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Gabapentin prevalence: clinical and forensic experience in St. Louis, Missouri, USA.

ABSTRACT: Gabapentin (Neurontin) is an anti-epileptic drug that has had wide off-label prescription use since market release due to presumed negligible abuse potential. However, trends in drug misuse have demonstrated that gabapentin misuse is occurring, particularly in those with a history of opioid misuse. This is concerning, because although gabapentin has no direct ligand activity at opioid receptors, it does potentiate the analgesic effect of opioids, and concurrent use of gabapentin and opioids may increase the risk of respiratory depressive effects of opioids. This study investigates the incidence of gabapentin detected in urine samples collected for clinical drug screening purposes in a local hospital emergency department and in postmortem samples submitted by medical examiners in the St. Louis metropolitan area. The prevalence of gabapentin and co-detected drugs in both populations is contrasted, compared, and discussed. This study found that 30% of urine samples collected from patients with suspected drug intoxication presenting to SSM Health Saint Louis University Hospital, a quaternary care medical center, were positive for gabapentin, and nearly two thirds of those were also positive for oxycodone. Over a 6-month period, the incidence of gabapentin positive postmortem cases increased from 18% to 20%. Nearly all gabapentin positive postmortem cases were also positive for an opioid, the most significant being fentanyl, suggesting that gabapentin misuse may be due to its potentiating effect of opioid drug action. This study also highlights the limited utility of immunoassay-based urine drug screens.

SUBMITTER: Riley SB

PROVIDER: S-EPMC8635626 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:ImportanceIn the absence of a national strategy in response to the COVID-19 pandemic, many public health decisions fell to local elected officials and agencies. Outcomes of such policies depend on a complex combination of local epidemic conditions and demographic features as well as the intensity and timing of such policies and are therefore unclear.ObjectiveTo use a decision analytical model of the COVID-19 epidemic to investigate potential outcomes if actual policies enacted in March 2020 (during the first wave of the epidemic) in the St Louis region of Missouri had been delayed.Design, setting, and participantsA previously developed, publicly available, open-source modeling platform (Local Epidemic Modeling for Management & Action, version 2.1) designed to enable localized COVID-19 epidemic projections was used. The compartmental epidemic model is programmed in R and Stan, uses bayesian inference, and accepts user-supplied demographic, epidemiologic, and policy inputs. Hospital census data for 1.3 million people from St Louis City and County from March 14, 2020, through July 15, 2020, were used to calibrate the model.ExposuresHypothetical delays in actual social distancing policies (which began on March 13, 2020) by 1, 2, or 4 weeks. Sensitivity analyses were conducted that explored plausible spontaneous behavior change in the absence of social distancing policies.Main outcomes and measuresHospitalizations and deaths.ResultsA model of 1.3 million residents of the greater St Louis, Missouri, area found an initial reproductive number (indicating transmissibility of an infectious agent) of 3.9 (95% credible interval [CrI], 3.1-4.5) in the St Louis region before March 15, 2020, which fell to 0.93 (95% CrI, 0.88-0.98) after social distancing policies were implemented between March 15 and March 21, 2020. By June 15, a 1-week delay in policies would have increased cumulative hospitalizations from an observed actual number of 2246 hospitalizations to 8005 hospitalizations (75% CrI: 3973-15 236 hospitalizations) and increased deaths from an observed actual number of 482 deaths to a projected 1304 deaths (75% CrI, 656-2428 deaths). By June 15, a 2-week delay would have yielded 3292 deaths (75% CrI, 2104-4905 deaths)-an additional 2810 deaths or a 583% increase beyond what was actually observed. Sensitivity analyses incorporating a range of spontaneous behavior changes did not avert severe epidemic projections.Conclusions and relevanceThe results of this decision analytical model study suggest that, in the St Louis region, timely social distancing policies were associated with improved population health outcomes, and small delays may likely have led to a COVID-19 epidemic similar to the most heavily affected areas in the US. These findings indicate that an open-source modeling platform designed to accept user-supplied local and regional data may provide projections tailored to, and more relevant for, local settings.

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Gabapentin prevalence: clinical and forensic experience in St. Louis, Missouri, USA.

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