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Liu C, Shen W, Xie H, Li Y, Cui R, Wu R, Xiao L, Li J, Guo Y, Liao Y, Zhao C, Xu Y, Wang Q. Improving the detection capability and efficiency of SARS-CoV-2 RNA specimens by the specimen turn-around process with multi-department cooperation. Front Public Health 2024; 11:1294341. [PMID: 38249400 PMCID: PMC10796989 DOI: 10.3389/fpubh.2023.1294341] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 12/12/2023] [Indexed: 01/23/2024] Open
Abstract
Objective Improving the detection capability and efficiency of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA specimens is very important for the prevention and control of the outbreak of Coronavirus disease 2019 (COVID-19). In this study, we evaluated the detection capability and efficiency of two outbreaks of COVID-19 before and after the process re-engineering in April and July 2022. Methods This retrospective cross-sectional study involved 359,845 SARS-CoV-2 RNA specimens 2 weeks before and 2 weeks after the two outbreaks of COVID-19 in April and July. The number, transportation time and detection time of specimens, and the number of reports of more than 24 h were analyzed by SPSS software. Results While 16.84% of people chose nasopharyngeal swabs (NPS) specimens, 83.16% chose oropharyngeal swabs (OPS) specimens to detect SARS-CoV-2 RNA. There were significant upward trends in the percentage of 10 sample pooling (P-10) from April before process re-engineering to July after process re-engineering (p < 0.001). Compared with April, the number of specimens in July increased significantly not only 2 weeks before but also 2 weeks after the outbreak of COVID-19, with an increase of 35.46 and 93.94%, respectively. After the process re-engineering, the number of reports more than 24 h in the 2 weeks before and after the outbreak of COVID-19 in July was significantly lower than that in April before process re-engineering (0% vs. 0.06% and 0 vs. 0.89%, both p < 0.001). Conclusion The present study shows that strengthening the cooperation of multi-departments in process re-engineering, especially using the P-10 strategy and whole process informatization can improve the detection capability and efficiency of SARS-CoV-2 RNA specimens.
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Affiliation(s)
- Chenggui Liu
- Department of Clinical Laboratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Wei Shen
- Department of Clinical Laboratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Huiqiong Xie
- Departments of Nursing, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Ying Li
- Department of Specimen Sampling, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Rong Cui
- Department of Specimen Transportation, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Rongcheng Wu
- Department of Information Technology, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Li Xiao
- Department of Medical Administration, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Jing Li
- Department of Hospital Infection Control, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yanjun Guo
- Departments of Medical Equipment, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yi Liao
- Department of Clinical Laboratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Chonghui Zhao
- Department of Clinical Laboratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Yunfei Xu
- Department of Clinical Laboratory, Chengdu Women's and Children's Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Chengdu, China
| | - Qin Wang
- Department of Clinical Laboratory, Sichuan Province Orthopedic Hospital, Chengdu, China
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Validation of SARS-CoV-2 pooled testing for surveillance using the Panther Fusion® system: Impact of pool size, automation, and assay chemistry. PLoS One 2022; 17:e0276729. [PMID: 36342921 PMCID: PMC9639840 DOI: 10.1371/journal.pone.0276729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 10/12/2022] [Indexed: 11/09/2022] Open
Abstract
Combining diagnostic specimens into pools has been considered as a strategy to augment throughput, decrease turnaround time, and leverage resources. This study utilized a multi-parametric approach to assess optimum pool size, impact of automation, and effect of nucleic acid amplification chemistries on the detection of SARS-CoV-2 RNA in pooled samples for surveillance testing on the Hologic Panther Fusion® System. Dorfman pooled testing was conducted with previously tested SARS-CoV-2 nasopharyngeal samples using Hologic’s Aptima® and Panther Fusion® SARS-CoV-2 Emergency Use Authorization assays. A manual workflow was used to generate pool sizes of 5:1 (five samples: one positive, four negative) and 10:1. An automated workflow was used to generate pool sizes of 3:1, 4:1, 5:1, 8:1 and 10:1. The impact of pool size, pooling method, and assay chemistry on sensitivity, specificity, and lower limit of detection (LLOD) was evaluated. Both the Hologic Aptima® and Panther Fusion® SARS-CoV-2 assays demonstrated >85% positive percent agreement between neat testing and pool sizes ≤5:1, satisfying FDA recommendation. Discordant results between neat and pooled testing were more frequent for positive samples with CT>35. Fusion® CT (cycle threshold) values for pooled samples increased as expected for pool sizes of 5:1 (CT increase of 1.92–2.41) and 10:1 (CT increase of 3.03–3.29). The Fusion® assay demonstrated lower LLOD than the Aptima® assay for pooled testing (956 vs 1503 cp/mL, pool size of 5:1). Lowering the cut-off threshold of the Aptima® assay from 560 kRLU (manufacturer’s setting) to 350 kRLU improved the assay sensitivity to that of the Fusion® assay for pooled testing. Both Hologic’s SARS-CoV-2 assays met the FDA recommended guidelines for percent positive agreement (>85%) for pool sizes ≤5:1. Automated pooling increased test throughput and enabled automated sample tracking while requiring less labor. The Fusion® SARS-CoV-2 assay, which demonstrated a lower LLOD, may be more appropriate for surveillance testing.
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