Journal of Analytical Toxicology 2014;38:322 –326 doi:10.1093/jat/bku044 Advance Access publication May 6, 2014
Urine Specimen Detection of Zolpidem Use in Patients with Pain Lindsey M. Mann1, Rabia S. Atayee1,2, Brookie M. Best1,3, Candis M. Morello1,4 and Joseph D. Ma1,2* 1 University of California, San Diego (UCSD), Skaggs School of Pharmacy and Pharmaceutical Sciences, La Jolla, CA, USA, 2Doris A. Howell Palliative Care Services, San Diego, CA, USA, 3UCSD Department of Pediatrics, Rady’s Children’s Hospital, San Diego, CA, USA and 4 Diabetes Intense Medical Management Clinic, Veterans Affairs San Diego Healthcare System, La Jolla, CA, USA
*Author to whom correspondence should be addressed. Email: [email protected]
This study examined zolpidem and concurrent opioid, benzodiazepine, other central nervous system (CNS) depressants, and alcohol use. Urine specimens were analyzed using liquid chromatography –mass spectrometry (LC – MS/MS). Specimens were tested for zolpidem (n 5 71,919) and separated into a provider-reported medication list documenting (n 5 5,257) or not documenting zolpidem use (n 5 66,662). Zolpidem-positive specimens were further separated into reported and unreported use cohorts. The total number of zolpidempositive specimens in the reported and unreported use cohorts was 3,391 and 3,190, respectively. Non-informed prescribers were 4.4% (3,190/71,919) among the general population and 48.5% (3,190/ 6,581) when only zolpidem users were considered. In the zolpidem user population, the most common concurrent opioids in both cohorts were hydrocodone and oxycodone. Alprazolam and clonazepam were higher in the unreported use cohort (P 0.05). The unreported use cohort also had a higher detection of zolpidem plus a benzodiazepine (49.7 vs. 46%; P 0.05), zolpidem plus an opioid and a benzodiazepine (40.8% vs. 37.4%; P 0.05) and zolpidem plus an opioid, a benzodiazepine, and an other CNS depressant (12.9 vs. 10.9%; P 0.05). Concurrent use of zolpidem, an opioid, a benzodiazepine and an other CNS depressant is prevalent in a pain patient population.
Introduction Zolpidem is a non-benzodiazepine hypnotic that binds to the omega-1 subunit of the GABA-A receptor, thus conferring its sedative properties (1). In contrast, benzodiazepines bind to each subunit of this receptor. The way zolpidem binds to the GABA-A receptor is postulated to be why zolpidem does not possess anxiolytic and anticonvulsive effects until very high doses beyond what is approved for use (2). Zolpidem undergoes extensive metabolism, with ,1% of parent, but .50% of zolpidem carboxylic acid, excreted in urine (3). The elimination half-life of zolpidem is 2 h. In contrast, zolpidem carboxylic acid is present in urine for 2 to 3 days following single-dose zolpidem administration (3). Zolpidem has not been found to cause changes in sleep patterns or cause rebound insomnia, and has a lower risk of abuse than benzodiazepines (1, 4, 5). Zolpidem can cause excessive sedation and/or respiratory depression, particularly when taken with opioids (1, 6). When benzodiazepines and/or alcohol are concurrently used with zolpidem, the risk of excessive sedation and/or respiratory depression is compounded due to an additive pharmacodynamic response (1, 6, 7). Patients may not be aware of the additive risk with concurrent medication use as benzodiazepines are also used as sleep aids (8) and alcohol is often consumed to help with sleep disturbances (9). The prescribing information states that zolpidem should not be taken if a patient has taken another
medication that causes sedation and/or has recently consumed alcohol. In addition, the risk of ‘sleep-driving’ is also increased with concurrent zolpidem and other central nervous system (CNS) depressants and/or alcohol use (1). Pain providers may not be aware their patient is taking zolpidem if a patient has not reported zolpidem use and/or if multiple health care providers are involved in the patient’s care in an effort to manage numerous medical conditions. To date, few data have examined non-informed prescriber percentages and the prevalence of concurrent zolpidem use with opioids, benzodiazepines (10), other CNS depressants and alcohol consumption. The purpose of this retrospective data analysis was to examine zolpidem use patterns as well as the percentage of non-informed prescribers in a pain patient population. Knowledge of concurrent use patterns with zolpidem may lead to improved patient monitoring and help clinicians address which patients are at highest risk of additive CNS effects (e.g., oversedation, confusion) and respiratory depression.
