3.8 Article

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

Journal

INFECTION AND CHEMOTHERAPY
Volume 54, Issue 3, Pages 470-482

Publisher

KOREAN SOC ANTIMICROBIAL THERAPY
DOI: 10.3947/ic.2022.0073

Keywords

Severe fever with thrombocytopenia syndrome; Banyangvirus; Tick-borne disease; Fatality prediction; Cross-correlation analysis

Funding

  1. research grant from the Jeju National University Hospital in 2020
  2. [2020-39]

Ask authors/readers for more resources

This study identified the correlation between the viral load of severe fever with thrombocytopenia syndrome (SFTS) and laboratory parameters, and identified three correlation patterns. The dynamic changes in laboratory parameters can be used to predict the changes in viral load, and to promptly assess the clinical course of patients.
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 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 CPKin 5 days after the onset of symptoms; this scoring system had 87.5% sensitivity and 86.0% 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 could provide timely treatment to critical patients by rapidly assessing their clinical course.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

3.8
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available