METHODS: A systematic review of the published English literature was conducted to identify malaria distribution from 1980 to June 2019 in Malaysia. Two investigators independently extracted data from PubMed, Scopus, Web of Science and Elsevier databases for original papers.
RESULTS: The review identified 46 epidemiological studies in Malaysia over the 39-year study period, on which sufficient information was available. The majority of studies were conducted in Malaysia Borneo (31/46; 67.4%), followed by Peninsular Malaysia (13/46; 28.3%) and in both areas (2/46; 4.3%). More than half of all studies (28/46; 60.9%) were assessed by both microscopy and PCR. Furthermore, there was a clear trend of decreases of all human malaria species with increasing Plasmodium knowlesi incidence rate throughout the year of sampling period. The summary estimates of sensitivity were higher for P. knowlesi than other Plasmodium species for both microscopy and PCR. Nevertheless, the specificities of summary estimates were similar for microscopy (40-43%), but varied for PCR (2-34%).
CONCLUSIONS: This study outlined the epidemiological changes in Plasmodium species distribution in Malaysia. Malaria cases shifted from predominantly caused by human malaria parasites to simian malaria parasites, which accounted for the majority of indigenous cases particularly in Malaysia Borneo. Therefore, malaria case notification and prompt malaria diagnosis in regions where health services are limited in Malaysia should be strengthened and reinforced to achieving the final goal of malaria elimination in the country.
Method: Scopus, PubMed, and Web of Science (all databases) were searched by 2 reviewers until 29th October 2020. Articles were screened and narratively synthesized according to PRISMA-DTA guidelines based on predefined eligibility criteria. Articles that made direct reference test comparisons to human clinicians were evaluated using the MI-CLAIM checklist. The risk of bias was assessed by JBI-DTA critical appraisal, and certainty of the evidence was evaluated using the GRADE approach. Information regarding the quantification method of dental pain and disease, the conditional characteristics of both training and test data cohort in the machine learning, diagnostic outcomes, and diagnostic test comparisons with clinicians, where applicable, were extracted.
Results: 34 eligible articles were found for data synthesis, of which 8 articles made direct reference comparisons to human clinicians. 7 papers scored over 13 (out of the evaluated 15 points) in the MI-CLAIM approach with all papers scoring 5+ (out of 7) in JBI-DTA appraisals. GRADE approach revealed serious risks of bias and inconsistencies with most studies containing more positive cases than their true prevalence in order to facilitate machine learning. Patient-perceived symptoms and clinical history were generally found to be less reliable than radiographs or histology for training accurate machine learning models. A low agreement level between clinicians training the models was suggested to have a negative impact on the prediction accuracy. Reference comparisons found nonspecialized clinicians with less than 3 years of experience to be disadvantaged against trained models.
Conclusion: Machine learning in dental and orofacial healthcare has shown respectable results in diagnosing diseases with symptomatic pain and with improved future iterations and can be used as a diagnostic aid in the clinics. The current review did not internally analyze the machine learning models and their respective algorithms, nor consider the confounding variables and factors responsible for shaping the orofacial disorders responsible for eliciting pain.
METHODS: Two real-time PCR methods currently used in Sabah for confirmatory malaria diagnosis and surveillance reporting were evaluated: the QuantiFast™ Multiplex PCR kit (Qiagen, Germany) targeting the P. knowlesi 18S SSU rRNA; and the abTES™ Malaria 5 qPCR II kit (AITbiotech, Singapore), with an undisclosed P. knowlesi gene target. Diagnostic accuracy was evaluated using 52 P. knowlesi, 25 Plasmodium vivax, 21 Plasmodium falciparum, and 10 Plasmodium malariae clinical isolates, and 26 malaria negative controls, and compared against a validated reference nested PCR assay. The limit of detection (LOD) for each PCR method and Plasmodium species was also evaluated.
RESULTS: The sensitivity of the QuantiFast™ and abTES™ assays for detecting P. knowlesi was comparable at 98.1% (95% CI 89.7-100) and 100% (95% CI 93.2-100), respectively. Specificity of the QuantiFast™ and abTES™ for P. knowlesi was high at 98.8% (95% CI 93.4-100) for both assays. The QuantiFast™ assay demonstrated falsely-positive mixed Plasmodium species at low parasitaemias in both the primary and LOD analysis. Diagnostic accuracy of both PCR kits for detecting P. vivax, P. falciparum, and P. malariae was comparable to P. knowlesi. The abTES™ assay demonstrated a lower LOD for P. knowlesi of ≤ 0.125 parasites/µL compared to QuantiFast™ with a LOD of 20 parasites/µL. Hospital microscopy demonstrated a sensitivity of 78.8% (95% CI 65.3-88.9) and specificity of 80.4% (95% CI 67.6-89.8) compared to reference PCR for detecting P. knowlesi.
CONCLUSION: The QuantiFast™ and abTES™ commercial PCR kits performed well for the accurate detection of P. knowlesi infections. Although the QuantiFast™ kit is cheaper, the abTES™ kit demonstrated a lower LOD, supporting its use as a second-line referral-laboratory diagnostic tool in Sabah, Malaysia.
RESULTS: A noticeable variation between the RDT (Alltest Biotech, China) and nPCR results was observed, for RDT 78% (46/59) were P. falciparum positive, 6.8% (4/59) were co-infected with both P. falciparum and Plasmodium vivax, 15.3% (9/59) were negative by the RDT. However, when the nPCR was applied only 44.1% (26/59) and 55.9% (33/59) was P. falciparum positive and negative respectively. The pfhrp2 was further amplified form all nPCR positive samples. Only 17 DNA samples were positive from the 26 positive P. falciparum, interestingly, variation in band sizes was observed and further confirmed by DNA sequencing, and sequencing analysis revealed a high-level of genetic diversity of the pfhrp2 gene in the parasite population from the study area. However, despite extreme sequence variation, diversity of PfHRP2 does not appear to affect RDT performance.