Methods This retrospective data analysis was IRB-approved by the University of California, San Diego (UCSD) Human Research Protections Program. Urine specimens were collected at pain physician practices from patients on chronic opioid therapy for routine drug monitoring purposes. More than 800,000 de-identiﬁed specimens collected between November 2011 and May 2012 were available for analysis. Specimens from a single or ﬁrst visit, subjects who were at least 18 years of age, had a urine creatinine concentration of 20 mg/dL and who were tested for zolpidem as part of a multiplex pain medication assay panel (Table I) were selected for analysis (n ¼ 71,919). Specimens were ﬁrst separated into a provider-reported medication list documenting zolpidem use (n ¼ 5,257) and a provider-reported medication list that did not document zolpidem use (n ¼ 66,662). Urine specimens that were positive for zolpidem use were further separated into reported and unreported use cohorts. Specimens that were 10 ng/mL [lower limit of quantitation (LLOQ)] for zolpidem or zolpidem carboxylic acid were considered positive for zolpidem. To be included in the analysis, each subject also had to be tested for each drug/metabolite listed in Table I. Subjects with concomitant (Table I) parent drug or metabolite urine concentrations above the LLOQ were reported as having taken the concomitant drug (11), with some exceptions resulting in study exclusion. Specimens were excluded if they were positive for hydromorphone only [n ¼ 273, 264 (reported use, unreported use)] since the multiplex pain medication assay panel was unable to discriminate if hydromorphone concentrations were due to hydrocodone or
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hydromorphone use. Specimens were excluded if they were positive for oxymorphone only [n ¼ 72, 74 (reported use, unreported use)] since the multiplex pain medication assay panel was unable to discriminate if oxymorphone concentrations were due to oxycodone or oxymorphone use. Specimens were analyzed and quantiﬁed by using GC, liquid chromatography – mass spectrometry (LC – MS) and LC – MS – MS. The method and details for each assay are described elsewhere (3, 12 –15). In brief, the following transitions for zolpidem and zolpidem carboxylic acid were used: zolpidem-D6: 314.3 ! 263.1, zolpidem: 308 ! 235.2, 308 ! 263.2, zolpidem carboxylic acid: 338.2 ! 293.1, ZCA: 338.2 ! 265.1. The lower limit of quantitation for zolpidem and zolpidem carboxylic acid was 10 ng/mL. The upper limit of linearity for both the zolpidem and zolpidem carboxylic acid was 100,000 ng/mL. Statistical and graphical analyses were performed using Microsoft Excel 2010 and OriginPro v8.6. Frequencies, expressed as a percentage, were determined for each analyte in the reported and unreported use cohorts in the zolpidem user population. Non-informed prescriber percentages were determined based on previous deﬁnitions (16). The non-informed prescriber percentage for the overall population represents the probability that any patient who provided a urine sample is taking zolpidem without the knowledge of their prescriber. This was calculated as the number of patients positive for zolpidem who did not document zolpidem use on the medication list divided by the total number of patients eligible for analysis. The non-informed prescriber percentage for the zolpidem user population is the probability that a given zolpidem user out of all subjects with detectable zolpidem in urine is taking the medication without the knowledge of their pain specialist. This was calculated as the number of patients positive for zolpidem who did not document zolpidem use on the medication list divided by the total
Table I Panel of Drugs Tested Concurrently with Zolpidem Drug class
Parent drugs included in detection assay [lower limit of quantitation (ng/mL)]
Metabolites included in detection assay [lower limit of quantitation (ng/mL)]
Buprenorphine (10) Codeine (50) Fentanyl (2) Hydrocodone (50) Meperidine (50) Methadone (100)
Norbuprenorphine (20) Morphine (50) Norfentanyl (8) Norhydrocodone (50), Hydromorphone (50) Normeperidine (50) 2-Ethylidine-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP) (100) Hydromorphone (50) Noroxycodone (50), Oxymorphone (50) None None Alpha-hydroxyalprazolam (20)
Other sedating Medications
Morphine (50) Oxycodone (50) Tapentadol (50) Tramadol (100) Alprazolam (not measured) Clonazepam (not measured) Diazepam (not measured) Lorazepam (40) Temazepam (50) Oxazepam (40) Carisoprodol (100) Cyclobenazprine (50) Gabapentin (100) Pregabalin (100) None
7-Amino-clonazepam (20) Nordiazepam (40), oxazepam (40), temazepam (50) None Oxazepam (40) None Meprobamate (100) None None None Ethyl glucuronide (500), ethyl sulfate (500)
number of specimens that were positive for zolpidem. Z tests with Yates Correction was performed to determine if there was a difference in prevalence in detection rates of a medication between the reported and unreported use cohorts of the zolpidem user population. Statistical signiﬁcance was deﬁned as P 0.05.
