] ENT side effects (ENTD) [10] Physical Ailments (PYLM) [58] Movement and Support Disorders (MVSD) [12] the analysis results. The total relation matrix and weighting priorities are denoted in Table 10. ...
Identifying and managing the most critical side effects encourages patients to take medications regularly and adhere to the course of treatment. Therefore, priority should be given to the more important ones, among these side effects. However, the number of studies that make a priority examination is limited. There is a need for a new study that determines which of these effects are more priority to increase the quality of the treatment. Accordingly, this study aims to define the most important side effects of antidepressant drugs with a novel model. Quantum Spherical fuzzy M-SWARA technique is considered to compute the importance weights of the items. The main contribution of this study is that the most critical side effects can be understood for antidepressant drugs by establishing a novel decision-making model. The findings demonstrate that psychological side effects are defined as the most critical side effects of antidepressant drugs. Furthermore, physical side effects also play a key role in this condition. Side effects in antidepressant treatment have a great impact on the effectiveness of treatment and patient compliance.
... Stomach Ailments (STLM) [2] Respiratory Ailments (RRLM) [4] Psychological side effects (PYDD) [7] ENT side effects (ENTD) [10] Physical Ailments (PYLM) [58] Movement and Support Disorders (MVSD) [12] the analysis results. The total relation matrix and weighting priorities are denoted in Table 10. ...
BACKGROUND
This study aims to define the most important side effects of antidepressant drugs. Within this framework, a comprehensive literature review has been carried out and six different side effects of these drug types are selected. In the following step, a novel model is suggested to define which side effects are more critical. In this model, the Quantum Spherical fuzzy M-SWARA technique is considered to compute the importance weights of the items. Moreover, a comparative analysis is also performed with the Quantum Spherical fuzzy DEMATEL method to measure the consistency of the results obtained. The main contribution of this study is that priority analysis is made to determine the most important side effects of antidepressant drugs so that it can be possible to optimize the treatment plan. Similarly, the main methodological novelty of this study is the generation of a new decision-making technique named M-SWARA to identify the causal directions of the side effects. It is determined that the analysis results are similar in both techniques that explains the consistency of the results. The findings demonstrate that psychological side effects are defined as the most critical side effect of antidepressant drugs. Furthermore, physical side effects also play a key role in this condition. Side effects in antidepressant treatment have a great impact on the effectiveness of treatment and patient compliance. The treatment is started by choosing among the drugs that are thought to be effective in the decision-making phase of the treatment by the physician. Due to the individual situation and adverse effects, it is possible to change the medication during the treatment period. Therefore, it is vital to know the side effects of these drugs correctly and to apply the treatment process accordingly. This situation causes a significant deterioration in the quality of life of patients.
OBJECTIVE
In this study, it is aimed to determine the most important side effects of antidepressant drugs. In this context, a comprehensive literature review has been carried out and basically 6 different side effects of these drug types are determined. After that, a novel model is suggested to determine which side effects are more important. In this model, the Quantum Spherical fuzzy M-SWARA technique is taken into consideration to calculate the importance weights of the criteria. On the other hand, a comparative analysis is carried out with the Quantum Spherical fuzzy DEMATEL method to test the consistency of the results obtained. The main contributions of this study are demonstrated as follows. (i) One of the most important features of the study is the priority analysis to determine the most important side effects of antidepressant drugs. Detecting critical side effects of psychiatric drugs allows optimizing the treatment plan. Each patient has a different side effect tolerance and risk profile. Detection of side effects helps physicians select medications and adjust dosages based on patients' individual characteristics, medical history, and sensitivity to side effects (Arbelo et al., 2021). Thus, it is ensured that patients have the most appropriate treatment plan and achieve the best results by minimizing side effects. (ii) The main methodological novelty of this study is the generation of a new decision-making technique named M-SWARA. Although classical SWARA approach provides many benefits, the causal relationship between the items cannot be considered (Dinçer et al., 2022). However, the side effects of psychiatric drugs may have a strong influence on each other. Owing to this situation, some improvements are made to the classical SWARA technique and M-SWARA methodology is proposed. This newly developed technique helps to consider the cause-and-effect relationship between the criteria (Xu et al., 2023). (iii) The use of the DEMATEL technique in the evaluation of the criteria provides some advantages. The side effects of psychiatric drugs can be effective on each other. For example, stomach side effects can have an effect on physical side effects. Many different decision-making techniques are used in literature. The most important advantage of the DEMATEL method over the others is that it also examines the cause-effect relationship between the criteria (Govindan et al., 2022; Chai et al., 2022). Therefore, it is seen that the DEMATEL technique is the most optimal method in the analysis to be made to determine the most significant side effect. (iv) In the model developed in this study, integrating Quantum theory and Spherical fuzzy numbers also provides some advantages. Quantum theory allows different possibilities to be considered (Kayacık et al., 2022). On the other hand, Spherical fuzzy numbers also help to work with a larger data set (Kou et al., 2023). This contributes to minimizing the uncertainty in the process and achieving more accurate results (Ai et al., 2023). (v) In this study, two different methods are taken into consideration for weighting the criteria. Thus, it becomes possible to make a comparative analysis. This helps to test the accuracy, consistency and reliability of the results obtained. In this way, more effective strategies can be developed.
METHODS
A novel model is suggested to find the most critical side effects of antidepressant drugs. For this purpose, both Quantum Spherical fuzzy M-SWARA and DEMATEL methods are taken into consideration. In this section, these models are explained.
RESULTS
In this study, it is aimed to define the most essential side effects of antidepressant drugs. For this purpose, a detailed literature review has been carried out and 6 different side effects of these drug types are identified. In the next process, a novel model is suggested to determine which side effects are more important. In this model, the Quantum Spherical fuzzy M-SWARA technique is taken into consideration to calculate the significance weights of the criteria. Additionally, a comparative analysis is carried out with the Quantum Spherical fuzzy DEMATEL method to test the reliability of the results. It is concluded that psychological side effects are defined as the most critical side effect of antidepressant drugs. Similarly, physical ailments also play a key role in this situation. On the other hand, stomach ailments and ENT disorders are on the last ranks. Similarly, the core symptoms of psychiatric disorders are psychological and physical, which are an important part of them. For this reason, this modeling may provide some solution to the dilemma of whether these are the symptoms of psychiatric disorders or the side effects of antidepressant drugs, which are perhaps the most difficult things for physicians in the drug treatment process.
CONCLUSIONS
One of the most important contributions of the study is making priority analysis to determine the most important side effects of antidepressant drugs. Detection of side effects helps physicians select medications and adjust dosages based on patients' individual characteristics, medical history, and sensitivity to side effects. This situation helps patients have the most appropriate treatment plan and achieve the best results by minimizing side effects. Side effect studies are generally performed in single drug use and homogeneous patient groups. In the study, the patients in the sample group whose side effect reports were collected include a sample group suitable for real-life use, who also use drugs other than antidepressants due to different types of diseases. In this respect, it stands out differently from similar studies that include a single drug and a homogeneous sample population.
Zusammenfassung: Fragestellung: Die Aufmerksamkeitsdefizit-/Hyperaktivitätsstörung (ADHS) und der Konsum psychoaktiver Substanzen treten bei Jugendlichen häufig gemeinsam auf. In den verfügbaren Leitlinien wird die Gruppe von Kindern und Jugendlichen mit ADHS und komorbider SUD nur wenig berücksichtigt. Methodik: Die Gemeinsame Suchtkommission der deutschen kinder- und jugendpsychiatrischen Fachgesellschaft und Verbände hat eine Stellungnahme mit konkreten Behandlungsempfehlungen erarbeitet. Sie soll Orientierung im Sinne eines Best Practice-Vorgehens geben. Ergebnisse: Eine frühe Behandlung mit Stimulanzien bei Jugendlichen mit ADHS und SUD kann das Risiko für die spätere Entwicklung einer SUD verringern. Trotz ihrer nachweislichen Wirksamkeit muss ein mögliches Missbrauchspotenzial der Stimulanzien berücksichtigt werden. Um das Missbrauchspotenzial zu minimieren, werden lang wirkende bzw. retardierte Zubereitungsformen von Stimulanzien und Nicht-Stimulanzien empfohlen. Es ist wichtig, die spezifische SUD und deren Behandlung bei der Verschreibung von Stimulanzien zu berücksichtigen. Schlussfolgerungen: Trotz Bedenken wird der Einsatz von Stimulanzien bei Patienten mit komorbider ADHS und SUD grundsätzlich empfohlen, auch wenn in jedem Einzelfall eine sorgfältige Abwägung notwendig ist, da die Vorteile einer frühzeitigen gleichzeitigen Behandlung überwiegen. Zudem sind eine sorgfältige Überwachung und therapeutisches Monitoring unerlässlich.
