Evidence map›Paper›PMID 33501347›Full record

ArticleFrontiers in robotics and AI2020

Exploring the Applicability of Robot-Assisted UV Disinfection in Radiology.

Conor McGinn, Robert Scott, Niamh Donnelly, Kim L Roberts, Marina Bogue, Christine Kiernan, Michael Beckett

Open access · goldAbstract read
In one paragraph

Article in Frontiers in robotics and AI, 2020. 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
6.6field-weighted citation impact, top 3% 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

10 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. UV Disinfection Robots: A Review.Robotics and autonomous systems · 2023
    Article
  5. Article
  6. Article
  7. Review
  8. Review
  9. UVC-PURGE: A Novel Cost-Effective Disinfection Robot for Combating COVID-19 Pandemic.IEEE access : practical innovations, open solutions · 2022
    Article
  10. Portable Ultraviolet-C Chambers for Inactivation of SARS-CoV-2.Journal of research of the National Institute of Standards and Technology · 2021
    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

7 authors at 1 institution in 1 country.

Conor McGinnSchool of Engineering, Trinity College Dublin, Dublin, Ireland.
Robert ScottSchool of Engineering, Trinity College Dublin, Dublin, Ireland.
Niamh DonnellyAkara Robotics, Dublin, Ireland.
Kim L RobertsDepartment of Microbiology, Trinity College Dublin, Dublin, Ireland.
Marina BogueDepartment of Microbiology, Trinity College Dublin, Dublin, Ireland.
Christine KiernanSchool of Medicine, Trinity College Dublin, Dublin, Ireland.
Michael BeckettDepartment of Microbiology, Trinity College Dublin, Dublin, Ireland.
Trinity College Dublin · IE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The importance of infection control procedures in hospital radiology departments has become increasingly apparent in recent months as the impact of COVID-19 has spread across the world. Existing disinfectant procedures that rely on the manual application of chemical-based disinfectants are time consuming, resource intensive and prone to high degrees of human error. Alternative non-touch disinfection methods, such as Ultraviolet Germicidal Irradiation (UVGI), have the potential to overcome many of the limitations of existing approaches while significantly improving workflow and equipment utilization. The aim of this research was to investigate the germicidal effectiveness and the practical feasibility of using a robotic UVGI device for disinfecting surfaces in a radiology setting. We present the design of a robotic UVGI platform that can be deployed alongside human workers and can operate autonomously within cramped rooms, thereby addressing two important requirements necessary for integrating the technology within radiology settings. In one hospital, we conducted experiments in a CT and X-ray room. In a second hospital, we investigated the germicidal performance of the robot when deployed to disinfect a CT room in <15 minutes, a period which is estimated to be 2-4 times faster than current practice for disinfecting rooms after infectious (or potentially infectious) patients. Findings from both test sites show that UVGI successfully inactivated all of measurable microbial load on 22 out of 24 surfaces. On the remaining two surfaces, UVGI reduced the microbial load by 84 and 95%, respectively. The study also exposes some of the challenges of manually disinfecting radiology suites, revealing high concentrations of microbial load in hard-to-reach places. Our findings provide compelling evidence that UVGI can effectively inactivate microbes on commonly touched surfaces in radiology suites, even if they were only exposed to relatively short bursts of irradiation. Despite the short irradiation period, we demonstrated the ability to inactivate microbes with more complex cell structures and requiring higher UV inactivation energies than SARS-CoV-2, thus indicating high likelihood of effectiveness against coronavirus.

Indexed as

COVID-19disinfection methodsHCAIradiology robotroboticsUVGIUV robot

Identifiers

PMID33501347
PMCPMC7815819
OpenAlexW3118898663

What OpenQuestion 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 OpenQuestion graph.