Coronavirus disease 2019 in elderly patients: Characteristics and prognostic factors based on 4-week follow-up

Lang Wang, Wenbo He, Xiaomei Yu, Dalong Hu, Mingwei Bao, Huafen Liu, Jiali Zhou, Hong Jiang, Lang Wang, Wenbo He, Xiaomei Yu, Dalong Hu, Mingwei Bao, Huafen Liu, Jiali Zhou, Hong Jiang

Abstract

Objective: To investigate the characteristics and prognostic factors in the elderly patients with COVID-19.

Methods: Consecutive cases over 60 years old with COVID-19 in Renmin Hospital of Wuhan University from Jan 1 to Feb 6, 2020 were included. The primary outcomes were death and survival till March 5. Data of demographics, clinical features, comorbidities, laboratory tests and complications were collected and compared for different outcomes. Cox regression was performed for prognostic factors.

Results: 339 patients with COVID-19 (aged 71±8 years,173 females (51%)) were enrolled, including 80 (23.6%) critical, 159 severe (46.9%) and 100 moderate (29.5%) cases. Common comorbidities were hypertension (40.8%), diabetes (16.0%) and cardiovascular disease (15.7%). Common symptoms included fever (92.0%), cough (53.0%), dyspnea (40.8%) and fatigue (39.9%). Lymphocytopenia was a common laboratory finding (63.2%). Common complications included bacterial infection (42.8%), liver enzyme abnormalities (28.7%) and acute respiratory distress syndrome (21.0%). Till Mar 5, 2020, 91 cases were discharged (26.8%), 183 cases stayed in hospital (54.0%) and 65 cases (19.2%) were dead. Shorter length of stay was found for the dead compared with the survivors (5 (3-8) vs. 28 (26-29), P < 0.001). Symptoms of dyspnea (HR 2.35, P = 0.001), comorbidities including cardiovascular disease (HR 1.86, P = 0.031) and chronic obstructive pulmonary disease (HR 2.24, P = 0.023), and acute respiratory distress syndrome (HR 29.33, P < 0.001) were strong predictors of death. And a high level of lymphocytes was predictive of better outcome (HR 0.10, P < 0.001).

Conclusions: High proportion of severe to critical cases and high fatality rate were observed in the elderly COVID-19 patients. Rapid disease progress was noted in the dead with a median survival time of 5 days after admission. Dyspnea, lymphocytopenia, comorbidities including cardiovascular disease and chronic obstructive pulmonary disease, and acute respiratory distress syndrome were predictive of poor outcome. Close monitoring and timely treatment should be performed for the elderly patients at high risk.

Keywords: Coronavirus infections; Pneumonia; Prognosis; SARS-CoV-2.

Conflict of interest statement

Declaration of Competing Interest The authors declare that there is no conflict of interests.

Copyright © 2020. Published by Elsevier Ltd.

Figures

Fig. 1
Fig. 1
Univariate Cox regression for prognostic factors. Univariate Cox regression analysis of risk factors associated with fatality. AKI, acute kidney injury; APTT, activated partial thromboplastin time; ARDS, acute respiratory distress syndrome; COPD, chronic obstructive pulmonary disease; CKD, chronic kidney disease; HR, hazard ratio. ⁎⁎P < 0.01, ⁎⁎⁎P < 0.001.
Fig. 2
Fig. 2
Multivariate Cox regression for prognostic factors. Multivariate Cox regressions were performed for comorbidities (A) and complications (B), in which the “Age” factor was added to correct the models. AKI, acute kidney injury; ARDS, acute respiratory distress syndrome; COPD, chronic obstructive pulmonary disease; HR, hazard ratio. *P < 0.05, ⁎⁎⁎P < 0.001.

References

    1. Huang C., Wang Y., Li X. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497–506.
    1. Guan W.J., Ni Z.Y., Hu Y. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020
    1. 6th Ed. National Health Commision of the People's Republic of China; 2020. Interim guidance for novel coronavirus pneumonia. Accessed February 27th, 2020.
    1. Report of the WHO-China Joint Mission on Coronavirus Disease . 2019. Accessed Mar 5th, 2020.
    1. Khwaja A. KDIGO clinical practice guidelines for acute kidney injury. Nephron Clin Pract. 2012;120(4):c179–c184.
    1. Ferguson N.D., Fan E., Camporota L. The berlin definition of ARDS: an expanded rationale, justification, and supplementary material. Intensive Care Med. 2012;38(10):1573–1582.
    1. Jansen J.M., Gerlach T., Elbahesh H., Rimmelzwaan G.F., Saletti G. Influenza virus-specific CD4+ and CD8+ T cell-mediated immunity induced by infection and vaccination. J Clin Virol. 2019;119:44–52.
    1. Whitmire J.K., Ahmed R. Costimulation in antiviral immunity: differential requirements for CD4(+) and CD8(+) t cell responses. Curr==70== Opin Immunol. 2000;12(4):448–455.
    1. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases (COVID-19) in China. Zhonghua Liu Xing Bing Xue Za Zhi. 2020;41(2):145–151.
    1. Bellani G., Laffey J.G., Pham T. Epidemiology, patterns of care, and mortality for patients with acute respiratory distress syndrome in intensive care units in 50 countries. JAMA. 2016;315(8):788–800.
    1. Zumla A., Hui D.S., Perlman S. Middle east respiratory syndrome. Lancet. 2015;386(9997):995–1007.
    1. Gu J., Gong E., Zhang B. Multiple organ infection and the pathogenesis of Sars. J Exp Med. 2005;202(3):415–424.
    1. Chu H., Zhou J., Wong B.H. Middle east respiratory syndrome coronavirus efficiently infects human primary t lymphocytes and activates the extrinsic and intrinsic apoptosis pathways. J Infect Dis. 2016;213(6):904–914.

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