Evidence map›Paper›PMID 31919146›Full record

ArticleJournal of epidemiology and community health2020

Individual and county-level variation in outcomes following non-fatal opioid-involved overdose.

Evan Marie Lowder, Joseph Amlung, Bradley R Ray

Open access · hybridAbstract read
In one paragraph

Article in Journal of epidemiology and community health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
4.1field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 39 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 2 countries.

Evan Marie LowderCriminology, Law and Society, George Mason University, Fairfax, Virginia, USA elowder@gmu.edu.ORCID 0000-0002-5855-2479
Joseph AmlungRegenstrief Institute, Indianapolis, Indiana, USA.
Bradley R RaySchool of Social Work, Wayne State University, Detroit, Michigan, USA.
George Mason University · USRegenstrief Institute · USWayne State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA lack of large-scale, individually linked data often has impeded efforts to disentangle individual-level variability in outcomes from area-level variability in studies of many diseases and conditions. This study investigated individual and county-level variability in outcomes following non-fatal overdose in a state-wide cohort of opioid overdose patients.

methodsParticipants were 24 031 patients treated by emergency medical services or an emergency department for opioid-involved overdose in Indiana between 2014 and 2017. Outcomes included repeat non-fatal overdose, fatal overdose and death. County-level predictors included sociodemographic, socioeconomic and treatment availability indicators. Individual-level predictors included age, race, sex and repeat non-fatal opioid-involved overdose. Multilevel models examined outcomes following non-fatal overdose as a function of patient and county characteristics.

results10.9% (n=2612) of patients had a repeat non-fatal overdose, 2.4% (n=580) died of drug overdose and 9.2% (n=2217) died overall. Patients with a repeat overdose were over three times more likely to die of drug-related causes (OR=3.68, 99.9% CI 2.62 to 5.17, p<0.001). County-level effects were limited primarily to treatment availability indicators. Higher rates of buprenorphine treatment providers were associated with lower rates of mortality (OR=0.82, 95% CI 0.68 to 0.97, p=0.024), but the opposite trend was found for naltrexone treatment providers (OR=1.20, 95% CI 1.03 to 1.39, p=0.021). Cross-level interactions showed higher rates of Black deaths relative to White deaths in counties with high rates of naltrexone providers (OR=1.73, 95% CI 1.09 to 2.73, p=0.019).

conclusionAlthough patient-level differences account for most variability in opioid-related outcomes, treatment availability may contribute to county-level differences, necessitating multifaceted approaches for the treatment and prevention of opioid abuse.

Indexed as

AdultAnalgesics, OpioidBlack or African AmericanBlack PeopleCohort StudiesEmergency Medical ServicesEthnicityFemaleHumansIndianaLocal GovernmentMaleMiddle AgedMultilevel AnalysisNaltrexoneNarcotic AntagonistsAnalgesics, OpioidNaltrexoneNarcotic Antagonistsepidemiologygeographymortalitymultilevel modellingsubstance abuse

Identifiers

PMID31919146
PMCPMC7079264
OpenAlexW3000133335

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.