Active case detection using loop-mediated isothermal amplification technology and treatment versus standard of care for malaria in pregnancy in Ethiopia (LAMPREG): a pragmatic randomised diagnostic outcomes trial
Bibliographic record
Abstract
Background Malaria in pregnancy is a substantial public health risk, particularly in sub-Saharan Africa. Conventional diagnostic tools, such as microscopy and rapid diagnostic tests (RDTs), often miss infections with low-level parasitaemia. We aimed to evaluate the effectiveness of a screen-and-treat strategy using loop-mediated isothermal amplification (LAMP) technology compared with the standard of care to improve maternal and infant health outcomes in rural Ethiopia, where intermittent preventive treatment in pregnancy is not implemented. Methods We conducted a pragmatic randomised diagnostic outcomes trial across eight health facilities (three hospitals and five health centres) in Ethiopia. Pregnant women aged at least 18 years in their first or second trimester, established via ultrasound dating, were randomly assigned to the LAMP group (in which patients were tested for malaria with LAMP, RDT, and microscopy at every visit, regardless of the presentation of malaria symptoms) or the standard-of-care group (in which patients were tested for malaria with RDT and microscopy only at visits where they were symptomatic for malaria, which is the standard of care in Ethiopia). Randomisation was done by data managers, stratified by gravidity, and done without masking or concealment. Women who tested positive for malaria infection were treated with artemether–lumefantrine. The primary outcome was the proportion of liveborn infants with low birthweight (<2500 g) in both the intention-to-treat (ITT; all randomised participants) and per-protocol (participants for whom birthweight was recorded) populations. We assessed the diagnostic performance (ie, sensitivity, specificity, and positive and negative predictive values) of LAMP, RDT, and microscopy by comparing them to a molecular reference method (laboratory-developed test reference 28). This trial is registered with ClinicalTrials.gov (NCT03754322) and is completed. Findings 2425 women were enrolled between June 18, 2021, and July 19, 2023 (1570 [64·7%] randomly assigned to the LAMP group and 855 [35·3%] to the standard-of-care group). We did not meet the prespecified sample size of 2583. After imputation for missing data, the ITT analysis included 1570 women with 1521 livebirths in the LAMP group and 855 women with 842 livebirths in the standard-of-care group. Among these livebirths, the proportion of infants with low birthweight at delivery did not differ between the LAMP group (74 [4·9%] of 1521 infants) and the standard-of-care group (39 [4·6%] of 842 infants; odds ratio [OR] 1·24 [95% CI 0·70–2·18]; p=0·65). The per-protocol analysis had similar results (33 [3·4%] of 968 infants in the LAMP group vs 18 [3·4%] of 525 infants in the standard-of-care group; OR 0·99 [0·56–1·82]; p>0·99). In our trial populations, LAMP had better sensitivity (94·1% [95% CI 90·0–96·9]) than microscopy (67·2% [60·3–73·6]) and RDT (67·6% [60·8–74·0]). Specificity was 99·0% (95% CI 98·6–99·3) with LAMP, 99·7% (99·5–99·9) with microscopy, and 99·97% (99·8–100) with the RDT. The positive predictive value of LAMP (84·6% [95% CI 79·2–89·0]) was lower than that of both microscopy (93·2% [87·8–96·7]) and RDT (99·3% [96·1–100·0]). The negative predictive value of LAMP (99·7% [99·4–99·8]) was higher than both microscopy (98·1% [97·6–98·5]) and RDT (98·2% [97·7–98·6]). Common adverse events included headache (95 [6·1%] of 1570 participants in the LAMP group and 37 [4·3%] of 855 participants in the standard-of-care group) and preterm delivery (82 [5·2%] of 1570 participants in the LAMP group and 58 [6·8%] of 855 participants in the standard-of-care group). Severe adverse events included admission to hospital (20 [1·3%] of 1570 participants in the LAMP group and four [0·5%] of 855 participants in the standard-of-care group) and life-threatening conditions (16 [1·0%] of 1570 participants in the LAMP group and two [0·2%] of 855 participants in the standard-of-care group). No adverse events were related to the LAMP diagnostic intervention. Interpretation There was no benefit of LAMP over standard of care regarding low birthweight in the trial. LAMP was more accurate at detecting malaria in pregnancy when compared with microscopy and RDT. Future, powered studies should evaluate the effects of highly sensitive malaria tests, including in other transmission settings. Funding Grand Challenges Canada Transition to Scale, University of Calgary Vice President Research Fund, University of Calgary Cumming School of Medicine, and Foundation for Innovative New Diagnostics.
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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 | 0.010 | 0.012 |
| Meta-epidemiology (narrow) | 0.004 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".