Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center

Clemens Stiegler; Tanja Seel; Claus Schaefer

doi:doi:10.11648/j.cmr.20211003.14

| Peer-Reviewed

Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center

Clemens Stiegler, Tanja Seel, Claus Schaefer

Published in Clinical Medicine Research (Volume 10, Issue 3)

Received: 30 April 2021 Accepted: 19 May 2021 Published: 27 May 2021

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The aim of this study was to identify clinical and laboratory characteristics with impact on outcome of patients with SARS-CoV2-Infection in a secondary care center in Germany. Therefore, a total of 69 hospitalized patients with COVID-19, detected with positive Multiplex real-time PCR result, were recruited from March 2020 to May 2020 to investigate the influence of comorbidities, demographic information and laboratory parameters on outcome. Data of routine laboratory examinations of 57 patients were collected at admission to detect prognostic factors. Mean age of patients was 70.0 years (21-99 years, median 74.0 years, SD 16,9). 28 patients (40,6%) had a severe course of disease (death and/or need for intensive care medicine), 20 patients (29%) died. LDH > 460 U/l (p=0.004, OR 12.99, 95% CI 2.23-75.67), Diabetes mellitus (p=0.021, OR 9.53, 95% CI 1.14-64.48) and Troponin T > 38 pg/ml (p=0.026, OR 6.04, 95% CI 1.24-29.43) were associated with occurrence of severe illness in multivariate analysis. Elevated Troponin T > 38 pg/ml (p=0.002, HR 8.22, 95% CI 2.19 – 30.88) and Diabetes mellitus (p=0.05, HR 3.14, 95% CI 1 – 9.85) were also associated with death. Patients with these conditions should be monitored closely.

Published in	Clinical Medicine Research (Volume 10, Issue 3)
DOI	10.11648/j.cmr.20211003.14
Page(s)	84-94
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

COVID-19, Risk Factors, Severe Disease, Diabetes Mellitus, Troponin T, LDH, Laboratory Parameters

