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Record W2169416627 · doi:10.1177/1545109709331472

Outcomes of a Remote, Decentralized Health Center-Based HIV/AIDS Antiretroviral Program in Zambia, 2003 to 2007

2009· article· en· W2169416627 on OpenAlexaff
Riekje Elema, Clair Mills, Oliver Yun, Kamalini Lokuge, Charles Ssonko, Nashiola Nyirongo, Velepi Mtonga, Henry Zulu, David Tu, Meggy Verputten, D. O’Brien

Bibliographic record

VenueJournal of the International Association of Physicians in AIDS Care · 2009
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsEngineers Without Borders Canada
Fundersnot available
KeywordsMedicineLamivudineNevirapineViral loadStavudineInterquartile rangeAntiretroviral therapyInternal medicineCoinfectionHuman immunodeficiency virus (HIV)ImmunologyVirus

Abstract

fetched live from OpenAlex

A cross-sectional study of patients living with HIV/ AIDS treated during 2003 to 2007 in decentralized, rural health centers in Zambia was performed to measure virological outcomes after 12 months of antiretroviral therapy and identify factors associated with virological failure. Data from 228 patients who started antiretroviral therapy >12 months prior were analyzed. In all, 93% received stavudine + lamivudine + nevirapine regimens, and median antiretroviral therapy duration was 23.5 months (interquartile range 20-28). Of the 205 patients tested for viral load, 177 (86%) had viral load <1000 copies/mL. Probability of developing virological failure (viral load >1000 copies/mL) was 8.9% at 24 months and 19.6% at 32 months. Predictors for virological failure were <100% adherence, body mass index <18.5 kg/m(2), and women <40 years old. Of those with virological failure who underwent 3 to 6 months of intensive adherence counseling, 45% obtained virological success. In a remote, resource-limited setting in decentralized health centers, virological and immunological assessments of patients on antiretroviral therapy >12 months showed that positive health outcomes are achievable.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.133
Threshold uncertainty score0.409

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.012
GPT teacher head0.352
Teacher spread0.340 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

Explore more

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