| Title |
3D printed fluidic swab for COVID-19 testing with improved diagnostic yield and user comfort
|
|---|---|
| Published in |
Nano Convergence, September 2023
|
| DOI | 10.1186/s40580-023-00393-3 |
| Pubmed ID | |
| Authors |
Joochan Kim, Jaehyung Jeon, Hyowon Jang, Youngkwang Moon, Abdurhaman Teyib Abafogi, Danny van Noort, Jinkee Lee, Taejoon Kang, Sungsu Park |
| Abstract |
The current standard method of diagnosing coronavirus disease 2019 (COVID-19) involves uncomfortable and invasive nasopharyngeal (NP) sampling using cotton swabs (CS), which can be unsuitable for self-testing. Although mid-turbinate sampling is an alternative, it has a lower diagnostic yield than NP sampling. Nasal wash (NW) has a similar diagnostic yield to NP sampling, but is cumbersome to perform. In this study, we introduce a 3D printed fluidic swab (3DPFS) that enables easy NW sampling for COVID-19 testing with improved diagnostic yield. The 3DPFS comprises a swab head, microchannel, and socket that can be connected to a syringe containing 250 µL of NW solution. The 3DPFS efficiently collects nasal fluid from the surface of the nasal cavity, resulting in higher sensitivity than CS for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This was confirmed by both reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and lateral flow assays (LFA) in virus-spiked nasal samples and clinical samples. Additionally, users reported greater comfort when using the 3DPFS compared to CS. These findings suggest that the 3DPFS can improve the performance of COVID-19 testing by facilitating efficient and less painful nasal sample collection. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Unspecified | 1 | 100% |
| Lecturer | 1 | 100% |
| Readers by discipline | Count | As % |
|---|---|---|
| Unspecified | 1 | 100% |
| Computer Science | 1 | 100% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 September 2023.
All research outputs
#17,020,992
of 25,011,008 outputs
Outputs from Nano Convergence
#77
of 125 outputs
Outputs of similar age
#171,435
of 315,141 outputs
Outputs of similar age from Nano Convergence
#3
of 6 outputs
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So far Altmetric has tracked 125 research outputs from this source. They receive a mean Attention Score of 4.6. This one is in the 27th percentile – i.e., 27% of its peers scored the same or lower than it.
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