Efficacy of antimalarial herbal medicines used by communities in malaria affected regions globally: a protocol for systematic review and evidence and gap map
Bibliographic record
Abstract
Introduction With the rising resistance to artemisinin-based combination treatments, there is a need to hasten the discovery and development of newer antimalarial agents. Herbal medicines are key for the development of novel drugs. Currently, herbal medicine usage in communities for treatment of malaria symptoms is common as an alternative to conventional (modern) antimalarial agents. However, the efficacy and safety of most of the herbal medicines has not yet been established. Therefore, this systematic review and evidence gap map (EGM) is intended to collate and map the available evidence, identify the gaps and synthesise the efficacy of herbal antimalarial medicines used in malaria affected regions globally. Methods and analysis The systematic review and EGM will be done following PRISMA and Campbell Collaboration guidelines respectively. This protocol has been registered in PROSPERO. Data sources will include PubMed, MEDLINE Ovid, EMBASE, Web of Science, Google Scholar and grey literature search. Data extraction will be done in duplicate using a data extraction tool tailored in Microsoft Office excel for herbal antimalarials discovery research questions following the PICOST framework. The Risk of Bias and overall quality of evidence will be assessed using Cochrane risk of bias tool (clinical trials), QUIN tool (in vitro studies), Newcastle-Ottawa tool (observational studies) and SYRCLE’s risk of bias tool for animal studies (in vivo studies). Data analysis will be done using both structured narrative and quantitative synthesis. The primary review outcomes will be clinically important efficacy and adverse drug reactions. Laboratory parameters will include Inhibitory Concentration killing 50% of parasites, IC 50; Ring Stage Assay, RSA 0–3 hou; Trophozoite Survival Assay, TSA 50. Ethics and dissemination The review protocol was approved by the School of Biomedical Science Research Ethics Committee, Makerere University College of Health Sciences (SBS-2022-213). PROSPERO registration number CRD42022367073.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".