Evidence map›Paper›PMID 35427400›Full record

SynthesisPloS one2022

Risk and predictive factors for severe dengue infection: A systematic review and meta-analysis.

Kangzhuang Yuan, Yuan Chen, Meifeng Zhong, Yongping Lin, Lidong Liu

Abstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in PloS one, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing 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

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

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  12. Dengue encephalitis: what's new?Current opinion in infectious diseases · 2025
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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

5 authors.

Kangzhuang YuanDivision of Clinical Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China.
Yuan ChenDivision of Clinical Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China.
Meifeng ZhongDivision of Clinical Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China.
Yongping LinDivision of Clinical Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China.
Lidong LiuDivision of Clinical Laboratory Medicine, The First Affiliated Hospital of Guangzhou Medical University, Guangzhou, Guangdong, P.R. China.ORCID 0000-0001-5509-513X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDengue is a major public health issue worldwide and severe dengue (SD) is life threatening. It is critical to triage patients with dengue infection in the early stage. However, there is limited knowledge on early indicators of SD. The objective of this study is to identify risk factors for the prognosis of SD and try to find out some potential predictive factors for SD from dengue fever (DF) in the early of infection.

methodsThe PubMed, Cochrane Library and Web of Science databases were searched for relevant studies from June 1999 to December 2020. The pooled odds ratio (OR) or standardized mean difference (SMD) with 95% confidence intervals (CI) of identified factors was calculated using a fixed or random effect model in the meta-analysis. Tests for heterogeneity, publication bias, subgroup analyses, meta-regression, and a sensitivity analysis were further performed.

findingsA total of 6,848 candidate articles were retrieved, 87 studies with 35,184 DF and 8,173 SD cases met the eligibility criteria. A total of 64 factors were identified, including population and virus characteristics, clinical symptoms and signs, laboratory biomarkers, cytokines, and chemokines; of these factors, 34 were found to be significantly different between DF and SD, while the other 30 factors were not significantly different between the two groups after pooling the data from the relevant studies. Additionally, 9 factors were positive associated with SD within 7 days after illness when the timing subgroup analysis were performed.

conclusionsPractical factors and biomarkers for the identification of SD were established, which will be helpful for a prompt diagnosis and early effective treatment for those at greatest risk. These outcomes also enhance our knowledge of the clinical manifestations and pathogenesis of SD.

Indexed as

DengueSevere DengueBiomarkersHumansOdds RatioPrognosisRisk FactorsBiomarkers

Identifiers

PMID35427400
PMCPMC9012395

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.