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Record W4385783385 · doi:10.1177/10436596231191248

Secondary Prophylaxis Among First Nations People With Acute Rheumatic Fever in Australia: An Integrative Review

2023· review· en· W4385783385 on OpenAlexaboutno aff
Kerissa Govender, Amanda Müller

Bibliographic record

VenueJournal of Transcultural Nursing · 2023
Typereview
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsCINAHLMedicineThematic analysisCritical appraisalAcute rheumatic feverFamily medicineAlternative medicineRheumatic feverNursingQualitative researchPsychological interventionInternal medicine

Abstract

fetched live from OpenAlex

INTRODUCTION: The prevalence of acute rheumatic fever (ARF) and rheumatic heart disease (RHD) among Australia's First Nations populations are some of the highest in the world, accounting for 95% of the 2,244 ARF notifications between 2015 and 2019 in Australia. A key issue in treating ARF is long-term secondary prophylaxis, yet only one in five patients received treatment in 2019. This review identifies barriers to secondary prophylaxis of ARF in Australia's First Nations people. METHODS: An integrative review was undertaken utilizing PubMed, CINAHL, ProQuest, and Wiley Online. Joanna Briggs Institute critical appraisal tools were used, followed by thematic analysis. RESULTS: The key themes uncovered included: issues with database and recall systems, patient/family characteristics, service delivery location and site, pain of injection, education (including language barriers), and patient-clinician relationship. CONCLUSIONS: A national RHD register, change in operation model, improved pain management, improved education, and need for consistent personnel is suggested.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.882
Threshold uncertainty score0.896

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.053
GPT teacher head0.395
Teacher spread0.342 · 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 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

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