No association between HIV status and risk of non-fatal overdose among people who inject drugs in Vancouver, Canada

BACKGROUND:

The evidence to date on whether HIV infection increases the risk of accidental drug overdose among people who inject drugs (PWID) is equivocal. Thus, we sought to estimate the effect of HIV infection on risk of non-fatal overdose among two parallel cohorts of HIV-positive and -negative PWID.

METHODS:

Data were collected from a prospective cohort of PWID in Vancouver, Canada between 2006 and 2013. During biannual follow-up assessments, non-fatal overdose within the previous 6months was assessed. Bivariable and multivariable generalized mixed-effects regression models were used to determine the unadjusted and adjusted associations between HIV status, plasma HIV-1 RNA viral load, and likelihood of non-fatal overdose.

RESULTS:

A total of 1760 eligible participants (67% male, median age=42, and 42% HIV-positive at baseline) were included. Among 15,070 unique observations, 649 (4.3%) included a report of a non-fatal overdose within the previous 6months (4.4% among seropositive and 4.3% among seronegative individuals). We did not observe a difference in the likelihood of overdose by HIV serostatus in crude (odds ratio [OR]: 1.05, p=0.853) analyses or analyses adjusted for known overdose risk factors (adjusted OR [AOR]: 1.19, p=0.474). In a secondary analysis, among HIV-positive PWID, we did not observe an association between having a detectable viral load and overdose (AOR: 1.03, p=0.862).

CONCLUSIONS:

Despite the evidence that HIV infection is a risk factor for fatal overdose, we found no evidence for a relationship between HIV disease and non-fatal overdose. However, overdose remains high among PWID, indicating the need for ongoing policy addressing this problem, and research into understanding modifiable risk factors that predict non-fatal overdose.

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By:  Escudero DJ1, Marshall BD1, Kerr T2, Hayashi K2, Feng C3, Guillemi SA3, Hogg RS3, Montaner J2, Wood E2, Milloy MJ4.

• 1Department of Epidemiology, Brown University School of Public Health, 2nd Floor, 121 S. Main St., Providence, RI 02906, United States.
• 2British Columbia Centre for Excellence in HIV/AIDS, 608-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada; Division of AIDS, Department of Medicine, University of British Columbia, 667-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada.
• 3British Columbia Centre for Excellence in HIV/AIDS, 608-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada.
• 4British Columbia Centre for Excellence in HIV/AIDS, 608-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada; Division of AIDS, Department of Medicine, University of British Columbia, 667-1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada. Electronic address: uhri-mjsm@cfenet.ubc.ca. 
• Addict Behav. 2016 Apr 1;60:8-12. doi: 10.1016/j.addbeh.2016.03.029. 

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Neighborhood-Level & Spatial Characteristics Associated with Lay Naloxone Reversal Events & Opioid Overdose Deaths

There were over 23,000 opioid overdose deaths in the USA in 2013, and opioid-related mortality is increasing. Increased access to naloxone, particularly through community-based lay naloxone distribution, is a widely supported strategy to reduce opioid overdose mortality; however, little is known about the ecological and spatial patterns of the distribution and utilization of lay naloxone. 

This study aims to investigate the neighborhood-level correlates and spatial relationships of lay naloxone distribution and utilization and opioid overdose deaths. We determined the locations of lay naloxone distribution sites and the number of unintentional opioid overdose deaths and reported reversal events in San Francisco census tracts (n = 195) from 2010 to 2012. 

We used Wilcoxon rank-sum tests to compare census tract characteristics across tracts adjacent and not adjacent to distribution sites and multivariable negative binomial regression models to assess the association between census tract characteristics, including distance to the nearest site, and counts of opioid overdose deaths and naloxone reversal events. 

Three hundred forty-two opioid overdose deaths and 316 overdose reversals with valid location data were included in our analysis. Census tracts including or adjacent to a distribution site had higher income inequality, lower percentage black or African American residents, more drug arrests, higher population density, more overdose deaths, and more reversal events (all p < 0.05). 

In multivariable analysis, greater distance to the nearest distribution site (up to a distance of 4000 m) was associated with a lower count of Naloxone reversals [incidence rate ratio (IRR) = 0.51 per 500 m increase, 95% CI 0.39-0.67, p < 0.001] but was not significantly associated with opioid overdose deaths. 

