Homeliuk T. M., Marushchak M. I.

HEMOGRAM INDICATORS IN PATIENTS WITH COMMUNITY-ACQUIRED PNEUMONIA CAUSED BY COVID-19 DEPENDING ON THE CHARLSON COMORBIDITY INDEX


About the author:

Homeliuk T. M., Marushchak M. I.

Heading:

CLINICAL AND EXPERIMENTAL MEDICINE

Type of article:

Scentific article

Annotation:

Introduction. Several studies have shown a higher incidence of severe cases and mortality among COVID-19 patients with comorbidities such as diabetes, high blood pressure, obesity, and cardiovascular disease compared to patients without comorbidities. This raises the question of how multimorbidity -the presence of 2 or more chronic comorbidities – may affect disease severity and mortality in patients with SARS-CoV-2 infection. The aim of our research was to investigate hemogram indicators in patients with community-acquired pneumonia caused by COVID-19 depending on the Charlson comorbidity index. Material and methods. A retrospective non-interventional cohort study was conducted on the medical records of 208 patients who were hospitalized for community-acquired pneumonia with a negative smear test for SARSCoV-2 between mid-January and the end of April 2021. The main group consisted of patients with identification of SARS-CoV-2 nucleic acid and signs of pneumonia on high-resolution computed tomography. According to the severity of pneumonia, patients were divided into three groups: II group – patients with pneumonia of category 2 of complexity (n=124), group III – patients with pneumonia of category 3 of complexity (n=68), group IV – patients with pneumonia of category 4 of complexity ( n=16). The severity of pneumonia was calculated according to the PORT scale. Comparison groups were made up of patients with identification of SARS-CoV-2 nucleic acid and manifestations of pneumonia on high-resolution computed tomography. The indicators of the general analysis (erythrocytes, hemoglobin, ESR, platelets) of blood were determined on the automatic hematology analyzer «Yumizen H500 CT». Patient data and information about concomitant diseases were collected from the patients’ medical records. The Charlson Comorbidity Index (Charlson Comorbidity Index) for overall mortality prediction was calculated using a special computer program. Statistical analysis of data was carried out using the “STATISTICA 7.0” software. Comparative analysis of absolute indicators was carried out using the parametric ANOVA test. The results. It was established that patients with community-acquired pneumonia caused by SARS-CoV-2 of 4 complexity categories had the lowest indicators of erythrocytes, hemoglobin, platelets, and the highest erythrocyte sedimentation rate, compared to the data of patients of 2 and 3 complexity categories and the comparison group. At the same time, the ESR was probably lower by 10.20% in the II group compared to the data of the III group, but it remained probably higher compared to the values of the comparison group. Comparing the obtained data of the Charlson comorbidity index in patients with community-acquired pneumonia caused by SARS-CoV-2 with respect to the comparison group, it was found that its indicators were probably higher in the III (by 57.89%) and IV (by 167.67%) observation groups. Kruskel-Wallis analysis of rank variations showed the presence of statistically significant differences in the individual studied indicators of the hemogram in patients with community-acquired pneumonia of different categories of complexity depending on the comorbidity index. The probable influence of a high comorbid burden (CCI ≥3 points) on the level of erythrocytes and ESR in patients with pneumonia of the 4th complexity category in relation to the comparison, as well as the influence of a low comorbid burden (CCI 0-2 points) on the level of the color index and ESR in patients with pneumonia of the 2nd category of complexity compared to the comparison group. It is worth noting that among patients with a low comorbidity index, the ESR indicator was probably higher in all studied groups compared to the comparison group, while with a high SSI, this indicator in the IV group was probably higher than the similar indicator in the II group by 47.06%. When establishing the relationship between the studied parameters of the hemogram and the comorbidity index in community-acquired pneumonia caused by SARS-CoV-2, probable weak negative associations were found between the growth of SSI and a decrease in the level of erythrocytes, hemoglobin, color index and platelets. Conclusions. The results of this study indicate the lowest indicators of erythrocytes, hemoglobin, platelets and the highest erythrocyte sedimentation rate in patients with community-acquired pneumonia caused by SARS-CoV-2 of 4 severity categories in relation to data in patients of 2 and 3 severity categories and the comparison group. At the same time, a probable influence of a high comorbid burden (CCI ≥3 points) on the level of erythrocytes and ESR in patients with pneumonia of the 4th category of complexity in relation to the comparison group is revealed, as well as an influence of a low comorbid burden (CCI 0-2 points) on the level of color index and ESR in patients with pneumonia of 2 severity categories compared to the comparison group.

