Evidence map›Paper›PMID 38943203›Full record

ArticleMalaria journal2024

Diagnostic accuracy of an automated microscope solution (miLab™) in detecting malaria parasites in symptomatic patients at point-of-care in Sudan: a case-control study.

Muzamil M Abdel Hamid, Abdelrahim O Mohamed, Fayad O Mohammed, Arwa Elaagip, Sayed A Mustafa, Tarig Elfaki, Waleed M A Jebreel, Musab M Albsheer, Sabine Dittrich, Ewurama D A Owusu and 1 more

Registry-linked trialAbstract read
In one paragraph

Article in Malaria journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04558515 (Clinical Evaluation of Automated Microscope Solutions for Malaria Diagnosis), which is not on this map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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.

NCT04558515 completednot on this map

Clinical Evaluation of Automated Microscope Solutions for Malaria Diagnosis

TypeobservationalSponsorFoundation for Innovative New Diagnostics, SwitzerlandRan2020 to 2021Enrolled190ConditionsMalariaArmsNovel malaria diagnostics & tools
3 · Its place in the literature

Who cites it

11 citing papers in PubMed.

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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

11 authors.

Muzamil M Abdel HamidDepartment of Parasitology and Medical Entomology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan. mahdi@iend.org.
Abdelrahim O MohamedDepartment of Parasitology and Medical Entomology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan.
Fayad O MohammedDepartment of Parasitology and Medical Entomology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan.
Arwa ElaagipDepartment of Parasitology and Medical Entomology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan.
Sayed A MustafaMalaria Control Program, Federal Ministry of Health, Khartoum, Sudan.
Tarig ElfakiMalaria Control Program, Federal Ministry of Health, Khartoum, Sudan.
Waleed M A JebreelDepartment of Parasitology and Medical Entomology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan.
Musab M AlbsheerDepartment of Parasitology and Medical Entomology, Institute of Endemic Diseases, University of Khartoum, Khartoum, Sudan.
Sabine DittrichFIND, Geneva, Switzerland.
Ewurama D A OwusuFIND, Geneva, Switzerland.
Seda YerlikayaFIND, Geneva, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMicroscopic detection of malaria parasites is labour-intensive, time-consuming, and expertise-demanding. Moreover, the slide interpretation is highly dependent on the staining technique and the technician's expertise. Therefore, there is a growing interest in next-generation, fully- or semi-integrated microscopes that can improve slide preparation and examination. This study aimed to evaluate the clinical performance of miLab™ (Noul Inc., Republic of Korea), a fully-integrated automated microscopy device for the detection of malaria parasites in symptomatic patients at point-of-care in Sudan.

methodsThis was a prospective, case-control diagnostic accuracy study conducted in primary health care facilities in rural Khartoum, Sudan in 2020. According to the outcomes of routine on-site microscopy testing, 100 malaria-positive and 90 malaria-negative patients who presented at the health facility and were 5 years of age or older were enrolled consecutively. All consenting patients underwent miLab™ testing and received a negative or suspected result. For the primary analysis, the suspected results were regarded as positive (automated mode). For the secondary analysis, the operator reviewed the suspected results and categorized them as either negative or positive (corrected mode). Nested polymerase chain reaction (PCR) was used as the reference standard, and expert light microscopy as the comparator.

resultsOut of the 190 patients, malaria diagnosis was confirmed by PCR in 112 and excluded in 78. The sensitivity of miLab™ was 91.1% (95% confidence interval [CI] 84.2-95.6%) and the specificity was 66.7% (95% Cl 55.1-67.7%) in the automated mode. The specificity increased to 96.2% (95% Cl 89.6-99.2%), with operator intervention in the corrected mode. Concordance of miLab with expert microscopy was substantial (kappa 0.65 [95% CI 0.54-0.76]) in the automated mode, but almost perfect (kappa 0.97 [95% CI 0.95-0.99]) in the corrected mode. A mean difference of 0.359 was found in the Bland-Altman analysis of the agreement between expert microscopy and miLab™ for quantifying parasite counts.

conclusionWhen used in a clinical context, miLab™ demonstrated high sensitivity but low specificity. Expert intervention was shown to be required to improve the device's specificity in its current version. miLab™ in the corrected mode performed similar to expert microscopy. Before clinical application, more refinement is needed to ensure full workflow automation and eliminate human intervention. Trial registration ClinicalTrials.gov: NCT04558515.

Indexed as

MalariaMicroscopyPoint-of-Care SystemsSensitivity and SpecificityAdolescentAdultCase-Control StudiesChildChild, PreschoolFemaleHumansMaleMiddle AgedProspective StudiesSudanYoung AdultArtificial intelligenceAutomated microscopeMalariamiLab™Sudan

Identifiers

PMID38943203
PMCPMC11212432

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Registered trials

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.