Araştırma Makalesi
BibTex RIS Kaynak Göster
Yıl 2022, Cilt: 12 Sayı: 2, 116 - 121, 31.08.2022

Öz

Kaynakça

  • 1. Lu H, Stratton CW, Tang Y. Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle. Journal of Medical Virology 2020;92:401–2. https://doi.org/10.1002/jmv.25678.
  • 2. Arabi YM, Harthi A, Hussein J, A Bouchama, S Johani, A H Hajeer, et al. Severe neurologic syndrome associated with Middle East respiratory syndrome corona virus (MERS-CoV). Infection2015;43(4):495–501. https://doi.org/10.1007/s15010-015-0720-y.
  • 3. Neuman BW, Buchmeier MJ. Supramolecular Architecture of the Coronavirus Particle. Advances in virus research 2016;96:1–27. https://doi.org/10.1016/bs.aivir.2016.08.005.
  • 4. Shereen MA, Khan S, Kazmi A, Bashir N, & Siddique R. COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses. Journal of advanced research 2020;24:91–8. https://doi.org/10.1016/j.jare.2020.03.005.
  • 5. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis 2020;34:101623. doi:10.1016/j.tmaid.2020.101623.
  • 6. Gorgun S. A Comprehensive COVID-19 Meta-Analysis: Clinical Data of 18,450 Patients. COVID-19 Pandemic: Case Studies & Opinions 2020;01(03):33–43.
  • 7. Pascarella G, Strumia A, Piliego C, Bruno F, Del Buono R, Costa F, et al. COVID-19 diagnosis and management: a comprehensive review. J Intern Med 2020; 288(2):192-206. doi: 10.1111/joim.13091.
  • 8. Paz S, Mauer C, Ritchie A, Robishaw JD, Caputi M. A simplified SARS-CoV-2 detection protocol for research laboratories. PLoS One 2020;18;15(12):e0244271. doi: 10.1371/journal.pone.0244271.
  • 9. Kronbichler A, Kresse D, Yoon S, Lee KH, Effenberger M, Shin JI. Asymptomatic patients as a source of COVID-19 infections: A systematic review and meta-analysis. Int J Infect Dis 2020;98:180-6. doi: 10.1016/j.ijid.2020.06.052. 10. Krähenbühl M, Oddo M, Piquilloud L, Pantet O. COVID-19: Prise en charge aux soins intensifs [COVID-19: Intensive care management]. Rev Med Suisse 2020;29:16(N° 691-2):863-868.
  • 11. Swiss Academy of Medical Sciences. COVID-19 pandemic: triage for intensive-care treatment under resource scarcity. Swiss Med Wkly 2020;24;150:w20229. doi: 10.4414/smw.2020.20229.
  • 12. Phua J, Weng L, Ling L, Egi M, Lim CM, Divatia JV, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations [published correction appears in Lancet Respir Med 2020; 8(5): e42] Lancet Respir Med 2020;8(5):506-517. doi:10.1016/S2213-2600(20)30161-2.
  • 13. Li LQ, Huang T, Wang YQ, Wang ZP, Liang Y, Huang TB, et al. COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol 2020;92(6):577-583. doi:10.1002/jmv.25757.
  • 14. Liu S, Yao N, Qiu Y, He C. Predictive performance of SOFA and qSOFA for in-hospital mortality in severe novel coronavirus disease. Am J Emerg Med 2020;38(10):2074–2080.
  • 15. Bhatraju PK, Ghassemieh BJ, Nichols M, Kim R, Jerome KR, Nalla AK, et al. Covid-19 in critically ill patients in the Seattle region-case series. N Engl J Med 2020. https://doi.org/10.1056/ NEJMoa2004500.
  • 16. Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging (Albany NY) 2020;8;12(7):6049-6057. doi: 10.18632/aging.103000.
  • 17. Wu Z, McGoogan JM. Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239-1242. doi:10.1001/jama.2020.2648.
  • 18. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382(18):1708-1720. doi:10.1056/NEJMoa2002032.
  • 19. Aktimur R, Cetinkunar S, Yildirim K, Aktimur SH, Ugurlucan M, Ozlem N. Neutrophil-to-lymphocyte ratio as a diagnostic biomarker for the diagnosis of acute mesenteric ischemia. Eur J Trauma Emerg Surg 2016;42(3):363-8.
  • 20. Cetinkunar S, Guzel H, Emre Gokce I, Erdem H, Gulkan S, Aktimur R, et al. High levels of platelet/lymphocyte ratio are associated with metastatic gastric cancer. J BUON 2015;20(1):78-83. 21. Yang AP, Liu JP, Tao WQ, Li HM. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol 2020; 84:106504. doi:10.1016/j.intimp.2020.106504
  • 22. Liu Y, Du X, Chen J, Jin Y, Peng L, Wang HHX, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. J Infect 2020;81(1): e6-e12. doi:10.1016/j.jinf.2020.04.002
  • 23. Qu R, Ling Y, Zhang YH, Wei LY, Chen X, Li XM, et al. Platelet-to-lymphocyte ratio is associated with prognosis in patients with coronavirus disease-19. J Med Virol 2020;92(9):1533-1541.