These findings affirm that locating lay naloxone distribution sites in areas with high levels of substance use and overdose risk facilitates reversals of opioid overdoses in those immediate areas but suggests that alternative delivery methods may be necessary to reach individuals in other areas with less concentrated risk.

Purchase full article at:   http://goo.gl/V40N93

By:  Rowe C1, Santos GM2,3, Vittinghoff E3, Wheeler E4, Davidson P5, Coffin PO2,3.

• 1San Francisco Department of Public Health, 25 Van Ness Avenue, Ste. 500, San Francisco, CA, 94102, USA. chris.rowe@sfdph.org.
• 2San Francisco Department of Public Health, 25 Van Ness Avenue, Ste. 500, San Francisco, CA, 94102, USA.
• 3University of California, San Francisco, 500 Parnassus Avenue, San Francisco, CA, 94143, USA.
• 4Drug Overdose Prevention and Education Project, Harm Reduction Coalition, 1440 Broadway, Suite 902, Oakland, CA, 94612, USA.
• 5University of California, San Diego, 9500 Gilman Drive, La Jolla, California, CA, 92093, USA. 

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The Role of Clinicians in Addressing the Opioid Overdose Epidemic - Slides

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Stakeholder Perceptions & Operational Barriers in the Training & Distribution of Take-Home Naloxone within Prisons in England

BACKGROUND:

The aim of the study was to assess potential barriers and challenges to the implementation of take-home naloxone (THN) across ten prisons in one region of England.

METHODS:

Qualitative interviews deploying a grounded theory approach were utilised over a 12- to 18-month period that included an on-going structured dialogue with strategic and operational prison staff from the ten prisons and other key stakeholders (n = 17). Prisoner perceptions were addressed through four purposive focus groups belonging to different establishments (n = 26). Document analysis also included report minutes and access to management information and local performance reports. The data were thematically interpreted using visual mapping techniques.

RESULTS:

The distribution and implementation of THN in a prison setting was characterised by significant barriers and challenges. As a result, four main themes were identified: a wide range of negative and confused perceptions of THN amongst prison staff and prisoners; inherent difficulties with the identification and engagement of eligible prisoners; the need to focus on individual prison processes to enhance the effective distribution of THN; and the need for senior prison staff engagement.

CONCLUSIONS:

The distribution of THN within a custodial setting requires consideration of a number of important factors which are discussed...

Since I’ve come to this jail, everyone [has been] banging on about getting myself sorted and off the drugs and everything you know. It’s taken a while and I’m in the right place to move forward for once, no more gear – nothing. I’m done with that life….. I’m clean now with no intention of using, so why do I need this? [Male prisoner, Prison 5]

What’ll happen is that I will leave here and as soon I get my feet on the ground the police will stop me, as always, and say…..’What’s this? You must be using again - you’re nicked [arrested]'. [Male prisoner, Prison 2]

Many of my staff understand what we are trying to do here which is get prisoners off drugs and abstinent by the time they leave here…if not abstinent entirely then at least in a positon to consider an abstinent life. For many staff, and it’s not just uniformed staff [prison officers], just handing out Naloxone give out the wrong message that says it’s alright now you can keep on using. I don’t agree with this view myself but I know they [staff] think it. [Healthcare Manager, Naloxone Action Group]

I am very concerned that Naloxone could be given out by prison officers or anyone else without healthcare input. The risks will be too great if something went wrong and the wrong person got hold of it. [Healthcare nurse, Naloxone Action Group] 

Full article at:   http://goo.gl/588N9e

By:   Sondhi A1, Ryan G2, Day E3.

• 1Therapeutic Solutions (Addictions) Communications House, 26 York Street, London, W1U 6PZ, UK. arun.sondhi@therapeutic-solutions.org.uk.
• 2Public Health England, 2nd Floor Skipton House London Road Elephant & Castle, London, SE1 6LH, UK.
• 3Addiction Psychiatry, Addictions Department, National Addiction Centre, Addiction Sciences Building, 4 Windsor Walk, Denmark Hill, London, SE5 8AF, UK.
• Harm Reduct J. 2016 Feb 3;13(1):5. doi: 10.1186/s12954-016-0094-1. 

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Correlates of Overdose Risk Perception among Illicit Opioid Users

BACKGROUND:

Opioid-related mortality continues to increase in the United States. The current study assesses demographic and behavioral predictors of perceived overdose risk among individuals who use opioids illicitly. By examining these correlates in the context of established overdose risk factors, we aim to assess whether characteristics and behaviors that have been associated with actual overdose risk translate to higher perception of risk.