Methamphetamine Toxicities and Clinical ManagementMethamphetamine increases the release and blocks the uptake of norepinephrine, serotonin, and dopamine. This article reviews the morbidity and mortality associated with methamphetamine use and discusses prevention and treatment strategies.
People crave autonomy in healthcare and will often reach for the pharmacy aisle before calling a doctor. Patients may be putting themselves at risk for toxicity and drug interactions with the expanding use of herbal medications, OTCs, and dietary supplements. Clinicians need to be aware of potential drug interactions between prescribed and nonprescribed substances. It is important to take a thorough medication history that includes dietary habits, OTCs, supplements, and herbal remedies to predict and prevent potential interactions.
Psychiatric
disorders with substance abuse are considered the leading causes of most violent and aggressive behaviors in the general population. This study was aimed to assess the impact of substance abuse and the therapeutic approaches adopted by psychiatrists in aggressive vs non-aggressive outpatients (n = 400) attending community-based psychiatric services and recruited over a 3-year period. Clinical and therapeutic variables were collected from medical records and the Modified Overt Aggression Scale (MOAS) was used to assess any aggressive/violent behavior. Violent behaviors were significantly higher in alcohol and substance abusers compared to non-abusers (p < 0.01), except for heroin abusers. Mean weighted MOAS score was significantly higher in patients taking antipsychotics (p < 0.005). The administration of Haloperidol, Zuclopenthixol, and Clozapine was more frequent in aggressive than in non-aggressive patients. The most frequently administered drug in these patients was Haloperidol (23.91%), with a higher mean daily dosage in violent vs non-violent patients. Our results confirm the well-established relationship between substance abuse and violent behaviors in psychiatric inpatients also within outpatient community services. Observed rates of most frequently prescribed antipsychotics to aggressive patients did not show any preference for newer generation compounds, with clinicians operating in the community setting likely being in need for further evidence and specific training to support their treatment choice.
Introduction and objective: Assessing the abuse potential of new substances with central nervous system activity is essential for preventing possible risks of misuse and addiction. The same methodology is recommended for the evaluation of the abuse potential of recreational drugs. This systematic review aims to assess the pharmacological effects related to the abuse potential and pharmacokinetics of cathinones, which are evaluated in both experimental and prospective observational studies in humans. Materials and Methods: A systematic search of the published literature was conducted to retrieve studies that had administered cathinone, mephedrone, methylone, and diethylpropion to evaluate their acute pharmacological effects related to abuse potential. Results: The search yielded 583 results, 18 of which were included to assess the abuse potential of cathinone (n = 5), mephedrone (n = 7), methylone (n = 1), and diethylpropion (n = 5). All four substances induce stimulant and euphorigenic effects that resemble those of amphetamines and MDMA, and their different intensities may be associated with varying levels of abuse potential. Conclusions: Cathinone, mephedrone, methylone, and diethylpropion induce a range of desirable and reinforcing effects that may, to some extent, result in abuse potential. Further investigation is needed to minimize and prevent their impact on society and public health.
Advanced heart failure patients commonly suffer from ventricular arrhythmias which can be managed by antiarrhythmic drugs like mexiletine. These ventricular arrhythmias can be complicated by illicit drug use which alter outcomes and can potentially impact the patient-physician relationship through countertransference. However, mexiletine can lead to false positive urine drug screen testing for amphetamine, and these false-positive urine drug screen test results can affect the decision-making process. Health care providers should be aware of this fact and should either use confirmatory testing or look for confounding compounds in patients who deny using illicit substances and have a positive urine drug screen. Our patient is 64 years old who arrived at the emergency department after experiencing a shock by his intracardiac defibrillator. The patient tested positive for amphetamine on his urine drug screen and was later ruled out by confirmatory quantitative testing.
Background
Hyponatraemia associated with antipsychotic drugs is a rare but potentially life-threatening adverse drug reaction (ADR); the underlying pharmacological mechanism has not been explained yet.
Methods
We investigated the relationship between pharmacological targets of antipsychotic drugs and the occurrence of hyponatraemia by conducting a nested case-control study using the Food and Drug Administration Adverse Event Reporting System (FAERS) database. Multiple logistic regression was used to determine the associations between antipsychotics receptor occupancy and hyponatraemia. We also performed a systematic review of clinical studies on this association.
Results
Of 139,816 reports involving at least one antipsychotic, 1.1% reported hyponatraemia. Olanzapine was the most frequently suspected drug (27%). A significant positive association was found between dopamine D3, D4 and hyponatraemia, while adrenergic α1, serotonin 5-HT1A, and 5-HT2A receptor occupancies were negatively associated. A multivariable stepwise regression model showed that dopamine D3 (Adj. Odds Ratio=1.21; 95% CI=1.09–1.34; p<0.05) predicted the risk for hyponatraemia (p<0.05), while serotonin 5-HT2A occupancy (Adj. OR=0.78; 95% CI=0.68–0.90; p<0.01) exhibited a protective effect against hyponatraemia. Among the eleven studies included in the systematic review, incidence rates of hyponatraemia diverged between 0.003 % and 86%, whereas the odds of developing hyponatraemia from effect studies ranged between 0.83 to 3.47.
Conclusions
Antipsychotic drugs having a combined modest occupancy for D3 and 5-HT2A receptors and higher levels of D3 receptor occupancy, correspond to different degrees of risk for hyponatraemia. Based on the few, relatively large-scale available studies, atypical antipsychotics have a more attenuated risk profile for hyponatraemia.
The published experience with biologics in childbearing age with autoimmune and inflammatory diseases mainly deals with the use of TNFα inhibitors (TNFα-i). Limited data are available for biologics targeting other cytokines or immunocompetent cells, especially for the inflammasome targeted therapy including IL-1 inhibitors and colchicine. We conducted a nested case-control study by using the US Food and Drug Administration Adverse Event Reporting System database aimed at quantifying the association between the use of IL-1 inhibitors/colchicine in pregnant women and the occurrence of maternal/fetal adverse effects. The reporting odds ratio was used as a measure of disproportional reporting. From the total cohort (40,033 pregnant women), we retrieved 7,620 reports related to neonatal AEs, 2,889 to fetal disorders, 8,364 to abortion, 8,787 to congenital disorders, and 7,937 to labor/delivery complications. Inflammasome-targeted drugs did not present any disproportionate reporting for all these clusters of AEs. TNFα-i confirmed their safety during pregnancy with aROR < 1 for all clusters of AEs except for labor complications. Finally, we performed a systematic review of the current literature. Data from the eligible studies (12 observational studies and 6 case reports; yielding a total of 2,075 patients) were reassuring. We found no major safety issues on malformations risk of inflammasome targeted therapies in pregnancy. However, due to limited data, the routine use of these agents should be considered in pregnancy only if risk benefit assessment justifies the potential risk to the fetus.
False-positive urine drug screens can occur and lead to implicit bias. Confirmatory testing with gas chromatography/mass spectrometry can be performed. A morbidly obese patient with newly diagnosed atrial fibrillation spent multiple days in the cardiac intensive care unit (ICU) due to a false-positive test for methamphetamine. The patient was planned to undergo direct cardioversion with conscious-sedation anesthesia. His care was delayed because anesthesia was not comfortable administering sedatives in the setting of a positive urine drug screen for presumed methamphetamine use. Knowing that esmolol can cause a false positive on urine drug screen is imperative for delivering the best patient-centered care.
