Systemic inflammatory index a simple marker of thrombo-inflammation and prognosis in severe COVID-19 patients

Authors

  • Jayanthy Ramesh Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India
  • Johann Varghese Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India
  • S. L. Sagar Reddy Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India
  • Moganti Rajesh Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India

DOI:

https://doi.org/10.18203/2349-3933.ijam20213165

Keywords:

Systemic inflammatory index, Severe COVID-19, Thrombo-inflammation, Diabetes mellitus

Abstract

Background: COVID-19 pandemic has challenged the healthcare resources globally, inspiring the need for identifying simple, economical biomarkers. COVID-19 is an immune-inflammatory disorder and systemic inflammatory index (SII) derived from the peripheral blood has been proposed as a marker.

Methods: Retrospective study of severe COVID-19 hospitalized patients (total N=154 including diabetic subset N=57). Data regarding hematological variables such as absolute neutrophil count (ANC), absolute lymphocyte count (ALC), platelet count along with thrombo-inflammatory proteins, D-dimer, C-reactive protein (CRP) were extracted from medical records. SII was calculated from ANC×platelets/lymphocyte count. Clinically applicable cut-offs were derived using the receiver operating characteristic curve (ROC) analysis for SII, CRP and D-dimer. Correlations between hematological parameters and D-dimer, CRP were analyzed to validate them as biomarkers of thrombo-inflammation and as predictors of clinical outcome.

Results: Among 154 severe COVID-19 patients, significant association with mortality was seen with respect to ANC (p<0.001), SII (p=0.01), CRP (p=0.004) and D-dimer (p=0.001). In the total COHORT, based on ROC curve, applicable cut-off for outcome prediction were for SII 14.85×105 (area under curve (AUC)-0.691, sensitivity-67%, specificity-64%,odds ratio (OR)-3.44), CRP 19.7 mg/l (AUC-0.718, OR-5.71), D-dimer 0.285 mcg/ml (AUC-0.773, OR-6.94) respectively. In the diabetic subset, the cut-offs for SII 14.85×105 (AUC-0.68, sensitivity-80%, specificity-54%, OR-4.7), CRP 52.5 mg/l (AUC-0.723, OR-5.36) and D-dimer 0.285 mcg/ml (AUC-0.771, OR-11.3) respectively.

Conclusions: Clinically applicable thresholds for SII serve as reliable biomarkers of thrombo-inflammation and prognosis in severe COVID-19 patients. Diabetic patients with similar thresholds had higher risk and prediction for mortality. In the resource constrained health care settings, who might not afford D-dimer, SII may serve as an economical bio-maker.

Author Biographies

Jayanthy Ramesh, Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India

Professor 

Dpartment of Endocrinology 

King George Hospital

Andhra Medical College 

Visakhapatnam

Johann Varghese, Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India

DM Trainee
Department of Endocrinology

S. L. Sagar Reddy, Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India

DM Trainee
Department of Endocrinology

Moganti Rajesh, Department of Endocrinology, Andhra Medical College, King George Hospital, Visakhapatnam, Andhra Pradesh, India

DM Trainee
Department of Endocrinology

References

Martin A, Markhvida M, Hallegatte S, Walsh B. Socio-economic impacts of COVID-19 on household consumption and poverty. Economic Disaster Climate Change. 2020;4(3):453-79.

Nicola M, Alsafi Z, Sohrabi C, Kerwan A, Al-Jabir A, Iosifidis C, et al. The socio-economic implications of the coronavirus and COVID-19 pandemic: a review. Int J Surg. 2020;78:185-93.

Wu Y, Hou B, Liu J, Chen Y, Zhong P. Risk factors associated with long-term hospitalization in patients with COVID-19: a single-centered, retrospective study. Front Med (Lausanne). 2020;7:315.

Palaiodimos L, Chamorro-Pareja N, Karamanis D, Li W, Zavras PD, Chang KM, et al. Diabetes is associated with increased risk for in-hospital mortality in patients with COVID-19: a systematic review and meta-analysis comprising 18,506 patients. Hormones (Athens). 2021;20(2):305-14.

Liao D, Zhou F, Luo L, Xu M, Wang H, Xia J, et al. Haematological characteristics and risk factors in the classification and prognosis evaluation of COVID-19: a retrospective cohort study. Lancet Haematol. 2020;7(9):671-8.

Ramesh J, Reddy SS, Rajesh M, Varghese J. Evaluation of simple and cost-effective immuno-haematological markers to predict outcome in hospitalized severe COVID-19 patients, with a focus on diabetes mellitus-A retrospective study in Andhra Pradesh, India. Diabetes Metab Syndr. 2021;15(3):739-45.

Lagunas-Alvarado M, Mijangos-Huesca FJ, Terán-González JO, Lagunas-Alvarado MG, Martínez-Zavala N, Reyes-Franco I, et al. Systemic immune inflammatory index in sepsis. Medicinainterna de México. 2017;33(3):303-9.

Huang Y, Gao Y, Wu Y, Lin H. Prognostic value of systemic immune-inflammation index in patients with urologic cancers: a meta-analysis. Cancer Cell Int. 2020;20(1):1-8.

Fois AG, Paliogiannis P, Scano V, Cau S, Babudieri S, Perra R, et al. The systemic inflammation index on admission predicts in-hospital mortality in COVID-19 patients. Molecules. 2020;25(23):5725.

