Evidence map›Paper›PMID 39194616›Full record

ArticleBiosensors2024

An Electrochemical Biosensor for the Detection of Pulmonary Embolism and Myocardial Infarction.

Yaw-Jen Chang, Fu-Yuan Siao, En-Yu Lin

Abstract read
In one paragraph

Article in Biosensors, 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
–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

1 citing paper in PubMed.

  1. Review
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.

Yaw-Jen ChangDepartment of Mechanical Engineering, Chung Yuan Christian University, Chung Li District, Taoyuan City 320314, Taiwan.
Fu-Yuan SiaoDepartment of Emergency and Critical Care Medicine, Changhua Christian Hospital, Changhua 50006, Taiwan.ORCID 0009-0007-5768-4051
En-Yu LinDepartment of Mechanical Engineering, Chung Yuan Christian University, Chung Li District, Taoyuan City 320314, Taiwan.

Funding

Changhua Christian Hospital 111-CCH-IRP-063
6 · The paper itself

Abstract

Due to the clinical similarities between pulmonary embolism (PE) and myocardial infarction (MI), physicians often encounter challenges in promptly distinguishing between them, potentially missing the critical window for the correct emergency response. This paper presents a biosensor, termed the PEMI biosensor, which is designed for the identification and quantitative detection of pulmonary embolism or myocardial infarction. The surface of the working electrode of the PEMI biosensor was modified with graphene oxide and silk fibroin to immobilize the mixture of antibodies. Linear sweep voltammetry was employed to measure the current-to-potential mapping of analytes, with the calculated curvature serving as a judgment index. Experimental results showed that the curvature exhibited a linear correlation with the concentration of antigen FVIII, and a linear inverse correlation with the concentration of antigen cTnI. Given that FVIII and cTnI coexist in humans, the upper and lower limits were determined from the curvatures of a set of normal concentrations of FVIII and cTnI. An analyte with a curvature exceeding the upper limit can be identified as pulmonary embolism, while a curvature falling below the lower limit indicates myocardial infarction. Additionally, the further the curvature deviates from the upper or lower limits, the more severe the condition. The PEMI biosensor can serve as an effective detection platform for physicians.

Indexed as

Biosensing TechniquesElectrochemical TechniquesMyocardial InfarctionPulmonary EmbolismElectrodesGraphiteHumansTroponin Igraphene oxideGraphiteTroponin Icardiac troponin I (cTnI)factor VIII (FVIII)myocardial infarctionpulmonary embolismsilk fibroin (SF)

Identifiers

PMID39194616
PMCPMC11352896

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.