Journal Home > Volume 2 , Issue 2
Background

We aimed to investigate risk factors predicting oxygen demand in COVID-19 patients.

Methods

Patients admitted to Shizuoka General Hospital with COVID-19 from August 2020 to August 2021 were included. First, we divided patients into groups with and without oxygen demand. Then, we compared patients' clinical characteristics and laboratory and radiological findings to determine factors predicting oxygen demand.

Results

One hundred seventy patients with COVID-19 (aged 58±15 years, 57 females) were enrolled. Common comorbidities were cardiovascular diseases (47.6%), diabetes mellitus (28.8%), and dyslipidemia (26.5%). Elder age, higher body mass index, cardiovascular diseases, diabetes mellitus, lower lymphocyte count, albumin, hepatic attenuation value, and the liver-to-spleen ratio (L/S), higher D-dimer, aspartate aminotransferase, lactate dehydrogenase, troponin-T, C-reactive protein, KL-6, chest and abdominal circumference, and visceral fat were found in patients with oxygen demand. According to the multivariate logistic regression analysis, L/S, lymphocyte count, D-dimer, and abdominal circumference under the diaphragm were independent risk factors predicting oxygen demand in COVID-19 patients.

Conclusions

On admission, L/S, lymphocyte count, D-dimer, and abdominal circumference were predictive factors for oxygen demand. These factors may help in the appropriate triage of COVID-19 patients in the decision to admit them to the hospital.


menu
Abstract
Full text
Outline
About this article

The liver-to-spleen ratio is a risk factor predicting oxygen demand in COVID-19 patients

Show Author's information Hiromasa Nakayasu( )Shogo SakuraiShuichi SugiyamaKotaro ShiratoriKohei OkawaYoshihiro KitaharaShingo TakahashiToshihiro MasudaYutaro KishimotoMika SaigusaAkito YamamotoTaisuke AkamatsuSatoru MoritaKazuhiro AsadaToshihiro Shirai
Department of Respiratory Medicine, Shizuoka General Hospital, 4-27-1 Kita-Ando, Aoi, 420-0805 Shizuoka, Japan

Abstract

Background

We aimed to investigate risk factors predicting oxygen demand in COVID-19 patients.

Methods

Patients admitted to Shizuoka General Hospital with COVID-19 from August 2020 to August 2021 were included. First, we divided patients into groups with and without oxygen demand. Then, we compared patients' clinical characteristics and laboratory and radiological findings to determine factors predicting oxygen demand.

Results

One hundred seventy patients with COVID-19 (aged 58±15 years, 57 females) were enrolled. Common comorbidities were cardiovascular diseases (47.6%), diabetes mellitus (28.8%), and dyslipidemia (26.5%). Elder age, higher body mass index, cardiovascular diseases, diabetes mellitus, lower lymphocyte count, albumin, hepatic attenuation value, and the liver-to-spleen ratio (L/S), higher D-dimer, aspartate aminotransferase, lactate dehydrogenase, troponin-T, C-reactive protein, KL-6, chest and abdominal circumference, and visceral fat were found in patients with oxygen demand. According to the multivariate logistic regression analysis, L/S, lymphocyte count, D-dimer, and abdominal circumference under the diaphragm were independent risk factors predicting oxygen demand in COVID-19 patients.

Conclusions

On admission, L/S, lymphocyte count, D-dimer, and abdominal circumference were predictive factors for oxygen demand. These factors may help in the appropriate triage of COVID-19 patients in the decision to admit them to the hospital.

Keywords: COVID-19, SARS-CoV-2, Oxygen demand, The liver-to-spleen ratio, Abdominal circumference

References(37)

[1]

X. Dong, Y.Y Cao, X.X. Lu, et al., Eleven faces of coronavirus disease 2019, Allergy 75 (7) (2020) 1699–1709, doi:10.1111/all.14289.

[2]

Z. Wu, J.M. McGoogan, Characteristics of and important lessons from the coronavirus disease 2019 (COVID-19) outbreak in China: summary of a report of 72314 cases from the Chinese Center for Disease Control and Prevention, JAMA 323 (13) (2020) 1239–1242, doi:10.1001/jama.2020.2648.

[3]

H. Peckham, N.M. de Gruijter, C. Raine, et al., Male sex identified by global COVID-19 meta-analysis as a risk factor for death and ICU admission, Nat. Commun. 11 (1) (2020) 6317, doi:10.1038/s41467-020-19741-6.

[4]

M. Terada, H. Ohtsu, S. Saito, et al., Risk factors for severity on admission and the disease progression during hospitalization in a large cohort of patients with COVID-19 in Japan, BMJ Open 11 (6) (2021) e047007, doi:10.1136/bmjopen-2020-047007.

