Evidence map›Paper›PMID 33087393›Full record

ReviewBMJ global health2020

Bacterial versus non-bacterial infections: a methodology to support use-case-driven product development of diagnostics.

Camille Escadafal, Steffen Geis, A M Siqueira, Selidji T Agnandji, Techalew Shimelis, Birkneh Tilahun Tadesse, Marguerite Massinga Loembé, Victoria Harris, B Leticia Fernandez-Carballo, Aurélien Macé and 3 more

Abstract readReview
In one paragraph

Review in BMJ global health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 2 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

10 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
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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

13 authors.

Camille EscadafalMalaria and Fever Programme, Foundation for Innovative New Diagnostics, Geneva, Switzerland camille.escadafal@finddx.org.ORCID 0000-0002-0268-750X
Steffen GeisMalawi Epidemiology and Intervention Research Unit (MEIRU), Chilumba, Karonga, Malawi.
A M SiqueiraInstituto Nacional de Infectologia Evandro Chagas (INI), FIOCRUZ, Rio de Janeiro, Brazil.
Selidji T AgnandjiCERMEL, Lambarene, Moyen-Ogooué, Gabon.
Techalew ShimelisHawassa University College of Medicine and Health Sciences, Hawassa, Southern Nations, Ethiopia.
Birkneh Tilahun TadesseHawassa University College of Medicine and Health Sciences, Hawassa, Southern Nations, Ethiopia.
Marguerite Massinga LoembéAfrica Center for Disease Control and Prevention (ACDC), Addis Ababa, Ethiopia.
Victoria HarrisFoundation for Innovative New Diagnostics, Geneva, Switzerland.
B Leticia Fernandez-CarballoMalaria and Fever Programme, Foundation for Innovative New Diagnostics, Geneva, Switzerland.
Aurélien MacéFoundation for Innovative New Diagnostics, Geneva, Switzerland.
Stefano OngarelloFoundation for Innovative New Diagnostics, Geneva, Switzerland.
William RodriguezFoundation for Innovative New Diagnostics, Geneva, Switzerland.
Sabine DittrichMalaria and Fever Programme, Foundation for Innovative New Diagnostics, Geneva, Switzerland.ORCID 0000-0002-4522-2788

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Acute febrile illness (AFI) is one of the most common reasons for seeking medical care in low-income and middle-income countries. Bacterial infections account for a relatively small proportion of AFIs; however, in the absence of a simple diagnostic test to guide clinical decisions, healthcare professionals often presume that a non-malarial febrile illness is bacterial in origin, potentially resulting in inappropriate antibiotic use. An accurate differential diagnostic tool for AFIs is thus essential, to both limit antibiotic use to bacterial infections and address the antimicrobial resistance crisis that is emerging globally, without resorting to multiple or complex pathogen-specific assays. The Biomarker for Fever-Diagnostic (BFF-Dx) study is one of the largest fever biomarker studies ever undertaken. We collected samples and classified disease aetiology in more than 1900 individuals, distributed among enrolment centres in three countries on two continents. Identical protocols were followed at each study site, and the same analyses were conducted in each setting, enabling like-with-like comparisons to be made among the large sample set generated. The BFF-Dx methodology can act as a model for other researchers, facilitating wider utility of the work in the future. The established sample collection is now accessible to researchers and companies and will facilitate the development of future fever-related diagnostic tests. Here, we outline the methodology used to determine the sample populations and to differentiate bacterial versus non-bacterial AFIs. Future publications will set out in more detail the study's demographics, the causes of fever identified and the performance of selected biomarkers.

Indexed as

Bacterial InfectionsFeverHumansdiagnostics and toolspublic health

Identifiers

PMID33087393
PMCPMC7580043

What OpenQuestion holds

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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.