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Factors associated with sedative use and misuse among heroin users.

ABSTRACT: BACKGROUND:Rates of both opioid and sedative use and misuse are rising. Comorbid opioid and sedative use is associated with especially severe consequences (e.g., overdose and poor health outcomes). Heroin users report multiple motivations for sedative use, including self-medication. We aimed to understand differences in lifetime substance use characteristics between heroin users with different sedative use histories. METHODS:Substance use data were collected from 385 non-treatment seeking heroin users. Subjects were divided into four lifetime sedative-use groups: no use, medical use only, non-medical use only, and mixed medical and non-medical use. We examined patterns of use of various substances of abuse (tobacco, alcohol, marijuana, cocaine, heroin, and sedatives) and individual characteristics associated with each. RESULTS:Non-medical sedative use (alone or in addition to medical use) was associated with more negative consequences from using all substances. Medical sedative use alone was not related to increased overdose or emergency room visits associated with heroin use. Non-medical sedative use was associated with increases in 15 of the 21 measured heroin consequences and only one of those - health problems - was also associated with medical sedative use. CONCLUSIONS:Concomitant non-medical sedative use and heroin use is associated with significantly greater negative outcomes than those experienced by heroin users who report use of sedatives only as prescribed. Understanding these differences offers insight into risks related to using both substances and may help treatment providers create targeted harm reduction interventions for this population.

SUBMITTER: Moses TEH

PROVIDER: S-EPMC5889740 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Factors associated with sedative use and misuse among heroin users.

Moses Tabitha E H TEH Lundahl Leslie H LH Greenwald Mark K MK

Drug and alcohol dependence 20180202

<h4>Background</h4>Rates of both opioid and sedative use and misuse are rising. Comorbid opioid and sedative use is associated with especially severe consequences (e.g., overdose and poor health outcomes). Heroin users report multiple motivations for sedative use, including self-medication. We aimed to understand differences in lifetime substance use characteristics between heroin users with different sedative use histories.<h4>Methods</h4>Substance use data were collected from 385 non-treatment ...[more]

PMID: 29413433

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Project description:BackgroundInjection drug use is a growing major public health concern. Injection drug users (IDUs) have a higher incidence of co-morbidities including HIV, Hepatitis, and other infections. An effective humoral response is critical for optimal homeostasis and protection from infection; however, the impact of injection heroin use on humoral immunity is poorly understood. We hypothesized that IDUs have altered B cell and antibody profiles.Methods and findingsA comprehensive systems biology-based cross-sectional assessment of 130 peripheral blood B cell flow cytometry- and plasma- based features was performed on HIV-/Hepatitis C-, active heroin IDUs who participated in a syringe exchange program (n = 19) and healthy control subjects (n = 19). The IDU group had substantial polydrug use, with 89% reporting cocaine injection within the preceding month. IDUs exhibited a significant, 2-fold increase in total B cells compared to healthy subjects, which was associated with increased activated B cell subsets. Although plasma total IgG titers were similar between groups, IDUs had significantly higher IgG3 and IgG4, suggestive of chronic B cell activation. Total IgM was also increased in IDUs, as well as HIV Envelope-specific IgM, suggestive of increased HIV exposure. IDUs exhibited numerous features suggestive of systemic inflammation, including significantly increased plasma sCD40L, TNF-?, TGF-?, IL-8, and ceramide metabolites. Machine learning multivariate analysis distilled a set of 10 features that classified samples based on group with absolute accuracy.ConclusionsThese results demonstrate broad alterations in the steady-state humoral profile of IDUs that are associated with increased systemic inflammation. Such dysregulation may impact the ability of IDUs to generate optimal responses to vaccination and infection, or lead to increased risk for inflammation-related co-morbidities, and should be considered when developing immune-based interventions for this growing population.

Project description:BACKGROUND:The US is experiencing an unprecedented opioid overdose epidemic fostered in recent years by regional contamination of the heroin supply with the fentanyl family of synthetic opioids. Since 2011 opioid-related overdose deaths in the East Coast state of Massachusetts have more than tripled, with 75% of the 1374 deaths with an available toxicology positive for fentanyl. Fentanyl is 30-50X more potent than heroin and its presence makes heroin use more unpredictable. A rapid ethnographic assessment was undertaken to understand the perceptions and experiences of people who inject drugs sold as 'heroin' and to observe the drugs and their use. METHODS:A team of ethnographers conducted research in northeast Massachusetts and Nashua, New Hampshire in June 2016, performing (n=38) qualitative interviews with persons who use heroin. RESULTS:(1) The composition and appearance of heroin changed in the last four years; (2) heroin is cheaper and more widely available than before; and (3) heroin 'types' have proliferated with several products being sold as 'heroin'. These consisted of two types of heroin (alone), fentanyl (alone), and heroin-fentanyl combinations. In the absence of available toxicological information on retail-level heroin, our research noted a hierarchy of fentanyl discernment methods, with embodied effects considered most reliable in determining fentanyl's presence, followed by taste, solution appearance and powder color. This paper presents a new 'heroin' typology based on users' reports. CONCLUSION:Massachusetts' heroin has new appearances and is widely adulterated by fentanyl. Persons who use heroin are trying to discern the substances sold as heroin and their preferences for each form vary. The heroin typology presented is inexact but can be validated by correlating users' discernment with drug toxicological testing. If validated, this typology would be a valuable harm reduction tool. Further research on adaptations to heroin adulteration could reduce risks of using heroin and synthetic opioid combinations.