Intensive Care Prediction During Treatment Of Covid-19 Patients

Yıl 2022, Cilt: 12 Sayı: 2, 116 - 121, 31.08.2022

Öz

Aim: We aimed to research the routine examinations, clinical and radiological findings of patients hospitalized with the diagnosis of Covid-19, the clinical course of the patients whose treatments were ongoing, and the markers that could predict the possibility of admission to the intensive care unit.
Materials and Methods: Retrospectively compared the examinations and findings on the day of hospitalization of the patients who were followed up for Covid-19 treatment with the data on the first day of their admission to the intensive care unit.
Results: Out of 195 patients treated with the diagnosis of Covid-19 in the service on the first day. Fever, shortness of breath, chest pain, and cough were the most common symptoms. Platelet and lymphocyte ratio was higher in the patients' first days in the service compared to the first days in intensive care, and the change that occurred was statistically significant (p<0.05). A significant difference was found between SOFA score and gender (p<0.05) and between SOFA score and age (p<0.05).
Conclusion: Covid-19 patients with comorbid diseases such as advanced age, diabetes, hypertension, heart and respiratory failure, and acute and chronic renal failure carry a higher risk.

Kaynakça

  • 1. Lu H, Stratton CW, Tang Y. Outbreak of pneumonia of unknown etiology in Wuhan, China: The mystery and the miracle. Journal of Medical Virology 2020;92:401–2. https://doi.org/10.1002/jmv.25678.
  • 2. Arabi YM, Harthi A, Hussein J, A Bouchama, S Johani, A H Hajeer, et al. Severe neurologic syndrome associated with Middle East respiratory syndrome corona virus (MERS-CoV). Infection2015;43(4):495–501. https://doi.org/10.1007/s15010-015-0720-y.
  • 3. Neuman BW, Buchmeier MJ. Supramolecular Architecture of the Coronavirus Particle. Advances in virus research 2016;96:1–27. https://doi.org/10.1016/bs.aivir.2016.08.005.
  • 4. Shereen MA, Khan S, Kazmi A, Bashir N, & Siddique R. COVID-19 infection: Origin, transmission, and characteristics of human coronaviruses. Journal of advanced research 2020;24:91–8. https://doi.org/10.1016/j.jare.2020.03.005.
  • 5. Rodriguez-Morales AJ, Cardona-Ospina JA, Gutiérrez-Ocampo E, Villamizar-Peña R, Holguin-Rivera Y, Escalera-Antezana JP, et al. Clinical, laboratory and imaging features of COVID-19: A systematic review and meta-analysis. Travel Med Infect Dis 2020;34:101623. doi:10.1016/j.tmaid.2020.101623.
  • 6. Gorgun S. A Comprehensive COVID-19 Meta-Analysis: Clinical Data of 18,450 Patients. COVID-19 Pandemic: Case Studies & Opinions 2020;01(03):33–43.
  • 7. Pascarella G, Strumia A, Piliego C, Bruno F, Del Buono R, Costa F, et al. COVID-19 diagnosis and management: a comprehensive review. J Intern Med 2020; 288(2):192-206. doi: 10.1111/joim.13091.
  • 8. Paz S, Mauer C, Ritchie A, Robishaw JD, Caputi M. A simplified SARS-CoV-2 detection protocol for research laboratories. PLoS One 2020;18;15(12):e0244271. doi: 10.1371/journal.pone.0244271.
