Evidence map›Paper›PMID 34230505›Full record

ArticleScientific reports2021

A unique volatile signature distinguishes malaria infection from other conditions that cause similar symptoms.

Hannier Pulido, Nina M Stanczyk, Consuelo M De Moraes, Mark C Mescher

Abstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. No skin off your back: the sampling and extraction of sebum for metabolomics.Metabolomics : Official journal of the Metabolomic Society · 2023
    Review
  7. 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

4 authors.

Hannier PulidoDepartment of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland.
Nina M StanczykDepartment of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland.
Consuelo M De MoraesDepartment of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland.
Mark C MescherDepartment of Environmental Systems Science, ETH Zürich, 8092, Zürich, Switzerland. mescher@usys.ethz.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent findings suggest that changes in human odors caused by malaria infection have significant potential as diagnostic biomarkers. However, uncertainty remains regarding the specificity of such biomarkers, particularly in populations where many different pathological conditions may elicit similar symptoms. We explored the ability of volatile biomarkers to predict malaria infection status in Kenyan schoolchildren exhibiting a range of malaria-like symptoms. Using genetic algorithm models to explore data from skin volatile collections, we were able to identify malaria infection with 100% accuracy among children with fever and 75% accuracy among children with other symptoms. While we observed characteristic changes in volatile patterns driven by symptomatology, our models also identified malaria-specific biomarkers with robust predictive capability even in the presence of other pathogens that elicit similar symptoms.

Indexed as

BiomarkersChildConfidence IntervalsDiagnosis, DifferentialHumansMalariaVolatile Organic CompoundsBiomarkersVolatile Organic Compounds

Identifiers

PMID34230505
PMCPMC8260776

What OpenQuestion holds

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Registered trials

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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.