[5]

Y. Uchida, H. Uemura, S. Yamaba, et al., Significance of liver dysfunction associated with decreased hepatic CT attenuation values in Japanese patients with severe COVID-19, J. Gastroenterol. 55 (11) (2020) 1098–1106, doi:10.1007/s00535-020-01717-4.

[6]

G. Favre, K. Legueult, C. Pradier, et al., Visceral fat is associated to the severity of COVID-19, Metabolism 115 (2021) 154440, doi:10.1016/j.metabol.2020.154440.

[7]

I. Zeb, D. Li, K. Nasir, et al., Computed tomography scans in the evaluation of fatty liver disease in a population based study: the multi-ethnic study of atherosclerosis, Acad. Radiol. 19 (7) (2012) 811–818, doi:10.1016/j.acra.2012.02.022.

[8]

Y. Kanda, Investigation of the freely available easy-to-use software ‘EZR’ for medical statistics, Bone Marrow Transplant 48 (3) (2013) 452–458, doi:10.1038/bmt.2012.244.

[9]

C. Danwang, F.T. Endomba, J.R. Nkeck, et al., A meta-analysis of potential biomarkers associated with severity of coronavirus disease 2019 (COVID-19), Biomark. Res. 8 (2020) 37, doi:10.1186/s40364-020-00217-0.

[10]

M. Ou, J. Zhu, P. Ji, et al., Risk factors of severe cases with COVID-19: a metaanalysis, Epidemiol. Infect. 148 (2020) e175, doi:10.1017/S095026882000179.

[11]

S. Ghahramani, R. Tabrizi, K.B. Lankarani, et al., Laboratory features of severe vs. non-severe COVID-19 patients in Asian populations: a systematic review and metaanalysis, Eur. J. Med. Res. 25 (1) (2020) 30, doi:10.1186/s40001-020-00432-3.

[12]

A. Mazzoni, L. Salvati, L. Maggi, et al., Impaired immune cell cytotoxicity in severe COVID-19 is IL-6 dependent, J. Clin. Invest. 130 (9) (2020) 4694–4703, doi:10.1172/JCI138554.

[13]

B. Diao, C. Wang, Y. Tan, et al., Reduction and functional exhaustion of T cells in patients with coronavirus disease 2019 (COVID-19), Front. Immunol. 11 (2020) 827, doi:10.3389/fimmu.2020.00827.

[14]

S. Tavakolpour, T. Rakhshandehroo, E.X. Wei, et al., Lymphopenia during the COVID-19 infection: what it shows and what can be learned, Immunol. Lett. 225 (2020) 31–32, doi:10.1016/j.imlet.2020.06.013.

[15]

Y. Ouyang, J. Yin, W. Wang, et al., Downregulated gene expression spectrum and immune responses changed during the disease progression in patients with COVID-19, Clin. Infect. Dis. 71 (16) (2020) 2052–2060, doi:10.1093/cid/ciaa462.

[16]

M.B. Pepys, G.M. Hirschfield, C-reactive protein: a critical update, J. Clin. Invest. 111 (12) (2003) 1805–1812, doi:10.1172/JCI18921.

[17]

I. Garrido, R. Liberal, G. Macedo, Review article: COVID-19 and liver disease-what we know on 1st May 2020,, Aliment Pharmacol. Ther 52 (2) (2020) 267–275, doi:10.1111/apt.15813.

[18]

Z. Xu, L. Shi, Y. Wang, et al., Pathological findings of COVID-19 associated with acute respiratory distress syndrome, Lancet Respir. Med. 8 (4) (2020) 420–422, doi:10.1016/S2213-2600(20)30076-X.

[19]

S.M. Lagana, S. Kudose, A.C. Iuga, et al., Hepatic pathology in patients dying of COVID-19: a series of 40 cases including clinical, histologic, and virologic data, Mod. Pathol. 33 (11) (2020) 2147–2155, doi:10.1038/s41379-020-00649-x.

[20]

P. Mehta, D.F. McAuley, M. Brown, et al., COVID-19: consider cytokine storm syndromes and immunosuppression, Lancet 395 (10229) (2020) 1033–1034, doi:10.1016/S0140-6736(20)30628-0.

[21]

C. Zhang, L. Shi, F.S. Wang, Liver injury in COVID-19: management and challenges, Lancet Gastroenterol. Hepatol. 5 (5) (2020) 428–430, doi:10.1016/S2468-1253(20)30057-1.