METHODS:

We conducted a cross-sectional survey of 172 adult illicit opioid users in San Francisco, CA and used multivariable logistic regression to identify predictors of perception of high risk for opioid overdose.

RESULTS:

Age (aOR=0.96, 95%CI=0.93-1.00) and number of injection days per month (0.91, 0.86-0.97) were associated with a lower odds of perceived high overdose risk. There was no independent association between use of opioid analgesics, concurrent use of opioids and benzodiazepines or cocaine, or HIV status and overdose risk perception.

CONCLUSIONS:

Opioid users who injected more frequently and those who were older were less likely to perceive themselves as being at risk of overdose, notwithstanding that those who inject more are at higher risk of overdose and those who are older are at higher risk overdose mortality. In addition, despite being established overdose risk factors, there was no relationship between use of opioid analgesics, concurrent use of opioids and cocaine or benzodiazepines, or self-reported HIV status and overdose risk perception. These findings highlight key populations of opioid users and established risk factors that may merit focused attention as part of education-based overdose prevention and opioid management strategies.

Purchase full article at:   http://goo.gl/guoVZL

By:  Rowe C1, Santos GM2, Behar E3, Coffin PO2.

• 1San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102, USA. Electronic address: chris.rowe@sfdph.org.
• 2San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102, USA; University of California, San Francisco, 500 Parnassus Avenue, San Francisco, CA 94143, USA.
• 3San Francisco Department of Public Health, 25 Van Ness Avenue, Suite 500, San Francisco, CA 94102, USA. 
• Drug Alcohol Depend. 2015 Dec 30. pii: S0376-8716(15)01833-5. doi: 10.1016/j.drugalcdep.2015.12.018. 

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What are opioids:  http://goo.gl/ncoQ9R 

Extended-Release Naltrexone: A Qualitative Analysis of Barriers to Routine Use

Highlights

• The Consolidated Framework for Implementation Research structured a qualitative analysis of features of extended-release naltrexone that inhibited use for the treatment of alcohol and opioid use disorders.
• The processes of ordering, storing, and using and the cost of extended-release naltrexone were characteristics of the intervention that reduced use.
• Features of the outer setting (environment) that inhibited use included requirements for patients with opioid use disorders to be opioid free for 7 to 10 days and health plan formulary, benefit management, and reimbursement policies.
• Program cultures, resistance to change, and weak linkages with primary care for ongoing injections also affected routine use of the medication.

The Medication Research Partnership (a national health plan and nine addiction treatment centers contracted with the health plan) sought to facilitate the adoption of pharmacotherapy for alcohol and opioid use disorders. Qualitative analysis of interviews with treatment center change leaders, individuals working for the manufacturer and its technical assistance contractor, and health plan managers extracted details on the processes used to order, store, bill for, and administer extended-release naltrexone. Qualitative themes were categorized using domains from the Consolidated Framework for Implementation Research (intervention characteristics, outer setting, inner setting, and provider characteristics).

Characteristics of XR-NTX that inhibited use included the complexity of ordering and using the medication; cost was also a barrier. Outer setting barriers reflected patient needs and external health plan policies on formulary coverage, benefit management, and reimbursement. Program structures, the lack of physician linkages, a culture resistant to the use of medication, and unease with change were inner setting elements that limited use of XR-NTX. Patient stereotypes and a lack of knowledge about XR-NTX affected practitioner willingness to treat patients and prescribe XR-NTX. The Consolidated Framework for Implementation Research provided a useful lens to understand and interpret the processes affecting access to XR-NTX.

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By:   Kelly Alanis-Hirsch, P.hD.,  Raina Croff, Ph.D., James H. Ford II, Ph.D., Kim Johnson, Ph.D., Mady Chalk, Ph.D., Laura Schmidt, Ph.D., Dennis McCarty, Ph.D.

Affiliations

OHSU-PSU School of Public Health, Oregon Health & Science University

Correspondence

Corresponding author at: OHSU-PSU School of Public Health, Oregon Health & Science University, 3181 SW Sam Jackson Park Road, Portland, OR 97239. Tel.: +503 494 1177.

mccartyd@ohsu.edu

DOI: http://dx.doi.org/10.1016/j.jsat.2015.10.003

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Opioid Prescribing After Nonfatal Overdose and Association with Repeated Overdose

BACKGROUND:

Nonfatal opioid overdose is an opportunity to identify and treat substance use disorders, but treatment patterns after the overdose are unknown.

