The role of CD4+, CD8+, CD4+/CD8+ and neutrophile to lymphocyte ratio in predicting and determining COVID-19 severity in Indonesian patients

ABSTRACT Background Biomarkers that are cost-effective and accurate for predicting severe coronavirus disease 2019 (COVID-19) are urgently needed. We would like to assess the role of various inflammatory biomarkers on admission as disease severity predictors and determine the optimal cut-off of the...

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Published in:Transactions of the Royal Society of Tropical Medicine and Hygiene 2023-08, Vol.117 (8), p.591-597
Main Authors: Masyeni, Sri, Budhitresna, Anak Agung Gede, Adiwinata, Randy, Wibawa, Surya, Nugraha, Putu Arya, Antara, Jarwa, Asmara, Dewa Putu Gede Wedha, Widyaningsih, Putu Dyah, Yenny, Luh Gede Sri, Widiastika, Made, Kahari, Siska, Wardhana, Clareza Arief, Pasek, Arya Widiyana, Putrawan, Oka, Santosa, Agus, Herawati, Sianny, Arisanti, Nih Luh Putu Eka, Astini, Wining, Fatawy, Rois Muqsith, Kameoka, Masanori, Nelwan, Erni Juwita
Format: Article
Language:English
Subjects:
Biomarkers
CD4-Positive T-Lymphocytes
CD8-Positive T-Lymphocytes
COVID-19 - diagnosis
Cross-Sectional Studies
Humans
Indonesia - epidemiology
Prognosis
Retrospective Studies
ROC Curve
SARS-CoV-2
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Summary:ABSTRACT Background Biomarkers that are cost-effective and accurate for predicting severe coronavirus disease 2019 (COVID-19) are urgently needed. We would like to assess the role of various inflammatory biomarkers on admission as disease severity predictors and determine the optimal cut-off of the neutrophile-to-lymphocyte ratio (NLR) for predicting severe COVID-19. Methods We conducted a cross-sectional study in six hospitals in Bali and recruited real-time PCR-confirmed COVID-19 patients aged >18 y from June to August 2020. Data collection included each patient's demographic, clinical, disease severity and hematological data. Multivariate and receiver operating characteristic curve analyses were performed. Results A total of 95 Indonesian COVID-19 patients were included. The highest NLR among severe patients was 11.5±6.2, followed by the non-severe group at 3.3±2.8. The lowest NLR was found in the asymptomatic group (1.9±1.1). The CD4+ and CD8+ values were lowest in the critical and severe disease groups. The area under the curve of NLR was 0.959. Therefore, the optimal NLR cut-off value for predicting severe COVID-19 was ≥3.55, with sensitivity at 90.9% and a specificity of 16.7%. Conclusions Lower CD4+ and CD8+ and higher NLR values on admission are reliable predictors of severe COVID-19 among Indonesian people. NLR cut-off ≥3.55 is the optimal value for predicting severe COVID-19.
ISSN:0035-9203
1878-3503
DOI:10.1093/trstmh/trad012