Evidence map›Paper›PMID 38182696›Full record

ArticleParasitology research2024

An algorithm for visceral leishmaniasis diagnosis in Brazil from a 10-year analysis of National Reference Laboratory data.

Job Alves de Souza Filho, Marcos Paulo Gomes Mol, Fernanda Alvarenga Cardoso Medeiros

Abstract read
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In one paragraph

Article in Parasitology research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.6field-weighted citation impact, top 18% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Job Alves de Souza FilhoFundação Ezequiel Dias, Brazilian National Reference Laboratory for the Diagnosis of Visceral Leishmaniasis, Octavio Magalhães Institute, Belo Horizonte, MG, Brazil. job.filho@funed.mg.gov.br.
Marcos Paulo Gomes MolFundação Ezequiel Dias, Research and Development Board, Belo Horizonte, MG, Brazil.
Fernanda Alvarenga Cardoso MedeirosFundação Ezequiel Dias, Brazilian National Reference Laboratory for the Diagnosis of Visceral Leishmaniasis, Octavio Magalhães Institute, Belo Horizonte, MG, Brazil.
Ezequiel Dias Foundation · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Visceral leishmaniasis (VL) requires diagnostic assays to complement clinical suspicion. However, there is no standardization of a diagnostic flow using available assays. This study aimed to evaluate the performance of parasitological, molecular, and serological assays for diagnosing VL and propose a diagnostic flow based on performance, practicality, and invasiveness. We conducted a study of 10-year (2010-2020) routine diagnoses of VL at the Brazilian National Reference Laboratory. We propose a diagnostic flow where individuals suspected of VL are initially screened for antibodies using an immunochromatographic test (ICT) with rK39 antigen on the nitrocellulose membrane. This is followed by a blood polymerase chain reaction (PCR) for Leishmania sp. kDNA and direct parasitological exam and/or PCR in bone marrow aspirate. A positive result in any of these assays can define a VL case. If clinical suspicion persists in negative individuals, the diagnostic flow should be repeated. The proposed flow has the potential to standardize and improve the diagnosis of VL. It reduces the need for invasive tests without compromising diagnostic accuracy.

Indexed as

Leishmaniasis, VisceralAlgorithmsAntibodiesBiological AssayBrazilHumansAntibodiesDiagnostic flowICTPCRrK39Visceral leishmaniasis

Identifiers

PMID38182696
OpenAlexW4390630617

What OpenQuestion holds

Textmetadata
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.