OBJECTIVE:

To determine prescribed opioid dosage after an opioid overdose and its association with repeated overdose.

SETTING:

A large U.S. health insurer.

PARTICIPANTS:

2848 commercially insured patients aged 18 to 64 years who had a nonfatal opioid overdose during long-term opioid therapy for noncancer pain between May 2000 and December 2012.

MEASUREMENTS:

Nonfatal opioid overdose was identified using International Classification of Diseases, Ninth Revision, Clinical Modification, codes from emergency department or inpatient claims. The primary outcome was daily morphine-equivalent dosage (MED) of opioids dispensed from 60 days before to up to 730 days after the index overdose. We categorized dosages as large (≥100 mg MED), moderate (50 to <100 mg MED), low (<50 mg MED), or none (0 mg MED). Secondary outcomes included time to repeated overdose stratified by daily dosage as a time-varying covariate.

RESULTS:

Over a median follow-up of 299 days, opioids were dispensed to 91% of patients after an overdose. Seven percent of patients (n = 212) had a repeated opioid overdose. At 2 years, the cumulative incidence of repeated overdose was 17% (95% CI, 14% to 20%) for patients receiving high dosages of opioids after the index overdose, 15% (CI, 10% to 21%) for those receiving moderate dosages, 9% (CI, 6% to 14%) for those receiving low dosages, and 8% (CI, 6% to 11%) for those receiving no opioids.

LIMITATION:

The cohort was limited to commercially insured adults.

CONCLUSION:

Almost all patients continue to receive prescription opioids after an overdose. Opioid discontinuation after overdose is associated with lower risk for repeated overdose.

Purchase full article at:   http://goo.gl/SEQNPN

By:   Larochelle MR, Liebschutz JM, Zhang F, Ross-Degnan D, Wharam JF.

From Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston University School of Medicine, and Boston Medical Center, Boston, Massachusetts.

Ann Intern Med. 2015 Dec 29. doi: 10.7326/M15-0038. [Epub ahead of print]

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Non-Fatal Overdoses & Related Risk Factors among People Who Inject Drugs in St. Petersburg, Russia & Kohtla-Järve, Estonia

Background

This study seeks to identify the prevalence of, and risk factors associated with, non-fatal overdose among people currently injecting drugs (PWID) in St. Petersburg (Russia) and in Kohtla-Järve (Estonia).

Methods

Five hundred eighty-eight study participants in Kohtla-Järve (in 2012) and 811 in St. Petersburg (in 2012–2013) were recruited using respondent driven sampling for interviewing and HIV testing.

Results

Three-quarters (76 %) of the current PWID were male. Participants from St. Petersburg were older (mean age 32.1 vs. 29.6 years, p < 0.0001) and reported a longer average duration of injecting drugs (mean duration: 13.3 vs. 10.9 years, p < 0.0001). Main drugs injected were opioids (fentanyl in Kohtla-Järve, heroin in St Petersburg). HIV prevalence was 63 % (95 % CI 59–67 %) in Kohtla-Järve and 56 % (95 % CI 52–59 %) in St. Petersburg. Two thirds of the PWID in Kohtla-Järve and St. Petersburg reported ever having experienced a drug overdose involving loss of consciousness or stopping breathing. In Kohtla-Järve, 28 % (95 % CI 24–31 %) of participants and, in St Petersburg, 16 % (95 % CI 14–19 %) of participants reported an overdose within the previous 12 months. Characteristics of injection drug use practice (longer duration of injection drug use, main drug injected), correlates of high-risk injection behaviour (higher injecting frequency, sharing), and problem alcohol use were associated with the risk of overdose within the previous 12 months. The significant factors effects did not differ between the sites.

Conclusions

PWID are at high risk for overdose. Effective overdose prevention efforts at the public health scale are therefore warranted.