Urine drug testing is one of the objective tools available to assess adherence. To monitor adherence, quantitative urinary results can assist in differentiating “new” drug use from “previous” (historical) drug use. “Spikes” in urinary concentration can assist in identifying patterns of drug use. Coupled chromatographic-mass spectrometric methods are capable of identifying very small amounts of analyte and can make clinical interpretation rather challenging, specifically for drugs that have a longer half-life. Polypharmacy is common in treatment and rehabilitation programs because of co-morbidities. Medications prescribed for comorbidities can cause drug-drug interaction and phenoconversion of genotypic extensive metabolizers into phenotypic poor metabolizers of the treatment drug. This can have significant impact on both pharmacokinetic (PK) and pharmacodynamic properties of the treatment drug. Therapeutic drug monitoring (TDM) coupled with PKs can assist in interpreting the effects of phenoconversion. TDM-PKs reflects the cumulative effects of pathophysiological changes in the patient as well as drug-drug interactions and should be considered for treatment medications/drugs used to manage pain and treat substance abuse. Since only a few enzyme immunoassays for TDM are available, this is a unique opportunity for clinical laboratory scientists to develop TDM-PK protocols that can have a significant impact on patient care and personalized medicine. Interpretation of drug screening results should be done with caution while considering pharmacological properties and the presence or absence of the parent drug and its metabolites. The objective of this manuscript is to review and address the variables that influence interpretation of different drugs analyzed from a rehabilitation and treatment programs perspective.
Background:
Exposure to drugs of abuse is frequently assessed using urine drug screening (UDS) immunoassays. Although fast and relatively inexpensive, UDS assays often cross-react with unrelated compounds, which can lead to false-positive results and impair patient care. The current process of identifying cross-reactivity relies largely on case reports, making it sporadic and inefficient, and rendering knowledge of cross-reactivity incomplete. Here, we present a systematic approach to discover cross-reactive substances using data from electronic health records (EHRs).
Methods:
Using our institution's EHR data, we assembled a data set of 698651 UDS results across 10 assays and linked each UDS result to the corresponding individual's previous medication exposures. We hypothesized that exposure to a cross-reactive ingredient would increase the odds of a false-positive screen. For 2201 assay- ingredient pairs, we quantified potential cross-reactivity as an odds ratio from logistic regression. We then evaluated cross-reactivity experimentally by spiking the ingredient or its metabolite into drug-free urine and testing the spiked samples on each assay.
Results:
Our approach recovered multiple known cross-reactivities. After accounting for concurrent exposures to multiple ingredients, we selected 18 compounds (13 parent drugs and 5 metabolites) to evaluate experimentally. We validated 12 of 13 tested assay-ingredient pairs expected to show cross-reactivity by our analysis, discovering previously unknown cross-reactivities affecting assays for amphetamines, buprenorphine, cannabinoids, and methadone.
Conclusions:
Our findings can help laboratorians and providers interpret presumptive positive UDS results. Our data-driven approach can serve as a model for high-throughput discovery of substances that interfere with laboratory tests.
There has been only a few reports regarding aripiprazole causing false positive urine amphetamine drug screens, exclusively on children accidently ingesting aripiprazole. Herein, we present the first reported case of a 40 year old woman affected by Bipolar I Disorder, treated with aripirazole at therapeutic oral dose ranging from 15 mg/day to 30 mg/day, in the context of a depressive episode with mixed and psychotic features, showing a false positive urine amphetamine drug screen. We document the relationship between aripiprazole-dose, plasma concentration and amphetamines values in toxicologic urine examinations over time. Awareness of potential false positive urine amphetamine drug screens during aripiprazole treatment can condition therapeutic choices and prevent legal implications.
Introduction: ADHD is characterized by a developmentally inappropriate level of inattentiveness, impulsivity and/or hyperactivity. In adults, the disorder is frequently accompanied by Emotional Dysregulation (ED), associated to a variety of related psychiatric comorbidities, complicating its recognition and treatment management.
Areas covered: This paper reviews randomized active comparator-controlled or placebo-controlled trials evaluating the use of pharmacotherapy in adults with ADHD and ED, other neurodevelopmental disorders, Bipolar Disorder (BD) and Anxiety Disorders (ADs). When controlled data are unavailable, the authors have included open-label and observational studies.
Expert opinion: ED in adult patients with ADHD is a very common and impairing problem that can be treated with stimulants or atomoxetine. ADHD studies in adults with other neurodevelopment disorders are scarce; stimulants seem to be the most effective and safe drugs in treating ADHD symptoms, without worsening the core features of other neurodevelopmental disorders. In patients with ADHD and comorbid BD, the treatment of BD alone may result in residual symptoms of ADHD. Patients should be treated hierarchically: BD should be treated first, while ADHD should be treated combining ADHD medications and mood stabilizers after mood stabilization. The available evidence for treating patients with ADHD and comorbid ADs in adults supports the idea of an anti-anxiety/ADHD-specific treatment association.
Objective
Psychiatric disorders are often considered the leading cause of violence. This may be due to a stereotype created by media and general opinion.
Method
The Modified Overt Aggression Scale (MOAS) was used to evaluate the severity of aggressive and violent behaviors in 400 patients who attended a post-acute psychiatric service in Milan from 2014 to 2016 and suffered from different psychiatric disorders. The psychopathological clinical picture was evaluated by Clinical Global Impression (CGI). The study also assessed the possible correlation between epidemiologic and sociodemographic factors, clinical variables, and aggression and violence.
Results
Of the total number of subjects, 21.50% showed a MOAS score >0, 11.50% presented mild aggression (0–10 MOAS weighted score), 9% moderate aggression (11–20), and 1% severe aggression (MOAS >20). With respect to violent behaviors, 16% of patients showed a score >0 in one MOAS subscale other than verbal aggression according to violence definition. The severity of clinical picture seemed to be related to higher weighted MOAS score. Multivariate testing of different sociodemographic and clinical variables showed that violence was related to unemployment status, and significantly correlated to compulsory admission (TSO), suicide attempts (TS), and personality disorders, while the severity of clinical psychiatric picture seemed to play a secondary role.
Conclusion
Results have shown that personality disorders and sociodemographic factors, including economic factors, seem to be major determinants of violence among patients diagnosed with mental disorders.
Case–non-case studies are among the methods used to assess drug safety by analyzing the disproportionality of adverse drug reaction reports in pharmacovigilance databases. First used in the 1980s, the last few decades have seen a significant increase in the use of this study design. The principle of case–non-case studies is to compare the drug exposure of cases of an adverse reaction of interest with that of cases with other reported reactions and called “non-cases”. Their results are presented in the form of reporting odds ratio (ROR), the interpretation of which makes it possible to highlight pharmacovigilance signals. This article describes the principle of case–non-case studies, the calculation method of the ROR and its confidence interval, the different analytical modalities and how to interpret its results with regard to the advantages and limitations of this type of study. © 2019 Société française de pharmacologie et de thérapeutique
Adult attention deficit/hyperactivity disorder (ADHD) has moved from the blurred edge of clinical focus to clear recognition as a prevalent and significant disorder in its own right. It is a relatively common comorbidity which if identified and treated may open the door to better outcomes for hard-to-treat patients. Conversely, failure to identify and treat adult ADHD is linked to negative outcomes. The recognition of the importance of adult ADHD in a subset of our patients challenges us to overcome our anxiety about this diagnosis and prevent the societal marginalization of vulnerable patients. Adult ADHD responds well to integrated pharmacological and psychotherapeutic intervention. Its treatment responsiveness reduces disability and allows the comorbidity which is typically present to be addressed. Mastering this challenge can make the diagnosis and treatment of adult ADHD a rewarding experience.
Introduction:
Proper psychiatric evaluation of patients necessitates that the clinician be vigilant in ruling out secondary causes of symptoms, such as substance-induced symptoms. Immunoassay-type urine drug screens (UDSs) offer clinicians rapid drug screen results, ease of use, and inexpensive cost. Unfortunately, these screens are not without their limitations. This review aims to outline the nuances and limitations of immunoassay UDSs and to provide the clinician with information that facilitates more accurate interpretation of UDS results. Specifically, false positive results associated with psychiatric medications and the availability and methods for acquisition of commercialized UDS masking agents will be reviewed.
