Evidence map›Paper›PMID 33821724›Full record

ArticleClinical toxicology (Philadelphia, Pa.)2021

Methadone and suboxone

Megan Chenworth, Jeanmarie Perrone, Jennifer S Love, Rachel Graves, Whitney Hogg-Bremer, Abeed Sarker

Open access · bronzeAbstract read
In one paragraph

Article in Clinical toxicology (Philadelphia, Pa.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
3.7field-weighted citation impact, top 7% 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

17 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  17. The Growing Impact of Natural Language Processing in Healthcare and Public Health.Inquiry : a journal of medical care organization, provision and financing
    Review
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

6 authors at 3 institutions in 1 country.

Megan ChenworthDepartment of Emergency Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
Jeanmarie PerroneDepartment of Emergency Medicine, Center for Addiction Medicine and Policy, University of Pennsylvania, Philadelphia, PA, USA.
Jennifer S LoveDepartment of Emergency Medicine, Oregon Health and Science University, Portland, OR, USA.
Rachel GravesDepartment of Emergency Medicine, Center for Addiction Medicine and Policy, University of Pennsylvania, Philadelphia, PA, USA.
Whitney Hogg-BremerDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, USA.
Abeed SarkerDepartment of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, USA.
University of Pennsylvania · USEmory University · USOregon Health & Science University · US

Funding

Mining Social Media Big Data for Toxicovigilance: Automating the Monitoring of Prescription Medication Abuse via Natural Language Processing and Machine Learning MethodsR01DA046619 · NIDA · UNIVERSITY OF PENNSYLVANIA · PI SARKER, ABEED H · 2018 to 2021
$1.4M
NIDA NIH HHS R01 DA046619
6 · The paper itself

Abstract

backgroundAccording to the latest medical evidence, Methadone and buprenorphine-naloxone (Suboxone

objectiveThis study aimed to use Twitter to assess the public perceptions about methadone and buprenorphine-naloxone, and to compare their discussion contents based on themes/topics, subthemes, and sentiment.

methodsWe conducted a descriptive analysis of a small and automatic analysis of a large volume of microposts ("tweets") that mentioned "

resultsWe manually analyzed 900 tweets, most of which related to

conclusionsTwitter content about methadone and Suboxone

Indexed as

Opiate Substitution TreatmentPublic OpinionSocial MediaAnalgesics, OpioidBuprenorphine, Naloxone Drug CombinationHumansMethadoneNarcotic AntagonistsNatural Language ProcessingOpioid-Related DisordersAnalgesics, OpioidBuprenorphine, Naloxone Drug CombinationMethadoneNarcotic Antagonistsbuprenorphinemedication assisted treatmentmethadoneopioid use disordersocial mediaTwitter

Identifiers

PMID33821724
PMCPMC9177078
OpenAlexW3151188302

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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.