Table 1

Socio-demographic, injection drug use, HIV prevalence and care and environmental characteristics of current injection drug users participating and the prevalence of self-reported non lethal overdose within the last 12 months from cross sectional studies in Kohtla-Järve, Estonia (in 2012) and St Petersburg, Russia (in 2012 – 2013)

	Kohtla-Järve (Estonia), N = 588			St Petersburg (Russia), N = 811
Characteristics	n	%	Overdose last 12 months (%)	n	%	Overdose last 12 months (%)
Socio-demographi indicators
Age			p = 0.134			p = 0.337
29 or less	295	50 %	25 %	245	30 %	18 %
30 or more	293	50 %	30 %	566	70 %	15 %
Gender			p = 0.833			p = 0.423
Male	435	74 %	27 %	631	78 %	16 %
Female	152	26 %	28 %	180	22 %	18 %
Main source of income (last 6 months)			p = 0.239			p = 0.021
Work (full/part time)	192	33 %	23 %	590	73 %	14 %
Social benefits	263	45 %	30 %	22	3 %	14 %
Other	127	22 %	31 %	199	25 %	23 %
Drug use characteristics
Duration of injecting			p < 0.001			p = 0.008
< = 9 years	230	39 %	16 %	170	21 %	9 %
= > 10 years	356	61 %	35 %	640	79 %	18 %
Frequency of injecting (last 4 weeks)			p < 0.001			p < 0.001
< Daily	447	76 %	24 %	524	65 %	11 %
Daily +	139	24 %	40 %	287	35 %	26 %
Main drug injected (last 4 weeks)			p < 0.001			p = 0.116
Amphetamine	195	35 %	14 %	27	3 %	4 %
Fentanyl	350	62 %	34 %	4	0 %	25 %
Heroin	1	0 %		563	69 %	18 %
Methadone	0	0 %		217	27 %	14 %
Injecting multiple drugs (last 4 weeks)			p = 0.124			p = 0.003
No	378	64 %	25 %	495	61 %	8 %
Yes	210	36 %	31 %	316	39 %	21 %
Non-injecting drug use (last 4 weeks)			p = 0.575			p = 0.037
No	324	57 %	27 %	755	93 %	15 %
Yes	246	43 %	29 %	56	7 %	27 %
Sharing (last 4 weeks)			p < 0.001			p < 0.001
No	492	85 %	24 %	277	34 %	7 %
Yes	88	15 %	49 %	534	66 %	21 %
Problem alcohol use			p = 0.009			p < 0.001
No	247	42 %	22 %	275	34 %	8 %
Yes	341	58 %	32 %	536	66 %	21 %
Mental health (MHI 5)			p = 0.003			p < 0.001
> = 52	362	62 %	23 %	536	66 %	13 %
<52	221	38 %	35 %	275	34 %	23 %
Structural (environmental) characteristics
Homelessness (current)			p = 0.619			p = 0.454
No	583	99 %	27 %	798	98 %	16 %
Yes	5	1 %	40 %	13	2 %	14 %
Ever been in prison			p < 0.001			p = 0.368
No	266	45 %	19 %	537	66 %	17 %
Yes	322	55 %	35 %	274	34 %	15 %
Main source of syringes (last 4 weeks)			p = 0.0018			p = 0.0121
Needle and syringe program (NSP)	445	77 %	30 %	119	15 %	11 %
Pharmacy	76	13 %	16 %	615	76 %	19 %
Other	26	5 %	35 %	30	4 %	10 %
None	29	5 %	7 %	46	6 %	4 %
Currently receiving drug treatment			p > 0.9			p = 0.133
No	216	68 %	32 %	563	97 %	18 %
Yes	102	32 %	32 %	19	3 %	32 %
HIV infection and care
HIV infected			p = 0.013			p = 0.021
No	218	37 %	22 %	359	44 %	13 %
Yes	370	63 %	31 %	452	56 %	19 %
Currently on ART			p = 0.342			p = 0.051
No	247	67 %	33 %	403	90 %	20 %
Yes	123	33 %	28 %	47	10 %	9 %

Full article at:   http://goo.gl/3bJM3D

By:   Anneli Uusküla, Mait Raag, Sigrid Vorobjov, Kristi Rüütel, Alexandra Lyubimova, Olga S. Levina, and Robert Heimer

Department of Public Health, University of Tartu, Ravila st 19, 50409 Tartu, Estonia

Infectious Diseases and Drug Monitoring Department, National Institute for Health Development, Hiiu 42, 11619 Tallinn, Estonia

NGO Stellit, St Petersburg, Russian Federation

Department of Epidemiology of Microbial Diseases and the Center for Interdisciplinary Research on AIDS, Yale University School of Public Health, 60 College St, New Haven, CT 06510 USA

Anneli Uusküla, Phone: + 3727374195, Email: ee.tu@aluksuu.ilenna.

Contributor Information.

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