Active case detection of malaria in pregnancy using loop-mediated amplification (LAMP): a pilot outcomes study in South West Ethiopia
Bibliographic record
Abstract
BACKGROUND: 125 million women are pregnant each year in malaria endemic areas and are, therefore, at risk of Malaria in Pregnancy (MiP). MiP is the direct consequence of Plasmodium infection during pregnancy. The sequestration of Plasmodium falciparum parasites in the placenta adversely affects fetal development and impacts newborn birth weight. Importantly, women presenting with MiP commonly develop anaemia. In Ethiopia, the Ministry of Health recommends screening symptomatic women only at antenatal care visits with no formal intermittent preventive therapy. Since MiP can display low-level parasitaemia, current tests which include microscopy and RDT are challenged to detect these cases. Loop mediated isothermal Amplification (LAMP) technology is a highly sensitive technique for DNA detection and is field compatible. This study aims to evaluate the impact of active malaria case detection during pregnancy using LAMP technology in terms of birth outcomes. METHODS: A longitudinal study was conducted in two health centres of the Kafa zone, South West Ethiopia. Both symptomatic and asymptomatic pregnant women were enrolled in the first or second trimester and allocated to either Standard of Care (SOC-microscopy and RDT) or LAMP (LAMP, microscopy and RDT). Women completed at least three visits prior to delivery, and the patient was referred for treatment if Plasmodium infection was detected by any of the testing methods. The primary outcome was to measure absolute birth weight, proportion of low birth weight, and maternal/neonatal haemoglobin in each arm. Secondary outcomes were to assess the performance of microscopy and RDT versus LAMP conducted in the field. RESULTS: One hundred and ninety-nine women were included and assigned to either LAMP or SOC. Six were lost to follow up. In this cohort, 66.8% of women did not display any clinical symptoms and 70.9% were multi-parous. A reduced proportion of low birth weight newborns was observed in the LAMP group (0%) compared to standard of care (14%) (p <0.001). Improved neonatal haemoglobin was observed in the LAMP (13.1 g/dL) versus the SOC (12.8 g/dL) (p = 0.024) arm. RDT and microscopy had an analytical sensitivity of 66.7% and 55.6% compared to LAMP as a reference standard. CONCLUSIONS: These results support the use of highly sensitive tools for rapid on-site active case detection of MiP which may improve birth outcomes in the absence of IPT. However, further large-scale studies are required to confirm this finding.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".