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Record W2067950090 · doi:10.1586/14737167.2013.852470

Cost–effectiveness analysis of rheumatic heart disease prevention strategies

2013· review· en· W2067950090 on OpenAlexaff
Rizwan A. Manji, Julia Witt, Paramjit S. Tappia, Young–Jin Jung, Alan H. Menkis, Bram Ramjiawan

Bibliographic record

VenueExpert Review of Pharmacoeconomics & Outcomes Research · 2013
Typereview
Languageen
FieldMedicine
TopicStreptococcal Infections and Treatments
Canadian institutionsSt. Boniface HospitalUniversity of Manitoba
Fundersnot available
KeywordsMedicineIntensive care medicineSecondary prophylaxisAntibiotic prophylaxisHeart diseaseCost effectivenessDeveloping countryCost-effectiveness analysisPediatricsRheumatic feverSecondary preventionPrimary preventionDiseaseAntibioticsInternal medicine

Abstract

fetched live from OpenAlex

Rheumatic heart disease (RHD), secondary to group A streptococcal infection is endemic in the developing as well as parts of the developed world with significant costs to the patient, and to the healthcare system. We briefly review the prevalence and cost of RHD in developed and developing nations. We subsequently develop a Markov model to evaluate the cost-effectiveness of three strategies (vs standard no prevention) for preventing RHD in a developing world country: primary prophylaxis (throat swab to detect and subsequently treat group A streptococci as needed); primary prophylaxis (antibiotic prophylaxis for all) with benzathine penicillin G once monthly to all patients (ages 5-21 years) regardless of evidence of infection; and secondary prophylaxis with monthly only to those with echocardiographic evidence of early RHD. Our model suggests that echocardiographic screening and secondary prophylaxis is the best strategy although the strategies change depending on parameters used.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.797
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.003
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)0.0030.000

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 head0.181
GPT teacher head0.625
Teacher spread0.444 · 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

Citations45
Published2013
Admission routes1
Has abstractyes

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