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Record W1981664678 · doi:10.1086/318836

<i>Plasmodium falciparum</i>Malaria in Laos: Chloroquine Treatment Outcome and Predictive Value of Molecular Markers

2001· article· en· W1981664678 on OpenAlexafffund
Dylan R. Pillai, Annie‐Claude Labbé, V. Vanisaveth, Bouasy Hongvangthong, S. Pomphida, S. Inkathone, Kathleen Zhong, Kevin C. Kain

Bibliographic record

VenueThe Journal of Infectious Diseases · 2001
Typearticle
Languageen
FieldMedicine
TopicMalaria Research and Control
Canadian institutionsUniversity of TorontoToronto General Hospital
FundersNational Institutes of HealthUniversity of TorontoEuropean Commission
KeywordsChloroquineMalariaPlasmodium falciparumConfidence intervalInternal medicineDrug resistanceMedicineBiologyVirologyImmunologyGenetics

Abstract

fetched live from OpenAlex

A 28-day treatment trial was undertaken, to determine the efficacy of chloroquine in Laos and to assess the predictive value of molecular markers (cg2, pfmdr1, and pfcrt) that were previously linked to chloroquine resistance. In total, 522 febrile patients were screened for falciparum malaria by rapid diagnostic assays. Of 81 patients (15.5% prevalence) who were positive by the assays and microscopy, 48 were eligible to participate in the 28-day trial. Nine patients defaulted. Chloroquine cured 54% (95% confidence interval, 45.8-61.8) of falciparum-infected patients. Of 18 (46%) patients with treatment failure, 13 (72%) experienced high-grade resistance. Polymorphisms in cg2 and the N86Y mutation in PfMDR1 were not predictive of treatment outcome. A mutation in PfCRT (K76T) was perfectly associated with in vivo chloroquine resistance. However, K76T was also present in in vivo-sensitive isolates, which suggests that the presence of this mutation was necessary, but not sufficient, to predict in vivo outcome in this cohort.

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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.009
GPT teacher head0.274
Teacher spread0.265 · 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 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

Citations118
Published2001
Admission routes2
Has abstractyes

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