Methods:
A literature review was conducted to identify false positive UDSs associated with psychiatric medications. References for each article identified were also reviewed. Additionally, a Google® search was conducted to identify commercially available preparations used to mask UDS results and the methods of acquisition of these products.
Results:
A total of 14 articles were identified using PubMed. No articles for mood stabilizing agents were identified. Entering the phrase how to pass a drug test into Google® search yielded about 12.6 million results, and select references were reviewed based on relevance and user reviews.
Discussion:
Several psychiatric medications are documented as potential sources of false positive UDSs. Additionally, several agents are available for consumer purchase that may result in false negative UDSs. The clinician must be vigilant in interpreting immunoassay UDS results and should utilize more advanced forms of testing as clinically appropriate.
Some amphetamine (AMP) and ecstacy (MDMA) urine immunoassay (IA) kits are prone to false-positive results due to poor specificity of the antibody. We employed two techniques, high-resolution mass spectrometry (HRMS) and an in silico structure search, to identify compounds likely to cause false-positive results. Hundred false-positive IA specimens for AMP and/or MDMA were analyzed by an Agilent 6230 time-of-flight (TOF) mass spectrometer. Separately, SciFinder (Chemical Abstracts) was used as an in silico structure search to generate a library of compounds that are known to cross-react with AMP/MDMA IAs. Chemical formulas and exact masses of 145 structures were then compared against masses identified by TOF. Compounds known to have cross-reactivity with the IAs were identified in the structure-based search. The chemical formulas and exact masses of 145 structures (of 20 chemical formulas) were compared against masses identified by TOF. Urine analysis by HRMS correlates accurate mass with chemical formulae, but provides little information regarding compound structure. Structural data of targeted antigens can be utilized to correlate HRMS-derived chemical formulas with structural analogs.
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Legitimate use of legal intranasal decongestants containing l-methamphetamine may complicate interpretation of urine drug tests positive for amphetamines. Our study hypotheses were that
commonly used immunoassays would produce no false-positive results and a recently developed enantiomer-specific gas chromatography–mass
spectrometry (GC–MS) procedure would find no d-amphetamine or d-methamphetamine in urine following controlled Vicks VapoInhaler administration at manufacturer's recommended doses. To evaluate
these hypotheses, 22 healthy adults were each administered one dose (two inhalations in each nostril) of a Vicks VapoInhaler
every 2 h for 10 h on Day 1 (six doses), followed by a single dose on Day 2. Every urine specimen was collected as an individual
void for 32 h after the first dose and assayed for d- and l-amphetamines specific isomers with a GC–MS method with >99% purity of R-(−)-α-methoxy-α-(trifluoromethyl)phenylacetyl derivatives and 10 µg/L lower limits of quantification. No d-methamphetamine or d-amphetamine was detected in any urine specimen by GC–MS. The median l-methamphetamine maximum concentration was 62.8 µg/L (range: 11.0–1,440). Only two subjects had detectable l-amphetamine, with maximum concentrations coinciding with l-methamphetamine peak levels, and always ≤4% of the parent's maximum. Three commercial immunoassays for amphetamines EMIT® II Plus, KIMS® II and DRI® had sensitivities, specificities and efficiencies of 100, 97.8, 97.8; 100, 99.6, 99.6 and 100, 100, 100%, respectively. The
immunoassays had high efficiencies, but our first hypothesis was not affirmed. The EMIT® II Plus assay produced 2.2% false-positive results, requiring an enantiomer-specific confirmation.
Urine drug screen (UDS) immunoassays are a quick and inexpensive method for determining the presence of drugs of abuse. Many
cross-reactivities exist with other analytes, potentially causing a false-positive result in an initial drug screen. Knowledge
of these potential interferents is important in determining a course of action for patient care. We present an inclusive review
of analytes causing false-positive interferences with drugs-of-abuse UDS immunoassays, which covers the literature from the
year 2000 to present. English language articles were searched via the SciFinder platform with the strings ‘false positive
[drug] urine’ yielding 173 articles. These articles were then carefully analyzed and condensed to 62 that included data on
causes of false-positive results. The discussion is separated into six sections by drug class with a corresponding table of
cross-reacting compounds for quick reference. False-positive results were described for amphetamines, opiates, benzodiazepines,
cannabinoids, tricyclic antidepressants, phencyclidine, lysergic acid diethylamide and barbiturates. These false-positive
results support the generally accepted practice that immunoassay positive results are considered presumptive until confirmed
by a second independent chemical technique.
A series of patients whose urine screened positive for 3,4-methylenedioxymethamphetamine (MDMA) using a commercial enzyme immunoassay test (Ecstasy EMIT II assay), failed to confirm by substance-specific liquid chromatography-tandem mass spectrometry tests for MDMA. Further evaluation of these urine specimens indicates that they were positive for trazodone and its metabolite meta-chlorophenylpiperazine (m-CPP). Independent tests of standards showed significant cross-reactivity on the Ecstasy EMIT II assay with trazodone, m-CPP, and the related recreational drug trifluoromethylphenylpiperazine (TFMPP). This is of further forensic significance because m-CPP is emerging as an illicit recreational drug in its own right or as an adulterant in illicit cocaine and MDMA. The hallucinogen benzylpiperazine was also assessed but found not to cross-react significantly with this assay. Patients taking trazodone may get false-positive results on the urine EMIT test for MDMA.
Background:
Previous reports describe false-positive urine immunoassay screens for phencyclidine (PCP) associated with use of tramadol, dextromethorphan, or diphenhydramine. The likelihood of these false positives is unknown.
Objective:
We sought to find the relative frequency of false-positive PCP screens associated with these medications and to look for any other medications with similar associations.
Methods:
In an IRB-approved study, we retrospectively reviewed charts of all ED encounters with positive urine screens for PCP in our hospital from 2007 through 2011, inclusive. Urine samples were tested for drugs of abuse using the Siemens Syva EMIT II Immunoassay. Our laboratory routinely confirmed all positive screens using GC-MS with results classified as either "confirmed" (true positive) or "failed to confirm" (false positive). We recorded all medications mentioned in the chart as current medications or medications given before the urine sample. We used Fisher's exact test to compare frequencies of tramadol, dextromethorphan, diphenhydramine, and other medications between the two groups.
Results:
Tramadol, dextromethorphan, alprazolam, clonazepam, and carvedilol were significantly more frequent among the false-positive group, but the latter three were also associated with polysubstance abuse. Diphenhydramine was more frequently recorded among the false-positive group, but this was not statistically significant.
Conclusion:
False-positive urine screens for PCP are associated with tramadol and dextromethorphan and may also occur with diphenhydramine. Positive PCP screens associated with alprazolam, clonazepam, and carvedilol were also associated with polysubstance abuse.
The aim of this paper is to report the first case of atomoxetine leading to false-positive urine drug screen. An otherwise healthy 27-year-old female with a history of attention deficit hyperactivity disorder (ADHD) treated with atomoxetine had an acute onset tonic-clonic seizure. On arrival to the hospital, a urine toxicological drug screen with immunochemical cloned enzyme donor immunoassay (CEDIA) was performed. Results were positive for amphetamines; however, the presence of these substances could not be confirmed with urine gas chromatography-mass spectrometry (GC-MS). She denied any illicit drug use, herbal medications, or supplements, and her other prescription medications have not been previously known to cause a false-positive result for amphetamines. While stimulant treatments for ADHD could certainly result in a positive result on urine screen for amphetamines, there have been no reports of false-positive results for amphetamines secondary to patients using atomoxetine. We implicate atomoxetine, and/or its metabolites, as a compound or compounds which may interfere with urine drug immunoassays leading to false-positive results for amphetamines CEDIA assays.
