Charlson comorbidity index to predict 28-day mortality in critically ill COVID-19 patients
Abstract
BACKGROUND Severe COVID-19 patients may become critically ill and require treatment in the intensive care unit (ICU). As intensive care resources are limited, mortality predictors should be used to guide resource allocation. This study aimed to validate the Charlson comorbidity index (CCI) as the mortality predictor of critical COVID-19 patients in the ICU.
METHODS A retrospective cohort study was done in adult patients admitted to the ICU with severe COVID-19 at Cipto Mangunkusumo Hospital and Universitas Indonesia Hospital from March to August 2020. We extracted the subject’s CCI score from the medical records and the 28-day mortality after ICU admission. The CCI score was validated by the Hosmer–Lemeshow calibration test, determination of area under the curve (AUC), and optimal cut-off point for the critical patients in the ICU. We used the chi-square test to examine the association of comorbidities with mortality.
RESULTS Mortality was higher in CCI scores >4 (odds ratio [OR]: 8.83; 95% confidence interval [CI] = 1.81–43.01). The CCI score had moderate discrimination ability (AUC 76.1%; 95% CI = 0.661–0.881). Chronic kidney disease (CKD) (OR: 18.00, 95% CI = 2.19–147.51), congestive heart failure (CHF) (OR: 4.25, 95% CI = 1.23–14.75), and uncontrolled diabetes mellitus (DM) (OR: 18.429, 95% CI = 2.19–155.21) increased the risk of 28-day mortality.
CONCLUSIONS The CCI score could predict the 28-day mortality of critical COVID-19 patients. The coexistence of CKD, CHF, DM, peripheral vascular disease, and peptic ulcer in COVID-19 patients should be considered for patient management.
References
Chu YT, Ng YY, Wu SC. Comparison of different comorbidity measures for use with administrative data in predicting short- and long-term mortality. BMC Health Serv Res. 2010;10:140. https://doi.org/10.1186/1472-6963-10-140
Sinvani L, Kuriakose R, Tariq S, Kozikowski A, Patel V, Smilios C, et al. Using Charlson comorbidity index to predict short-term clinical outcomes in hospitalized older adults. J Healthc Qual. 2019;41(3):146-53. https://doi.org/10.1097/JHQ.0000000000000153
Zhou W, Qin X, Hu X, Lu Y, Pan J. Prognosis models for severe and critical COVID-19 based on the Charlson and Elixhauser comorbidity indices. Int J Med Sci. 2020;17(15):2257-63. https://doi.org/10.7150/ijms.50007
Christensen DM, Strange JE, Gislason G, Torp-Pedersen C, Gerds T, Fosbøl E, et al. Charlson comorbidity index score and risk of severe outcome and death in Danish COVID-19 patients. J Gen Intern Med. 2020;35(9):2801-3. https://doi.org/10.1007/s11606-020-05991-z
Ternavasio-de la Vega HG, Castaño-Romero F, Ragozzino S, Sánchez González R, Vaquero-Herrero MP, Siller-Ruiz M, et al. The updated Charlson comorbidity index is a useful predictor of mortality in patients with Staphylococcus aureus bacteraemia. Epidemiol Infect. 2018;146(16):2122-30. https://doi.org/10.1017/S0950268818002480
Lau TW, Fang C, Leung F. Assessment of postoperative short-term and long-term mortality risk in Chinese geriatric patients for hip fracture using the Charlson comorbidity score. Hong Kong Med J. 2016;22(1):16-22. https://doi.org/10.12809/hkmj154451
Roffman CE, Buchanan J, Allison GT. Charlson comorbidities index. J Physiother. 2016;62(3):171. https://doi.org/10.1016/j.jphys.2016.05.008
World Health Organization (WHO). WHO COVID-19: case definitions: updated in public health surveillance for COVID-19 [Internet]. World Health Organization (WHO); [cited 2020 Dec 16]. Available from: https://apps.who.int/iris/handle/10665/337834.
