Risk Factors of Transfer to Mechanical Ventilation of COVID-19 Patients in a Retrospective Non-Randomized Study

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Abstract

Background. The COVID-19 pandemic is associated with significant number of complications and mortality and a burden on the healthcare system. In 10–15% of hospitalized patients, the invasive and non-invasive mechanical ventilation (IMV/NIMV) is required. At the same time, it is important to stratify the risk of mechanical ventilation upon admission to the hospital. Aims — to identify clinical and laboratory risk factors for transfer to IMV and NIMV in hospitalized patients with COVID-19-associated pneumonia. Methods. A retrospective one-center nonrandomized study of 386 consecutive hospitalized patients with COVID-19-associated pneumonia was performed. The primary endpoints were IMV (n=22) and NIMV (n=28). Risk factors of artificial ventilation were considered for periods up to 14 and 28 days for both variants. To select a risk predictor, a univariate analysis based on Cox survival regression was performed, followed by multivariate analysis to determine risk factors at these time points. Results. After 28 days from admission the mortal exit was registered in 20 patients from 386 patients (5.2%). 22 patients (5.7%) were transferred to IMV, and 28 patients (7.3%) — to NIV, and 9 of the latter were transferred later to IMV. As a result of univariate and multivariate analyzes, the risk factors for transfer to mechanical ventilation on 14th day were: age > 65 years (OR=5.91), a history of stroke (OR=17.04), an increased serum level of urea (OR=6.36), LDH (OR=7.39), decreased sodium (OR=12.32), GFR <80 mL/min/1.73 m2 (OR=13.75) and platelets (OR=4.14); on the 28th day — age > 65 years (OR=4.58), J-wave on the ECG (OR=2.98), an increase of LDH (OR=9.99) and a decrease in albumin (OR=2.77) in serum. Predictors of the transfer of patients with COVID-19 to NIV within the period up to 14 days from the beginning of hospitalization were the age > 65 years (OR=5.09), procalcitonin level in the blood > 0.25 ng/ml (OR=0.19), leukocytes > 11×109 (OR=19.64) and increased LDH (OR=3.9). Conclusions. In patients with COVID-19, the risk factors for transfer to IMV/NIVL in the period of 14 and 28 days from the beginning of hospitalization were identified, which enable patient’s mechanical ventilation stratification and to plan respiratory support resources.

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About the authors

Irina A. Lakman

Ufa State Aviation Technikal University; Bashkir State University

Email: Lackmania@mail.ru
ORCID iD: 0000-0001-9876-9202
SPIN-code: 4521-9097

Dr.-Ing., Assoc.Prof. of Biomedical Engineering Department, Head of the Scientific laboratory for the study of social and economic problems of the regions

Russian Federation, K. Marx Str. 12, 450015, Ufa; Z. Validi Str. 32, 450078, Ufa

Timur I. Musin

Bashkir State Medical University

Email: tyrannyah@gmail.com
ORCID iD: 0000-0002-9927-6626
SPIN-code: 7066-0715

Assistant Professor of Department of Internal Diseases

Russian Federation, 3, Lenin Str. 450008, Ufa

Aliya R. Galiullina

Ufa State Aviation Technical University

Email: algaliull244@yandex.ru
ORCID iD: 0000-0003-4862-9476

master's student of Biomedical Engineering Department

Russian Federation, K. Marx Str. 12, 450015, Ufa

Zilya A. Bagmanova

Bashkir State Medical University

Email: zilya20641@yandex.ru
ORCID iD: 0000-0003-1149-6702
SPIN-code: 6427-4345

MD, PhD, Professor of Department of Internal Diseases

Russian Federation, Lenin Str. 3, 450008, Ufa

Ruslan M. Gumerov

Bashkir State Medical University

Email: rmgumerov@gmail.com
ORCID iD: 0000-0002-6110-0377
SPIN-code: 3357-2603

Assistant Professor of Department of Internal Diseases

Russian Federation, Lenin Str. 3, 450008, Ufa

Paruir A. Davtyan

Bashkir State Medical University

Email: davtyanparuir@gmail.com
ORCID iD: 0000-0002-5972-6418
SPIN-code: 8816-1568