[22]

J. Sun, A. Aghemo, A. Forner, et al., COVID-19 and liver disease, Liver Int 40 (6) (2020) 1278–1281, doi:10.1111/liv.14470.

[23]

E. Guler, N.G. Unal, A. Cinkooglu, et al., Correlation of liver-to-spleen ratio, lung CT scores, clinical, and laboratory findings of COVID-19 patients with two consecutive CT scans, Abdom. Radiol. (NY) 46 (4) (2021) 1543–1551, doi:10.1007/s00261-020-02805-y.

[24]

S. Singh, A Khan, Clinical characteristics and outcomes of coronavirus disease 2019 among patients with preexisting liver disease in the United States: a multicenter research network study, Gastroenterology 159 (2) (2020) 768–771.e3, doi:10.1053/j.gastro.2020.04.064.

[25]

Y. Chang, J. Jeon, T.J. Song, et al., Association between the fatty liver index and the risk of severe complications in COVID-19 patients: a nationwide retrospective cohort study, BMC Infect. Dis. 22 (1) (2022) 384, doi:10.1186/s12879-022-07370-x.

[26]

A.S. Meijnikman, S. Bruin, A.K. Groen, et al., Increased expression of key SARSCoV-2 entry points in multiple tissues in individuals with NAFLD, J. Hepatol. 74 (3) (2021) 748–749, doi:10.1016/j.jhep.2020.12.007.

[27]

A. Hussain, K. Mahawar, Z. Xia, et al., Obesity and mortality of COVID-19, Meta-analysis, Obes. Res. Clin. Pract. 14 (4) (2020) 295–300, doi:10.1016/j.orcp.2020.07.002.

[28]

J. Yang, J. Hu, C. Zhu, Obesity aggravates COVID-19: a systematic review and metaanalysis, J. Med. Virol. 93 (1) (2021) 257–261, doi:10.1002/jmv.26237.

[29]

M. Watanabe, D. Caruso, D. Tuccinardi, et al., Visceral fat shows the strongest association with the need of intensive care in patients with COVID-19, Metabolism 111 (2020) 154319, doi:10.1016/j.metabol.2020.154319.

[30]

Y. Yang, L. Ding, X. Zou, et al., Visceral adiposity and high intramuscular fat deposition independently predict critical illness in patients with SARS-CoV-2, Obesity (Silver Spring) 28 (11) (2020) 2040–2048, doi:10.1002/oby.22971.

[31]

A. Petersen, K. Bressem, J. Albrecht, et al., The role of visceral adiposity in the severity of COVID-19: highlights from a unicenter cross-sectional pilot study in Germany, Metabolism 110 (2020) 154317, doi:10.1016/j.metabol.2020.154317.

[32]

R. Pranata, M.A. Lim, I. Huang, et al., Visceral adiposity, subcutaneous adiposity, and severe coronavirus disease-2019 (COVID-19): systematic review and meta-analysis, Clin. Nutr. ESPEN 43 (2021) 163–168, doi:10.1016/j.clnesp.2021.04.001.

[33]

K. Kiernan, N.J. MacIver, The role of the adipokine leptin in immune cell function in health and disease, Front. Immunol. 11 (2020) 3656, doi:10.3389/fimmu.2020.622468.

[34]

V. Guglielmi, L. Colangeli, M. D’Adamo, et al., Susceptibility and severity of viral infections in obesity: lessons from influenza to COVID-19. Does leptin play a role? Int. J. Mol. Sci. 22 (6) (2021) 3183, doi:10.3390/ijms22063183.

[35]

K. Ohashi, R. Shibata, T. Murohara, et al., Role of anti-inflammatory adipokines in obesity-related diseases, Trends Endocrinol. Metab. 25 (7) (2014) 348–355, doi:10.1016/j.tem.2014.03.009.

[36]

F. Tonon, S. Di Bella, F. Giudici, et al., Discriminatory value of adiponectin to leptin ratio for COVID-19 pneumonia, Int. J. Endocrinol. 2022 (2022) 9908450, doi:10.1155/2022/9908450.

[37]

J.L. Kuk, T.S. Church, S.N. Blair, et al., Does measurement site for visceral and abdominal subcutaneous adipose tissue alter associations with the metabolic syndrome? Diabetes Care 29 (3) (2006) 679–684, doi:10.2337/diacare.29.03.06.dc05-1500.

Publication history
Copyright
Acknowledgements
Rights and permissions

Publication history

Received: 11 February 2023
Revised: 02 April 2023
Accepted: 10 April 2023
Published: 20 April 2023
Issue date: June 2023

Copyright

© 2023 The Author(s). Tsinghua University Press.

Acknowledgements

None.

Rights and permissions

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Return