Evidence map›Paper›PMID 40165016›Full record

ReviewACS sensors2025

Portable Point-of-Care Diagnosis Platforms and Emerging Predictive Biomarkers for Rapid Detection of Severe Dengue Viral Infection.

Tharmaraj Vairaperumal, Po-Tseng Lee, Ping-Yen Liu

Abstract readReview
In one paragraph

Review in ACS sensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

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

  1. Pooled it
  2. Pooled it
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. 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.

Tharmaraj VairaperumalInstitute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan, ROC.ORCID 0000-0001-7747-4712
Po-Tseng LeeInstitute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan, ROC.
Ping-Yen LiuInstitute of Clinical Medicine, College of Medicine, National Cheng Kung University, Tainan 70403, Taiwan, ROC.ORCID 0000-0002-3643-5204

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Dengue virus (DENV) infection is a major global public health problem, particularly in tropical and subtropical regions where Aedes mosquitoes are prevalent. The clinical spectrum of dengue ranges from mild febrile illness to severe conditions such as dengue hemorrhagic fever and dengue shock syndrome. Early prediction of dengue progress is crucial for timely therapeutic medications, which can reduce both morbidity and mortality. Traditional diagnostic methods such as serological tests and polymerase chain reactions are often time-consuming and require sophisticated infrastructure and skilled personnel. To overcome these limitations, the development of point-of-care (POC) diagnosis platforms and novel predictive biomarkers is crucial to providing rapid, real-time diagnostic tools that can be used in low-resource settings and at the patient's bedside. Predictive biomarkers enable the identification of disease risk in the early stages and can reduce hospitalization visits. This review offers a comprehensive overview of portable POC diagnosis platforms and emerging predictive biomarkers for the rapid diagnosis of severe DENV infection. Its provides an overview of its epidemiology, discusses the global burden of DENV, and explores DENV infection with different serotypes, as well as the clinical spectrum and severity of dengue. The key focus is on the latest advancements in POC diagnosis readout methods and portable POC devices for DENV diagnosis, including colorimetric assay, electrochemical method, lateral flow strip, and microfluidic chip platforms. In addition, the review article explores various emerging predictive biomarkers for the rapid detection of DENV, while also highlighting the limitations associated with protein, nucleic acid, and metabolic biomarkers. Finally, we address the current challenges, limitations, and potential future directions of POC diagnosis platforms for the diagnosis of severe DENV infection.

Indexed as

DengueDengue VirusPoint-of-Care SystemsPoint-of-Care TestingSevere DengueBiomarkersHumansBiomarkersDengue diagnosisDengue virusDENVpoint-of-careportable devicepredictive biomarkersrapid detectionviral infection

Identifiers

PMID40165016
PMCPMC12105087

What Socratic 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 Socratic graph.