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Record W4200007066 · doi:10.1371/journal.pntd.0009954

Roadblocks in Chagas disease care in endemic and nonendemic countries: Argentina, Colombia, Spain, and the United States. The NET-Heart project

2021· review· en· W4200007066 on OpenAlexaff
Andrés F. Miranda‐Arboleda, Ezequiel Zaidel, Rachel Marcus, María‐Jesús Pinazo, Luis Eduardo Echeverría, Clara Saldarriaga, Álvaro Sosa Liprandi, Adrián Baranchuk

Bibliographic record

VenuePLoS neglected tropical diseases · 2021
Typereview
Languageen
FieldMedicine
TopicTrypanosoma species research and implications
Canadian institutionsKingston Health Sciences CentreQueen's University
Fundersnot available
KeywordsLatin AmericansMedicinePublic healthNeglected tropical diseasesChagas diseaseHealth careDiseaseGlobal healthEnvironmental healthEconomic growthPolitical scienceImmunologyNursing

Abstract

fetched live from OpenAlex

BACKGROUND: Chagas disease (CD) is endemic in Latin America; however, its spread to nontropical areas has raised global interest in this condition. Barriers in access to early diagnosis and treatment of both acute and chronic infection and their complications have led to an increasing disease burden outside of Latin America. Our goal was to identify those barriers and to perform an additional analysis of them based on the Inter American Society of Cardiology (SIAC) and the World Heart Federation (WHF) Chagas Roadmap, at a country level in Argentina, Colombia, Spain, and the United States, which serve as representatives of endemic and nonendemic countries. METHODOLOGY AND PRINCIPAL FINDINGS: This is a nonsystematic review of articles published in indexed journals from 1955 to 2021 and of gray literature (local health organizations guidelines, local policies, blogs, and media). We classified barriers to access care as (i) existing difficulties limiting healthcare access; (ii) lack of awareness about CD and its complications; (iii) poor transmission control (vectorial and nonvectorial); (iv) scarce availability of antitrypanosomal drugs; and (v) cultural beliefs and stigma. Region-specific barriers may limit the implementation of roadmaps and require the application of tailored strategies to improve access to appropriate care. CONCLUSIONS: Multiple barriers negatively impact the prognosis of CD. Identification of these roadblocks both nationally and globally is important to guide development of appropriate policies and public health programs to reduce the global burden of this disease.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.596
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
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 head0.033
GPT teacher head0.328
Teacher spread0.295 · 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 designNot applicable
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

Citations26
Published2021
Admission routes1
Has abstractyes

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