References

[1]	Xiaochen Li, Shuyun Xu, Muqing Yu, Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan, J Allergy Clin Immunol. 2020 Jul; 146 (1): 110-118, doi: 10.1016/j.jaci.2020.04.006. Epub 2020 Apr 12
[2]	Zainab Shahid, BS, Ricci Kalayanamitra, BS, Brendan McClafferty, COVID-19 and Older Adults: What We Know, J Am Geriatr Soc. 2020 May, doi: 10.1111/jgs.16472
[3]	WHO-China Joint Mission. Report of the WHO-China Joint Mission on Coronavirus Disease 2019 (COVID-19). https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf. Accessed March 26, 2020.
[4]	Uranga, A., Quintana, J. M., Aguirre, U., Predicting 1-year mortality after hospitalization for community-aquired pneumonia, PloS One 13: e0192750, doi: 10.1371/journal.phone.0192750
[5]	Lingxi Guo, Dong Wei, Xinxin Zhang, Clinical Features Predicting Mortality Risk in Patients With Viral Pneumonia: The MuLBSTA Score, Front. Microbiol. 10: 2752, doi: 10.3389/fmicb.2019.02752
[6]	Wenhua Liang, Hengrui Liang, Limin Ou, Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19, JAMA Intern Med. 2020 Aug; 180 (8): 1–9. doi: 10.1001/jamainternmed.2020.2033
[7]	Rod J. E., Oviedo-Trespalacios Oscar, Cortes-Ramirez Javier, A brief-review of the risk factors for covid-19 severity, Rev Saude Publica. 2020; 54: 60, doi: 10.11606/s1518-8787.2020054002481
[8]	García Luis F., Immune Response, Inflammation, and the Clinical Spectrum of COVID-19, Front Immunol. 2020; 11: 1441, doi: 10.3389/fimmu.2020.01441
[9]	Almirall J., Serra-Prat M., Bolíbar I., Risk Factors for Community-Acquired Pneumonia in Adults: A Systematic Review of Observational Studies, Respiration 2017; 94: 299-311, doi: 10.1159/000479089
[10]	Paces J, Strizova Z, Smrz D, COVID-19 and the immune system, Physiol Res Actions. 2020 Jul 16; 69 (3): 379-388. doi: 10.33549/physiolres.934492.
[11]	Barton L. M., Duval E. J., Stroberg E., COVID-19 Autopsies, Oklahoma, USA, Am J Clin Pathol. 2020 May 5; 153 (6): 725-733. doi: 10.1093/ajcp/aqaa062.
[12]	Park M. D., Macrophages: a Trojan horse in COVID-19? Nat Rev Immunol. 2020 Apr 17: 1. doi: 10.1038/s41577-020-0317-2 [Epub ahead of print]
[13]	Huang C., Wang Y., Li X., Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China, Lancet, 2020 Feb 15; 395 (10223): 497-506. doi: 10.1016/S0140-6736(20)30183-5. Epub 2020 Jan 24.
[14]	Tan C., Huang Y., Shi F., C-reactive protein correlates with computed tomographic findings and predicts severe COVID-19 early, J Med Virol. 2020 Apr 25: 10.1002/jmv.25871., doi: 10.1002/jmv.25871
[15]	Zhou F., Yu T., Du R. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study, Lancet. 2020 28 March-3 April; 395 (10229): 1054–1062, doi: 10.1016/S0140-6736(20)30566-3
[16]	Ponti G., Maccaferri M., Ruini C., Biomarkers associated with COVID-19 disease progression, Crit Rev Clin Lab Sci. 2020: 1–11, doi: 10.1080/10408363.2020.1770685
[17]	Hulme K. D., Gallo L. A., Short K. R., Influenza Virus and Glycemic Variability in Diabetes: A Killer Combination? Front Microbiol. 2017; 8: 861, doi: 10.3389/fmicb.2017.00861
[18]	Singh AK, Gupta R, Ghosh A, Misra A., Diabetes in COVID-19: Prevalence, pathophysiology, prognosis and practical considerations, Diabetes Metab Syndr. Jul-Aug 2020; 14 (4): 303-310, doi: 10.1016/j.dsx.2020.04.004.
[19]	Ceriello A., Esposito K., Piconi L., Oscillating glucose is more deleterious to endothelial function and oxidative stress than mean glucose in normal and type 2 diabetic patients. Diabetes. 2008 May; 57 (5): 1349-54, DOI: 10.2337/db08-0063.
[20]	Rao S., Lau A., and So H-C. Exploring diseases/traits and blood proteins causally related to 284 expression of ACE2, the putative receptor of 2019-nCov: a Mendelian Randomization analysis Highlights Tentative Relevance of Diabetes-Related Traits. vol. 285, Diabetes Care. 2020 Jul; 43 (7): 1416-1426. doi: 10.2337/dc20-0643.
[21]	Fernandez C., Rysa J., Almgren P., Plasma levels of the proprotein convertase furin and incidence of diabetes and mortality. J Intern Med. 2018; 284: 377–387, doi: 10.1111/joim.12783
[22]	Maddaloni E., Buzzetti R. Covid-19 and diabetes mellitus: unveiling the interaction of two pandemics. Diabetes Metab Res Rev. 2020 Mar 31 doi: 10.1002/dmrr.3321