  • 9. Kronbichler A, Kresse D, Yoon S, Lee KH, Effenberger M, Shin JI. Asymptomatic patients as a source of COVID-19 infections: A systematic review and meta-analysis. Int J Infect Dis 2020;98:180-6. doi: 10.1016/j.ijid.2020.06.052. 10. Krähenbühl M, Oddo M, Piquilloud L, Pantet O. COVID-19: Prise en charge aux soins intensifs [COVID-19: Intensive care management]. Rev Med Suisse 2020;29:16(N° 691-2):863-868.
  • 11. Swiss Academy of Medical Sciences. COVID-19 pandemic: triage for intensive-care treatment under resource scarcity. Swiss Med Wkly 2020;24;150:w20229. doi: 10.4414/smw.2020.20229.
  • 12. Phua J, Weng L, Ling L, Egi M, Lim CM, Divatia JV, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations [published correction appears in Lancet Respir Med 2020; 8(5): e42] Lancet Respir Med 2020;8(5):506-517. doi:10.1016/S2213-2600(20)30161-2.
  • 13. Li LQ, Huang T, Wang YQ, Wang ZP, Liang Y, Huang TB, et al. COVID-19 patients' clinical characteristics, discharge rate, and fatality rate of meta-analysis. J Med Virol 2020;92(6):577-583. doi:10.1002/jmv.25757.
  • 14. Liu S, Yao N, Qiu Y, He C. Predictive performance of SOFA and qSOFA for in-hospital mortality in severe novel coronavirus disease. Am J Emerg Med 2020;38(10):2074–2080.
  • 15. Bhatraju PK, Ghassemieh BJ, Nichols M, Kim R, Jerome KR, Nalla AK, et al. Covid-19 in critically ill patients in the Seattle region-case series. N Engl J Med 2020. https://doi.org/10.1056/ NEJMoa2004500.
  • 16. Wang B, Li R, Lu Z, Huang Y. Does comorbidity increase the risk of patients with COVID-19: evidence from meta-analysis. Aging (Albany NY) 2020;8;12(7):6049-6057. doi: 10.18632/aging.103000.
  • 17. Wu Z, McGoogan JM. Characteristics of and Important Lessons from the Coronavirus Disease 2019 (COVID-19) Outbreak in China: Summary of a Report of 72 314 Cases from the Chinese Center for Disease Control and Prevention. JAMA. 2020;323(13):1239-1242. doi:10.1001/jama.2020.2648.
  • 18. Guan WJ, Ni ZY, Hu Y, Liang WH, Ou CQ, He JX, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med 2020;382(18):1708-1720. doi:10.1056/NEJMoa2002032.
  • 19. Aktimur R, Cetinkunar S, Yildirim K, Aktimur SH, Ugurlucan M, Ozlem N. Neutrophil-to-lymphocyte ratio as a diagnostic biomarker for the diagnosis of acute mesenteric ischemia. Eur J Trauma Emerg Surg 2016;42(3):363-8.
  • 20. Cetinkunar S, Guzel H, Emre Gokce I, Erdem H, Gulkan S, Aktimur R, et al. High levels of platelet/lymphocyte ratio are associated with metastatic gastric cancer. J BUON 2015;20(1):78-83. 21. Yang AP, Liu JP, Tao WQ, Li HM. The diagnostic and predictive role of NLR, d-NLR and PLR in COVID-19 patients. Int Immunopharmacol 2020; 84:106504. doi:10.1016/j.intimp.2020.106504
  • 22. Liu Y, Du X, Chen J, Jin Y, Peng L, Wang HHX, et al. Neutrophil-to-lymphocyte ratio as an independent risk factor for mortality in hospitalized patients with COVID-19. J Infect 2020;81(1): e6-e12. doi:10.1016/j.jinf.2020.04.002
  • 23. Qu R, Ling Y, Zhang YH, Wei LY, Chen X, Li XM, et al. Platelet-to-lymphocyte ratio is associated with prognosis in patients with coronavirus disease-19. J Med Virol 2020;92(9):1533-1541.
Toplam 21 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Klinik Tıp Bilimleri
Bölüm Araştırma Makalesi
Yazarlar

