Evidence map›Paper›PMID 32206993›Full record

ArticleJournal of general internal medicine2020

Baseline Factors Associated with Mortality in Patients Who Engaged in Buprenorphine Treatment for Opioid Use Disorder: a Cohort Study.

Danielle R Fine, Liyang Yu, Virginia A Triant, Travis P Baggett, Joshua P Metlay

Open access · hybridAbstract read
In one paragraph

Article in Journal of general internal medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
2.2field-weighted citation impact, top 12% 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

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

  1. Pooled it
  2. Article
  3. Article
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  5. Article
  6. Article
  7. Article
  8. Assessing opioid overdose risk: a review of clinical prediction models utilizing patient-level data.Translational research : the journal of laboratory and clinical medicine · 2021
    Review
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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

5 authors at 2 institutions in 1 country.

Danielle R FineDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA. drfine@mgh.harvard.edu.
Liyang YuDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Virginia A TriantDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Travis P BaggettDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Joshua P MetlayDivision of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
Massachusetts General Hospital · USHarvard University · US

Funding

Enhancing cardiovascular risk estimation in individuals aging with HIV/HCV co-infectionR01AG062393 · NIA · MASSACHUSETTS GENERAL HOSPITAL · PI TRIANT, VIRGINIA ATHENA · 2019 to 2023
$4.5M
Optimizing Cardiovascular Risk Prediction in HIVR01HL132786 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI D'AGOSTINO, RALPH B, TRIANT, VIRGINIA ATHENA · 2017 to 2020
$3.5M
NHLBI NIH HHS R01 HL132786NIA NIH HHS R01 AG062393NIH HHS T32 2015D006913
6 · The paper itself

Abstract

backgroundOpioid agonist therapy (OAT) has been shown to reduce mortality in patients with opioid use disorder (OUD), yet mortality in individuals receiving OAT remains higher than in an age- and gender-matched population.

objectiveTo identify baseline risk factors in patients who engaged in buprenorphine treatment that are associated with this elevated risk of death.

designWe performed a retrospective cohort study from January 1, 2007, to December 31, 2018, using a centralized clinical data registry within a multi-hospital health system in Boston, MA, USA.

participantsAll adult patients who had ≥ 2 consecutive encounters with sublingual buprenorphine on the active medication list from January 1, 2007, to December 31, 2018. MAIN MEASURES: We abstracted several sociodemographic, clinical, and healthcare use characteristics from the clinical data registry. The primary outcome was all-cause mortality and the secondary outcome was opioid overdose-related mortality. We performed multivariable cox regression to identify baseline characteristics independently associated with these outcomes. KEY

resultsOf 5948 patients in the cohort, the majority were white (80.7%) and male (59.7%), with a mean age of 38.2 years. The all-cause mortality rate was 24.0 deaths per 1000 person-years. Baseline characteristics independently associated with an increased hazard of all-cause mortality included homelessness (adjusted hazard ratio [aHR] = 1.39; 95% confidence interval [CI] = 1.09, 1.78), an opioid on the active medication list (aHR = 1.28; 95% CI = 1.08, 1.52), and entry into the cohort during an inpatient hospitalization (aHR = 1.43; 95% CI = 1.18, 1.73). Homelessness was also associated with an increased hazard of opioid overdose-related mortality (aHR = 1.77; 95% CI = 1.25, 2.50).

conclusionsWe identified several novel and potentially modifiable predictors of mortality among patients engaging in buprenorphine treatment who remain at an increased risk of death compared with the general population. Understanding these risk factors can assist healthcare providers in risk stratification and inform the design of targeted interventions to improve outcomes in a high-risk patient population.

Indexed as

BuprenorphineOpioid-Related DisordersAdultAnalgesics, OpioidCohort StudiesFemaleHumansMaleOpiate Substitution TreatmentRetrospective StudiesAnalgesics, OpioidBuprenorphinebuprenorphineopioid abuseopioid-related disorderssubstance abusesubstance-related disorders

Identifiers

PMID32206993
PMCPMC7403281
OpenAlexW3012842323

What OpenQuestion holds

Textmetadata
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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.