Evidence map›Paper›PMID 36912628›Full record

ReviewACS sensors2023

Sensing Technologies for Extravasation Detection: A Review.

Ikue Hirata, Arianna Mazzotta, Pooyan Makvandi, Ilaria Cesini, Chiara Brioschi, Andrea Ferraris, Virgilio Mattoli

Full text readReview
In one paragraph

Review in ACS sensors, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Explainable Knowledge-Guided Algorithm for Contrast Extravasation Detection on Computed Tomography.IEEE journal of translational engineering in health and medicine · 2026
    Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. Article
  10. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Ikue HirataCenter for Materials Interfaces, Istituto Italiano di Tecnologia, 56025 Pontedera, Pisa, Italy.
Arianna MazzottaCenter for Materials Interfaces, Istituto Italiano di Tecnologia, 56025 Pontedera, Pisa, Italy.
Pooyan MakvandiCenter for Materials Interfaces, Istituto Italiano di Tecnologia, 56025 Pontedera, Pisa, Italy.ORCID 0000-0003-2456-0961
Ilaria CesiniCenter for Materials Interfaces, Istituto Italiano di Tecnologia, 56025 Pontedera, Pisa, Italy.
Chiara BrioschiIIT-Bracco Joint Lab, Istituto Italiano di Tecnologia, 16163 Genova, Italy.
Andrea FerrarisIIT-Bracco Joint Lab, Istituto Italiano di Tecnologia, 16163 Genova, Italy.
Virgilio MattoliCenter for Materials Interfaces, Istituto Italiano di Tecnologia, 56025 Pontedera, Pisa, Italy.ORCID 0000-0002-4715-8353

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Peripheral intravenous catheters are administered for various purposes, such as blood sampling or the infusion of contrast agents and drugs. Extravasation happens when the catheter is unintentionally directed outside of the vein due to movement of the intravascular catheter, enhanced vascular permeability, or occlusion of the upstream vein. In this article, extravasation and its mechanism are discussed. Subsequently, the sensorized devices (e.g., single sensor and multimodal detection) to identify the extravasation phenomena are highlighted. In this review article, we have shed light on both physiological and engineering points of view of extravasation and its detection approaches. This review provides an overview on the most recent and relevant technologies that can help in the early detection of extravasation.

Indexed as

Catheterization, PeripheralContrast MediaEngineeringContrast MediableedingBlood extravasationcontrast agentdrug infusioninfiltrationinfrared sensorsintravenous cathetersPIVCradiofrequency sensorthermal imagingultrasound sensors

Identifiers

PMID36912628
PMCPMC10043935

What OpenQuestion holds

Textfull text, public
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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.