COVID-19 enfeksiyonunda yoğun bakımda BNP'nin prognostik bir biyobelirteç olarak yeniden tanımlanması

Yıl 2022, , 116 - 127, 31.08.2022

Özge Turgay Yıldırım , Ayşe Ayyıldız , Selim Yıldırım

https://doi.org/10.36516/jocass.1123404

Öz

Amaç
Coronavirus hastalığı 2019 (COVID-19), küresel bir pandemiye neden olmuş ve artan ölüm oranları, araştırmacıları daha yüksek ölüm riski altındaki hastaları belirlemek için prognostik faktörleri araştırmaya zorlamıştır.Biz bu çalışmada, yoğun bakım ünitesinde yatan kritik hastalarda, beyin natriüretik peptidinin (BNP) mortalitenin bir belirleyicisi olarak kullanılabilirliğini araştırmayı amaçladık.
Materyal ve Metod
Bu retrospektif çalışmaya COVID-19 tanısı konan ve yoğun bakım ünitesinde takip edilen 50 hasta dahil edilmiştir. Bilinen kalp yetmezliği olan ve takiplerinde ekokardiyografide kalp yetmezliği saptanan hastalar çalışma dışı bırakılmıştır.
Bulgular
Hastalar yoğun bakım ünitesinde yatışları sırasındaki mortalite durumlarına göre iki gruba ayrıldı. Bu gruplar kronik hastalık, cinsiyet ve yaş açısından istatistiksel olarak benzerdi (p>0.05). Mortalite ile seyreden grup, hayatta kalan grupla karşılaştırıldığında yoğun bakım ünitesine kabulde daha yüksek BNP seviyelerine sahipti (mortalite ile seyreden grup 93,2 pg/mL (43,5-357,3) ve hayatta kalan grup 62,9 (25,0-147,1), p=0.004). Regresyon analizi, daha yüksek BNP düzeylerinin ve daha düşük lenfosit sayılarının bu hastalarda mortalitenin bir göstergesi olarak kullanılabileceğini ortaya koydu. ROC eğrisi analizi, BNP için hastane içi ölümü öngörmede en iyi eşik değerinin %73,1 duyarlılık ve %70,8 özgüllük ile 85,6 pg/mL olduğunu gösterdi.
Sonuç
Yoğun bakım ünitesinde takip edilen COVID-19 hastalarında yoğun bakıma kabuldeki yüksek BNP seviyeleri hastane içi mortalite göstergesi olarak kullanılabilir.

Anahtar Kelimeler

Beyin natriüretik peptidi, COVID-19, prognoz, mortalite, yoğun bakım

Redefinition of BNP as a prognostic biomarker in intensive care at COVID-19 infection

Öz

Aim
Coronavirus disease 2019 (COVID-19) has caused a global pandemic and increased mortality has forced researchers to identify prognostic factors to identify patients at higher risk of mortality. In this study, we aimed to investigate the usability of Brain natriuretic peptide (BNP) as a predictor of mortality in critically ill patients hospitalized in the intensive care unit.
Material and Method
This retrospective study included 50 patients diagnosed with COVID-19 and followed in the intensive care unit. Patients with known heart failure who were found to have heart failure on echocardiography during follow-up were excluded from the study.
Results
The patients were divided into two groups based on their mortality status during hospitalization in the intensive care unit. These groups were found to be statistically similar in terms of chronic disease, gender and age (p>0.05). Non-survivor group had higher levels of BNP at the admission to intensive care unit when compared to survivor group (93.2 pg/mL (43.5-357.3) vs. 62.9 (25.0-147.1), p=0.004, respectively). Regression analysis revealed that higher BNP levels and lower lymphocyte counts can be used as a predictor of mortality for these patients. ROC curve analysis indicated that best cut-off value for predicting in-hospital death for BNP was 85.6 pg/mL with a sensitivity of 73.1% and a specificity of 70.8%.
Conclusions
High BNP levels at admission to the intensive care unit can be used as an in-hospital mortality indicator in COVID-19 patients followed up in the intensive care unit.

