Evidence map›Paper›PMID 36522386›Full record

ArticleScientific data2022

A Brazilian classified data set for prognosis of tuberculosis, between January 2001 and April 2020.

Maicon Herverton Lino Ferreira da Silva Barros, Guto Leoni Santos, Maria Gabriela de Almeida Rodrigues, Vanderson Sampaio, Theo Lynn, Patricia Takako Endo

Abstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Maicon Herverton Lino Ferreira da Silva Barros *Universidade de Pernambuco (UPE), Programa de Pós-graduação em Engenharia de Computação (PPGEC), Recife, 50720-001, Brazil.ORCID 0000-0002-0275-3298
Guto Leoni Santos *Universidade Federal de Pernambuco (UFPE), Centro de Informática (CIn), Recife, 50740-560, Brazil.
Maria Gabriela de Almeida Rodrigues *Universidade Estadual do Amazonas (UEA), Programa de Pós-graduação em Medicina Tropical (PPGMT), Manaus, 69850-000, Brazil.
Vanderson Sampaio *Instituto Todos pela Saúde (ITpS), São Paulo, 01310-942, Brazil.ORCID 0000-0001-7307-8851
Theo Lynn *Dublin City University (DCU), Dublin, Ireland.
Patricia Takako Endo *Universidade de Pernambuco (UPE), Programa de Pós-graduação em Engenharia de Computação (PPGEC), Recife, 50720-001, Brazil. patricia.endo@upe.br.ORCID 0000-0002-9163-5583

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

After COVID-19, tuberculosis (TB) is the leading cause of death by an infectious disease in the world. This work presents a data set based on data collected from the Brazilian Information System for Notifiable Diseases (SINAN) for the period from January 2001 to April 2020 relating to patients diagnosed with tuberculosis in Brazil. The data from SINAN was pre-processed to generate a new data set with two distinct treatment outcome classes: CURED and DIED. The data set comprises 37 categorical attributes (including socio-demographic, clinical, and laboratory data) as well as the target class. There are 927,909 records of patients classified as CURED and 36,190 classified as DIED, totaling 964,099 records.

Indexed as

TuberculosisBrazilHumansInformation SystemsPrognosis

Identifiers

PMID36522386
PMCPMC9753864

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.