Tags:

SARS-CoV-2,pneumonia,Charlson comorbidity index,hemogram

Bibliography:

  1. Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. JAMA. 2020;323(11):1061-1069. DOI: 1001/jama.2020. 1585.
  2. Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020;395(10223):497-506. DOI: 1016/S0140-6736(20)30183-5.
  3. Fang L, Karakiulakis G, Roth M. Are patients with hypertension and diabetes mellitus at increased risk for COVID-19 infection? Lancet Respiratjry Medicine. 2020;8(4):e21. DOI: 1016/S2213-2600(20)30116-8.
  4. Varga Z, Flammer AJ, Steiger P, Haberecker M, Andermatt R, Zinkernagel AS, et al. Endothelial cell infection and endotheliitis in COVID-19. Lancet. 2020;395(10234):1417-1418. DOI: 1016/s0140-6736(20)30937-5.
  5. Hernández-Vásquez A, Azañedo D, Vargas-Fernández R, Bendezu-Quispe G. Association of Comorbidities With Pneumonia and Death Among COVID-19 Patients in Mexico: A Nationwide Cross-sectional Study. J Preventive Medicine & Public Health. 2020 Jul;53(4):211-219. DOI: 3961/jpmph. 20.186.
  6. Lim WS, van der Eerden MM, Laing R, Boersma WG, Karalus N, Town GI, et al. Defining community acquired pneumonia severity on presentation to hospital: an international derivation and validation study. Thorax. 2003;58(5):377-82. DOI: 1136/thorax.58.5.377.
  7. Haupt TH, Petersen J, Ellekilde G, Klausen HH, Thorball CW, Eugen-Olsen J, et al. Plasma suPAR level are associated mortality, admission time and Charlson Comorbidity Index in the acutely admitted medical patient: a prospective observation study. Critical Care. 2012;16:R130.
  8. Quan H, Li B, Couris CM, Fushimi K, Graham P, Hider P, et al. Updating and Validating the Charlson Comorbidity Index and Score for Risk Adjustment in Hospital Discharge Abstracts Using Data From 6 Countries. Am. J. Epidemiol. 2011;173(6):676-682
  9. 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;40:373-383. DOI: 1016/0021-9681(87) 90171-8.
  10. Centers for Disease Control and Prevention. Coronavirus disease 2019 (COVID-19). 2019 [cited 2020 Apr 30]. Available from: https://www. cdc.gov/coronavirus/2019-ncov/need-extra-precautions/groups-at-higher-risk.html.
  11. Mo P, Xing Y, Xiao Y, Deng L, Zhao Q, Wang H, et al. Clinical characteristics of refractory COVID-19 pneumonia in Wuhan, China. Clinical Infectious Diseases. 2021 Dec 6;73(11):e4208-e4213. DOI: 1093/cid/ ciaa270.
  12. Zheng Y, Zhang Y, Chi H, Chen S, Peng M, Luo L, et al. The hemocyte counts as a potential biomarker for predicting disease progression in COVID-19: a retrospective study. Clin Chem Lab Med. 2020;58:1106-15. DOI: 1515/cclm-2020-0377.
  13. Fois AG, Paliogiannis P, Scano V, Gau S, Babudieri S, Perra R, et al. The systemic inflammation index on admission predicts in-hospital mortality in COVID-19 patients. Molecules. 2020;25(23):5725. DOI: 3390/molecules 25235725.
  14. Lippi G, Plebani M, Henry BM. Thrombocytopenia is associated with severe coronavirus disease 2019 (COVID-19) infections: a metaanalysis. Clin Chim Acta. 2020;506:145-148. DOI: 1016/j.cca.2020.03.022.
  15. Subramaniam S, Scharrer I. Procoagulant activity during viral infections. Front Biosci (Landmark Ed). 2018;23:1060-81. DOI: 2741/4633.
  16. Bai B, Xu Z, Hu Y, Qu M, Cheng J, Luo S, et al. Patient hematology during hospitalization for viral pneumonia caused by SARS-CoV-2 and non-SARS-CoV-2 agents: a retrospective study. Eur J Med Res. 2021 May 14;26(1):45. DOI: 1186/s40001-021-00515-9.
  17. Kurt C, Altunçeki Ç Yildirim A. Contribution of Erythrocyte Sedimentation Rate to Predict Disease Severity and Outcome in COVID-19 Patients. Can J Infect Dis Med Microbiol. 2022 Aug 11;2022:6510952. DOI: 1155/ 2022/6510952.
  18. Ge LP, Li J, Bao QL, Chen P, Jiang Q, Zhu LR. Prognostic and predictive value of plasma D-dimer in advanced non-small cell lung cancer patients undergoing first-line chemotherapy. Clin Transl Oncol. 2015;17:57-64.
  19. Xin T. Changes and clinical significance of serum levels of strem-1, fibrinogen and d-dimer in patients with severe pneumonia. J Clin Pulm. 2018;23:155-158.

Publication of the article:

«Bulletin of problems biology and medicine» Issue 1 (168), 2023 year, 161-170 pages, index UDK 616.24-002-06:616.98:578.834.1]-074

DOI: