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Treating Persons Who Inject Drugs: The Need for Holistic and Respectful Care

2019· article· en· W2950150001 on OpenAlexaff
Elizabeth A. Ayello, R. Gary Sibbald

Bibliographic record

VenueAdvances in Skin & Wound Care · 2019
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsTrillium Health CentreUniversity of Toronto
Fundersnot available
KeywordsMedicineAddictionBrain diseaseBuprenorphinePopulationDiseasePsychiatryCellulitisIntervention (counseling)Intensive care medicineSurgeryPathologyInternal medicineEnvironmental health

Abstract

fetched live from OpenAlex

The American Psychiatric Association defines addiction as …a complex condition, a brain disease that is manifested by compulsive substance use despite harmful consequence. People with addiction (severe substance use disorder) have an intense focus on using a certain substance(s)… to the point that it takes over their life.1 With addiction, there are accompanying physical changes in the frontal cortex of the brain that impair judgment, decision-making, learning, memory, and behavior.1 The biochemical rewiring of the brain may make it difficult to overcome addictions even if a patient is motivated to change! One of the most difficult aspects of care is treating persons who inject drugs (PWIDs). This month’s CE/CME article by Dr Barbara Pieper focuses on certain aspects of care for PWIDs, including skin and soft tissue infections, vascular damage/disease, and wounds. Other important findings inlcude the presence of cellulitis and abscesses, especially in the groin and on the legs and feet. Skin and wound healers must be aware of these complications, which can lead to a high morbidity and mortality in this growing patient population. These complications are not always given as much attention in the literature compared with the susceptibility to viral diseases such as HIV or hepatitis C. Dr Pieper and other practitioners like her are very specific in their plea for PWIDs to receive respectful, nonjudgmental care. We must provide a safe environment for PWIDs to seek treatment because they may experience negative attitudes from other healthcare professionals based on their addiction. For regular follow-up of nonacute signs and symptoms, PWIDs should avoid the fragmented treatment from frequent visits to the emergency department, but these patients need to be comfortable with their healthcare providers to access ongoing care. As part of our review of this topic, we reread a 2014 report published by UNAIDS.2 There were several statements in the document that highlight the patient’s voice: “Health-care workers do not trust me, as if I just want drugs,” “I would like to give up drugs, but I cannot get help,” “There are no friendly health-care services near where I live,” “I am treated as a criminal and this makes it hard to take care of my health,” and “Without clean needles and syringes, I have to share.” Statements such as these may help providers understand why PWIDs recognize the signs and symptoms of infection but are reluctant to access healthcare and may delay seeking needed treatment. Dr Pieper recognizes how this stigma can also result in some PWIDs creating their own solutions to address their care needs. Their ad hoc treatment plans can include draining their own abscesses as well as increasing drug use to manage pain, neither of which is likely to lead to desirable health outcomes. An improved and empathetic approach to the management of addictive disorders and patients with these often devastating skin and vascular complications is needed. Closing the gap for these patients could involve healthcare providers advocating to change punitive laws that criminalize drug use, expanding evidence-informed services such as needle exchanges and expert interprofessional addiction services, and reducing stigma and personal discrimination against persons with addiction disorders.2FigureElizabeth A. Ayello, PhD, RN, CWON, ETN, MAPWCA, FAANFigureR. Gary Sibbald, MD, DSc (Hons), MEd, BSc, FRCPC (Med Derm), FAAD, MAPWCA, JM

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.301
Threshold uncertainty score0.679

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.020
GPT teacher head0.355
Teacher spread0.335 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations3
Published2019
Admission routes1
Has abstractyes

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