Evidence map›Paper›PMID 33951766›Full record

ArticleThe Korean journal of parasitology2021

Performance Evaluation of Biozentech Malaria Scanner in Plasmodium knowlesi and P. falciparum as a New Diagnostic Tool.

Egy Rahman Firdaus, Ji-Hoon Park, Fauzi Muh, Seong-Kyun Lee, Jin-Hee Han, Chae-Seung Lim, Sung-Hun Na, Won Sun Park, Jeong-Hyun Park, Eun-Taek Han

Abstract readEvaluation Study
In one paragraph

Article in The Korean journal of parasitology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Egy Rahman FirdausDepartment of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Ji-Hoon ParkDepartment of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Fauzi MuhDepartment of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Seong-Kyun LeeDepartment of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Jin-Hee HanDepartment of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Chae-Seung LimDepartment of Laboratory Medicine, Korea University College of Medicine, Seoul 08308, Korea.
Sung-Hun NaDepartment of Obstetrics and Gynecology, Kangwon National University Hospital, Kangwon National University School of Medicine, Chuncheon 24341, Korea.
Won Sun ParkDepartment of Physiology, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Jeong-Hyun ParkDepartment of Anatomy and Cell Biology, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.
Eun-Taek HanDepartment of Medical Environmental Biology and Tropical Medicine, School of Medicine, Kangwon National University, Chuncheon 24341, Korea.

Funding

Korea Association of Health Promotion 2019-02Ministry of Science, ICT and Future PlanningNational Research Foundation of Korea 2015R1A4A1038666National Research Foundation of Korea 2017R1A2A2A05069562
6 · The paper itself

Abstract

The computer vision diagnostic approach currently generates several malaria diagnostic tools. It enhances the accessible and straightforward diagnostics that necessary for clinics and health centers in malaria-endemic areas. A new computer malaria diagnostics tool called the malaria scanner was used to investigate living malaria parasites with easy sample preparation, fast and user-friendly. The cultured Plasmodium parasites were used to confirm the sensitivity of this technique then compared to fluorescence-activated cell sorting (FACS) analysis and light microscopic examination. The measured percentage of parasitemia by the malaria scanner revealed higher precision than microscopy and was similar to FACS. The coefficients of variation of this technique were 1.2-6.7% for Plasmodium knowlesi and 0.3-4.8% for P. falciparum. It allowed determining parasitemia levels of 0.1% or higher, with coefficient of variation smaller than 10%. In terms of the precision range of parasitemia, both high and low ranges showed similar precision results. Pearson's correlation test was used to evaluate the correlation data coming from all methods. A strong correlation of measured parasitemia (r2=0.99, P<0.05) was observed between each method. The parasitemia analysis using this new diagnostic tool needs technical improvement, particularly in the differentiation of malaria species.

Indexed as

ComputersDiagnostic Tests, RoutineErythrocytesHumansMalariaMalaria, FalciparumParasitemiaPlasmodium falciparumPlasmodium knowlesicomputer visiondiagnosismalariaparasitemiaP. falciparumPlasmodium knowlesi

Identifiers

PMID33951766
PMCPMC8106981

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.