Results In the provider-reported medication list documenting zolpidem use (n ¼ 5,257), 1,522 and 3,376 specimens had detectable zolpidem and zolpidem carboxylic acid, respectively. The total number of specimens positive for zolpidem was 3,391. In the provider-reported medication list that did not document zolpidem use (n ¼ 66,662), 1,142 and 3,146 specimens had detectable zolpidem and zolpidem carboxylic acid, respectively. The total number of specimens positive for zolpidem use was 3,190. The non-informed prescriber percentage for the general population was 4.4% (3,190/71,919). For the zolpidem user population (n ¼ 6,581), 2,664 (78.5%; 2,664/3,391) specimens in the reported use cohort and 2,537 (79.5%; 2,537/3,190) specimens in the unreported use cohort were positive for an opioid (Table II). The non-informed prescriber percentage for the zolpidem user population was 48.5% (3,190/6,581). The most common concurrent opioids detected in both cohorts were hydrocodone and oxycodone. Concurrent buprenorphine detection was higher (P 0.05), while concurrent hydrocodone detection was lower (P 0.05),
Table II Percentage of Zolpidem Users (n ¼ 6,581; 3,391 in the Reported Use Cohort and 3,190 in the Unreported Use Cohort) Positive for Concurrent Opioid or Benzodiazepine Use Drug
Reported zolpidem use cohort, % (n)
Unreported zolpidem use cohort, % (n)
Buprenorphine Codeine Fentanyl Hydrocodonea Meperidine Methadone Morphine Oxycodoneb Tapentadol Tramadol Any opioid Alprazolam Clonazepam Diazepam Lorazepam Temazepam Oxazepam Any benzodiazepine Carisoprodol Cyclobenazprine Gabapentin Pregabalin Alcohol
2.3% (77) 2.1% (70) 6% (205) 36% (1,220) 0.1% (2) 5.2% (175) 12.2% (415) 30.6 (1,037) 0.6% (20) 7.8% (265) 78.5% (2,664) 19.3% (656) 12.8% (435) 9.6% (327) 7.5% (256) 12.1% (412) 14.4% (488) 46% (1,562) 4.8% (164) 6.4% (218) 10.9% (371) 5.5% (188) 7% (236)
7.2% 2.1% 5% 31.3% 0.3% 5.8% 12.2% 32.2% 1.1% 6.7% 79.5% 21.9% 15.7% 9.7% 7.7% 12.4% 15.2% 49.7% 9.2% 5.5% 10.3% 5.3% 7.7%
(230)* (67) (161) (997)* (9) (186) (390) (1,028) (34) (213) (2,537) (699)* (502)* (311) (247) (397) (484) (1,587)* (292)* (176) (327) (168) (245)
a Included specimens positive for hydrocodone only (n ¼ 12, 8 [reported use, unreported use]), norhydrocodone only (n ¼ 57, 47), hydrocodone plus norhydrocodone (n ¼ 176, 163), hydrocodone plus hydromorphone (n ¼ 0, 2) and hydrocodone plus norhydrocodone plus hydromorphone (n ¼ 975, 777). b Included specimens positive for oxycodone only (n ¼ 6, 16 [reported use, unreported use]), noroxycodone only (n ¼ 47, 44), oxycodone plus noroxycodone (n ¼ 23, 39), oxycodone plus oxymorphone (n ¼ 2, 4) and oxycodone plus noroxycodone plus oxymorphone (n ¼ 959, 925). *P 0.05 between reported and unreported use cohorts.