[23]	Kulcsar K. A., Coleman C. M., Beck S. E., Frieman M. B. Comorbid diabetes results in immune dysregulation and enhanced disease severity following MERS-CoV infection. JCI Insight. 2019; 4 (20): 131774. doi: 10.1172/jci.insight.131774.pii.
[24]	Vaduganathan M., Vardeny O., Michel T., Renin-Angiotensin-Aldosterone-System Inhibitors in Patients with Covid-19, Engl J Med. 2020 Mar 30: NEJMsr2005760. doi: 10.1056/NEJMsr2005760
[25]	Yang P, Gu H, Zhao Z, et al. Angiotensin-converting enzyme 2 (ACE2) mediates influenza H7N9 virus-induced acute lung injury. Sci Rep 2014; 4: 7027-7027, doi: 10.1038/srep07027
[26]	Reynolds H. R., Samrachana Adhikari S., Pulgarin C., Renin–Angiotensin–Aldosterone System Inhibitors and Risk of Covid-19, N Engl J Med. 2020 May 1: NEJMoa2008975, doi: 10.1056/NEJMoa2008975
[27]	Perico L, Benigni A., Casiraghi F., Immunity, endothelial injury and complement-induced coagulopathy in COVID-19, Nat Rev Nephrol. 2020 Oct 19: 1–19. doi: 10.1038/s41581-020-00357-4
[28]	Teuwen L. A., Geldhof V., Pasut A., COVID-19: the vasculature unleashed, Nat Rev Immunol. 2020 Jul; 20 (7): 389-391, doi: 10.1038/s41577-020-0343-0.
[29]	Garvin MR, Alvarez C, Miller JI, A mechanistic model and therapeutic interventions for COVID-19 involving a RAS-mediated bradykinin storm, Elife. 2020 Jul 7; 9: e59177. doi: 10.7554/eLife.59177
[30]	Shi S., Qin M., Cai Y., Characteristics and clinical significance of myocardial injury in patients with severe coronavirus disease 2019, Eur Heart J. 2020 May 11: ehaa408., doi: 10.1093/eurheartj/ehaa408
[31]	Corrales-Medina VF, Musher DM, Wells GA, Cardiac complications in patients with community-acquired pneumonia: incidence, timing, risk factors, and association with short-term mortality. Circulation. 2012 Feb 14; 125 (6): 773-81. doi: 10.1161/CIRCULATIONAHA.111.040766.
[32]	Oudit G. Y., Kassiri Z., Jiang C., SARS-coronavirus modulation of myocardial ACE2 expression and inflammation in patients with SARS, Eur J Clin Invest. 2009 Jul; 39 (7): 618-25., doi: 10.1111/j.1365-2362.2009.02153.x. Epub 2009 May 6.
[33]	Madjid M., Vela D., Khalili-Tabrizi H., Systemic infections cause exaggerated local inflammation in atherosclerotic coronary arteries: clues to the triggering effect of acute infections on acute coronary syndromes, Tex Heart Inst J. 2007; 34 (1): 11-8.,
[34]	Olloquequi J., COVID-19 Susceptibility in chronic obstructive pulmonary disease, Eur J Clin Invest. 2020 Oct; 50 (10): e13382. doi: 10.1111/eci.13382.
[35]	Zhaohai Zheng Z., Peng F., Xu B., Risk factors of critical & mortal COVID-19 cases: A systematic literature review and meta-analysis, J Infect. 2020 Aug; 81 (2): e16-e25. Doi: 10.1016/j.jinf.2020.04.021.
[36]	Sardu C., Gambardella J., Morelli M. B., Hypertension, Thrombosis, Kidney Failure, and Diabetes: Is COVID-19 an Endothelial Disease? A Comprehensive Evaluation of Clinical and Basic Evidence, J Clin Med. 2020 May; 9 (5): 1417. doi: 10.3390/jcm9051417
[37]	Yang X, Yu Y, Xu J, Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. The Lancet Respiratory medicine. 2020; 8 (5): 475-81
[38]	Scheen A. J., Metformin and COVID-19: From cellular mechanisms to reduced mortality, Diabetes Metab. 2020 Nov; 46 (6): 423–426, doi: 10.1016/j.diabet.2020.07.006
[39]	Bramante C., Ingraham N., Murray T. et al., Observational study of metformin and risk of mortality in patients hospitalized with Covid-19. medRxiv. 2020; 28 doi: 0.1101/2020.06.19.20135095
[40]	Cariou B., Hadjadj S., Wargny M. et al., Phenotypic characteristics and prognosis of in-patients with COVID-19 and diabetes: the CORONADO study. Diabetologia. 2020; 63: 1500–1515, doi: 10.1007/s00125-020-05180-x.
[41]	Chen Y., Yang D., Cheng B. et al., Clinical characteristics and outcomes of patients with diabetes and COVID-19 in association with glucose-lowering medication. Diabetes Care. 2020; 43: 1399–1407, doi: 10.2337/dc20-0660.
[42]	Luo P., Qiu L., Liu Y. et al., Metformin treatment was associated with decreased mortality in COVID-19 patients with diabetes in a retrospective analysis. Am J Trop Med Hyg. 2020; 103: 69–72, doi: 10.4269/ajtmh.20-0375.
[43]	Cameron A. R., Morrison V. L., Levin D. et al., Anti-Inflammatory Effects of Metformin Irrespective of Diabetes Status, Circ Res Actions. 2016 Aug 19; 119 (5): 652-65. doi: 10.1161/CIRCRESAHA.116.308445.