Immunoassays are routinely used to provide rapid urine drug screening results in the clinical setting. These screening tests are prone to false-positive results and ideally require confirmation by mass spectrometry. In this study, we have examined a large number of urine specimens where drugs other than amphetamines may have caused a false-positive amphetamine immunoassay screening result. 12,250 Urine drug screens in a clinical laboratory that used the CEDIA amphetamine/ecstasy method were reviewed for false-positive results over a 6-year period (2015–2020). An additional 3,486 referred samples, for which confirmatory mass spectrometry was requested, were also reviewed. About 86 in-house samples and 175 referral samples that were CEDIA false-positive screens were further analyzed by an LC–QTOF general unknown screen. Potential cross-reacting drugs were identified, and their molecular similarities to the CEDIA targets were determined. Commercial standards were also analyzed for cross-reactivity in the amphetamine/ecstasy CEDIA screen. Positive amphetamine results in 3.9% of in-house samples and 9.9% of referred tests for confirmatory analysis were false positive for amphetamines. Of these false-positive specimens, on average, 6.8 drugs were detected by the LC–QTOF screen. Several drugs were identified as possible cross-reacting drugs to the CEDIA amphetamine/ecstasy assay. Maximum common substructure scores for 70 potential cross-reacting compounds were calculated. This was not helpful in identifying cross-reacting drugs. False-positive amphetamine screens make up to 3.9–9.9% of positive amphetamine screens in the clinical laboratory. Knowledge of cross-reacting drugs may be helpful when mass spectrometry testing is unavailable.
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Objective:
The present work was designed to investigate whether fenofibrate could ameliorate olanzapine deleterious effect on insulin resistance via its effect on fibroblast growth factor-21 (FGF-21)-adiponectin axis without affecting olanzapine antipsychotic effect in postweaning socially isolated reared female rats.
Method:
Treatment with olanzapine (6 mg/kg, intraperitoneally) or fenofibrate (100 mg/kg, orally) have been started 5 weeks after isolation, then behavioral tests, hippocampal content of neurotransmitters, and brain-derived neurotrophic factor (BDNF) were assessed. Moreover, insulin resistance, lipid profile, FGF-21, adiponectin, inflammatory, and oxidative stress markers of adipose tissue were assessed.
Results:
Treatment of isolated-reared animals with olanzapine, or fenofibrate significantly ameliorated the behavioral and biochemical changes induced by postweaning social isolation. Co-treatment showed additive effects in improving hippocampal BDNF level. Besides, fenofibrate reduced the elevation in weight gain, adiposity index, insulin resistance, lipid profile, and FGF-21 level induced by olanzapine treatment. Also, fenofibrate increased adiponectin level which was reduced upon olanzapine treatment. Moreover, fenofibrate improved both adipose tissue oxidative stress and inflammatory markers elevation as a result of olanzapine treatment.
Conclusion:
Fenofibrate could ameliorate olanzapine-induced insulin resistance without affecting its central effect in isolated reared rats via its action on FGF-21-adiponectin axis.
Sympathomimetic drugs comprise a broad category of substances including both illicit and prescribed drugs that have deleterious effects when ingested or abused. The clinical syndromes that result from overstimulation of the sympathetic nervous system by reuptake inhibition of biogenic amines, such as norepinephrine and dopamine, carry significant morbidity. Recognition and awareness of the appropriate supportive measures are required to mitigate life-threatening complications of multiple organ systems. The sympathomimetic toxidrome is recognized by a constellation of symptoms including agitation, hyperthermia, tachycardia, and hypertension, and the primary treatment involves supportive care, including the liberal use of benzodiazepines.
Background
Glyco-metabolic deteriorations are the most limiting adverse reactions to antipsychotics in the long term. They have been incompletely investigated and the properties of antipsychotics that determine their magnitude are not clarified.
To rank antipsychotics by the magnitude of glyco-metabolic alterations and to associate it to their pharmacological and chemical properties, we conducted a network meta-analysis.
Methods
We searched PubMed, Embase, and Psycinfo on 10 September 2020. We selected studies containing the endpoint-baseline difference or the distinct values of at least one outcome among glucose, HbA1c, insulin, HOMA-IR, triglycerides, total/HDL/LDL cholesterols. Of 2094 articles, 46 were included in network meta-analysis. Study quality was assessed by the RoB 2 and ROBINS-I tools. Mean differences (MD) were obtained by random-effects network meta-analysis; relations between MD and antipsychotic properties were analyzed by linear regressions. Antipsychotic properties investigated were acidic and basic pK a , polar surface area, polarizability, and occupancies of D2, H1, M1, M3, α 1A, α 2A, 5-HT1A, 5-HT2A, 5-HT2C receptors.
Results
We meta-analyzed 46 studies (11 464 patients); on average, studies lasted 15.47 weeks, patients had between 17.68 and 61.06 years of mean age and 61.64% were males. Olanzapine and clozapine associated with greater deteriorations, aripiprazole and ziprasidone with smaller deteriorations. Higher polarizability and 5-HT1A receptor occupancy were associated with smaller deteriorations, H1, M1, and M3 receptor occupancies with larger deteriorations.
Conclusions
Drug rankings may guide antipsychotic switching toward metabolically safer drugs. Mechanistic insights may suggest improvements for combination therapies and drug development. More data are required regarding newer antipsychotics.
Context.—Emergency department physicians frequently request urine drug screens, but many are unaware of their limitations, including the potential for false-positive results. Promethazine, a phenothiazine derivative, is used for the treatment of allergies, agitation, nausea, and vomiting. Many patients taking promethazine are subject to urine drug screens and any potential interferences are important to recognize.
Design.—During an 11-month period, all patients presenting to the Massachusetts General Hospital emergency department who had a finding of promethazine in their serum drug screen, and who also had a urine drug screen performed, were selected for inclusion in the study. The urine drug screen results (n = 22 patients/samples) were then studied.
Objective.—To determine if promethazine use can cause false-positive urine amphetamine results in widely used drug of abuse immunoassays.
Results.—Thirty-six percent of patients taking promethazine had false-positive test results for urine amphetamines using the EMIT II Plus Monoclonal Amphetamine/Methamphetamine Immunoassay. Sixty-four percent of patients showed cross-reactivity greater than 20% higher than the blank calibrator rate. In a separate, related study, no promethazine-induced false-positive results were seen with the EMIT II Plus, Triage, and TesTcard 9 amphetamine assays, or the Triage methamphetamine assay. Reduced chlorpromazine interference was also seen with these other assays.
Conclusions.—False-positive urine amphetamine results can be obtained in patients taking promethazine. Promethazine metabolite(s), and not the parent compound, are the likely cause of these urine false-positive results obtained with EMIT II Plus Monoclonal Amphetamine/Methamphetamine Immunoassay. Immunoassays from different manufacturers can have very different “interference” profiles, which the pathologist and laboratory scientist must understand and relay to clinicians.
Point-of-care (POC) urine drug screening (UDS) assays provide immediate information for patient management. However, POC UDS assays can produce false-positive results, which may not be recognized until confirmatory testing is completed several days later. To minimize the potential for patient harm, it is critical to identify sources of interference. Here, we applied an approach based on statistical analysis of electronic health record (EHR) data to identify medications that may cause false positives on POC UDS assays. From our institution’s EHR data, we extracted 120,670 POC UDS and confirmation results, covering 12 classes of target drugs, along with each individual’s prior medication exposures. Our approach is based on the idea that exposure to an interfering medication will increase the odds of a false-positive UDS result. For a given assay–medication pair, we quantified the association between medication exposures and UDS results as an odds ratio from logistic regression. We evaluated interference experimentally by spiking compounds into drug-free urine and testing the spiked samples on the POC device. Our dataset included 446 false-positive UDS results (presumptive positive screen followed by negative confirmation). We quantified the odds ratio of false positives for 528 assay–medication pairs. Of the six assay–medication pairs we evaluated experimentally, two showed interference capable of producing a presumptive positive: labetalol on the 3,4-methylenedioxymethamphetamine (MDMA) assay (at 200 μg/mL) and ranitidine on the methamphetamine assay (at 50 μg/mL). Ranitidine also produced a presumptive positive for opiates at 1,600 μg/mL and for propoxyphene at 800 μg/mL. These findings highlight the generalizability and the limits of our approach to use EHR data to identify medications that interfere with clinical immunoassays.
