Evidence map›Paper›PMID 23394216›Full record

ArticleBMC infectious diseases2013

Clinical and laboratory features that discriminate dengue from other febrile illnesses: a diagnostic accuracy study in Rio de Janeiro, Brazil.

Regina P Daumas, Sonia R L Passos, Raquel V C Oliveira, Rita M R Nogueira, Ingebourg Georg, Keyla B F Marzochi, Patrícia Brasil

Open access · goldAbstract read
In one paragraph

Article in BMC infectious diseases, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed, 2 pooled it
6.8field-weighted citation impact, top 3% 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

31 citing papers in PubMed, 2 syntheses or guidelines pooled it, 72 citations in OpenAlex.

  1. Pooled it
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  12. Epidemiological and clinical analysis of the outbreak of dengue fever in Zhangshu City, Jiangxi Province, in 2019.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2021
    Article
  13. Article
  14. Article
  15. Development and Performance of Dengue Diagnostic Clinical Algorithms in Colombia.The American journal of tropical medicine and hygiene · 2020
    Article
  16. Etiologies of Acute Undifferentiated Febrile Illness in Bangkok, Thailand.The American journal of tropical medicine and hygiene · 2019
    Article
  17. Article
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  20. Prospective evaluation of the SD BIOLINE Dengue Duo rapid test during a dengue virus epidemic.European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology · 2017
    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

7 authors at 1 institution in 1 country.

Regina P DaumasGermano Sinval Faria Teaching Primary Care Center/National School of Public Health, Oswaldo Cruz Foundation - Fiocruz, Rio de Janeiro, 21041-210, Brazil. regina.daumas@gmail.com
Sonia R L Passos
Raquel V C Oliveira
Rita M R Nogueira
Ingebourg Georg
Keyla B F Marzochi
Patrícia Brasil
Fundação Oswaldo Cruz · BR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDengue is an acute febrile illness caused by an arbovirus that is endemic in more than 100 countries. Early diagnosis and adequate management are critical to reduce mortality. This study aims to identify clinical and hematological features that could be useful to discriminate dengue from other febrile illnesses (OFI) up to the third day of disease.

methodsWe conducted a sectional diagnostic study with patients aged 12 years or older who reported fever lasting up to three days, without any evident focus of infection, attending an outpatient clinic in the city of Rio de Janeiro, Brazil, between the years 2005 and 2008. Logistic regression analysis was used to identify symptoms, physical signs, and hematological features valid for dengue diagnosis. Receiver-operating characteristic (ROC) curve analyses were used to define the best cut-off and to compare the accuracy of generated models with the World Health Organization (WHO) criteria for probable dengue.

resultsBased on serological tests and virus genome detection by polymerase chain reaction (PCR), 69 patients were classified as dengue and 73 as non-dengue. Among clinical features, conjunctival redness and history of rash were independent predictors of dengue infection. A model including clinical and laboratory features (conjunctival redness and leukocyte counts) achieved a sensitivity of 81% and specificity of 71% and showed greater accuracy than the WHO criteria for probable dengue.

conclusionsWe constructed a predictive model for early dengue diagnosis that was moderately accurate and performed better than the current WHO criteria for suspected dengue. Validation of this model in larger samples and in other sites should be attempted before it can be applied in endemic areas.

Indexed as

AdultDengueDiagnosis, DifferentialDiagnostic Tests, RoutineFemaleFeverHumansMaleOdds RatioROC CurveTime FactorsYoung Adult

Identifiers

PMID23394216
PMCPMC3574824
OpenAlexW1965305135

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.