Charlson ME, Pompei P, Ales KL, MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation. J Chronic Dis. 1987;40(5):373-83. https://doi.org/10.1016/0021-9681(87)90171-8
Bernard S, Inderjeeth C, Raymond W. Higher Charlson comorbidity index scores do not influence functional independence measure score gains in older rehabilitation patients. Australas J Ageing. 2016;35(4):236-41. https://doi.org/10.1111/ajag.12351
Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395(10229):1054-62. https://doi.org/10.1016/S0140-6736(20)30566-3
D'Marco L, Puchades MJ, Romero-Parra M, Gimenez-Civera E, Soler MJ, Ortiz A, et al. Coronavirus disease 2019 in chronic kidney disease. Clin Kidney J. 2020;13(3):297-306. https://doi.org/10.1093/ckj/sfaa104
Alvarez-Garcia J, Lee S, Gupta A, Cagliostro M, Joshi AA, Rivas-Lasarte M, et al. Prognostic impact of prior heart failure in patients hospitalized with COVID-19. J Am Coll Cardiol. 2020;76(20):2334-48. https://doi.org/10.1016/j.jacc.2020.09.549
Bader F, Manla Y, Atallah B, Starling RC. Heart failure and COVID-19. Heart Fail Rev. 2021;26(1):1-10. https://doi.org/10.1007/s10741-020-10008-2
Ng TM, Toews ML. Impaired norepinephrine regulation of monocyte inflammatory cytokine balance in heart failure. World J Cardiol. 2016;8(10):584-9. https://doi.org/10.4330/wjc.v8.i10.584
Court O, Kumar A, Parrillo JE, Kumar A. Clinical review: myocardial depression in sepsis and septic shock. Crit Care. 2002;6(6):500-8. https://doi.org/10.1186/cc1822
Gonzalez Cañas E, Gimenez Gaibar A, Rodriguez Lorenzo L, Castro Rios JG, Martinez Toiran A, Bella Cueto MR, et al. Acute peripheral arterial thrombosis in COVID-19. Role of endothelial inflammation. Br J Surg. 2020;107(10):e444-5. https://doi.org/10.1002/bjs.11904
Erener S. Diabetes, infection risk and COVID-19. Mol Metab. 2020;39:101044. https://doi.org/10.1016/j.molmet.2020.101044
Cao Y, Li L, Feng Z, Wan S, Huang P, Sun X, et al. Comparative genetic analysis of the novel coronavirus (2019-nCoV/SARS-CoV-2) receptor ACE2 in different populations. Cell Discov. 2020;6(11). https://doi.org/10.1038/s41421-020-0147-1
Wu C, Chen X, Cai Y, Xia J, Zhou X, Xu S, et al. Risk factors associated with acute respiratory distress syndrome and death in patients with coronavirus disease 2019 pneumonia in Wuhan, China. JAMA Intern Med. 2020;180(7):934-43. https://doi.org/10.1001/jamainternmed.2020.0994
Perrotta F, Corbi G, Mazzeo G, Boccia M, Aronne L, D'Agnano V, et al. COVID-19 and the elderly: insights into pathogenesis and clinical decision-making. Aging Clin Exp Res. 2020;32(8):1599-608. https://doi.org/10.1007/s40520-020-01631-y
Melazzini F, Lenti MV, Mauro A, De Grazia F, Di Sabatino A. Peptic ulcer disease as a common cause of bleeding in patients with coronavirus disease 2019. Am J Gastroenterol. 2020;115(7):1139-40. https://doi.org/10.14309/ajg.0000000000000710
Copyright (c) 2023 Adhrie Sugiarto, Pryambodho, Meilina Imelda, Dita Aditianingsih
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with Medical Journal of Indonesia agree to the following terms:
- Authors retain copyright and grant Medical Journal of Indonesia right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial License that allows others to remix, adapt, build upon the work non-commercially with an acknowledgment of the work’s authorship and initial publication in Medical Journal of Indonesia.
- Authors are permitted to copy and redistribute the journal's published version of the work non-commercially (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Medical Journal of Indonesia.