Background:
Amphetamine urine drug screening by immunoassay is prone to cross-react with other compounds leading to false positive results. Tetracaine is a local anesthetic drug used in the clinical setting as an ointment during urinary catheterization. In our laboratory, tetracaine is often detected by gas chromatography-mass spectrometry in the urine of patients admitted in the emergency department with false positive amphetamine results. The objectives of this study were to investigate if there was cross-reactivity to tetracaine in an amphetamine immunoassay and to retrospectively evaluate the potential contribution of tetracaine to false positive amphetamine results.
Methods:
An interference study was conducted using negative urine samples spiked with increasing concentrations of tetracaine hydrochloride and analyzed with the CEDIA Amphetamine/Ecstasy immunoassay. Retrospectively, urine samples of patients which yielded positive amphetamine immunoassay results and were analyzed by gas chromatography-mass spectrometry were reviewed (n = 417). The presence of tetracaine and/or other drugs by gas chromatography-mass spectrometry were gathered.
Results:
Tetracaine caused false positive amphetamine results by immunoassay (cut-off 1000 µg/L) with a concentration of above 40 mg/L. Retrospective analysis of all positive amphetamine immunoassay samples showed that in 45 out of the 417 (10.8%) urine samples no amphetamine-like derivative was identified by gas chromatography - mass spectrometry. In 37 out of 45 (82.2%) of these false positive cases tetracaine was detected, of whom 59.5% (22/37) had an estimated tetracaine concentration of ≥40 mg/L.
Conclusions:
This study confirmed the interference of tetracaine in the CEDIA Amphetamine/Ecstasy immunoassay and that tetracaine may have contributed to around 80% of the false positive amphetamine cases in the urine samples of patients admitted to the emergency department at our institution.
Amphetamines, frequently used recreational drugs with high risk of toxicity, are commonly included in urine drug screens. This screening is based on enzyme immunoassay, which is a quick and easy-to-perform technique, but may lack specificity resulting from cross-reactivity with other compounds, causing false positive results. We present two cases of presumed false positive MULTIGENT® amphetamine/methamphetamine and MULTIGENT® ecstasy (Abbott®) immunoassays with the beta-blocker metoprolol. Both metoprolol-poisoned patients presented positive urine screening despite no history of drug abuse. No confirmation for amphetamine molecular structures was found with gas chromatography-mass spectrometry. The cross-reactivity was further investigated by doping urine samples with metoprolol and its two major phase-I metabolites. Metoprolol showed positive results for both amphetamine and MDMA tests at low concentrations (200 and 150 μg/mL, respectively). Metoprolol metabolites cross-reacted with the amphetamines immunoassay only, but at higher concentrations (i.e., 2000 μg/mL for α-hydroxymetoprolol and 750 μg/mL for O-demethylmetoprolol). In conclusion, false positive results in amphetamines and MDMA immunoassays are possible in the presence of metoprolol. Toxicologists should be aware of frequent analytical interferences with immunoassays and a detailed medication history should be taken into consideration for interpretation. In vitro investigation of suspected cross-reactivity should include not only the parent drug but also its related metabolites.
Background
Hyponatraemia induced by antidepressant drugs is a rare but potentially life-threatening adverse reaction. Whether it is associated with all or only some antidepressant drugs is still unclear. This needs to be clarified to guide antidepressant therapies, especially in patients with electrolytic imbalances.
Objectives
The primary objective of this study was to quantify the strength of association between the use of different antidepressant drugs and hyponatraemia by using information reported to the US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS). The secondary objective was to investigate the putative relationship between different antidepressant pharmacological targets and the risks of hyponatraemia induced by antidepressant drugs using the ‘pharmacovigilance–pharmacodynamic’ method.
Methods
We used the FAERS database to conduct a case/non-case analysis on spontaneous reports, focusing on events of hyponatraemia/syndrome of inappropriate antidiuretic hormone secretion (SIADH) reported in connection with the use of antidepressant drugs. Risk was expressed as a measure of disproportionality using the reporting odds ratio while adjusting for sex, age and concomitant medications associated with hyponatraemia/SIADH. We assessed to what extent the receptor-binding properties of antidepressant drugs could associate with the reporting odds ratios of hyponatraemia/SIADH of antidepressant drugs, building a linear regression model that included as independent variables the binding affinities (pKi) to the serotonin transporter, dopamine transporter, norepinephrine transporter, and serotonin 5-HT2C, 5-HT2A and 5-HT1A, and α1- and α2-adrenergic receptors.
Results
There were 2233 reports identified. The adjusted reporting odds ratio for the association between antidepressant drug use and hyponatraemia was 1.91 (95% confidence interval 1.83–2.00). The association was strongest for mirtazapine, followed by selective serotonin reuptake inhibitors, and lowest with serotonin-modulating antidepressant drugs. A significant linear correlation was found between the adjusted reporting odds ratios for hyponatraemia and pKi for the adrenergic receptors α1 and α2.
Conclusions
Hyponatraemia is reported at a disproportionately higher level with classes of antidepressant drugs (noradrenergic and specific serotonergic antidepressant [mirtazapine] and serotonin modulators [vortioxetine]) that are in general considered to have a better profile of tolerability in terms of hyponatraemia. With regard to the presented results, the risk of hyponatraemia with mirtazapine appears to be greater than what was reported in the literature; however, confounding by indication cannot be ruled out. Our pharmacovigilance–pharmacodynamic analysis also indicates that inhibition of the serotonin transporter may not be involved in the hyponatraemia linked to the use of antidepressant drugs.
Urine drug testing is an essential component of monitoring patients who are receiving long-term opioid therapy, and it has been suggested for patients receiving long-term benzodiazepine or stimulant therapy. Family physicians should be familiar with the characteristics and capabilities of screening and confirmatory drug tests. Immunoassays are qualitative tests used for initial screening of urine samples. They can give false-positive and false-negative results, so all results are considered presumptive until confirmatory testing is performed. Immunoassays for opioids may not detect commonly prescribed semisynthetic and synthetic opioids such as methadone and fentanyl;similarly, immunoassays for benzodiazepines may not detect alprazolam or clonazepam. Immunoassays can cross-react with other medications and give false-positive results, which have important implications for a patient’s pain treatment plan. False-negative results can cause missed opportunities to detect misuse. Urine samples can be adulterated with other substances to mask positive results on urine drug testing. Family physicians must be familiar with these substances, the methods to detect them, and their effects on urine drug testing.
Objectives:
To characterise adverse reactions associated with medication errors (ME) reported in US Food and Drug Administration Adverse Event Reporting System (US-FAERS), and to identify the signals of disproportionate reporting (SDR) for different drugs.
Methods:
ME associated Individual Case Study Report (ICSRs) were identified. ICSRs were categorized by patient age groups, affected stages of medication process and Anatomical Therapeutic Chemical classification system. Disproportionality analyses were performed for different age groups.
Results:
46,8677 ICSRs were retrieved. An increasing trend in reporting of cases of ME was observed during the studied period. Immunosuppressants and psycholeptic drugs were most frequently involved. Administration errors were reported most frequently, followed by prescribing and dispensing errors. In neonates, SDR following wrong drug administration, wrong dose, and accidental overdose were associated with methylergonovine, zidovudine, and acetaminophen. In elderlies, SDR were found for dose omission and underdose error associated with etanercept and evolocumab.
Conclusion:
While a detailed root-cause analysis for ME characteristic can rarely be performed on such a dataset, data mining for signals in spontaneous reporting database may assist in identifying potential ME in a more standardised and objective manner. Continued use of spontaneous reporting system for identifying MEs is encouraged to prevent unnecessary patient harm.
Background:
Comorbidity is highly prevalent between substance use disorders (SUDs) and schizophrenia. This systematic review and meta-analysis estimated prevalence rates of SUDs in epidemiological and treatment-seeking patients diagnosed with schizophrenia or first episode psychosis.