resident of Department of Internal Diseases

Russian Federation, Lenin Str. 3, 450008, Ufa

Shamil Z. Zagidullin

Bashkir State Medical University

Email: zshamil@inbox.ru
ORCID iD: 0000-0002-7249-3364

MD, PhD, Professor of Department of Internal Diseases

Russian Federation, Lenin Str. 3, 450008, Ufa

Anton V. Tyurin

Bashkir State Medical University

Email: anton.bgmu@gmail.com
ORCID iD: 0000-0002-0841-3024
SPIN-code: 5046-3704

MD, PhD, Associate Professor

Russian Federation, 3, Lenin Str. 450008, Ufa

Sergey V. Novikov

Ufa State Aviation Technikal University

Email: sn9177774405@gmail.com
ORCID iD: 0000-0002-8439-8620
SPIN-code: 7288-4074

PhD, Professor of Taxes and Taxation Department

Russian Federation, K. Marx Str. 12, 450015, Ufa

Valentin N. Pavlov

Bashkir State Medical University

Email: pavlov@bashgmu.ru
ORCID iD: 0000-0003-2125-4897
SPIN-code: 2799-6268

MD, PhD, Professor, Corresponding Member of the RAS

Russian Federation, 3, Lenin Str. 450008, Ufa

Uilya O. Urazbakhtina

Ufa State Aviation Technikal University

Email: urjuol@mail.ru
ORCID iD: 0000-0001-7715-302X
SPIN-code: 2189-3619

PhD of Technical Sciences, Associate Professor

Russian Federation, K. Marx Str. 12, 450015, Ufa

Benzhi Cai

Harbin Medical University

Email: caibz@ems.hrbmu.edu.cn
ORCID iD: 0000-0002-6342-4930

Prof., MSc, Department of Pharmacy at The Second Affiliated Hospital, and Department of Pharmacology at College of Pharmacy

China, Harbin 150086

Naufal S. Zagidullin

Bashkir State Medical University; Ufa State Aviation Technical University

Author for correspondence.
Email: znaufal@mail.ru
ORCID iD: 0000-0003-2386-6707

MD, PhD, Professor of Department of Internal Diseases, Professor of Biomedical Engineering Department

