Automated Author Profile

Wu, Jhong-Lin

Current S-Index

2.2

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.5

Average Dataset Index per dataset

Total Datasets

4

Total datasets for this author

Average FAIR Score

84.6%

Average FAIR Score per dataset

Total Citations

3

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Multicenter evaluation of two chemiluminescence and three lateral flow immunoassays for the diagnosis of COVID-19 and assessment of antibody dynamic responses to SARS-CoV-2 in Taiwan

This multicenter, retrospective study included 346 serum samples from 74 patients with coronavirus disease 2019 (COVID-19) and 194 serum samples from non-COVID-19 patients to evaluate the performance of five anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests, i.e. two chemiluminescence immunoassays (CLIAs): Roche Elecsys® Anti-SARS-CoV-2 Test (Roche Test) and Abbott SARS-CoV-2 IgG (Abbott Test), and three lateral flow immunoassays (LFIAs): Wondfo SARS-CoV-2 Antibody Test (Wondfo Test), ASK COVID-19 IgG/IgM Rapid Test (ASK Test), and Dynamiker 2019-nCoV IgG/IgM Rapid Test (Dynamiker Test). We found high diagnostic sensitivities (%, 95% confidence interval [CI]) for the Roche Test (97.4%, 93.4–99.0%), Abbott Test (94.0%, 89.1–96.8%), Wondfo Test (91.4%, 85.8–94.9%), ASK Test (97.4%, 93.4–99.0%), and Dynamiker Test (90.1%, 84.3–94.0%) after >21 days of symptom onset. Meanwhile, the diagnostic specificity was 99.0% (95% CI, 96.3–99.7%) for the Roche Test, 97.9% (95% CI, 94.8–99.2%) for the Abbott Test, and 100.0% (95% CI, 98.1–100.0%) for the three LFIAs. Cross-reactivity was observed in sera containing anti-cytomegalovirus (CMV) IgG/IgM antibodies and autoantibodies. No difference was observed in the time to seroconversion detection of the five serological tests. Specimens from patients with COVID-19 pneumonia demonstrated a shorter seroconversion time and higher chemiluminescent signal than those without pneumonia. Our data suggested that understanding the dynamic antibody response after COVID-19 infection and performance characteristics of different serological test are crucial for the appropriate interpretation of serological test result for the diagnosis and risk assessment of patient with COVID-19 infection.

Authors

  • Chen, Shey-Ying ;
  • Lee, Yu-Lin ;
  • Lin, Yi-Chun ;
  • Lee, Nan-Yao ;
  • Liao, Chia-Hung ;
  • Hung, Yuan-Pin ;
  • Lu, Min-Chi ;
  • Wu, Jhong-Lin ;
  • Tseng, Wen-Pin ;
  • Lin, Chien-Hao ;
  • Chung, Ming-Yi ;
  • Kang, Chun-Min ;
  • Lee, Ya-Fan ;
  • Lee, Tai-Fen ;
  • Cheng, Chien-Yu ;
  • Chen, Cheng-Pin ;
  • Huang, Chien-Hua ;
  • Liu, Chun-Eng ;
  • Cheng, Shu-Hsing ;
  • Ko, Wen-Chien ;
  • Hsueh, Po-Ren ;
  • Chen, Shyr-Chyr
1 Citation0 Mentions85% FAIR0.6 Dataset Index
10.6084/m9.figshare.130347982023

Multicenter evaluation of two chemiluminescence and three lateral flow immunoassays for the diagnosis of COVID-19 and assessment of antibody dynamic responses to SARS-CoV-2 in Taiwan

This multicenter, retrospective study included 346 serum samples from 74 patients with coronavirus disease 2019 (COVID-19) and 194 serum samples from non-COVID-19 patients to evaluate the performance of five anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests, i.e. two chemiluminescence immunoassays (CLIAs): Roche Elecsys® Anti-SARS-CoV-2 Test (Roche Test) and Abbott SARS-CoV-2 IgG (Abbott Test), and three lateral flow immunoassays (LFIAs): Wondfo SARS-CoV-2 Antibody Test (Wondfo Test), ASK COVID-19 IgG/IgM Rapid Test (ASK Test), and Dynamiker 2019-nCoV IgG/IgM Rapid Test (Dynamiker Test). We found high diagnostic sensitivities (%, 95% confidence interval [CI]) for the Roche Test (97.4%, 93.4–99.0%), Abbott Test (94.0%, 89.1–96.8%), Wondfo Test (91.4%, 85.8–94.9%), ASK Test (97.4%, 93.4–99.0%), and Dynamiker Test (90.1%, 84.3–94.0%) after >21 days of symptom onset. Meanwhile, the diagnostic specificity was 99.0% (95% CI, 96.3–99.7%) for the Roche Test, 97.9% (95% CI, 94.8–99.2%) for the Abbott Test, and 100.0% (95% CI, 98.1–100.0%) for the three LFIAs. Cross-reactivity was observed in sera containing anti-cytomegalovirus (CMV) IgG/IgM antibodies and autoantibodies. No difference was observed in the time to seroconversion detection of the five serological tests. Specimens from patients with COVID-19 pneumonia demonstrated a shorter seroconversion time and higher chemiluminescent signal than those without pneumonia. Our data suggested that understanding the dynamic antibody response after COVID-19 infection and performance characteristics of different serological test are crucial for the appropriate interpretation of serological test result for the diagnosis and risk assessment of patient with COVID-19 infection.

Authors

  • Chen, Shey-Ying ;
  • Lee, Yu-Lin ;
  • Lin, Yi-Chun ;
  • Lee, Nan-Yao ;
  • Liao, Chia-Hung ;
  • Hung, Yuan-Pin ;
  • Lu, Min-Chi ;
  • Wu, Jhong-Lin ;
  • Tseng, Wen-Pin ;
  • Lin, Chien-Hao ;
  • Chung, Ming-Yi ;
  • Kang, Chun-Min ;
  • Lee, Ya-Fan ;
  • Lee, Tai-Fen ;
  • Cheng, Chien-Yu ;
  • Chen, Cheng-Pin ;
  • Huang, Chien-Hua ;
  • Liu, Chun-Eng ;
  • Cheng, Shu-Hsing ;
  • Ko, Wen-Chien ;
  • Hsueh, Po-Ren ;
  • Chen, Shyr-Chyr
0 Citations0 Mentions85% FAIR0.3 Dataset Index
10.6084/m9.figshare.13034798.v32023

Multicenter evaluation of two chemiluminescence and three lateral flow immunoassays for the diagnosis of COVID-19 and assessment of antibody dynamic responses to SARS-CoV-2 in Taiwan

This multicenter, retrospective study included 346 serum samples from 74 patients with coronavirus disease 2019 (COVID-19) and 194 serum samples from non-COVID-19 patients to evaluate the performance of five anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests, i.e. two chemiluminescence immunoassays (CLIAs): Roche Elecsys® Anti-SARS-CoV-2 Test (Roche Test) and Abbott SARS-CoV-2 IgG (Abbott Test), and three lateral flow immunoassays (LFIAs): Wondfo SARS-CoV-2 Antibody Test (Wondfo Test), ASK COVID-19 IgG/IgM Rapid Test (ASK Test), and Dynamiker 2019-nCoV IgG/IgM Rapid Test (Dynamiker Test). We found high diagnostic sensitivities (%, 95% confidence interval [CI]) for the Roche Test (97.4%, 93.4–99.0%), Abbott Test (94.0%, 89.1–96.8%), Wondfo Test (91.4%, 85.8–94.9%), ASK Test (97.4%, 93.4–99.0%), and Dynamiker Test (90.1%, 84.3–94.0%) after >21 days of symptom onset. Meanwhile, the diagnostic specificity was 99.0% (95% CI, 96.3–99.7%) for the Roche Test, 97.9% (95% CI, 94.8–99.2%) for the Abbott Test, and 100.0% (95% CI, 98.1–100.0%) for the three LFIAs. Cross-reactivity was observed in sera containing anti-cytomegalovirus (CMV) IgG/IgM antibodies and autoantibodies. No difference was observed in the time to seroconversion detection of the five serological tests. Specimens from patients with COVID-19 pneumonia demonstrated a shorter seroconversion time and higher chemiluminescent signal than those without pneumonia. Our data suggested that understanding the dynamic antibody response after COVID-19 infection and performance characteristics of different serological test are crucial for the appropriate interpretation of serological test result for the diagnosis and risk assessment of patient with COVID-19 infection.

Authors

  • Chen, Shey-Ying ;
  • Lee, Yu-Lin ;
  • Lin, Yi-Chun ;
  • Lee, Nan-Yao ;
  • Liao, Chia-Hung ;
  • Hung, Yuan-Pin ;
  • Lu, Min-Chi ;
  • Wu, Jhong-Lin ;
  • Tseng, Wen-Pin ;
  • Lin, Chien-Hao ;
  • Chung, Ming-Yi ;
  • Kang, Chun-Min ;
  • Lee, Ya-Fan ;
  • Lee, Tai-Fen ;
  • Cheng, Chien-Yu ;
  • Chen, Cheng-Pin ;
  • Huang, Chien-Hua ;
  • Liu, Chun-Eng ;
  • Cheng, Shu-Hsing ;
  • Ko, Wen-Chien ;
  • Hsueh, Po-Ren ;
  • Chen, Shyr-Chyr
1 Citation0 Mentions85% FAIR0.6 Dataset Index
10.6084/m9.figshare.13034798.v22021

Multicenter evaluation of two chemiluminescence and three lateral flow immunoassays for the diagnosis of COVID-19 and assessment of antibody dynamic responses to SARS-CoV-2 in Taiwan

This multicenter, retrospective study included 346 serum samples from 74 patients with coronavirus disease 2019 (COVID-19) and 194 serum samples from non-COVID-19 patients to evaluate the performance of five anti-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) antibody tests, i.e. two chemiluminescence immunoassays (CLIAs): Roche Elecsys® Anti-SARS-CoV-2 Test (Roche Test) and Abbott SARS-CoV-2 IgG (Abbott Test), and three lateral flow immunoassays (LFIAs): Wondfo SARS-CoV-2 Antibody Test (Wondfo Test), ASK COVID-19 IgG/IgM Rapid Test (ASK Test), and Dynamiker 2019-nCoV IgG/IgM Rapid Test (Dynamiker Test). We found high diagnostic sensitivities (%, 95% confidence interval [CI]) for the Roche Test (97.4%, 93.4–99.0%), Abbott Test (94.0%, 89.1–96.8%), Wondfo Test (91.4%, 85.8–94.9%), ASK Test (97.4%, 93.4–99.0%), and Dynamiker Test (90.1%, 84.3–94.0%) after >21 days of symptom onset. Meanwhile, the diagnostic specificity was 99.0% (95% CI, 96.3–99.7%) for the Roche Test, 97.9% (95% CI, 94.8–99.2%) for the Abbott Test, and 100.0% (95% CI, 98.1–100.0%) for the three LFIAs. Cross-reactivity was observed in sera containing anti-cytomegalovirus (CMV) IgG/IgM antibodies and autoantibodies. No difference was observed in the time to seroconversion detection of the five serological tests. Specimens from patients with COVID-19 pneumonia demonstrated a shorter seroconversion time and higher chemiluminescent signal than those without pneumonia. Our data suggested that understanding the dynamic antibody response after COVID-19 infection and performance characteristics of different serological test are crucial for the appropriate interpretation of serological test result for the diagnosis and risk assessment of patient with COVID-19 infection.

Authors

  • Chen, Shey-Ying ;
  • Lee, Yu-Lin ;
  • Lin, Yi-Chun ;
  • Lee, Nan-Yao ;
  • Liao, Chia-Hung ;
  • Hung, Yuan-Pin ;
  • Lu, Min-Chi ;
  • Wu, Jhong-Lin ;
  • Tseng, Wen-Pin ;
  • Lin, Chien-Hao ;
  • Chung, Ming-Yi ;
  • Kang, Chun-Min ;
  • Lee, Ya-Fan ;
  • Lee, Tai-Fen ;
  • Cheng, Chien-Yu ;
  • Chen, Cheng-Pin ;
  • Huang, Chien-Hua ;
  • Liu, Chun-Eng ;
  • Cheng, Shu-Hsing ;
  • Ko, Wen-Chien ;
  • Hsueh, Po-Ren ;
  • Chen, Shyr-Chyr
1 Citation0 Mentions85% FAIR0.6 Dataset Index
10.6084/m9.figshare.13034798.v12020