Epidemiological Characteristics of Intestinal Protozoal Infections and Their Risk Factors in Malaysia: Systematic Review and Meta-Analysis Protocol
Bibliographic record
Abstract
Background Intestinal protozoal infections caused by Entamoeba histolytica, Giardia lamblia, and Cryptosporidium parvum are prevalent in Malaysia. They cause severe diarrheal diseases with symptoms such as bloody stools, abdominal pain, stomach discomfort, and bloating. These infection outbreaks have been reported in diverse socioeconomic backgrounds and geographical regions usually during the rainy season or in areas with poor sanitation. Despite the importance of these infections, data on its overall prevalence, risk factors, and diagnostic methods remain limited. Objective The aim of this study is to systematically review and synthesize evidence on the risk factors, prevalence, and detection methods for intestinal protozoal infections in Malaysia, offering insights that are applicable to other tropical and low-income regions. Methods Studies on intestinal protozoal infections among Malaysian patients published after January 2010 up to November 2024 will be eligible for inclusion. The eligibility criteria include studies investigating infections caused by E. histolytica, G. lamblia, and C. parvum using validated diagnostic methods such as microscopy, molecular techniques, or immunoassays. Case reports, reviews, and studies without original data will be excluded. Comprehensive database searches will be conducted in PubMed/MEDLINE, Scopus, ProQuest, Web of Science, Google Scholar, and the Cochrane Library. The reference lists of selected papers are also checked. A standardized data extraction form will be used to record study characteristics, outcomes, and associated variables. Risk of bias will be assessed using the Joanna Briggs Institute tools and Newcastle-Ottawa Scale approach. Data synthesis will utilize a random effects model to estimate pooled prevalence and identify risk factors associated with these infections. Subgroup analyses will examine variations by geographic region and diagnostic method. Statistical heterogeneity will be assessed using I2 statistic and meta-regression. Publication bias will be assessed using Egger and Begg funnel plot test. The results are reported in accordance with PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Results This systematic review was funded in June 2024. Database searches were started in July 2024, and we identified 1652 papers as of December 2024 for screening. Completion of study screening is anticipated by May 2025, with data extraction and analysis expected to conclude by December 2025. Conclusions Our study will address critical knowledge gaps in the epidemiology and risk factors of intestinal protozoal infections in Malaysia. Study limitations include potential bias in study selection, heterogeneity in diagnostic methods, and differences in the reporting quality of the included studies. Our findings will provide valuable insights into the prevalence of these infections, the associated risk factors, and the diagnostic techniques employed, which should strengthen public health measures, improve diagnostic procedures, and guide future research to reduce the prevalence of intestinal protozoal infections in Malaysia. Trial Registration PROSPERO (International Prospective Registry of Systematic Reviews) registration CRD42023456199; https://www.crd.york.ac.uk/PROSPERO/view/CRD42023456199 International Registered Report Identifier (IRRID) DERR1-10.2196/66350
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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 | 0.025 | 0.041 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.025 | 0.022 |
| Bibliometrics | 0.019 | 0.014 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.033 | 0.002 |
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".