MétaCan
Menu
Back to cohort
Record W2048500762 · doi:10.2471/06.036525

Tuberculosis in Rwanda: challenges to reaching the targets

2007· article· en· W2048500762 on OpenAlexaboutno aff
Michel Gasana, Greet Vandebriel, G Kabanda, Jules Mugabo, Simon Tsiouris, Aliou Ayaba, Alyssa Finlay, Jessica Justman, Ruben Sahabo, Wafaa El‐Sadr

Bibliographic record

VenueEurope PMC (PubMed Central) · 2007
Typearticle
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsnot available
FundersCenters for Disease Control and Prevention
KeywordsTuberculosisMedicineChristian ministryEnvironmental healthHuman immunodeficiency virus (HIV)Quarter (Canadian coin)Antiretroviral therapyFamily medicinePediatricsGeographyPathologyViral load

Abstract

fetched live from OpenAlex

Rwanda has a generalized HIV epidemic: 3.1% of adults are living with HIV/AIDS.1 Care, treatment and prevention services for the approximately 183 558 adults and 13 901 children living with HIV/AIDS have been rapidly scaled up over the past three years under the guidance of the Rwandan Ministry of Health’s Treatment Research for AIDS Center. By November 2006, almost 33 000 HIV-infected adults and children were receiving antiretroviral therapy.2 Expansion and enhancement of DOTS in the six-point Stop TB Strategy described by Laserson & Wells have been implemented in Rwanda by the health ministry’s national integrated programme to combat leprosy and TB since 1990. Through recent programme improvements, treatment success rates have increased from 58% in 2003 to 81% by the third quarter of 2006; however, case detection was an estimated 24% in 2005.3–5 Thus, Rwanda is close to achieving the WHO target for treatment success, but is below the target for case detection. Concerted efforts are being made to ensure that effective smear microscopy and directly-observed therapy are available nationwide. Further efforts are needed to reach the goals, especially for case detection. A recent national survey showing that the prevalence of multidrug resistance among new TB patients is 3.9% gives cause for concern.6

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)0.004
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.585
Threshold uncertainty score0.597

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.041
GPT teacher head0.297
Teacher spread0.256 · 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 designObservational
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

Citations7
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueEurope PMC (PubMed Central)Same topicTuberculosis Research and EpidemiologyFrench-language works237,207