Evidence map›Paper›PMID 34853326›Full record

ArticleScientific reports2021

A wearable microwave instrument can detect and monitor traumatic abdominal injuries in a porcine model.

Stefan Candefjord, Linh Nguyen, Ruben Buendia, Marianne Oropeza-Moe, Nina Gjerde Andersen, Andreas Fhager, Mikael Persson, Mikael Elam, Nils Petter Oveland

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
0.4field-weighted citation impact, top 36% 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

3 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. 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

9 authors at 4 institutions in 2 countries.

Stefan CandefjordDepartment of Electrical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden. stefan.candefjord@chalmers.se.
Linh NguyenDepartment of Electrical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
Ruben BuendiaDepartment of Electrical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
Marianne Oropeza-MoeDepartment of Production Animal Clinical Sciences, Faculty of Veterinary Medicine, Norwegian University of Life Sciences, Sandnes, Norway.
Nina Gjerde AndersenDepartment of Anesthesiology and Intensive Care, Stavanger University Hospital, Stavanger, Norway.
Andreas FhagerDepartment of Electrical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
Mikael PerssonDepartment of Electrical Engineering, Chalmers University of Technology, 412 96, Gothenburg, Sweden.
Mikael ElamMedTech West, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden.
Nils Petter OvelandDepartment of Anesthesiology and Intensive Care, Stavanger University Hospital, Stavanger, Norway.
Chalmers University of Technology · SESahlgrenska University Hospital · SEStavanger University Hospital · NONorwegian University of Life Sciences · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Abdominal injury is a frequent cause of death for trauma patients, and early recognition is essential to limit fatalities. There is a need for a wearable sensor system for prehospital settings that can detect and monitor bleeding in the abdomen (hemoperitoneum). This study evaluates the potential for microwave technology to fill that gap. A simple prototype of a wearable microwave sensor was constructed using eight antennas. A realistic porcine model of hemoperitoneum was developed using anesthetized pigs. Ten animals were measured at healthy state and at two sizes of bleeding. Statistical tests and a machine learning method were used to evaluate blood detection sensitivity. All subjects presented similar changes due to accumulation of blood, which dampened the microwave signal ([Formula: see text]). The machine learning analysis yielded an area under the receiver operating characteristic (ROC) curve (AUC) of 0.93, showing 100% sensitivity at 90% specificity. Large inter-individual variability of the healthy state signal complicated differentiation of bleedings from healthy state. A wearable microwave instrument has potential for accurate detection and monitoring of hemoperitoneum, with automated analysis making the instrument easy-to-use. Future hardware development is necessary to suppress measurement system variability and enable detection of smaller bleedings.

Indexed as

Microwave ImagingAbdominal InjuriesAnimalsDisease Models, AnimalFemaleHemoperitoneumMachine LearningMonitoring, PhysiologicROC CurveSwineWearable Electronic Devices

Identifiers

PMID34853326
PMCPMC8636634
OpenAlexW3215919801

What OpenQuestion holds

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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.