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in the unreported use cohort (Table II). Of the subjects positive for zolpidem, 1,562 (46%) and 1,587 (49.7%) of specimens in the reported and unreported use cohorts were also positive for a benzodiazepine (P 0.05; Table II). The most common concurrent benzodiazepine in both cohorts was alprazolam. Concurrent alprazolam and clonazepam detection were higher in the unreported use cohort (P 0.05; Table II). Among zolpidem users, 814 (24%) and 837 (26.2%) specimens in the reported and unreported use cohorts were also positive for an other (non-opioid, non-benzodiazepine) medication with sedative effects. Other medications detected with sedative effects included carisoprodol, cyclobenzaprine, gabapentin and pregabalin (Table II). Concurrent carisoprodol detection was higher in the unreported use cohort (P 0.05). The frequency of zolpidem users who were also positive for an opioid was not signiﬁcantly different between the reported and unreported use cohorts (Table II; Figure 1). Likewise, no difference was seen between cohorts in zolpidem users that were also positive for an other medication with sedative effects (Figure 1). In contrast, zolpidem users in the unreported use cohort had a higher detection of a concurrent benzodiazepine (49.7 vs. 46%; P 0.05, Table II, Figure 1), a concurrent opioid and a benzodiazepine (40.8% vs. 37.4%; P 0.05; Figure 1) and a concurrent opioid, a benzodiazepine and other medication with sedative effects (12.9% vs. 10.9%; P 0.05; Figure 1). Furthermore, 23 (0.7%) and 27 (0.8%) specimens were positive for zolpidem, an opioid, a benzodiazepine, another sedating medication and alcohol in the reported and unreported cohorts, respectively. Discussion This study evaluated zolpidem and zolpidem carboxylic acid detection rates in urine specimens from a pain patient population. In all subjects who tested positive for zolpidem, 40% of the urine specimens were positive for zolpidem itself, while
99% of specimens tested positive for zolpidem carboxylic acid. One possible reason for the lower detection rate of zolpidem is if the time of the urine drug test does not correlate with when the patient has consumed the dose or with the frequency of zolpidem use if taken on an as needed basis. Regarding zolpidem carboxylic acid, the larger number of positive specimens is in agreement with previous reports that the metabolite is present in urine for 2 to 3 days following single-dose zolpidem administration (3). We evaluated zolpidem use by patients who did and did not inform their pain provider. The measure of non-informed rates has been described elsewhere with tricyclic antidepressant use (16). Two rates of non-informed usage were calculated, the noninformed provider percentage in the general population was 4.4% and the rate of non-informed providers for zolpidem users was 48.5%. These results provide suggestion that 4.4% of all patients at a given pain practice take zolpidem without the knowledge of their pain specialist, and 48.5% of patients using zolpidem do so without the knowledge of their provider that manages their pain. Although one of the most common comorbidities in chronic pain patients is insomnia, patients may not be aware of the relationship and may choose to refrain from disclosing zolpidem use. Furthermore, patients may not be aware of additive pharmacodynamic effects of oversedation and/or confusion associated with zolpidem and may not realize that all of their providers need to know they are taking zolpidem. Thus, healthcare providers must frequently update patient medication lists as well as educate their patients about the importance of disclosing all medications regardless of how benign it may seem or what condition the medication is treating. Seventy-nine percent of zolpidem users with pain concurrently use an opioid (Table II). The observed percentage of positive specimens for an opioid is in agreement with previous studies in pain patient populations that have reported 74– 91% of specimens were positive for an opioid (10, 17). Opioid detection rates were similar between cohorts with the exception of
Figure 1. Percentage of subjects positive for zolpidem, any opioid, any benzodiazepine, any other sedating medication or other combination.
