Urine specimen detection of zolpidem use in patients with pain

Association of long-term benzodiazepine hypnotic use and prediabetes in US population: A cross-sectional analysis of national health and nutrition examination survey data

Benzodiazepine hypnotics' effects on glucose metabolism are seldom reported, and the association between long-term (≥4 weeks) benzodiazepine usage and prediabetes has not been studied. This study was aimed to investigate the association between benzodiazepine hypnotic usage for ≥ 3 months and the prevalence of prediabetes. We analyzed cross-sectional data from the National Health and Nutrition Examination Survey (NHANES) during 2005 to 2008, selecting adult participants without diabetes who used benzodiazepine hypnotics for at least 3 months or did not take any hypnotics. Individuals taking other hypnotics, antipsychotics, glucocorticoids, or hypoglycemic drugs were excluded. We defined prediabetes as an hemoglobin A1C (HbA1C) 5.7-6.4%, as suggested by the American Diabetes Association. Prescribed drug information was self-reported and checked by official interviewers, and HbA1C data in NHANES was recognized by the National Glycohemoglobin Standardization Program. We calculated the propensity score according to the covariates and adjusted it using multivariate logistic regression. Lower thresholds of HbA1C ≥ 5.5% or ≥ 5.3% were also analyzed. Among 4694 eligible participants, 38 received benzodiazepine hypnotics; using these hypnotics for ≥ 3 months was not significantly associated with the prevalence of prediabetes, as well as HbA1C ≥ 5.5% or ≥ 5.3%. Adjusted for propensity score, the respective odds ratios for prediabetes, HbA1C ≥ 5.5%, and HbA1C ≥ 5.3% were 1.09 (95% confidence interval [CI] 0.19-6.32), 0.83 (95% CI 0.22-3.13), and 1.22 (95% CI 0.3-4.93). No significant association was found between benzodiazepine hypnotic usage ≥ 3 months and the prevalence of prediabetes.

Trends in overdose deaths involving gabapentinoids and Z-drugs in the United States

INTRODUCTION

As policies have been implemented to limit access to prescription opioids, other drugs have been prescribed off-label, sometimes concurrently with opioids, to manage pain. There are concerns about the use of gabapentinoids and "Z-drugs" with opioids. As the opioid crisis transitions to illicit opioids and polysubstance use, little work quantifies the concurrent involvement of non-opioid prescription drugs and illicit opioids in overdose deaths.

METHODS

Data from the census of deaths in the United States for 1999-2020 were used to understand trends in deaths involving gabapentinoids/Z-drugs and opioid co-involvement. These trends were studied overall and by sex, race, age, and education.

RESULTS

Per capita overdose deaths involving gabapentinoids/Z-drugs increased almost continuously since 1999, averaging 15.8% annual growth. This rate increased to 32% in 2020, primarily due to overdoses involving synthetic opioids. Women typically had higher rates of overdose deaths involving both opioids and gabapentinoids/Z-drugs, though this disparity disappeared in 2020. White Americans and American Indians/Alaskan Natives historically had higher rates than other racial groups; however, Black Americans experienced over 60% annual growth in recent years. Low education groups have been disproportionately impacted. The age incidence tends to be older than overdoses involving opioids more generally.

CONCLUSION

Overdose deaths involving opioids and gabapentinoids/Z-drugs have tended to disproportionately affect women and older age groups compared to all opioid-involved overdoses. As deaths involving synthetic opioids likely reflect use of illicitly-obtained opioids, there may be less of a role for policies targeting the concurrent prescribing of gabapentinoids/Z-drugs with opioids to reduce these deaths.

The Risk of Overdose With Concomitant Use of Z-Drugs and Prescription Opioids: A Population-Based Cohort Study

OBJECTIVE

The Z-drugs (zolpidem, zopiclone, zaleplon) are widely used to treat insomnia in patients receiving prescription opioids, and the risk of overdose resulting from this coprescription has not been explored. The authors compared the rates of overdose among patients using opioids plus Z-drugs and patients using opioids alone.

METHODS

All individuals 15 to 85 years of age receiving prescription opioids, regardless of underlying indication and without evidence of cancer, were identified in the IBM MarketScan database (2004-2017). Patients with concomitant exposure to Z-drugs were matched 1:1 to patients with exposure to prescription opioids alone based on opioid prescribed, morphine equivalents, number of days' supply, and hospitalization within the past 30 days. The primary outcome was any hospitalization or emergency department visit due to an overdose within 30 days, using an intention-to-treat approach. Fine stratification on the propensity score was used to control for confounding.

RESULTS

A total of 510,529 exposed patients and an equal number of matched reference patients were analyzed. There were 217 overdose events among the exposed patients (52.5 events per 10,000 person-years) and 57 events among the reference patients (14.4 events per 10,000 person-years), corresponding to an unadjusted hazard ratio of 3.67 (95% CI=2.75, 4.90). Using fine stratification on the propensity score (c-statistic: 0.66), the adjusted hazard ratio was 2.29 (95% CI=1.79, 2.91). Results were consistent across sensitivity analyses.

CONCLUSIONS

Among patients receiving prescription opioids, after controlling for all confounding factors, concomitant treatment with Z-drugs was associated with a substantial relative increase in the risk of overdose. The potential implications are significant given the large number of opioid-treated patients receiving Z-drugs.