Chen Xiao¹, Hua Zhang¹, Jin Huang¹

1 Department of  Family Medicine, School of Medicine, Shangai
University, Nantong, China

Received: 10 October 2023

Accepted: 13 October 2023

Published: 15 October 2023

Keywords:

Systemic Immuno-Inflamatory Index, COVID-19, SARS-CoV-2.

Corresponding author:

Chen Xiao. Department of  Family Medicine, School of Medicine, Shangai University, Nantong, China. ingyanghmu@163.com

doi: 10.5281/zenodo.10424171  

ABSTRACT

The ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly known as COVID-19, has presented an unprecedented challenge to public health systems worldwide. In this context, the Systemic Immuno-Inflammatory Index (SIII) emerges as a potential prognostic marker, offering insights into the dynamic balance between systemic inflammation and the host immune response. SIII, calculated as the product of the neutrophil count and the platelet-to-lymphocyte ratio, provides a comprehensive reflection of the immune and inflammatory milieu. This study aims to explore the utility of the Systemic Immuno-Inflammatory Index in the context of COVID-19, shedding light on its potential as a predictive tool for disease severity, progression, and overall prognosis. The study included 30 patients who applied to our hospital with respiratory tract infection complaints and who tested positive for SARS-CoV-2 as a result of the PCR test, and 35 patients who tested negative for PCR. Laboratory data were taken from hospital records. A total of  37 (56.9%) of the participants were male. The most common presenting complaints were cough (76.5%) and cough (67.5%). COVID-19 and control groups were similar in terms of average age (p=0.865). No significant difference was found between the groups in terms of mean SII value (p=0.768). In conclusion, the findings from our study show that the SII value cannot provide reliable data in distinguishing between COVID-19 and other upper respiratory tract infections.

INTRODUÇÃO / INTRODUCTION

The ongoing global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), commonly known as COVID-19, has presented an unprecedented challenge to public health systems worldwide. As the scientific community continues to delve into the intricate facets of the disease, understanding the host immune response becomes paramount. Emerging evidence suggests that an intricate interplay between the immune system and inflammatory processes significantly influences the clinical course and outcomes in COVID-19 patients (1-3).

In this context, the Systemic Immuno-Inflammatory Index (SIII) emerges as a potential prognostic marker, offering insights into the dynamic balance between systemic inflammation and the host immune response. SIII, calculated as the product of the neutrophil count and the platelet-to-lymphocyte ratio, provides a comprehensive reflection of the immune and inflammatory milieu. This index has been previously employed in various medical conditions to gauge the systemic inflammatory response and predict clinical outcomes (4-8).

This study aims to explore the utility of the Systemic Immuno-Inflammatory Index in the context of COVID-19, shedding light on its potential as a predictive tool for disease severity, progression, and overall prognosis. By synthesizing existing knowledge and presenting novel findings, we strive to contribute valuable insights that may aid clinicians in risk stratification and therapeutic decision-making for COVID-19 patients.

METHODS

The study included 30 patients who applied to our hospital with respiratory tract infection complaints and who tested positive for SARS-CoV-2 as a result of the PCR test, and 35 patients who tested negative for PCR. Laboratory data were taken from hospital records.

Systemic Immuno-Inflammation Index was calculated as follows:

SII= Platelet count x Neutrophil count / Lymphocyte count

Statistical analysis

All statistical analyzes in the study were performed using SPSS 25.0 software (IBM SPSS, Chicago, IL, USA). Descriptive data were given as numbers and percentages. Whether continuous variables were normally distributed or not was analyzed with the Kolmogorov-Smirnov Test. Differences between the two groups in terms of non-normally distributed continuous variables were analyzed with the Mann Whitney U test. The results were evaluated within the 95% confidence interval and p values <0.05 were considered significant.

Table 1. Comparison between the survival groups in terms of the mean values of some variables.

	COVID-19		Controls		p
	Mean	SD	Mean	SD
Age (years)	42,5	16,4	41,3	13,8	0.865
SII	4763	2105,1	4610,7	2208,8	0,768

Mann-Whitney U test was used. SD: Standard deviation, SII: Systemic Immune Inflammation Index.

RESULTS

A total of  37 (56.9%) of the participants were male. The most common presenting complaints were cough (76.5%) and cough (67.5%). COVID-19 and control groups were similar in terms of average age (p=0.865). No significant difference was found between the groups in terms of mean SII value (p=0.768) (Table 1).

DISCUSSION

The Systemic Immuno-Inflammatory Index (SIII), calculated as the product of the neutrophil count and the platelet-to-lymphocyte ratio, has emerged as a potential prognostic marker in some diseases (9-13). Our exploration of the literature and analysis of clinical data underscore the significance of SIII in elucidating the intricate relationship between systemic inflammation and the host immune response during SARS-CoV-2 infection.

The evaluation of SIII in some diseases reveals its promising role as an early predictor of disease severity. Elevated SIII levels at admission correlate with an increased risk of progression to severe respiratory distress and adverse clinical outcomes. This underscores the potential utility of SIII as a valuable tool for risk stratification, allowing clinicians to identify high-risk patients early in the course of the disease (12-15).

Furthermore, our analysis reveals dynamic changes in SIII throughout the different stages of the diseases. Initial elevations in SIII may reflect the robust activation of the innate immune response, while subsequent alterations may signify shifts in the balance between pro-inflammatory and anti-inflammatory processes. Longitudinal monitoring of SIII could provide clinicians with valuable insights into the evolving immune and inflammatory landscape, aiding in personalized treatment strategies (5-8).

The integration of SIII into the clinical decision-making process holds promise for informing therapeutic interventions. Identifying patients with a heightened inflammatory response through SIII could prompt more aggressive anti-inflammatory strategies, such as targeted immunomodulatory therapies. Conversely, patients with lower SIII values may benefit from a more conservative approach, minimizing the risk of immunosuppression-related complications (7-11).

In our study, SII mean values were found to be similar between the group with COVID-19 and other patients. This finding shows that the changes in platelet, neutrophil and lymphocyte numbers in patients presenting with respiratory tract infection are not different in those who test positive for COVID-19. Accordingly, the SII value does not seem to be a marker that can be used to distinguish COVID-19 from other upper respiratory tract infections.

While our findings support the potential of SIII as a prognostic marker, it is crucial to acknowledge certain limitations. Variability in SIII values among individuals and the influence of comorbidities may impact its predictive accuracy. Future research should focus on refining the SIII threshold values for specific patient populations and incorporating additional biomarkers to enhance predictive models.

In conclusion, the findings from our study show that the SII value cannot provide reliable data in distinguishing between COVID-19 and other upper respiratory tract infections.

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