Cite This Article

Plain Text BibTeX RIS

APA Style

Clemens Stiegler, Tanja Seel, Claus Schaefer. (2021). Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center. Clinical Medicine Research, 10(3), 84-94. https://doi.org/10.11648/j.cmr.20211003.14

Copy | Download

ACS Style

Clemens Stiegler; Tanja Seel; Claus Schaefer. Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center. Clin. Med. Res. 2021, 10(3), 84-94. doi: 10.11648/j.cmr.20211003.14

Copy | Download

AMA Style

Clemens Stiegler, Tanja Seel, Claus Schaefer. Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center. Clin Med Res. 2021;10(3):84-94. doi: 10.11648/j.cmr.20211003.14

Copy | Download

@article{10.11648/j.cmr.20211003.14,
  author = {Clemens Stiegler and Tanja Seel and Claus Schaefer},
  title = {Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center},
  journal = {Clinical Medicine Research},
  volume = {10},
  number = {3},
  pages = {84-94},
  doi = {10.11648/j.cmr.20211003.14},
  url = {https://doi.org/10.11648/j.cmr.20211003.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cmr.20211003.14},
  abstract = {The aim of this study was to identify clinical and laboratory characteristics with impact on outcome of patients with SARS-CoV2-Infection in a secondary care center in Germany. Therefore, a total of 69 hospitalized patients with COVID-19, detected with positive Multiplex real-time PCR result, were recruited from March 2020 to May 2020 to investigate the influence of comorbidities, demographic information and laboratory parameters on outcome. Data of routine laboratory examinations of 57 patients were collected at admission to detect prognostic factors. Mean age of patients was 70.0 years (21-99 years, median 74.0 years, SD 16,9). 28 patients (40,6%) had a severe course of disease (death and/or need for intensive care medicine), 20 patients (29%) died. LDH > 460 U/l (p=0.004, OR 12.99, 95% CI 2.23-75.67), Diabetes mellitus (p=0.021, OR 9.53, 95% CI 1.14-64.48) and Troponin T > 38 pg/ml (p=0.026, OR 6.04, 95% CI 1.24-29.43) were associated with occurrence of severe illness in multivariate analysis. Elevated Troponin T > 38 pg/ml (p=0.002, HR 8.22, 95% CI 2.19 – 30.88) and Diabetes mellitus (p=0.05, HR 3.14, 95% CI 1 – 9.85) were also associated with death. Patients with these conditions should be monitored closely.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center
AU  - Clemens Stiegler
AU  - Tanja Seel
AU  - Claus Schaefer
Y1  - 2021/05/27
PY  - 2021
N1  - https://doi.org/10.11648/j.cmr.20211003.14
DO  - 10.11648/j.cmr.20211003.14
T2  - Clinical Medicine Research
JF  - Clinical Medicine Research
JO  - Clinical Medicine Research
SP  - 84
EP  - 94
PB  - Science Publishing Group
SN  - 2326-9057
UR  - https://doi.org/10.11648/j.cmr.20211003.14
AB  - The aim of this study was to identify clinical and laboratory characteristics with impact on outcome of patients with SARS-CoV2-Infection in a secondary care center in Germany. Therefore, a total of 69 hospitalized patients with COVID-19, detected with positive Multiplex real-time PCR result, were recruited from March 2020 to May 2020 to investigate the influence of comorbidities, demographic information and laboratory parameters on outcome. Data of routine laboratory examinations of 57 patients were collected at admission to detect prognostic factors. Mean age of patients was 70.0 years (21-99 years, median 74.0 years, SD 16,9). 28 patients (40,6%) had a severe course of disease (death and/or need for intensive care medicine), 20 patients (29%) died. LDH > 460 U/l (p=0.004, OR 12.99, 95% CI 2.23-75.67), Diabetes mellitus (p=0.021, OR 9.53, 95% CI 1.14-64.48) and Troponin T > 38 pg/ml (p=0.026, OR 6.04, 95% CI 1.24-29.43) were associated with occurrence of severe illness in multivariate analysis. Elevated Troponin T > 38 pg/ml (p=0.002, HR 8.22, 95% CI 2.19 – 30.88) and Diabetes mellitus (p=0.05, HR 3.14, 95% CI 1 – 9.85) were also associated with death. Patients with these conditions should be monitored closely.
VL  - 10
IS  - 3
ER  -

Copy | Download

Author Information

Clemens Stiegler

Department for Internal Medicine and Gastroenterology, Klinikum Neumarkt, Neumarkt in der Oberpfalz, Germany
Tanja Seel

Department for Internal Medicine and Gastroenterology, Klinikum Neumarkt, Neumarkt in der Oberpfalz, Germany
Claus Schaefer

Department for Internal Medicine and Gastroenterology, Klinikum Neumarkt, Neumarkt in der Oberpfalz, Germany

