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Record W2110698169 · doi:10.2174/1874279301206010005

Determinants of Cutaneous Injection-Related Infections Among Injection Drug Users at an Emergency Department

2012· article· en· W2110698169 on OpenAlexafffund
Elisa Lloyd‐Smith

Bibliographic record

VenueThe Open Infectious Diseases Journal · 2012
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of British ColumbiaProvidence Health CareAIDS Vancouver
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchHealth CanadaMichael Smith Health Research BC
KeywordsMedicineHazard ratioConfidence intervalReferralEmergency departmentEmergency medicineIncidence (geometry)Proportional hazards modelInternal medicineDowntownFamily medicinePsychiatry

Abstract

fetched live from OpenAlex

INTRODUCTION: Cutaneous injection-related infections (CIRI) are a primary reason injection drug users (IDU) access the emergency department (ED). METHODOLOGY: Using Cox proportional hazard regression, we examined predictors of ED use for CIRI, stratified by sex, among 1083 supervised injection facility (SIF) users. RESULTS: Over a four-year period, 289 (27%) visited the ED for CIRI, yielding an incidence density for females of 23.8 (95% confidence interval (CI): 19.3 - 29.0) and males of 19.2 per 100 person-years (95% CI: 16.7 - 22.1). Factors associated with ED use for CIRI among females included residing in the Downtown Eastside (DTES) (adjusted hazard ratio [AHR] = 2.06 [1.13 - 3.78]) and being referred to hospital by SIF nurses (AHR = 4.48 [2.76 - 7.30]). Among males, requiring assistance with injection (AHR = 1.38 [1.01 - 1.90]), being HIV-positive (AHR = 1.85 [1.34 - 2.55]), and being referred to hospital by SIF nurses (AHR = 2.97 [1.93 - 4.57]) were associated with an increased likelihood of an ED visit for CIRI. CONCLUSION: These results suggest SIF nurses have facilitated referral of hospital treatment for CIRI, highlighting the need for continued development of efficient and collaborative efforts to reduce the burden of CIRI.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.346
Teacher spread0.320 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2012
Admission routes2
Has abstractyes

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