The performance and utility of rapid diagnostic assays for Plasmodium falciparum malaria in a field setting in the Lao People's Democratic Republic
Bibliographic record
Abstract
Rapid diagnostic assays for malaria have the potential to improve the management and control of the disease in developing countries. The objectives of the present study were to evaluate, in a field setting, the performance of several such assays for Plasmodium falciparum infection and to examine the usefulness of these assays in identifying subjects for treatment trials in rural field sites. Residents of 12 villages in Laos who presented with fever were eligible for inclusion. Blood was collected by fingerprick for a dipstick assay, developed by the Program for Appropriate Technology in Health (PATH), performed and interpreted in the field by local healthcare workers. Compared with 'blinded' reference microscopy (N =196), the sensitivity and specificity of the PATH assay were 96.2% and 93.0%, respectively. Two rapid diagnostic assays (PATH and OptiMAL) were also performed on the subset of subjects eligible to participate in an in-vivo treatment trial (N = 97), and the results again compared with those of 'blinded' reference microscopy. In this subset, a subject was considered a 'true positive' if found positive by microscopy or the alternate rapid assay. Using this modified reference standard, the sensitivity and specificity of the PATH assay were 96.7% and 94.4%, and those of the OptiMAL assay were 91.8% and 100%, respectively. Both of the rapid assays tested therefore appear suitable for use in rural field settings by local healthcare providers and can accurately identify participants for treatment trials.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".