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Clemens Stiegler, Tanja Seel, Claus Schaefer. (2021). Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center. Clinical Medicine Research, 10(3), 84-94. https://doi.org/10.11648/j.cmr.20211003.14

Copy | Download

ACS Style

Clemens Stiegler; Tanja Seel; Claus Schaefer. Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center. Clin. Med. Res. 2021, 10(3), 84-94. doi: 10.11648/j.cmr.20211003.14

Copy | Download

AMA Style

Clemens Stiegler, Tanja Seel, Claus Schaefer. Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center. Clin Med Res. 2021;10(3):84-94. doi: 10.11648/j.cmr.20211003.14

Copy | Download

@article{10.11648/j.cmr.20211003.14,
  author = {Clemens Stiegler and Tanja Seel and Claus Schaefer},
  title = {Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center},
  journal = {Clinical Medicine Research},
  volume = {10},
  number = {3},
  pages = {84-94},
  doi = {10.11648/j.cmr.20211003.14},
  url = {https://doi.org/10.11648/j.cmr.20211003.14},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cmr.20211003.14},
  abstract = {The aim of this study was to identify clinical and laboratory characteristics with impact on outcome of patients with SARS-CoV2-Infection in a secondary care center in Germany. Therefore, a total of 69 hospitalized patients with COVID-19, detected with positive Multiplex real-time PCR result, were recruited from March 2020 to May 2020 to investigate the influence of comorbidities, demographic information and laboratory parameters on outcome. Data of routine laboratory examinations of 57 patients were collected at admission to detect prognostic factors. Mean age of patients was 70.0 years (21-99 years, median 74.0 years, SD 16,9). 28 patients (40,6%) had a severe course of disease (death and/or need for intensive care medicine), 20 patients (29%) died. LDH > 460 U/l (p=0.004, OR 12.99, 95% CI 2.23-75.67), Diabetes mellitus (p=0.021, OR 9.53, 95% CI 1.14-64.48) and Troponin T > 38 pg/ml (p=0.026, OR 6.04, 95% CI 1.24-29.43) were associated with occurrence of severe illness in multivariate analysis. Elevated Troponin T > 38 pg/ml (p=0.002, HR 8.22, 95% CI 2.19 – 30.88) and Diabetes mellitus (p=0.05, HR 3.14, 95% CI 1 – 9.85) were also associated with death. Patients with these conditions should be monitored closely.},
 year = {2021}
}

Copy | Download

TY  - JOUR
T1  - Prognostic Factors in Patients with COVID-19 Disease: A Retrospective Study in a Secondary Care Center
AU  - Clemens Stiegler
AU  - Tanja Seel
AU  - Claus Schaefer
Y1  - 2021/05/27
PY  - 2021
N1  - https://doi.org/10.11648/j.cmr.20211003.14
DO  - 10.11648/j.cmr.20211003.14
T2  - Clinical Medicine Research
JF  - Clinical Medicine Research
JO  - Clinical Medicine Research
SP  - 84
EP  - 94
PB  - Science Publishing Group
SN  - 2326-9057
UR  - https://doi.org/10.11648/j.cmr.20211003.14
AB  - The aim of this study was to identify clinical and laboratory characteristics with impact on outcome of patients with SARS-CoV2-Infection in a secondary care center in Germany. Therefore, a total of 69 hospitalized patients with COVID-19, detected with positive Multiplex real-time PCR result, were recruited from March 2020 to May 2020 to investigate the influence of comorbidities, demographic information and laboratory parameters on outcome. Data of routine laboratory examinations of 57 patients were collected at admission to detect prognostic factors. Mean age of patients was 70.0 years (21-99 years, median 74.0 years, SD 16,9). 28 patients (40,6%) had a severe course of disease (death and/or need for intensive care medicine), 20 patients (29%) died. LDH > 460 U/l (p=0.004, OR 12.99, 95% CI 2.23-75.67), Diabetes mellitus (p=0.021, OR 9.53, 95% CI 1.14-64.48) and Troponin T > 38 pg/ml (p=0.026, OR 6.04, 95% CI 1.24-29.43) were associated with occurrence of severe illness in multivariate analysis. Elevated Troponin T > 38 pg/ml (p=0.002, HR 8.22, 95% CI 2.19 – 30.88) and Diabetes mellitus (p=0.05, HR 3.14, 95% CI 1 – 9.85) were also associated with death. Patients with these conditions should be monitored closely.
VL  - 10
IS  - 3
ER  -

Copy | Download