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Record W4376114582 · doi:10.1080/14659891.2023.2202767

Determinants of emergency department use and hospitalization among people who inject drugs: A systematic review and meta-analysis

2023· review· en· W4376114582 on OpenAlexaff
Bahram Armoon, Marie‐Josée Fleury, Mark D. Griffiths, Azadeh Bayani, Rasool Mohammadi, Elaheh Ahounbar

Bibliographic record

VenueJournal of Substance Use · 2023
Typereview
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteDouglas College
Fundersnot available
KeywordsEmergency departmentMedicineScopusInclusion (mineral)Meta-analysisEmergency medicineFamily medicineGerontologyPsychiatryMEDLINEEnvironmental healthPsychologyInternal medicine

Abstract

fetched live from OpenAlex

Background The present study aimed to identify sociodemographic characteristics, risky behaviors, type of drug use, and service use variables associated with emergency department (ED) use and hospitalization among people who inject drugs (PWID).Methods Studies in English published from January 1, 1995, to December 15, 2021, were searched for on PubMed, Scopus, Cochrane, and Web of Science to identify primary studies on ED use and hospitalization among PWID.Results After a detailed assessment of 17,348 outputs, a total of 19 studies met the eligibility criteria for inclusion in the analysis. Greater risks of ED use and hospitalization among PWID were associated with (i) a history of homelessness, (ii) HIV-positive status, and (iii) injecting drugs more than four times per day. Individuals were more likely to use the ED if they (i) had a history of physical abuse, (ii) were using cocaine and methamphetamine, and (iii) had used primary care services. Women and individuals with chronic physical illnesses were more likely to be hospitalized.Conclusions The present study is the first to integrate determinants related to ED use and hospitalization based on sociodemographic characteristics, risky behaviors, type of drug, and service use determinants among PWID. To reduce ED use and hospitalization among PWID, the paper also recommends various strategies could be implemented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0130.002
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.151
GPT teacher head0.401
Teacher spread0.250 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designSystematic review
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2023
Admission routes1
Has abstractyes

Explore more

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