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Record W2062879940 · doi:10.3899/jrheum.140107

Cost for Tuberculosis Care in Developed Countries: Which Data for an Economic Evaluation?

2014· review· en· W2062879940 on OpenAlexvenueno aff
Leopoldo Trieste, Giuseppe Turchetti

Bibliographic record

VenueJournal of Rheumatology Supplement · 2014
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineTuberculosisEthambutolPyrazinamideIsoniazidIntensive care medicineDeveloping countryDeveloped countryEnvironmental healthPediatricsPopulationEconomic growth

Abstract

fetched live from OpenAlex

Tuberculosis (TB) seems to be eradicated in developed countries. However, current migration flows and increasing use of immunosuppressive and biologic drugs for rheumatic diseases are increasing the risk of latent TB and TB onset for citizens of developed countries. Because little is known about the economic burden of TB in developed countries, we set out to describe the order and dimension of the costs of TB care in developed countries. A review of the literature indicated that the cost for anti-TB therapy is about $2000 US per patient. Costs of drugs associated with standard therapy for active TB [2HRZE/4HR, i.e., 2 months of isoniazid (H), rifampin (R), pyrazinamide (Z), and ethambutol (E), followed by 4 months of HR] are about $600. Standard therapy for latent TB care costs about $80 for 9H and $256 for 4R, respectively. However, these data are very limited because of the horizon of analysis and because data are strongly localized. It can be concluded that in developed countries, available data on TB care costs are insufficient for detailed analysis of the economic burden of TB.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.009
metaresearch head score (Gemma)0.029
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.046

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.029
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.004
Bibliometrics0.0070.010
Science and technology studies0.0010.001
Scholarly communication0.0040.004
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.001

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 head0.200
GPT teacher head0.498
Teacher spread0.299 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations2
Published2014
Admission routes1
Has abstractyes

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