Methods:
A literature search of Medline, EMBASE, PsycINFO and CINAHL databases was conducted from 1990 to 2017 inclusive. Prevalence of co-morbid SUDs and schizophrenia were extracted and odds ratios (ORs) were calculated using random effects meta-analysis. Combining like studies was dictated how authors reported substance use.
Results:
There were 123 included articles with a total sample size of 165,811 subjects that yielded six epidemiological studies, 11 national or state case-registry studies, 20 large cohort studies and 86 clinical studies using in- or out-patient samples. The prevalence of any SUD was 41.7%, followed by illicit drugs (27.5%), cannabis (26.2%), alcohol (24.3%) and stimulant use (7.3%). Meta-analysis showed the pooled variance of any SUD in males was 48% which was significantly higher than that for females with schizophrenia (22.1%, OR 3.43, 95% CI 3.01, 3.92). Patients with SUD had an earlier age of onset of schizophrenia. Meta-regression showed prevalence increased over time for illicit drugs but not for other substances, including alcohol.
Conclusions:
The meta-analysis revealed that SUDs in schizophrenia is highly prevalent and rates have not changed over time. This indicates SUD are difficult to treat in this patient population and there is an urgent need for more informative studies to help develop better prevention, detection and treatment of SUDs in persons with schizophrenia and co-morbid disorders.
Objective:
False-positive urine drug of abuse screening (UDS) results can have serious implications in clinical practice, particularly when confirmation assay results are not immediately available to providers making medical decisions. Often it is not possible to identify the specific medication or other interfering compound that is responsible for the false-positive UDS result. Even when a potential interference is reported in the literature or package insert for one assay, the applicability to other UDS platforms/assays is often unknown. Mexiletine has been suggested as a cause of false-positive amphetamine results, but never confirmed as the causative agent in previous reports. The goal of this study was to confirm this drug as a cross-reacting compound in amphetamine screening tests.
Methods:
We evaluated several amphetamine screening assays: the Syva EMIT II Plus and the Roche KIMS automated immunoassays, along with the Noble Split-Specimen and Synchron QuikScreen point-of-care assays.
Results:
Urine samples from two patients treated with mexiletine were positive on all amphetamine screens but confirmed negative by mass spectrometry. Drug-free urine spiked with mexiletine caused positive results on all assays, although the EMIT II Plus and KIMS assays cross-reacted at lower mexiletine concentrations than the point-of-care assays.
Conclusion:
This report confirms that mexiletine can cross-react on several amphetamine screening assays. Assay manufacturers are encouraged to evaluate mexiletine cross-reactivity, and providers and laboratories should be aware of the potential for false-positive amphetamine screening results in patients taking mexiletine.
Objective:
The aim of this study was to highlight that concurrent administration of the common lipid-lowering agent fenofibrate may lead to false-positive amphetamine results in often-used immunoassay-based urine drug screens. It also aimed to show that there are significant moral and clinical challenges associated with the interpretation of such results amongst psychiatric inpatients.
Conclusions:
It is evident that different pathology laboratories may utilise different commercial urine drug-screen immunoassays in their toxicology analysis, with variability in the test specificities. Despite the relatively high prevalence of substance misuse in the population of psychiatric inpatients, there exists a need for increased vigilance towards the possibility of false-positive amphetamine results owing to likely cross-reactivity of fenofibrate with the test reagents. In cases where there is uncertainty when correlating clinically, or where false positives are suspected, gold-standard urine-sample analysis by mass spectrometry should be considered, particularly when the consequences for patients may include restrictive measures.
Background:
Within the framework of routine fitness examinations, French Air Force military crew underwent urine testing for 3,4 methylenedioxymetamphetamine (MDMA [ecstasy]). The cross-reactivity of a dyslipidemic drug, fenofibrate, with an MDMA immunoassay was studied and confirmed on a large population sample.
Methods:
A 3-year retrospective study was performed on the MDMA DRI Ecstasy Assay on the Unicel DXC 600. In the event of positive test result, a confirmatory testing was carried out by gas chromatography/mass spectrometry (GC/MS) to establish the presence of MDMA. When analysis by GC/MS did not confirm the presence of MDMA, a false-positive result was suspected and the samples were analyzed by high-performance liquid chromatography-mass spectrometry to identify a potential interfering substance.
Results:
A total of 15,169 urine samples, from 7,803 patients, were tested for 3 years. Of the tested samples, 22 (0.15%) were positive by DRI Ecstasy Assay. None of them were positive by GC/MS. A cross-reactivity of fenofibrate's metabolite with MDMA using this assay was systematically found.
Conclusion:
Fenofibrate's interference with MDMA immunoassay was confirmed. Fenofibrate being widely prescribed, physicians had to be alerted that this treatment could lead to false-positive results.
Urine drug screens (UDSs) are used to identify the presence of certain medications. One limitation of UDSs is the potential for false-positive results caused by cross-reactivity with other substances. Amphetamines have an extensive list of cross-reacting medications. The literature contains reports of false-positive amphetamine UDSs with multiple antidepressants and antipsychotics. We present 2 cases of presumed false-positive UDSs for amphetamines after ingestion of aripiprazole. Case 1 was a 16-month-old girl who accidently ingested 15 to 45 mg of aripiprazole. She was lethargic and ataxic at home with 1 episode of vomiting containing no identifiable tablets. She remained sluggish with periods of irritability and was admitted for observation. UDS on 2 consecutive days came back positive for amphetamines. Case 2 was of a 20-month-old girl who was brought into the hospital after accidental ingestion of an unknown quantity of her father's medications which included aripiprazole. UDS on the first day of admission came back positive only for amphetamines. Confirmatory testing with gas chromatography-mass spectrometry (GC-MS) on the blood and urine samples were also performed for both patients on presentation to detect amphetamines and were subsequently negative. Both patients returned to baseline and were discharged from the hospital. To our knowledge, these cases represent the first reports of false-positive amphetamine urine drug tests with aripiprazole. In both cases, aripiprazole was the drug with the highest likelihood of causing the positive amphetamine screen. The implications of these false-positives include the possibility of unnecessary treatment and monitoring of patients.
We present a false-positive result of ecstasy (3,4-methylenedioxy-NN-methylamphetamine) screening due to the therapeutic use of fenofibrate, an antihyperlipidemic drug. Our hypothesis was that the main metabolite of fenofibrate, fenofibric acid, was responsible for this cross-reactivity on a DRI(®) Ecstasy Assay, using a cut-off of 500 ng/mL. We estimated that the addition of 225 µg/mL pure fenofibric acid to blank urine would be sufficient to result in a positive DRI(®) Ecstasy Assay. The results obtained on the urine samples analyses of the patient show that the DRI(®) Ecstasy Assay resulted negative 2 days after discontinuing fenofibrate treatment, when the urine fenofibric acid concentration corrected by creatinine and determinated by gas chromatography-mass spectrometry was 20.3 µg/mg creatinine. The cross-reactivity data for fenofibric acid would seem to indicate that there was insufficient concentration of measured compound to account for the positive immunochemical results for ecstasy. This apparent discrepancy can be explained in several ways, one of them is that the β-glucuronidase-resistent fenofibric acid isomers are responsible. This process could explain the low recovery of free fenofibric acid when we use the developed method for its quantification in urine samples. Positive results on immunoassay screening must be considered presumptive until confirmation with another method based on a different principle, preferably gas chromatography-mass spectrometry or liquid chromatography-mass spectrometry.
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Abstract A wide range of comorbid psychiatric disorders overlap with attention-deficit hyperactivity disorder (ADHD) across the life span. There is a robust and complex link between ADHD and substance use disorders (SUD). The aim of this report was to review the neurobiological and other vulnerability factors explaining the comorbidity of ADHD and an addictive disorder, as well as the key aspects of the assessment and diagnosis of dually diagnosed ADHD patients. A comprehensive and systematic search of relevant databases (PubMed, Embase, and PsychINFO) was conducted to identify studies published in peer-reviewed journals until July 31, 2012, with the aim of exploring the association of ADHD and SUD with postgraduate training and residency education. Across the life span, ADHD is associated with significant impairment and comorbidity. Data from epidemiological, clinical and epidemiological studies show a very solid link between ADHD and SUD. Therefore, it is very important to carefully and systematically assess for any substance use in patients with suspected ADHD coming to initial assessment, and vice versa. While there are various valid and reliable rating and screening scales, diagnosis cannot solely rely on any of the instruments available for both SUD and ADHD in adult patients with dual pathology. The most important and effective tool in the assessment of dually diagnosed patients with ADHD and SUD is a full and comprehensive clinical and psychosocial assessment. Hence, it is essential to actively incorporate training opportunities on the assessment, diagnosis, and management of adult ADHD and dually diagnosed ADHD patients during postgraduate education residency or specialist training.
