Death by Fentanyl - Video

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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.

Corresponding author.

  

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Why the FUSS (Fentanyl Urine Screen Study)? A Cross-Sectional Survey to Characterize an Emerging Threat to People Who Use Drugs in British Columbia, Canada

Background

Fentanyl-detected illicit drug overdose deaths in British Columbia (BC) recently increased dramatically from 13 deaths in 2012 to 90 deaths in 2014, signaling an emerging public health concern. Illicit fentanyl is sold as pills or powders, often mixed with other substances like heroin or oxycodone; reports from coroners suggested that fentanyl was frequently taken unknowingly by people who use drugs. This study aimed to assess the prevalence and characteristics of fentanyl use among clients accessing harm reduction (HR) services in BC.

Methods

Participants attending HR services at 17 sites across BC were invited to complete an anonymous questionnaire describing drugs they have used within the last 3 days and provide a urine sample to test for fentanyl. Data from eligible participants were analyzed using descriptive, bivariate, and multivariate statistical methods.

Results

Surveys from 17 HR sites were received, resulting in analysis of responses from 242 eligible participants. Most participants used multiple substances (median = 3), with crystal meth (59 %) and heroin (52 %) use most frequently reported. Seventy participants (29 %) tested positive for fentanyl, 73 % of whom did not report using fentanyl. Controlling for age, gender, and health authority, reported use of fentanyl (odds ratio (OR) = 6.13, 95 % confidence interval (CI) = [2.52, 15.78], p < 0.001) and crystal methamphetamine (OR = 3.82, 95 % CI = [1.79, 8.63], p < 0.001) use were significantly associated with fentanyl detection.

Conclusions

The proportion of those testing positive who did not report knowingly using fentanyl represents a considerable public health concern. The risk of overdose among this vulnerable population highlights the need for targeted HR strategies, such as increased accessibility to naloxone, overdose education, and urine screens.

Below:  Prevalence of specific substance use and proportion of positive fentanyl test results among participants using these substances

Below:  Percent of participants reporting specific substance use by health authority

Full article at: http://goo.gl/bSpG6s

By:  Ashraf Amlani^1*, Geoff McKee³, Noren Khamis², Geetha Raghukumar², Erica Tsang² andJane A. Buxton¹²

¹British Columbia Centre for Disease Control, 655 West 12th Avenue, Vancouver BC V5Z 4R4, Canada

²Faculty of Medicine, University of British Columbia, Vancouver, Canada

³School of Public and Population Health, University of British Columbia, Vancouver, Canada

 

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Nosocomial hepatitis C virus transmission from tampering with injectable anesthetic opioids

The extent of provider-to-patient hepatitis C virus (HCV) transmission from diversion, self-injection, and substitution ("tampering") of anesthetic opioids is unknown. To quantify the contribution of opioid tampering to nosocomial HCV outbreaks, data from health care-related HCV outbreaks occurring in developed countries from 1990 to 2012 were collated, grouped, and compared. 

Tampering was associated with 17% (8 of 46) of outbreaks, but 53% (438 of 833) of cases. Of the tampering outbreaks, six (75%) involved fentanyl, five (63%) occurred in the United States, and one each in Australia, Israel, and Spain. Case counts ranged from 5 to 275 in the tampering outbreaks (mean, 54.8; median, 25), and 1-99 in the nontampering outbreaks (mean, 10.4; median, 5); between them, the difference in mean ranks of counts was significant (P < 0.01). 

To estimate HCV transmission risks from tampering, risk-assessment models were constructed, and these risks compared with those from surgery. HCV transmission risk from exposure to an opioid preparation tampered by a provider of unknown HCV infection status who is a person who injects drugs (PWID; 0.62%; standard error [SE] = 0.38%) exceeds 16,757 times the risk from surgery by a surgeon of unknown HCV infection status (0.000037%; SE = 0.000029%) and 135 times by an HCV-infected surgeon (0.0046%; SE = 0.0033%). To pose a 50% patient transmission risk, an infected surgeon may take 30 years, compared to <1 year for a PWID tamperer, and weeks or days for a PWID tamperer who intensifies access to opioids.

Disproportionately, many cases of HCV infection from nosocomial outbreaks were attributable to provider tampering of anesthetic opioids. Transmission risk from tampering is substantially higher than from surgery.

Via: http://ht.ly/SxmuB Purchase full article at: http://ht.ly/Sxn2o

By: Hatia RI1, Dimitrova Z1, Skums P1, Teo EY2, Teo CG1.

• 1Division of Viral Hepatitis, Centers for Disease Control and Prevention, Atlanta, GA.
• 2Department of Anesthesiology, Emory University School of Medicine, Atlanta, GA.

The Canary in the Coal Mine Tweets: Social Media Reveals Public Perceptions of Non-Medical Use of Opioids

Below:  Conceptual Framework for Categorizing Twitter Messages Containing Personal Experiences and General Perceptions

Below:  Author of Twitter Messages (individuals, organizations, news outlets, other (user name contained search terms, foreign languages, references to non-opioids)

We reviewed 540 messages, of which 375 (69%) messages were related to opioid behaviors. Of these, 316 (84%) originated from individual user accounts; 125 messages expressed personal experience with opioids. The majority of personal messages referenced using opioids to obtain a “high”, use for sleep, or other non-intended use (87,70%). General attitudes regarding opioid use included positive sentiment (52, 27%), comments on others peoples opioid use (57, 30%), and messages containing public health information or links (48, 25%).

In a sample of social media messages mentioning opioid medications, the most common theme amongst English users related to various forms of opioid misuse. Social media can provide insights into the types of misuse of opioids that might aid public health efforts to reduce non-medical opioid use.

Read more at:   http://goo.gl/ngfokf  HT @UCSF