Personal Protective Equipment: A Pandora&amp;#39;s Box

Chawla, Gopal; Abrol, Nupur; Kakkar, Kamna

doi:10.5005/jp-journals-10071-23443

Cited by 9 publications

(5 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Robots are widely suggested to be deployed in different scenarios during the pandemic, to help reduce the infection by performing disinfection, monitoring, delivering, food preparation, and telepresence [ [8] , [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] ]. Robots are also recommended to make intelligent decisions based on the inputs data from the population, which can be analysed through AI [ 17 ].…”

Section: Robots In Covid-19mentioning

confidence: 99%

A literature survey of the robotic technologies during the COVID-19 pandemic

Wang

2021

Journal of Manufacturing Systems

195

View full text Add to dashboard Cite

Since the late 2019, the COVID-19 pandemic has been spread all around the world. The pandemic is a critical challenge to the health and safety of the general public, the medical staff and the medical systems worldwide. It has been globally proposed to utilise robots during the pandemic, to improve the treatment of patients and leverage the load of the medical system. However, there is still a lack of detailed and systematic review of the robotic research for the pandemic, from the technologies’ perspective. Thus a thorough literature survey is conducted in this research and more than 280 publications have been reviewed, with the focus on robotics during the pandemic. The main contribution of this literature survey is to answer two research questions, i.e. 1) what the main research contributions are to combat the pandemic from the robotic technologies’ perspective, and 2) what the promising supporting technologies are needed during and after the pandemic to help and guide future robotics research. The current achievements of robotic technologies are reviewed and discussed in different categories, followed by the identification of the representative work’s technology readiness level. The future research trends and essential technologies are then highlighted, including artificial intelligence, 5 G, big data, wireless sensor network, and human-robot collaboration.

show abstract

Section: Robots In Covid-19mentioning

confidence: 99%

A literature survey of the robotic technologies during the COVID-19 pandemic

Wang

2021

Journal of Manufacturing Systems

195

View full text Add to dashboard Cite

show abstract

“…N95 respirators are a valuable resource, particularly during the COVID-19 pandemic. 19 , 20 However, it has been found that they have a high failure rate. 21 Ideally, a broad range of respirators should fit all users.…”

Section: Discussionmentioning

confidence: 99%

Safety Goggles with Elastic Headband to Improve N95 Fit Following Failed Quantitative Fit Test

Arora¹,

Johns²,

Shehabi³

et al. 2023

Indian Journal of Critical Care Medicine

View full text Add to dashboard Cite

A bstract Introduction N95 respirators, together with eye protection, form vital elements of personal protective equipment (PPE) for healthcare workers (HCW) caring for patients with respiratory infections, such as COVID-19. Duckbill N95 respirators are widely used but have a high failure rate when Fit Tested. The commonest site for inward leaks is the region between the nose and maxilla. Safety goggles with an elastic headband may press the upper rim of the respirator against the face, thereby reducing inward leaks. We hypothesized that the use of safety goggles with an elastic headband will improve the overall fit-factor of a duckbill N95 respirator and increase the proportion of users who pass a quantitative Fit Test. Methods About 60 volunteer HCWs, who had previously failed quantitative Fit Testing with a duckbill N95 respirator, participated in this before-and-after intervention study. A PortaCount® 8048 was used for quantitative Fit Testing. The test was first performed with a duckbill N95 respirator only. It was then repeated after participants donned a pair of safety goggles (3M Fahrenheit, ID 70071531621). Results Before the intervention, i.e., with the respirator only, 8 (13.3%) participants passed their Fit Test. This increased to 49 (81.7%) after the application of safety goggles (OR 42, 95% CI 7.14–1697.9, p < 0.0001). The adjusted mean overall fit factor, using Tobit regression analysis, increased from 40.3 to 193.0 ( t = 12.32, p < 0.001). Conclusion The use of safety goggles with an elastic headband significantly increases the proportion of users who pass a quantitative Fit Test and improves the fit-factor of a duckbill N95 respirator. How to cite this article Kamal M, Bhatti M, Stewart WC, Johns M, Collins D, Shehabi Y, et al . Safety Goggles with Elastic Headband to Improve N95 Fit Following Failed Quantitative Fit Test. Indian J Crit Care Med 2023;27(6):386–391.

show abstract

“… 9 Exhaled humidified gases also result in fogging of the eyeglasses, which is a frequent observation of those who wear eyeglasses. 9 , 10 In a recently reported prospective cohort study from India, all users complained of fogging when using PPE and caring for patients with COVID-19. 11 It is a commonly held notion that fogging of eyeglasses indicates poor seal of the N95 respirator and vice versa.…”

Section: Introductionmentioning

confidence: 99%

Prediction of N95 Respirator Fit from Fogging of Eyeglasses: A Pilot Study

Kyaw¹,

Johns²,

Lim³

et al. 2021

Indian Journal of Critical Care Medicine

View full text Add to dashboard Cite

A bstract Aim and objective Fogging of eyeglasses while wearing N95 respirators is common. It is commonly held that the N95 respirator has a poor fit if there is fogging of eyeglasses. We conducted this prospective, pilot study to determine if fogging of eyeglasses predicts poor fit of N95 respirator. Materials and methods Seventy volunteer healthcare workers from a tertiary intensive care unit in Sydney, Australia participated. The participants donned one of the following N95 respirators: three-panel flat-fold respirator (3M 1870), cup-shaped respirator (3M 1860), or a duckbill respirator. After a satisfactory “user seal check” as recommended by the manufacturer, the participants donned eyeglasses and checked for fogging. A quantitative fit test (QnFT) of the respirator was then performed (using PortaCount Respirator Fit Tester 8048, TSI Inc., Minnesota, USA). A fit factor of <100 on quantitative fit testing indicates poor fit. The sensitivity and specificity for fogging of eyeglasses (index test) to predict the poor fit of N95 respirator was determined, compared to QnFT (gold standard test). Results Fogging of eyeglasses as a predictor of poor respirator fit (i.e., fit factor <100 on QnFT) had sensitivity of 71% (95% CI, 54–85%) and specificity 46% (95% CI, 29–63%). The odds ratio of fogging as a predictor for poor fit was 2.10 (95% CI, 0.78–5.67), with a two-tailed p -value of 0.22 (not significant). The receiver operating characteristic curve for fogging of eyeglasses as a diagnostic test had the area under the curve of 0.59. Conclusion Fogging of eyeglasses is neither a sensitive nor a specific predictor for poor fit of N95 respirators. How to cite this article Kyaw S, Johns M, Lim R, Stewart WC, Rojas N, Thambiraj SR, et al. Prediction of N95 Respirator Fit from Fogging of Eyeglasses: A Pilot Study. Indian J Crit Care Med 2021;25(9):976–980.

show abstract

Personal Protective Equipment: A Pandora's Box

Cited by 9 publications

References 9 publications

A literature survey of the robotic technologies during the COVID-19 pandemic

A literature survey of the robotic technologies during the COVID-19 pandemic

Safety Goggles with Elastic Headband to Improve N95 Fit Following Failed Quantitative Fit Test

Prediction of N95 Respirator Fit from Fogging of Eyeglasses: A Pilot Study

Contact Info

Product

Resources

About