Research Article
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Year 2021, Volume: 4 Issue: 3, 353 - 357, 21.05.2021
https://doi.org/10.32322/jhsm.909574

Abstract

References

  • Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020; 382: 1199–207.
  • Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382: 727–33.
  • Lu R, Zhao X, Li J, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020; 395: 556–74.
  • Chen N, Zhou M, Dong X, et al. Epidemiological and clinical charac-teristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020; 395: 507-13. 

  • Chan KW, Wong VT, Tang S. COVID-19: an update on the epidemio-logical, clinical, preventive and therapeutic evidence and guidelines of integrative Chinese-western medicine for the management of 2019 novel coronavirus disease. Am J Chin Med 2020; 48: 737-62.
  • Huang C, Wang Y, Li X, et al. Clinical features of patients in-fected with 2019 novel coronavirus in Wuhan. China. LANCET 2020; 395: 497-506.
  • Gençay I, Büyükkoçak Ü, Ateş G, Çağlayan O. Mean platelet volume and platelet distribution width as mortality predictors in ıntensive care unit. J Health Sci Med 2020; 3: 51-5.

  • Tajarernmuang P, Phrommintikul A, Limsukon A, Pothirat C, Chittawatanarat K. The role of mean platelet volume as a predictor of mortality in critically ill patients: a systematic review and me-ta-analysis. Crit Care Res Pract 2016; 2016: 1-8.
  • Seyhan AU, Doğanay F, Yılmaz E, Aydıner Ö, Ak R, Tekol SD. The comparison of chest CT and RT-PCR during the diagnosis of COVID-19. J Clin Med Kazakhstan 2021; 18: 53-6.
  • Kayri M , Boysan M . Using Chaid Analysis in Researches and an Application Pertaining to Coping Strategies. AÜEBFD 2007; 40: 133-49.
  • Fluss R, Faraggi D, Reiser B. Estimation of the Youden Index and its associated cutoff point. Biom J 2005; 47: 458-72.
  • Martin JF, Trowbridge EA, Salmon G, Plumb J. The biological significance of platelet volume: its relationship to bleeding time, platelet thromboxane B2 production and megakaryocyte nuclear DNA con-centration. Thromb Res 1983; 32: 443-60.
  • Becchi C, Al Malyan M, Fabbri LP, Marsili M, Boddi V, Boncinelli S. Mean platelet volume trend in sepsis: is it a useful parameter? Minerva Anestesiol 2006; 72: 749-56.
  • Kaser A, Brandacher G, Steurer W, et al. Interleukin-6 stimulates thrombopoiesis through thrombopoietin: role in inflammatory thrombocytosis. Blood 2001; 98: 2720-5.
  • Gorelik O, Izhakian S, Barchel D, et al. Prognostic significance of platelet count changes during hospitalization for community-ac-quired pneumonia. Platelets 2017; 28: 380-6.
  • Lee JH, Park M, Han S, Hwang JJ, Park SH, Park SY. An increase in mean platelet volume during admission can predict the prognoses of patients with pneumonia in the intensive care unit: a retrospec-tive study. PLoS One 2018; 13: e208715. 

  • Chu SG, Becker RC, Berger PB, et al. Mean platelet volume as a pre-dictor of cardiovascular risk: a systematic review and meta-analysis. J Thromb Haemost 2010; 8: 148-56.
  • Imam Z, Odish F, Gill I, et al. Older age and comorbidity are independent mortality predictors in a large cohort of 1305 COVID‐19 patients in Michigan, United States. J Int Med 2020; 288: 469-76.
  • Russell TW, Hellewell J, Jarvis CI, et al. CMMID COVID-19 working group. Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020. Eurosurveillance 2020; 25: 2000256.
  • Doğanay F, Elkonca F, Seyhan AU, Yılmaz E, Batırel A, Ak R. Shock index as a predictor of mortality among the COVID-19 patients. Am J Emerg Med 2021; 40: 106-9.
  • Gumus H, Demir A, Yükkaldıran A. Is mean platelet volume a predictive marker for the diagnosis of COVID‐19 in children? Int J Clin Pract 2020: e13892.

Relationship between mean platelet volume and intensive care unit requirement in COVID-19 patients

Year 2021, Volume: 4 Issue: 3, 353 - 357, 21.05.2021
https://doi.org/10.32322/jhsm.909574

Abstract

Objective: Our aim in this study is to examine the relationship between the mean platelet volume (MPV) and the intensive care unit (ICU) requirement in patients with 2019 coronavirus disease (COVID-19).
Methods: This retrospective observational study was conducted with patients who were diagnosed with COVID-19 in the emergency department of a tertiary hospital. The study was continued with the remaining 711 patients after using the inclusion and exclusion criteria. CHAID analysis was used as the decision tree method in analyzing the data. The relationship between ICU requirement and MPV were evaluated.
Results: There were 711 patients included in this study. The median age of the population was 64 (49-76). According to the CHAID analysis, the study population was divided into 2 classes as those who aged 58 years or younger (Younger Group) and those who older than 58 years (Older Group), and the relationship between the 8.3 threshold value of MPV and the ICU requirement was analyzed. For the Younger group, a significant difference was found in terms of ICU requirement based on the 8.3 threshold value of MPV.
Conclusion: Advanced age, high MPV and PLT values in COVID-19 patients, are associated with the ICU requirement. The 8.3 threshold value of MPV can be used as one of the parameters determining the ICU requirement in relatively young patients. In the geriatric age group, it is not beneficial to use MPV measurement to assign the ICU requirement. Multi-center studies with a large number of patients are needed to present the strength of the results of our study more clearly.

