Electrocardiogram abnormalities and higher body mass index as clinically applicable factors for predicting poor outcome in patients with coronavirus disease 2019

Abstract

Background: Patients with coronavirus disease 2019 (COVID-19) have high resource utilization. Identifying the causes of severe COVID-19 is helpful for early intervention to reduce the consumption of medical resources. Methods: We included 103 patients with COVID-19 in this single-center observational study. To evaluate the incidence, predictors, and effects of COVID-19, we analyzed demographic information, laboratory results, comorbidities, and vital signs as factors for association with severe COVID-19. Results: The incidence of severe COVID-19 was 16.5% and the percent poor outcome (including mortality, entering in ICU or transferred to a superior hospital) was 6.8%. The majority of severe COVID-19 patients had abnormal electrocardiogram (ECG) (82.35%), hypertension (76.47%) and other cardiac diseases (58.82%). Multivariate logistic regression was used to determine the predictors of severe illness. Abnormal body mass index (BMI) and ECG (P < 0.05) were independent predictors of severe COVID-19. ECG abnormality was associated with increased odds of poor outcome (area under the receiver operating characteristic curves [AUC], 0.793; P = 0.010) and severe COVID-19 (AUC, 0.807; P < 0.0001). Overweight was also associated with increased odds of poor outcome (AUC, 0.728; P = 0.045) and severe illness COVID-19 (AUC, 0.816; P < 0.0001). Conclusion: Overweight and electrophysiological disorders on admission are important predictors of prognosis of patients with COVID-19.

Keywords

electrocardiogram abnormalities / overweight / coronavirus disease 2019

References

[1] Cui J, Li F, Shi Z L. Origin and evolution of pathogenic coronaviruses. Nat Rev Microbiol, 2019; 17(3): 181-192.

[2] World Health Organization. Coronavirus disease (COVID-19) situation reports. 2020. Accessed

[3] Grasselli G, Zangrillo A, Zabella A, et al. Baseline characteristics and outcomes of 1591 patients infected with SARS-CoV-2. JAMA, 2020; 323(16): 1574-1581.

[4] Huang C L, Wang Y M, Li X W, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet, 2020; 395(10223): 497-506. -->novel coronavirus in Wuhan, China. Lancet, 2020; 395(10223): 497-506.

[5] Rashedi J, Poor B M, Asgharzadeh V, et al. Risk factors for COVID-19. Infez Med, 2020; 28(4): 469-474.

[6] Fresán U, Guevara M, Elía F, et al. Independent role of severe obesity as a risk factor for COVID-19 hospitalization: a Spanish population-based cohort study. Obesity(Silver Spring), 2021; 29(1): 29-37.

[7] Ehmann L, Simon P, Busse D, et al. Risk of target non-attainment in obese compared to non-obese patients in calculated linezolid therapy. Clin Microbiol Infect, 2020; 26(9): 1222-1228.

[8] Zhang J J, Cao Y Y, Tan G, et al. Clinical, radiological, and laboratory characteristics and risk factors for severity and mortality of 289 hospitalized COVID-19 patients. Allergy, 2021; 76(2): 533-550.

[9] Gao L, Liang D, Wen X S, et al. Prognostic value of NT-proBNP in patients with severe COVID-19. Respir Res, 2020; 21(1): 83.

[10] Bompard F, Monnier H, Saab I, et al. Pulmonary embolism in patients with COVID-19 pneumonia. Eur Respir J, 2020; 56(1): 2001365.

[11] Petrakis D, Margină D, Tsarouhas K, et al. Obesity - a risk factor for increased COVID-19 prevalence, severity and lethality. Mol Med Rep, 2020; 22(1): 9-19.

[12] Zhou Y, Chi J, Lv W, et al. Obesity and diabetes as high-risk factors for severe coronavirus disease 2019 (Covid-19). Diabetes Metab Res Rev, 2021; 37(2): e3377.

[13] Wirth R, Becker C, Djukic M, et al. COVID-19 in old age-The geriatric perspective. Z Gerontol Geriatr, 2021; 54(2): 152-160.

[14] Li X C, Xu S Y, Yu M Q, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. J Allergy Clin Immunol, 2020; 146(1): 110-118.

[15] Gao F, Zheng K I, Wang X B, et al. Obesity is a risk factor for greater COVID-19 severity. Diabetes Care, 2020; 43(7): e72-e74.

[16] Guo T, Fan Y Z, Chen M, et al. Cardiovascular implications of fatal outcomes of patients with coronavirus disease 2019 (COVID-19). JAMA Cardiol, 2020; 5(7): 811-818.

[17] Zeng J H, Wu W B, Qu J X, et al. Cardiac manifestations of COVID-19 in Shenzhen, China. Infection, 2020; 48(6): 861-870.

[18] Chen W L, Kuo C D. Characteristics of heart rate variability can predict impending septic shock in emergency department patients with sepsis. Acad Emerg Med, 2007; 14(5): 392-397.

[19] de Castilho F M, Ribeiro A L P, da Silva J L P, et al. Heart rate variability as predictor of mortality in sepsis: A prospective cohort study. PLoS One, 2017; 12(6): e0180060.

[20] 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.

[21] Pan S W, Shu C C, Feng J Y, et al. Microbiological persistence in patients with mycobacterium avium complex lung disease: the predictors and the impact on radiographic progression. Clin Infect Dis, 2017; 65(6): 927-934.

[22] Günel C, Kırdar S, Ömürlü İ K, et al. Detection of the epstein-barr virus, human bocavirus and novel KI and KU polyomaviruses in adenotonsillar tissues. Int J Pediatr Otorhinolaryngol, 2015; 79(3): 423-427.

[23] Marbus S D, Schweitzer V A, Groeneveld G H, et al. Incidence and costs of hospitalized adult influenza patients in The Netherlands: a retrospective observational study. Eur J Health Econ, 2020; 21(5): 775-785.