Project description:BACKGROUND:Timely, precise, and localized surveillance of nonfatal events is needed to improve response and prevention of opioid-related problems in an evolving opioid crisis in the United States. Records of naloxone administration found in prehospital emergency medical services (EMS) data have helped estimate opioid overdose incidence, including nonhospital, field-treated cases. However, as naloxone is often used by EMS personnel in unconsciousness of unknown cause, attributing naloxone administration to opioid misuse and heroin use (OM) may misclassify events. Better methods are needed to identify OM. OBJECTIVE:This study aimed to develop and test a natural language processing method that would improve identification of potential OM from paramedic documentation. METHODS:First, we searched Denver Health paramedic trip reports from August 2017 to April 2018 for keywords naloxone, heroin, and both combined, and we reviewed narratives of identified reports to determine whether they constituted true cases of OM. Then, we used this human classification as reference standard and trained 4 machine learning models (random forest, k-nearest neighbors, support vector machines, and L1-regularized logistic regression). We selected the algorithm that produced the highest area under the receiver operating curve (AUC) for model assessment. Finally, we compared positive predictive value (PPV) of the highest performing machine learning algorithm with PPV of searches of keywords naloxone, heroin, and combination of both in the binary classification of OM in unseen September 2018 data. RESULTS:In total, 54,359 trip reports were filed from August 2017 to April 2018. Approximately 1.09% (594/54,359) indicated naloxone administration. Among trip reports with reviewer agreement regarding OM in the narrative, 57.6% (292/516) were considered to include information revealing OM. Approximately 1.63% (884/54,359) of all trip reports mentioned heroin in the narrative. Among trip reports with reviewer agreement, 95.5% (784/821) were considered to include information revealing OM. Combined results accounted for 2.39% (1298/54,359) of trip reports. Among trip reports with reviewer agreement, 77.79% (907/1166) were considered to include information consistent with OM. The reference standard used to train and test machine learning models included details of 1166 trip reports. L1-regularized logistic regression was the highest performing algorithm (AUC=0.94; 95% CI 0.91-0.97) in identifying OM. Tested on 5983 unseen reports from September 2018, the keyword naloxone inaccurately identified and underestimated probable OM trip report cases (63 cases; PPV=0.68). The keyword heroin yielded more cases with improved performance (129 cases; PPV=0.99). Combined keyword and L1-regularized logistic regression classifier further improved performance (146 cases; PPV=0.99). CONCLUSIONS:A machine learning application enhanced the effectiveness of finding OM among documented paramedic field responses. This approach to refining OM surveillance may lead to improved first-responder and public health responses toward prevention of overdoses and other opioid-related problems in US communities.

Project description:BACKGROUND:Polydrug use may challenge effective treatment for substance use disorders. We evaluate whether secondary substance use modifies the association between treatment and primary drug use among primary heroin, cocaine and methamphetamine (MA) users. METHODS:Data were obtained from prospective cohort studies on people who use illicit drugs (PWUD) in California, USA. Using repeated monthly data on self-reported secondary substance use (heroin, cocaine, MA, alcohol or marijuana; ?1day in a month), primary drug use (?1day in a month), and treatment participation, collected via timeline follow-back, we fitted generalized linear mixed multiple regression models controlling for potential confounders to examine the interactions between treatment and secondary substance use on the odds of primary heroin, cocaine and MA use, respectively. RESULTS:Included in our study were 587 primary heroin, 444 primary MA, and 501 primary cocaine users, with a median of 32.4, 13.3 and 18.9 years of follow-up, respectively. In the absence of secondary substance use, treatment was strongly associated with decreased odds of primary drug use (adjusted odds ratios (aORs): 0.25, 95% CI: 0.24, 0.27, 0.07 (0.06, 0.08), and 0.07 (0.07, 0.09)) for primary heroin, MA, and cocaine users, respectively. Secondary substance use of any kind moderated these associations (0.82 (0.78, 0.87), 0.25 (0.21, 0.30) and 0.53 (0.45, 0.61), respectively), and these findings were consistent for each type of secondary substance considered. Moreover, we observed different associations in terms of direction and magnitude between secondary substance use and primary drug use during off-treatment periods across substance types. CONCLUSION:This study demonstrates secondary substance use moderates the temporal associations between treatment and primary drug use among primary heroin, MA and cocaine users. Disparate patterns of polydrug use require careful measurement and analysis to inform targeted treatment for polydrug users.

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Factors associated with sedative use and misuse among heroin users.

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Factors associated with sedative use and misuse among heroin users.

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