Drug testing is often used as part of an assessment for substance use in children and adolescents. However, the indications for drug testing and guidance on how to use this procedure effectively are not clear. The complexity and invasiveness of the procedure and limitations to the information derived from drug testing all affect its utility. The objective of this clinical report is to provide guidance to pediatricians and other clinicians on the efficacy and efficient use of drug testing on the basis of a review of the nascent scientific literature, policy guidelines, and published clinical recommendations.
The US Food and Drug Administration (FDA) Adverse Event Reporting System (FAERS, formerly AERS) is a database that contains information on adverse event and medication error reports submitted to the FDA. Besides those from manufacturers, reports can be submitted from health care professionals and the public. The original system was started in 1969, but since the last major revision in 1997, reporting has markedly increased. Data mining algorithms have been developed for the quantitative detection of signals from such a large database, where a signal means a statistical association between a drug and an adverse event or a drug-associated adverse event, including the proportional reporting ratio (PRR), the reporting odds ratio (ROR), the information component (IC), and the empirical Bayes geometric mean (EBGM). A survey of our previous reports suggested that the ROR provided the highest number of signals, and the EBGM the lowest. Additionally, an analysis of warfarin-, aspirin- and clopidogrel-associated adverse events suggested that all EBGM-based signals were included in the PRR-based signals, and also in the IC- or ROR-based ones, and that the PRR- and IC-based signals were in the ROR-based ones. In this article, the latest information on this area is summarized for future pharmacoepidemiological studies and/or pharmacovigilance analyses.
Introduction:
The increasing abuse of amphetamine-like compounds presents a challenge for clinicians and clinical laboratories. Although these compounds may be identified by mass spectrometry-based assays, most clinical laboratories use amphetamine immunoassays that have unknown cross-reactivity with novel amphetamine-like drugs. To date, there has been a little systematic study of amphetamine immunoassay cross-reactivity with structurally diverse amphetamine-like drugs or of computational tools to predict cross-reactivity.
Methods:
Cross-reactivities of 42 amphetamines and amphetamine-like drugs with three amphetamines screening immunoassays (AxSYM(®) Amphetamine/Methamphetamine II, CEDIA(®) amphetamine/Ecstasy, and EMIT(®) II Plus Amphetamines) were determined. Two- and three-dimensional molecular similarity and modeling approaches were evaluated for the ability to predict cross-reactivity using receiver-operator characteristic curve analysis.
Results:
Overall, 34%-46% of the drugs tested positive on the immunoassay screens using a concentration of 20,000 ng/mL. The three immunoassays showed differential detection of the various classes of amphetamine-like drugs. Only the CEDIA assay detected piperazines well, while only the EMIT assay cross-reacted with the 2C class. All three immunoassays detected 4-substituted amphetamines. For the AxSYM and EMIT assays, two-dimensional molecular similarity methods that combined similarity to amphetamine/methamphetamine and 3,4-methylenedioxymethampetamine most accurately predicted cross-reactivity. For the CEDIA assay, three-dimensional pharmacophore methods performed best in predicting cross-reactivity. Using the best performing models, cross-reactivities of an additional 261 amphetamine-like compounds were predicted.
Conclusions:
Existing amphetamines immunoassays unevenly detect amphetamine-like drugs, particularly in the 2C, piperazine, and β-keto classes. Computational similarity methods perform well in predicting cross-reactivity and can help prioritize testing of additional compounds in the future.
This case report describes a false-positive amphetamine/ecstasy [3,4-methylenedioxymethamphetamine (MDMA)] and ecstasy (MDMA) screen after therapeutic use of antihyperlipidemic drug, fenofibrate. A 60-year-old male patient was admitted to inpatient psychiatry unit with the diagnosis of alcohol dependency. He was prescribed diazepam 30 mg/day, thiamine 300 mg/day, and naltrexone 50 mg/day. He had also been using fenofibrate 267 mg/day for 3 years for hyperlipidemia and trazodone 100 mg/day for 5 months for insomnia. On routine, urine drugs-of-abuse screening amphetamine/MDMA (CEDIA) test was positive for 4 different occasions and MDMA (DRI) test was positive on 5 different occasions. Gas chromatography/mass spectrometry confirmation of the first positive 3 samples were negative for amphetamine and MDMA. After discontinuation of fenofibrate, amphetamine/MDMA, and MDMA immunoassay results turned out to be negative. Caution should be given to interpretation of amphetamine/MDMA (CEDIA) and MDMA (DRI) tests in patients taking fenofibrate. Specific confirmation with a suitable method should be used to prevent erroneous interpretations.
Background:
Attention-deficit hyperactivity disorder (ADHD) is predominantly a diagnosis of childhood and adolescence but has also been recognized in adults. It is associated with high rates of comorbid psychiatric conditions, particularly substance use disorders (SUD).
Methods:
A review of the literature was conducted with a focus on ADHD, SUD, their comorbidity, and treatment considerations.
Results:
Literature suggests that the use of methylphenidate (MPH) in children does not increase SUD later in life, and may in fact reduce substance use and abuse in adolescence and adulthood. Concurrent treatment of ADHD-SUD, which may be supported theoretically, has yielded inconsistent data on clinical trials. While MPH use in adults with ADHDSUD may be effective in alleviating ADHD symptoms, the benefits on SUD are not clear and remain controversial. Studies suggest that adults with comorbid ADHD-SUD do not misuse or divert their medication, but MPH does not consistently improve substance use. However, data are lacking for substances other than cocaine and stimulants other than MPH. While the risk of stimulant abuse should not be ignored, it may be minimized by selecting medications that are not readily crushed and solubilized for parenteral administration, or by utilizing non-stimulant medications and/or psychotherapy.
Conclusion:
While there are a lack of evidence-based guidelines for the concurrent treatment of ADHD and SUD, evidence to date suggests that stimulant medications should not necessarily be avoided for patients with comorbid ADHDSUD and that concurrent treatment may be a successful approach to improve ADHD outcomes without worsening SUD symptoms.
Phenylephrine, an α(1) -adrenergic agonist, and methamphetamine, a prescription drug and substance of abuse, have similar chemical structures and thus have the potential to cross-react in qualitative screening tools such as a urine drug screening (UDS) performed by immunoassay. This cross-reactivity may yield a false-positive result that may affect the provision of care in certain patient populations and clinical situations. We describe a 36-year-old woman with confirmed brain death after a short hospital stay who had an initial UDS that was negative for methamphetamine. The patient was assessed for potential organ donation, which included obtaining a follow-up UDS. A urine sample was obtained after being hospitalized for 36 hours, which tested positive for methamphetamine, with no suspected ingestion of the target substance. Confirmatory laboratory testing indicated that intravenous phenylephrine and its metabolites were the likely cause of the false-positive UDS. However, the patient was not deemed to be a suitable candidate for organ donation, but clear documentation of the reason for denial of organ donation was not available in the patient's medical record. To our knowledge, this is the first case published in the English-language literature that describes the clinical occurrence of apparent immunoassay cross-reactivity of methamphetamine and phenylephrine that resulted in a false-positive UDS for methamphetamine. In addition, this report describes the potential implications of this situation on clinical care, including organ donation acceptance. Toxicology screening in the emergency department and intensive care unit is a tool to assist in the diagnosis of medical conditions, but it may not always be reliable. Therefore, positive immunoassay results that may change the management of a patient's condition should be quickly verified with confirmatory testing to minimize unfavorable consequences.