Muhammad S, Fischer I, Naderi S, Jouibari MF, Abdolreza S, Karimialavijeh E, et al. Systemic inflammatory index is a novel predictor of intubation requirement and mortality after SARS-CoV-2 infection. Pathogens. 2021;10(1):58.

Government of India Ministry of Health and Family Welfare. Fact sheet: Clinical management protocol: COVID-19 Directorate General of Health Services (EMR Division) Version 5. Available at: https:// www.mohfw.gov.in/pdf/ClinicalManagementProtocolforCOVID19.pdf. Accessed on 3 March 2021.

Zhang Y, Chen B, Wang L, Wang R, Yang X. Systemic immune-inflammation index is a promising non-invasive marker to predict survival of lung cancer: a meta-analysis. Medicine. 2019;98(3):13788.

Wang K, Diao F, Ye Z, Zhang X, Zhai E, Ren H, et al. Prognostic value of systemic immune‐inflammation index in patients with gastric cancer. Cancer Communication. 2017;36(1):1-7.

Yang YL, Wu CH, Hsu PF, Chen SC, Huang SS, Chan WL, et al. Systemic immune‐inflammation index (SII) predicted clinical outcome in patients with coronary artery disease. Europe J Clinic Investigation. 2020;50(5):13230.

Henry BM, Cheruiyot I, Vikse J, Mutua V, Kipkorir V, Benoit J, et al. Lymphopenia and neutrophilia at admission predicts severity and mortality in patients with COVID-19: a meta-analysis. Acta Bio Medica. 2020;91(3):2020008.

Li Y, Wang W, Yang F, Xu Y, Feng C, Zhao Y. The regulatory roles of neutrophils in adaptive immunity. Cell Communication Signaling. 2019;17(1):147.

Vorobjeva NV, Pinegin BV. Neutrophil extracellular traps: mechanisms of formation and role in health and disease. Biochemistry (Moscow). 2014;79(12):1286-96.

Kany S, Vollrath JT, Relja B. Cytokines in inflammatory disease. Int J Molecul Sci. 2019;20(23):6008.

Wang K, Chen W, Zhang Z, Deng Y, Lian JQ, Du P, Wei D, et al. CD147-spike protein is a novel route for SARS-CoV-2 infection to host cells. Signal Transduc Target Ther. 2020;5(1):1-0.

Costela-Ruiz VJ, Illescas-Montes R, Puerta-Puerta JM, Ruiz C, Melguizo-Rodríguez L. SARS-CoV-2 infection: the role of cytokines in COVID-19 disease. Cytokine Growth Factor Rev. 2020;54:62-75.

Tomar B, Anders HJ, Desai J, Mulay SR. Neutrophils and Neutrophil Extracellular Traps Drive Necroinflammation in COVID-19. Cells. 2020;9(6):1383.

Tsalamandris S, Antonopoulos AS, Oikonomou E, Papamikroulis GA, Vogiatzi G, Papaioannou S, et al. The role of inflammation in diabetes: current concepts and future perspectives. European Cardiol. 2019;14(1):50-9.

Alexander T, Thomson VS, Malviya A, Mohan B, Wander GS, Harikrishnan S, et al. Guidance for health care providers on management of cardiovascular complications in patients suspected or confirmed with COVID 19 virus infection. J Assoc Phys India. 2020;68(5):46-9.

Zhang L, Yan X, Fan Q, Liu H, Liu X, Liu Z, et al. D‐dimer levels on admission to predict in‐hospital mortality in patients with COVID‐19. J Thrombos Haemostasis. 2020;18(6):1324-9.

Qu R, Ling Y, Zhang YH, Wei LY, Chen X, Li XM, et al. Platelet‐to‐lymphocyte ratio is associated with prognosis in patients with coronavirus disease‐19. J Med Virol. 2020;92(9):1533-41.

CDC COVID-19 Response Team, CDC COVID-19 Response Team, CDC COVID-19 Response Team, Chow N, Fleming-Dutra K, Gierke R, et al. Preliminary estimates of the prevalence of selected underlying health conditions among patients with coronavirus disease 2019-United States, 12th February-28th March 2020. Morbidit Mortalit Weekly Rep. 2020;69(13):382-6.

Guotao L, Xingpeng Z, Zhihui D, Huirui W. SARS-CoV-2 infection presenting with hematochezia. Médecine et Maladies Infectieuses. 2020;50(3):293.

Tang N, Bai H, Chen X, Gong J, Li D, Sun Z. Anticoagulant treatment is associated with decreased mortality in severe coronavirus disease 2019 patients with coagulopathy. J Thrombosis Hemostasis. 2020;18(5):1094-9.

Adam SS, Key NS, Greenberg CS. D-dimer antigen: current concepts and future prospects. Blood J Am Soc Hematol. 2009;113(13):2878-87.

Tasić N, Paixão TR, Gonçalves LM. Biosensing of D-dimer, making the transition from the central hospital laboratory to bedside determination. Talanta. 2020;207:120270.

Thirumalaisamy PV, Meyer CG. Mild versus severe COVID-19: laboratory markers. Int J Infect Dis. 2020;95:304-7.

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Published

2021-08-21

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Original Research Articles