Ahmet Sen Sen Bu kişi benim 0000-0001-8981-6871

Cagatay Erman Ozturk Bu kişi benim 0000-0001-6959-1695

Sude Hatun Aktimur Bu kişi benim 0000-0002-7468-1721

Serhat Genc Bu kişi benim 0000-0003-2979-9920

Selim Gorgun Bu kişi benim 0000-0001-5841-591X

Yayımlanma Tarihi 31 Ağustos 2022
Yayımlandığı Sayı Yıl 2022 Cilt: 12 Sayı: 2

Kaynak Göster

APA Sen, A. S., Ozturk, C. E., Aktimur, S. H., Genc, S., vd. (2022). Intensive Care Prediction During Treatment Of Covid-19 Patients. Kafkas Journal of Medical Sciences, 12(2), 116-121.
AMA Sen AS, Ozturk CE, Aktimur SH, Genc S, Gorgun S. Intensive Care Prediction During Treatment Of Covid-19 Patients. Kafkas Journal of Medical Sciences. Ağustos 2022;12(2):116-121.
Chicago Sen, Ahmet Sen, Cagatay Erman Ozturk, Sude Hatun Aktimur, Serhat Genc, ve Selim Gorgun. “Intensive Care Prediction During Treatment Of Covid-19 Patients”. Kafkas Journal of Medical Sciences 12, sy. 2 (Ağustos 2022): 116-21.
EndNote Sen AS, Ozturk CE, Aktimur SH, Genc S, Gorgun S (01 Ağustos 2022) Intensive Care Prediction During Treatment Of Covid-19 Patients. Kafkas Journal of Medical Sciences 12 2 116–121.
IEEE A. S. Sen, C. E. Ozturk, S. H. Aktimur, S. Genc, ve S. Gorgun, “Intensive Care Prediction During Treatment Of Covid-19 Patients”, Kafkas Journal of Medical Sciences, c. 12, sy. 2, ss. 116–121, 2022.
ISNAD Sen, Ahmet Sen vd. “Intensive Care Prediction During Treatment Of Covid-19 Patients”. Kafkas Journal of Medical Sciences 12/2 (Ağustos 2022), 116-121.
JAMA Sen AS, Ozturk CE, Aktimur SH, Genc S, Gorgun S. Intensive Care Prediction During Treatment Of Covid-19 Patients. Kafkas Journal of Medical Sciences. 2022;12:116–121.
MLA Sen, Ahmet Sen vd. “Intensive Care Prediction During Treatment Of Covid-19 Patients”. Kafkas Journal of Medical Sciences, c. 12, sy. 2, 2022, ss. 116-21.
Vancouver Sen AS, Ozturk CE, Aktimur SH, Genc S, Gorgun S. Intensive Care Prediction During Treatment Of Covid-19 Patients. Kafkas Journal of Medical Sciences. 2022;12(2):116-21.