Evidence map›Paper›PMID 33273605›Full record

ArticleScientific reports2020

Classification of invasive bloodstream infections and Plasmodium falciparum malaria using autoantibodies as biomarkers.

Ralf Krumkamp, Nicole Sunaina Struck, Eva Lorenz, Marlow Zimmermann, Kennedy Gyau Boahen, Nimako Sarpong, Ellis Owusu-Dabo, Gi Deok Pak, Hyon Jin Jeon, Florian Marks and 3 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 32% of its field
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, 4 citations in OpenAlex.

  1. Observational
  2. Article
  3. Review
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

13 authors at 5 institutions in 5 countries.

Ralf KrumkampDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany.
Nicole Sunaina StruckDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany. struck@bnitm.de.
Eva LorenzDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany.
Marlow ZimmermannDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany.
Kennedy Gyau BoahenDepartment of Infectious Disease Epidemiology, Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR), Kumasi, Ghana.
Nimako SarpongDepartment of Infectious Disease Epidemiology, Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR), Kumasi, Ghana.
Ellis Owusu-DaboSchool of Public Health, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana.
Gi Deok PakEpidemiology Unit, International Vaccine Institute (IVI), Seoul, Republic of Korea.
Hyon Jin JeonEpidemiology Unit, International Vaccine Institute (IVI), Seoul, Republic of Korea.
Florian MarksEpidemiology Unit, International Vaccine Institute (IVI), Seoul, Republic of Korea.
Thomas JacobsResearch Group Protozoa Immunology, Bernhard Nocht Institute for Tropical Medicine, Hamburg, Germany.
Jürgen MayDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany.
Daniel EibachDepartment of Infectious Disease Epidemiology, Bernhard Nocht Institute for Tropical Medicine, Bernhard Nocht Str. 74, 20359, Hamburg, Germany.
German Center for Infection Research · DEBernhard Nocht Institute for Tropical Medicine · DEInternational Vaccine Institute · KRKumasi Centre for Collaborative Research in Tropical Medicine · GHKwame Nkrumah University of Science and Technology · GH

Funding

Bill & Melinda Gates Foundation OPPGH5231
6 · The paper itself

Abstract

A better understanding of disease-specific biomarker profiles during acute infections could guide the development of innovative diagnostic methods to differentiate between malaria and alternative causes of fever. We investigated autoantibody (AAb) profiles in febrile children (≤ 5 years) admitted to a hospital in rural Ghana. Serum samples from 30 children with a bacterial bloodstream infection and 35 children with Plasmodium falciparum malaria were analyzed using protein microarrays (Protoplex Immune Response Assay, ThermoFisher). A variable selection algorithm was applied to identify the smallest set of AAbs showing the best performance to classify malaria and bacteremia patients. The selection procedure identified 8 AAbs of which IFNGR2 and FBXW5 were selected in repeated model run. The classification error was 22%, which was mainly due to non-Typhi Salmonella (NTS) diagnoses being misclassified as malaria. Likewise, a cluster analysis grouped patients with NTS and malaria together, but separated malaria from non-NTS infections. Both current and recent malaria are a risk factor for NTS, therefore, a better understanding about the function of AAb in disease-specific immune responses is required in order to support their application for diagnostic purposes.

Indexed as

AlgorithmsAutoantibodiesBiomarkersChild, PreschoolCluster AnalysisFemaleHumansInfantMalaria, FalciparumMaleSepsisAutoantibodiesBiomarkers

Identifiers

PMID33273605
PMCPMC7712777
OpenAlexW3107284383

What OpenQuestion holds

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LicenceCC BY
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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.