References

  • Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia. N Engl J Med 2020; 382: 1199–207.
  • Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med 2020; 382: 727–33.
  • Lu R, Zhao X, Li J, et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 2020; 395: 556–74.
  • Chen N, Zhou M, Dong X, et al. Epidemiological and clinical charac-teristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet 2020; 395: 507-13. 

  • Chan KW, Wong VT, Tang S. COVID-19: an update on the epidemio-logical, clinical, preventive and therapeutic evidence and guidelines of integrative Chinese-western medicine for the management of 2019 novel coronavirus disease. Am J Chin Med 2020; 48: 737-62.
  • Huang C, Wang Y, Li X, et al. Clinical features of patients in-fected with 2019 novel coronavirus in Wuhan. China. LANCET 2020; 395: 497-506.
  • Gençay I, Büyükkoçak Ü, Ateş G, Çağlayan O. Mean platelet volume and platelet distribution width as mortality predictors in ıntensive care unit. J Health Sci Med 2020; 3: 51-5.

  • Tajarernmuang P, Phrommintikul A, Limsukon A, Pothirat C, Chittawatanarat K. The role of mean platelet volume as a predictor of mortality in critically ill patients: a systematic review and me-ta-analysis. Crit Care Res Pract 2016; 2016: 1-8.
  • Seyhan AU, Doğanay F, Yılmaz E, Aydıner Ö, Ak R, Tekol SD. The comparison of chest CT and RT-PCR during the diagnosis of COVID-19. J Clin Med Kazakhstan 2021; 18: 53-6.
  • Kayri M , Boysan M . Using Chaid Analysis in Researches and an Application Pertaining to Coping Strategies. AÜEBFD 2007; 40: 133-49.
  • Fluss R, Faraggi D, Reiser B. Estimation of the Youden Index and its associated cutoff point. Biom J 2005; 47: 458-72.
  • Martin JF, Trowbridge EA, Salmon G, Plumb J. The biological significance of platelet volume: its relationship to bleeding time, platelet thromboxane B2 production and megakaryocyte nuclear DNA con-centration. Thromb Res 1983; 32: 443-60.
  • Becchi C, Al Malyan M, Fabbri LP, Marsili M, Boddi V, Boncinelli S. Mean platelet volume trend in sepsis: is it a useful parameter? Minerva Anestesiol 2006; 72: 749-56.
  • Kaser A, Brandacher G, Steurer W, et al. Interleukin-6 stimulates thrombopoiesis through thrombopoietin: role in inflammatory thrombocytosis. Blood 2001; 98: 2720-5.
  • Gorelik O, Izhakian S, Barchel D, et al. Prognostic significance of platelet count changes during hospitalization for community-ac-quired pneumonia. Platelets 2017; 28: 380-6.
  • Lee JH, Park M, Han S, Hwang JJ, Park SH, Park SY. An increase in mean platelet volume during admission can predict the prognoses of patients with pneumonia in the intensive care unit: a retrospec-tive study. PLoS One 2018; 13: e208715. 

  • Chu SG, Becker RC, Berger PB, et al. Mean platelet volume as a pre-dictor of cardiovascular risk: a systematic review and meta-analysis. J Thromb Haemost 2010; 8: 148-56.
  • Imam Z, Odish F, Gill I, et al. Older age and comorbidity are independent mortality predictors in a large cohort of 1305 COVID‐19 patients in Michigan, United States. J Int Med 2020; 288: 469-76.
  • Russell TW, Hellewell J, Jarvis CI, et al. CMMID COVID-19 working group. Estimating the infection and case fatality ratio for coronavirus disease (COVID-19) using age-adjusted data from the outbreak on the Diamond Princess cruise ship, February 2020. Eurosurveillance 2020; 25: 2000256.
  • Doğanay F, Elkonca F, Seyhan AU, Yılmaz E, Batırel A, Ak R. Shock index as a predictor of mortality among the COVID-19 patients. Am J Emerg Med 2021; 40: 106-9.
  • Gumus H, Demir A, Yükkaldıran A. Is mean platelet volume a predictive marker for the diagnosis of COVID‐19 in children? Int J Clin Pract 2020: e13892.
There are 21 citations in total.

Details

Primary Language English
Subjects Health Care Administration
Journal Section Original Article
Authors

Rohat Ak 0000-0002-8324-3264

Fatih Doğanay 0000-0003-4720-787X

Publication Date May 21, 2021
Published in Issue Year 2021 Volume: 4 Issue: 3

Cite

AMA Ak R, Doğanay F. Relationship between mean platelet volume and intensive care unit requirement in COVID-19 patients. J Health Sci Med / JHSM. May 2021;4(3):353-357. doi:10.32322/jhsm.909574

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