A Comprehensive Analysis Exploring the Vital Role of the Systemic Immune-Inflammatory Index Upon Admission in Severe Hemorrhagic Fever with Renal Syndrome

Lihua Yao,1,2 Xinlu Wang,1 Zihao Wang,1 Xiaozhong Wang1 1Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330000, People’s Republic of China; 2Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of ChinaCorrespondence: Xiaozhong Wang, Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Mingde Road No. 1, Nanchang, Jiangxi, 330000, People’s Republic of China, Email [email protected]: To explore the value of the systemic immune-inflammatory index (SII) and the systemic inflammatory response index (SIRI) in patients with severe hemorrhagic fever with renal syndrome (HFRS) upon admission.Methods: This study included a total of 165 patients with HFRS, who were divided into mild and severe groups based on the severity of the disease. By reviewing medical records, we collected the white blood cell (WBC), SII, and SIRI values of patients upon admission. Univariate and multivariate logistics regression analyses were performed to identify risk factors for severe HFRS. The receiver operating characteristic (ROC) curve was applied to calculate the area under the ROC curve (AUC) to analyze the predictive value of SII and SIRI for severe HFRS, and the results were compared with WBC and SIRI.Results: Compared with the mild HFRS group, patients in the severe HFRS group had a longer duration of illness (P < 0.05), higher levels of WBC, neutrophil (NEUT), lymphocyte (LYMP), monocyte (MONO), procalcitonin (PCT), SIRI, alanine transaminase (ALT), and creatinine (Scr) (P < 0.05), while lower levels of ALB, platelet (PLT), platelet-to-lymphocyte rate (PLR), and SII, with statistically significant differences (P < 0.05). Binary logistics regression analysis indicated that WBC (OR: 1.190, 95% CI: 1.032– 1.371), SII (OR: 0.967, 95% CI: 0.951– 0.984), and SIRI (OR: 4.743, 95% CI: 2.077– 10.830) were risk factors for severe HFRS. The AUCs of WBC, SII, and SIRI for predicting severe HFRS were 0.765, 0.803, and 0.785, respectively.Conclusion: Low levels of SII and high levels of WBC and SIRI upon admission are risk factors for severe HFRS and have certain value in predicting the progression of HFRS to severe cases, among which SII exhibits the best predictive value.Keywords: hemorrhagic fever with renal syndrome, systemic immune inflammatory index, systemic immune-response index, risk factors, predictive score

Publication Details

Journal
SHILAP Revista de lepidopterología
Published
2024-10-01
Primary Topic
Viral Infections and Vectors
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Comprehensive Analysis Exploring the Vital Role of the Systemic Immune-Inflammatory Index Upon Admission in Severe Hemorrhagic Fever with Renal Syndrome

SHILAP Revista de lepidopterología
Viral Infections and Vectors
article

A Comprehensive Analysis Exploring the Vital Role of the Systemic Immune-Inflammatory Index Upon Admission in Severe Hemorrhagic Fever with Renal Syndrome

article en

Abstract

Lihua Yao,1,2 Xinlu Wang,1 Zihao Wang,1 Xiaozhong Wang1 1Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, 330000, People’s Republic of China; 2Department of Clinical Laboratory, Affiliated Hospital of North Sichuan Medical College, Nanchong, Sichuan, 637000, People’s Republic of ChinaCorrespondence: Xiaozhong Wang, Department of Clinical Laboratory, The Second Affiliated Hospital, Jiangxi Medical College, Nanchang University, Mingde Road No. 1, Nanchang, Jiangxi, 330000, People’s Republic of China, Email [email protected]: To explore the value of the systemic immune-inflammatory index (SII) and the systemic inflammatory response index (SIRI) in patients with severe hemorrhagic fever with renal syndrome (HFRS) upon admission.Methods: This study included a total of 165 patients with HFRS, who were divided into mild and severe groups based on the severity of the disease. By reviewing medical records, we collected the white blood cell (WBC), SII, and SIRI values of patients upon admission. Univariate and multivariate logistics regression analyses were performed to identify risk factors for severe HFRS. The receiver operating characteristic (ROC) curve was applied to calculate the area under the ROC curve (AUC) to analyze the predictive value of SII and SIRI for severe HFRS, and the results were compared with WBC and SIRI.Results: Compared with the mild HFRS group, patients in the severe HFRS group had a longer duration of illness (P < 0.05), higher levels of WBC, neutrophil (NEUT), lymphocyte (LYMP), monocyte (MONO), procalcitonin (PCT), SIRI, alanine transaminase (ALT), and creatinine (Scr) (P < 0.05), while lower levels of ALB, platelet (PLT), platelet-to-lymphocyte rate (PLR), and SII, with statistically significant differences (P < 0.05). Binary logistics regression analysis indicated that WBC (OR: 1.190, 95% CI: 1.032– 1.371), SII (OR: 0.967, 95% CI: 0.951– 0.984), and SIRI (OR: 4.743, 95% CI: 2.077– 10.830) were risk factors for severe HFRS. The AUCs of WBC, SII, and SIRI for predicting severe HFRS were 0.765, 0.803, and 0.785, respectively.Conclusion: Low levels of SII and high levels of WBC and SIRI upon admission are risk factors for severe HFRS and have certain value in predicting the progression of HFRS to severe cases, among which SII exhibits the best predictive value.Keywords: hemorrhagic fever with renal syndrome, systemic immune inflammatory index, systemic immune-response index, risk factors, predictive score

SHILAP Revista de lepidopterología
Good health and well-being
Openalex Percentile: Top 48%
Viral Infections and Vectors
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.