Russian Federation, Lenin Str. 3, 450008, Ufa; K. Marx Str. 12, 450015, Ufa

References

  1. Figliozzi S, Masci PG, Ahmadi N., et al. Predictors of adverse prognosis in COVID‐19: A systematic review and meta‐analysis. Eur J Clin Invest. 2020;50(10):e13362. doi: https://doi.org/10.1111/eci.13362
  2. Richardson S, Hirsch JS, Narasimhan M, et al. Presenting Characteristics, Comorbidities, and Outcomes Among 5700 Patients Hospitalized with COVID-19 in the New York City Area. JAMA. 2020;323(20):2052–2059. doi: https://doi.org/10.1001/jama.2020.6775
  3. Rosenbaum L. The Untold Toll — The Pandemic’s Effects on Patients without COVID-19. N Engl J Med. 2020;382:2368–2371. doi: https://doi.org/10,1056/NEJMms2009984
  4. Chowdhury MEH, Rahman T, Khandakar A, et al. An Early Warning Tool for Predicting Mortality Risk of COVID-19 Patients Using Machine Learning. Cognit Comput. 2021;1–16. doi: https://doi.org/10.1007/s12559-020-09812-7
  5. Yadaw AS, Li Y-C, Bose S, et al. Clinical features of COVID-19 mortality: Development and validation of a clinical prediction model. Lancet Digit Health. 2020;2(10):e516–e525. doi: https://doi.org/10.1016/S2589-7500(20)30217-X
  6. WHO Coronavirus disease (COVID-19) [Electronic recourse]. Available from: URL: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/question-and-answers-hub/q-a-detail/coronavirus-disease-covid-19
  7. Gómez CA, Sun C-K, Tsai I-T, et al. Mortality and risk factors associated with pulmonary embolism in coronavirus disease 2019 patients: A systematic review and meta-analysis. Sci Rep. 2021;11(1):16025. doi: https://doi.org/10.1038/s41598-021-95512-7
  8. Bushman D, Davidson A, Pathela P, et al. Risk Factors for Death Among Hospitalized Patients Aged 21–64 Years Diagnosed with COVID-19 — New York City, March 13 — April 9, 2020. J Racial Ethn Health Disparities. 2021:1–16. doi: https://doi.org/10.1007/s40615-021-01098-1
  9. Suardi LR, Pallotto C, Esperti S, et al. Risk factors for non-invasive/invasive ventilatory support in patients with COVID-19 pneumonia: A retrospective study within a multidisciplinary approach. Int J Infect Dis. 2020;100:258–263. doi: https://doi.org/10.1016/j.ijid.2020.09.012
  10. Zagidullin NSh, Motloch LJ, Musin TI, et al. J-waves in acute COVID-19: A novel disease characteristic and predictor of mortality? PloS One. 2021;16(10):е0257982. doi: https://doi.org/10.1371/journal.pone.0257982
  11. Atlam M, Torkey H, El-Fishawy N, et al. Coronavirus disease 2019 (COVID-19): Survival analysis using deep learning and Cox regression model. Pattern Anal Appl. 2021;24(3):993–1005. doi: https://doi.org/10.1007/s10044-021-00958-0
  12. Harrell FEJr, Califf RM, Pryor DB, et al. Evaluating the yield of medical tests. JAMA. 1982;247(18):2543–2546. PMID: 7069920
  13. Antzelevitch C, Yan G-X, Ackerman MJ, et al. J-Wave syndromes expert consensus conference report: Emerging concepts and gaps in knowledge. Europace. 2017;19(4):665–694. doi: https://doi.org/10.1093/europace/euw235
  14. Abdeen Y, Kaako A, Ahmad Amin Z, et al. The Prognostic Effect of Serum Albumin Level on Outcomes of Hospitalized COVID-19 Patients. Crit Care Res Pract. 2021;2021:9963274. doi: https://doi.org/10.1155/2021/9963274
  15. Gomi K, Ito T, Yamaguchi F, et al. Clinical features and mechanism of liver injury in patients with mild or moderate coronavirus disease 2019. JGH Open. 2021;5(8):888–895. doi: https://doi.org/10.1002/jgh3.12599
  16. Giovanelli N, Lazzer S, Cauci S. Muscle damage and inflammatory status biomarkers after a 3-stage trail running race. J Sports Med Phys Fitness. 2020;60(11):1486–1492. doi: https://doi.org/10.23736/S0022-4707.20.10997-6
  17. Allenbach Y, Saadoun D, Maalouf G, et al. Development of a multivariate prediction model of intensive care unit transfer or death: A French prospective cohort study of hospitalized COVID-19 patients. Observational Study. PLoS One. 2020;15(10):e0240711. doi: https://doi.org/10.1371/journal.pone.0240711
  18. Chebotareva N, Berns S, Androsova T, et al. Risk factors for invasive and non-invasive ventilatory support and mortality in hospitalized patients with COVID-19. Med Intensiva (Engl Ed). 2021;S0210-5691(21)00076-0. doi: https://doi.org/10.1016/j.medin.2021.04.002
  19. Миронов П.И., Лутфарахманов И.И., Сырчин Е.Ю., и др. Предикторы гибели пациентов с COVID-19, находящихся на искусственной вентиляции легких // Медицинский вестник Башкортостана. — 2020. — Т. 15. — № 6 (90). — С. 86–92. [Mironov PI, Lutfarahmanov II, Syrchin EYu., et al. Predictors of death in patients with Covid-19 on artificial lung ventilation. Medicinskij vestnik Bashkortostana. [Medical Bulletin of Bashkortostan]. 2020;15(6(90)):86–92. (In Russ.)]
  20. Szakmany T, Tuckwell W, Harte E, et al. Differences in Inflammatory Marker Kinetics between the First and Second Wave of COVID-19 Patients Admitted to the ICU: A Retrospective, Single-Center Study. J Clin Med. 2021;10(15):3290. doi: https://doi.org/10.3390/jcm10153290
  21. Авдеев С.Н., Царева Н.А., Мержоева З.М., и др. Практические рекомендации по кислородотерапии и респираторной поддержке пациентов с COVID-19 на дореанимационном этапе // Пульмонология. — 2020. — Т. 30. — № 2. — С. 151–163. [Avdeev SN, Tsareva NA, Merzhoeva ZM, et al. Practical guidelines for oxygen therapy and respira tory support for patients with COVID-19 in the pre-life support. Russian Pulmonology. 2020;30(2):151–163 (in Russ.)]. doi: https://doi.org/10.18093/0869-0189-2020-30-2-151-163
  22. Vitacca M, Nava S, Santus P, Harari S. Early consensus management for non-ICU acute respiratory failure SARS CoV-2 emergency in Italy: from ward to trenches. Eur Respir J. 2020;55(5):2000632. doi: https://doi.org/10.1183/13993003.00632-2020

Supplementary files

Supplementary Files
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1. Fig.1. Study design

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2. Fig.2. Multivariate analysis of risk factors for the transfer to mechanical ventilation of patients with COVID-19 in the period up to 14 days from the start of hospitalization (CI = 0.96)

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3. Fig.3. Multivariate analysis of risk factors for transfer to mechanical ventilation of patients with COVID-19 up to 28 days from the start of hospitalization (CI = 0.86)

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4. Fig.4. Multivariate analysis of risk factors for transfer to NIV in patients with COVID-19 up to 14 days from the start of hospitalization (CI 0.90)

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