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The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series

BACKGROUND: There is a correlation between the severe fever with thrombocytopenia syndrome (SFTS) viral load and disease severity; however, measurement of viral load is difficult in general laboratory and it takes time to obtain a viral load value. Here, the laboratory parameters for predicting the...

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Autores principales: Kim, Misun, Oh, Hyunjoo, Heo, Sang Taek, Song, Sung Wook, Lee, Keun Hwa, Kang, Myeong Jin, Yoo, Jeong Rae
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Infectious Diseases; Korean Society for Antimicrobial Therapy; The Korean Society for AIDS 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533152/
https://www.ncbi.nlm.nih.gov/pubmed/36196606
http://dx.doi.org/10.3947/ic.2022.0073
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author Kim, Misun
Oh, Hyunjoo
Heo, Sang Taek
Song, Sung Wook
Lee, Keun Hwa
Kang, Myeong Jin
Yoo, Jeong Rae
author_facet Kim, Misun
Oh, Hyunjoo
Heo, Sang Taek
Song, Sung Wook
Lee, Keun Hwa
Kang, Myeong Jin
Yoo, Jeong Rae
author_sort Kim, Misun
collection PubMed
description BACKGROUND: There is a correlation between the severe fever with thrombocytopenia syndrome (SFTS) viral load and disease severity; however, measurement of viral load is difficult in general laboratory and it takes time to obtain a viral load value. Here, the laboratory parameters for predicting the dynamic changes in SFTS viral load were identified. In addition, we tried to evaluate a specific time point for the early determination of clinical deterioration using dynamic change of laboratory parameters. MATERIALS AND METHODS: This observational study included SFTS patients in Korea (2013 - 2020). Cross-correlation analysis at lagged values was used to determine the temporal correlation between the SFTS viral loads and time-series variables. Fifty-eight SFTS patients were included in the non-severe group (NSG) and 11 in the severe group (SG). RESULTS: In the cross-sectional analyses, 10 parameters -white blood cell, absolute neutrophil cell, lymphocyte, platelet, activated partial thromboplastin time (aPTT), C-reactive protein, aspartate aminotransferase (AST), alanine transaminase (ALT), lactate dehydrogenase (LDH), and creatine phosphokinase (CPK)- were assessed within 30 days from the onset of symptoms; they exhibited three different correlation patterns: (1) positive, (2) positive with a time lag, and (3) negative. A prediction score system was developed for predicting SFTS fatality based on age and six laboratory variables -platelet, aPTT, AST, ALT, LDH, and CPK- in 5 days after the onset of symptoms; this scoring system had 87.5% sensitivity and 86.0% specificity (95% confidence interval: 0.831 - 1.00, P <0.001). CONCLUSION: Three types of correlation patterns between the dynamic changes in SFTS viral load and laboratory parameters were identified. The dynamic changes in the viral load could be predicted using the dynamic changes in these variables, which can be particularly helpful in clinical settings where viral load tests cannot be performed. Also, the proposed scoring system could provide timely treatment to critical patients by rapidly assessing their clinical course.
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spelling pubmed-95331522022-10-14 The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series Kim, Misun Oh, Hyunjoo Heo, Sang Taek Song, Sung Wook Lee, Keun Hwa Kang, Myeong Jin Yoo, Jeong Rae Infect Chemother Original Article BACKGROUND: There is a correlation between the severe fever with thrombocytopenia syndrome (SFTS) viral load and disease severity; however, measurement of viral load is difficult in general laboratory and it takes time to obtain a viral load value. Here, the laboratory parameters for predicting the dynamic changes in SFTS viral load were identified. In addition, we tried to evaluate a specific time point for the early determination of clinical deterioration using dynamic change of laboratory parameters. MATERIALS AND METHODS: This observational study included SFTS patients in Korea (2013 - 2020). Cross-correlation analysis at lagged values was used to determine the temporal correlation between the SFTS viral loads and time-series variables. Fifty-eight SFTS patients were included in the non-severe group (NSG) and 11 in the severe group (SG). RESULTS: In the cross-sectional analyses, 10 parameters -white blood cell, absolute neutrophil cell, lymphocyte, platelet, activated partial thromboplastin time (aPTT), C-reactive protein, aspartate aminotransferase (AST), alanine transaminase (ALT), lactate dehydrogenase (LDH), and creatine phosphokinase (CPK)- were assessed within 30 days from the onset of symptoms; they exhibited three different correlation patterns: (1) positive, (2) positive with a time lag, and (3) negative. A prediction score system was developed for predicting SFTS fatality based on age and six laboratory variables -platelet, aPTT, AST, ALT, LDH, and CPK- in 5 days after the onset of symptoms; this scoring system had 87.5% sensitivity and 86.0% specificity (95% confidence interval: 0.831 - 1.00, P <0.001). CONCLUSION: Three types of correlation patterns between the dynamic changes in SFTS viral load and laboratory parameters were identified. The dynamic changes in the viral load could be predicted using the dynamic changes in these variables, which can be particularly helpful in clinical settings where viral load tests cannot be performed. Also, the proposed scoring system could provide timely treatment to critical patients by rapidly assessing their clinical course. The Korean Society of Infectious Diseases; Korean Society for Antimicrobial Therapy; The Korean Society for AIDS 2022-09 2022-08-23 /pmc/articles/PMC9533152/ /pubmed/36196606 http://dx.doi.org/10.3947/ic.2022.0073 Text en Copyright © 2022 by The Korean Society of Infectious Diseases, Korean Society for Antimicrobial Therapy, and The Korean Society for AIDS https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (https://creativecommons.org/licenses/by-nc/4.0/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Kim, Misun
Oh, Hyunjoo
Heo, Sang Taek
Song, Sung Wook
Lee, Keun Hwa
Kang, Myeong Jin
Yoo, Jeong Rae
The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series
title The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series
title_full The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series
title_fullStr The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series
title_full_unstemmed The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series
title_short The Evaluation of Surrogate Laboratory Parameters for Predicting the Trend of Viral Loads in Patients with Severe Fever with Thrombocytopenia Syndrome: Cross-Correlation Analysis of Time Series
title_sort evaluation of surrogate laboratory parameters for predicting the trend of viral loads in patients with severe fever with thrombocytopenia syndrome: cross-correlation analysis of time series
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9533152/
https://www.ncbi.nlm.nih.gov/pubmed/36196606
http://dx.doi.org/10.3947/ic.2022.0073
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