Evidence map›Paper›PMID 40042316›Full record

ArticleInternational journal of laboratory hematology2025

The Diagnostic Performance of a Sysmex XN-31 Automated Malaria Analyzer vs. Expert Microscopy.

S Onsongo, K Otieno, L Mathenge, E Makotsi, G Kariuki, V Ngetich, G Muriithi, A T Harrison, T Odawo, S Kariuki

Abstract readComparative Study
In one paragraph

Article in International journal of laboratory hematology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–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

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. 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.

S OnsongoAga Khan Hospital, Kisumu, Kenya.ORCID https://orcid.org/0000-0001-5286-989X
K OtienoKEMRI Centre for Global Health Research (CGHR), Kisumu, Kenya.
L MathengeAga Khan Hospital, Kisumu, Kenya.
E MakotsiAga Khan Hospital, Kisumu, Kenya.
G KariukiAga Khan Hospital, Kisumu, Kenya.
V NgetichSysmex South Africa, Randburg, South Africa.
G MuriithiSysmex South Africa, Randburg, South Africa.
A T HarrisonSysmex South Africa, Randburg, South Africa.
T OdawoKEMRI Centre for Global Health Research (CGHR), Kisumu, Kenya.
S KariukiKEMRI Centre for Global Health Research (CGHR), Kisumu, Kenya.

Funding

Sysmex South Africa Ltd
6 · The paper itself

Abstract

introductionMalaria is a common and life-threatening infection. Malaria diagnosis needs to be fast and reliable. Although malaria microscopy is currently the gold standard, it is laborious, requires extensive training, and relies heavily on the proficiency of microscopists. Though malaria rapid tests are widely used, they show poor sensitivity at low parasitemia levels, are affected by gene deletions, and offer only qualitative results. There is a need to explore new techniques for the diagnosis of malaria. METHODOLOGY: A single-center, cross-sectional study evaluated the diagnostic performance of the Sysmex XN-31 automated analyzer for detecting malaria parasites compared to expert microscopy. The primary objective was to assess the XN-31's sensitivity, specificity, and ability to quantify malaria parasites relative to microscopy, the current gold standard. Blood samples from 310 adult patients undergoing routine malaria testing in a hospital setting were used. This included 118 confirmed malaria-positive cases. The Sysmex XN-31 results were compared to blinded expert microscopy on the same samples. Dried blood spot samples were collected for any discrepancies and resolved using molecular testing.

resultsThis study analyzed 310 patient samples for malaria using both microscopy and the XN-31 analyzer. Microscopy identified 122 positive samples (39%), with P. falciparum being the most prevalent species. Expert malaria microscopy demonstrated a sensitivity of 97.6% and a specificity of 100%. The XN-31 analyzer showed a sensitivity of 100% and a specificity of 99.46%. In malaria speciation, the XN-31 correctly flagged P. falciparum in 116 out of 117 cases (99.1%) among 125 positive cases. Additionally, five nonfalciparum malaria cases (Plasmodium malariae-four cases and Plasmodium ovale-one case) were accurately flagged as 'Malaria (Others).' However, five P. falciparum cases were incorrectly flagged as 'Malaria (Others),' highlighting limitations in malaria speciation by the analyzer. Statistical analysis revealed a strong correlation (Spearman coefficient of 0.8) between the parasite density measured via microscopy and the XN-31. Passing-Bablok regression indicated a strong linear relationship between these two methods.

conclusionThe Sysmex XN-31 analyzer provides a quick and accurate method for the diagnosis of malaria. It detects, quantifies, and speciates plasmodium infections in less than 1 minute. Our study showed that the analyzer shows high sensitivity and specificity comparable to those of expert microscopy in detecting Plasmodium species, making it a promising alternative to current diagnostic methods. By overcoming the numerous limitations of existing tests, the XN-31 proves to be well-suited for malaria testing, especially in malaria-endemic regions.

Indexed as

MalariaMicroscopyAdultCross-Sectional StudiesFemaleHumansMaleMiddle AgedPlasmodiumPlasmodium falciparumSensitivity and Specificityautomated analyserkenyanmalaria diagnosismalaria microscopyplasmodiumsysmex XN‐31

Identifiers

PMID40042316
PMCPMC12239696

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.