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buprenorphine and hydrocodone (Table II). The higher use of concurrent buprenorphine in zolpidem users in the unreported use cohort is of particular interest as a previous study evaluated buprenorphine use patterns in pain patients and reported that benzodiazepines (19–33%) were the most common concurrent class of medications associated with buprenorphine use (11). However, no data were reported on concurrent buprenorphine and zolpidem use (11). Determining the cause of different use patterns of zolpidem and opioids between cohorts is a further area of investigation. Future research should examine detection rates with opioids and other non-benzodiazepine hypnotic medications (e.g., zaleplon, zopiclone, eszopiclone). Additionally, studies utilizing external urine data are needed to conﬁrm the current study ﬁndings of the different detection rates of hydrocodone and buprenorphine associated with concurrent zolpidem use. The most common benzodiazepine detected in zolpidem users in both cohorts was alprazolam. This result is in contrast with a previous study in pain patients, whereby the most commonly detected benzodiazepines were oxazepam and temazepam (10). One reason for the discrepancy between studies is the different limit of quantitation for alpha-hydroxyalprazolam, which may have resulted in a larger number of positive specimens for alprazolam use. The lower limitation of quantitation in the current study was 20 ng/mL compared with a previous study of 50 ng/mL (10). Concurrent benzodiazepine use in zolpidem users was higher in the unreported use versus reported use cohorts (P 0.05) and could be due to higher alprazolam and clonazepam detection (Table II). This seems to also suggest a preference for a short-acting benzodiazepine in zolpidem users. Furthermore, zolpidem users in the unreported use cohort also had higher frequencies of concurrent use of an opioid and a benzodiazepine (Figure 1) and concurrent use of an opioid, a benzodiazepine and an other medication with CNS depressant effects (12.9 vs. 10.9%; P 0.05; Figure 1). Of note, these rates may be underestimates as additional medications with CNS depressant effects, such as over-the-counter diphenhydramine, were not analyzed. There is suggestion that patients with chronic pain who appropriately use or misuse opioid analgesics plus benzodiazepines and other CNS depressant medications have increased rates of adverse effects, overdose and death (7, 18). In special populations such as the older adult with chronic pain, they are at an even higher risk for adverse effects that may exacerbate falls, cognitive impairment and dementia (19). According to the 2012 American Geriatrics Society Updated Beers Criteria for Potentially Inappropriate Medication Use in Older Adults, expert recommendations are to avoid zolpidem (20). Although ,1% of specimens were positive for zolpidem, an opioid, a benzodiazepine, an other sedating medication, and alcohol, pain providers need to be aware of concurrent use of multiple medications that possess overlapping adverse effects. The current study lacked dose amount and time of dose administration data for zolpidem. Whether these factors impacted concurrent use with an opioid, benzodiazepine or other CNS depressants is unknown. Another study limitation was the presumption of medication use from physician-reported medication lists. Inaccurate medication lists were possible and could impact the results of our study. Studies have reported discrepancies upon comparing medication lists with what the patient is
actually taking (21, 22). Although electronic health records have been suggested to increase medication list accuracy, the utility of such technologies remains low (23, 24). Furthermore, one study reported that 55% of medication lists in electronic health records were accurate and the accuracy minimally increased if patients had electronic health records access (25).
Conclusions This was a data analysis in a pain population evaluating zolpidem use patterns by examining physician-reported medication lists and urine drug testing. These results highlight the differences in the use patterns of zolpidem with different opioids and benzodiazepines. Furthermore, among patients using zolpidem, a large discrepancy (48.5%) was noted between what pain providers believe patients to be taking versus what patients are actually taking. This analysis also suggested pain patients taking zolpidem without the pain provider’s knowledge are concurrently taking other medications with CNS depressant effects. All health care providers need to be aware of the importance of accurate and timely medication reporting. Patient counseling on the anticipated side effects and the treatment duration course may improve the percentage of non-informed prescriber use. Ideally if a sleep aid was needed, an open dialog would occur between the provider and the patient. Urine drug testing can be a helpful tool for providers to monitor reported and unreported drug therapy for patients with pain.
Acknowledgments The authors would like to acknowledge Amadeo J. Pesce, PhD, DABCC for his crucial guidance and support throughout the entirety of this study. Urine specimens were tested and provided by Millennium Laboratories. Dr Joseph D. Ma is a paid consultant of Millennium Laboratories, Inc.
Funding This work was supported in part by an educational grant provided by the University of California, San Diego Skaggs School of Pharmacy and Pharmaceutical Sciences from an unrestricted gift from the Millennium Research Institute (to L.M.M.).
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