Categories
How to Cite
Copyright notice
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Copyright (c) 2023 Nur Izyan Izzati Sathari, Priyaneka Baskaran, Laila Ab Mukmin, Mohd Zulfakar Mazlan, Wan Fadzlina Wan Muhd Shukeri
Keywords
Abstract
Introduction: This study aimed to derive and assess the performance of a multi-biomarker model from a combination of basic laboratory biomarkers in predicting mortality of hospitalized COVID-19 patients.
Methods: This was a cross-sectional study conducted in a university-affiliated hospital in Malaysia. Data of confirmed COVID-19 patients who were admitted from January 2020 to August 2021 were retrieved including their admission C-reactive protein (CRP), lactate dehydrogenase (LDH), and neutrophil-lymphocyte ratio (NLR). Patients were classified as non-survivors or survivors according to their hospital mortality status. Multi-variable logistic regression analysis was used to derive the multi-biomarker model.
Results: A total of 188 confirmed COVID-19 patients were analysed, of which 46 (23%) died in the hospital. Their mean age was 52 (SD 17) years, 104 (52%) were males, 114 (57%) had severe COVID-19 pneumonia, with mean APACHE II score of 14 (SD 10). On admission, those who died had higher median levels of CRP 96.0 (IQR 39.8–182.0) vs 23.0 (IQR 0–67.0 mg/L, p < 0.001), of LDH 973.0 (IQR 706.5–1520.0) vs 515.1 (408.8–738.8 IU/L, p < 0.001), and of NLR 10.1 (IQR 5.5–23.6) vs 2.8 (IQR 1.5–5.9, p < 0.001). The multi-biomarker model had a higher area under the curve (0.866, 95% CI 807-0.925) compared to its constituent individual biomarkers. At its optimal cutoff, this model had 78.9% sensitivity and 76.5% specificity for mortality prediction.
Conclusion: A multi-biomarker model of CRP, LDH, and NLR predicted in-hospital mortality with a very good performance in our hospitalised COVID-19 patients.
References
The Novel Coronavirus Pneumonia Emergency Response Epidemiology Team. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) — China, 2020. China CDC Wkly. 2020;2(8):113–22.
Yitbarek GY, Walle Ayehu G, Asnakew S, et al. The role of C-reactive protein in predicting the severity of COVID-19 disease: A systematic review. SAGE Open Med. 2021;9:20503121211050755. https://doi.org/10.1177/20503121211050755
Stringer D, Braude P, Myint PK, et al. The role of C-reactive protein as a prognostic marker in COVID-19. Int J Epidemiol. 2021;50(2):420-429. https://doi.org/10.1093/ije/dyab012
Huang Y, Guo L, Chen J, et al. Serum lactate dehydrogenase level as a prognostic factor for COVID-19: a retrospective study based on a large sample size. Front Med (Lausanne). 2022;8:671667. https://doi.org/10.3389/fmed.2021.671667
Szarpak L, Ruetzler K, Safiejko K, et al. Lactate dehydrogenase level as a COVID-19 severity marker. Am J Emerg Med. 2021;45:638-639. https://doi.org/10.1016/j.ajem.2020.11.025
Liu Y, Du X, Chen J, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. J Infect. 2020;81(1):e6-e12. https://doi.org/10.1016/j.jinf.2020.04.002
Shukeri WFWM, Ralib AM, Abdulah NZ, Mat-Nor MB. Sepsis mortality score for the prediction of mortality in septic patients. J Crit Care. 2018;43:163-168. https://doi.org/10.1016/j.jcrc.2017.09.009
Smilowitz NR, Nguy V, Yindalon A, et al. Multiple biomarker approach to risk stratification in COVID-19. Circulation. 2021;143(13):1338–40.
Zhou Z, Li Y, Ma Y, Zhang H, Deng Y, Zhu Z. Multi-biomarker is an early-stage predictor for progression of Coronavirus disease 2019 (COVID-19) infection. Int J Med Sci. 2021;18(13):2789-2798. https://doi.org/10.7150/ijms.58742
Wang Z, Cryar A, Lemke O, et al. A multiplex protein panel assay for severity prediction and outcome prognosis in patients with COVID-19: An observational multi-cohort study. EClinicalMedicine. 2022;49:101495. https://doi.org/10.1016/j.eclinm.2022.101495