Evidence map›Paper›PMID 25796396›Full record

ArticleEuropean journal of epidemiology2015

The detection of vector-borne-disease-related DNA in human stool paves the way to large epidemiological studies.

Alpha Kabinet Keita, Florence Fenollar, Cristina Socolovschi, Pavel Ratmanov, Hubert Bassene, Cheikh Sokhna, Adama Tall, Oleg Mediannikov, Didier Raoult

Abstract read
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In one paragraph

Article in European journal of epidemiology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.9field-weighted citation impact, top 17% 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

9 citing papers in PubMed, 16 citations in OpenAlex.

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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

9 authors at 5 institutions in 3 countries.

Alpha Kabinet KeitaUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.
Florence FenollarUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.
Cristina SocolovschiUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.
Pavel RatmanovDepartment of Public Health and Health Services Management, Far Eastern State Medical University, Khabarovsk, Russia.
Hubert BasseneUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.
Cheikh SokhnaUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.
Adama TallUnité d'Epidémiologie, Institut Pasteur de Dakar, BP 220, Dakar, Sénégal.
Oleg MediannikovUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France.
Didier RaoultUnité de Recherche sur les Maladies Infectieuses et Tropicales Emergentes (URMITE) UM63, UMR CNRS 7278, IRD 198, INSERM U1095 Faculté de Médecine, Aix-Marseille Université, 27 Bd Jean Moulin, 13385, Marseille Cedex 5, France. didier.raoult@gmail.com.
Institut de Recherche pour le Développement · FRInserm · FRCentre National de la Recherche Scientifique · FRFar Eastern State Medical University · RUInstitut Pasteur de Dakar · SN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The detection of Plasmodium spp. by the molecular analysis of human feces was reported to be comparable to detection in the blood. We believe that for epidemiological studies using molecular tools, it would be simpler to use feces, which are easier to obtain and require no training for their collection. Our aim was to evaluate the usefulness of feces for the detection of these pathogens towards developing a new tool for their surveillance. Between 2008 and 2010, 451 human fecal samples were collected in two Senegalese villages in which malaria and rickettsioses are endemic. Rickettsia and Plasmodium DNA were detected using quantitative PCR targeting Rickettsia of the spotted fever group, R. felis and Plasmodium spp. Two different sequences were systematically targeted for each pathogen. Twenty of the 451 fecal samples (4.4 %) were positive for Rickettsia spp., including 8 for R. felis. Inhabitants of Dielmo were more affected (18/230, 7.8 %; p = 0.0008) compared to those of Ndiop (2/221, 0.9 %). Children under 15 years of age were more often positive (19/285, 6.7 %) than were older children (1/166, 0.6 %; p = 0.005, odds ratio = 11.79). Only one sample was positive for Plasmodium spp. This prevalence is similar to that found in the blood of the Senegalese population reported previously. This preliminary report provides a proof of concept for the use of feces for detecting human pathogens, including microorganisms that do not cause gastroenteritis, in epidemiological studies.

Indexed as

AdolescentChildChild, PreschoolDNA, BacterialEpidemiologic StudiesFecesFemaleHumansMalariaMaleMolecular Diagnostic TechniquesPlasmodiumPolymerase Chain ReactionPrevalenceRickettsiaRickettsiaceae InfectionsDNA, BacterialAfricaFecal samplesHumanPlasmodium spp.Rickettsia spp.

Identifiers

PMID25796396
OpenAlexW2139743105

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.