Anahtar Kelimeler

Brain natriuretic peptide, COVID-19, prognosis, mortality, intensive care

Kaynakça

• 1. WHO Western Pacific | World Health Organization. Accessed May 9, 2021. https://www.who.int/westernpacific/emergencies/covid-19
• 2. Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. The Lancet. 2020;395(10223):497-506. doi:10.1016/S0140-6736(20)30183-5
• 3. Ñamendys-Silva SA, Alvarado-Ávila PE, Domínguez-Cherit G, et al. Outcomes of patients with COVID-19 in the intensive care unit in Mexico: A multicenter observational study. Heart & Lung. 2021;50(1):28-32. doi:10.1016/j.hrtlng.2020.10.013
• 4. Ghasemiyeh P, Mohammadi-Samani S. COVID-19 outbreak: Challenges in pharmacotherapy based on pharmacokinetic and pharmacodynamic aspects of drug therapy in patients with moderate to severe infection. Heart & Lung: The Journal of Cardiopulmonary and Acute Care. 2020;49(6):763-773. doi:10.1016/j.hrtlng.2020.08.025
• 5. Esme H, Kucukosmanoglu I. Ampiyemin eşlik ettiği COVID-19 olgusunda akciğerin histopatolojik bulguları. Çukurova Anestezi ve Cerrahi Bilimler Dergisi. 2022; 3(3):170-176.
• 6. Zuin M, Rigatelli G, Bilato C, Zuliani G, Roncon L. Heart failure as a complication of COVID-19 infection: systematic review and meta-analysis. Acta Cardiologica. 2021;0(0):1-7. doi:10.1080/00015385.2021.1890925
• 7. Uslu PU. Pandemi ve İnsomni. Eskisehir Medical Journal. 2020;1(1):5-9. doi:10.48176/esmj.2020.2
• 8. Yildirim ÖT, Turgay A, Tunay DL. COVID-19 Pandemisi ve Kardiyovasküler Etkileri. Çukurova Anestezi ve Cerrahi Bilimler Dergisi. 2020;3(3):128-133.
• 9. Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. The Lancet. 2020;395(10223):507-513. doi:10.1016/S0140-6736(20)30211-7
• 10. Omar T, Karakayalı M, Perincek G. Assessment of COVID-19 deaths from cardiological perspective. Acta Cardiologica. 2021;0(0):1-8. doi:10.1080/00015385.2021.1903704
• 11. Duyan M, Kıldan RNO. EVALUATION OF MORTALITY RISK WITH CURB-65 AND PSI IN PATIENTS WITH AND WITHOUT GERIATRIC COVID-19 PNEUMONIA. 2022; 5 (1):8-22.
• 12. Yildirim ÖT. COVID-19 Pandemisi, Anjiyotensin dönüştürücü enzim (ACE) inhibitörleri ve Anjiyotensin Resepör Blokörlerinin (ARB) kullanımı. Çukurova Anestezi ve Cerrahi Bilimler Dergisi. 2020;3(1):47-52.
• 13. Kinnunen P, Vuolteenaho O, Ruskoaho H. Mechanisms of atrial and brain natriuretic peptide release from rat ventricular myocardium: effect of stretching. Endocrinology. 1993;132(5):1961-1970. doi:10.1210/endo.132.5.8477647
• 14. Salah K, Stienen S, Pinto YM, et al. Prognosis and NT-proBNP in heart failure patients with preserved versus reduced ejection fraction. Heart. 2019;105(15):1182-1189. doi:10.1136/heartjnl-2018-314173
• 15. Bay M, Kirk V, Parner J, et al. NT-proBNP: a new diagnostic screening tool to differentiate between patients with normal and reduced left ventricular systolic function. Heart. 2003;89(2):150-154. doi:10.1136/heart.89.2.150
• 16. Pranata R, Huang I, Lukito AA, Raharjo SB. Elevated N-terminal pro-brain natriuretic peptide is associated with increased mortality in patients with COVID-19: systematic review and meta-analysis. Postgrad Med J. 2020;96(1137):387-391. doi:10.1136/postgradmedj-2020-137884
• 17. Chen T, Wu D, Chen H, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. BMJ. Published online March 26, 2020:m1091. doi:10.1136/bmj.m1091
• 18. Li P, Wu W, Zhang T, et al. Implications of cardiac markers in risk-stratification and management for COVID-19 patients. Crit Care. 2021;25(1):158. doi:10.1186/s13054-021-03555-z
• 19. Samuels, Witmer & Schaffner, Statistics for the Life Sciences, Global Edition, 5th Edition | Pearson. Accessed May 18, 2021. https://www.pearson.com/uk/educators/higher-education-educators/program/Samuels-Statistics-for-the-Life-Sciences-Global-Edition-5th-Edition/PGM1097920.html
• 20. Lawal B. Applied Statistical Methods in Agriculture, Health and Life Sciences. Springer International Publishing; 2014. doi:10.1007/978-3-319-05555-8
• 21. Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. 2nd ed. Springer-Verlag; 2012. doi:10.1007/978-1-4614-1353-0
• 22. Kleinbaum DG, Klein M. Logistic Regression: A Self-Learning Text. 3rd ed. Springer-Verlag; 2010. doi:10.1007/978-1-4419-1742-3
• 23. Szumilas M. Explaining Odds Ratios. J Can Acad Child Adolesc Psychiatry. 2010;19(3):227-229.
• 24. Fawcett T. An introduction to ROC analysis. Pattern Recognition Letters. 2006;27(8):861-874. doi:10.1016/j.patrec.2005.10.010
• 25. Perkins NJ, Schisterman EF. The inconsistency of “optimal” cutpoints obtained using two criteria based on the receiver operating characteristic curve. Am J Epidemiol. 2006;163(7):670-675. doi:10.1093/aje/kwj063
• 26. Schwartz RA, Kapila R. Pandemics throughout the centuries. Clinics in Dermatology. 2021;39(1):5-8. doi:10.1016/j.clindermatol.2020.12.006
• 27. Almeida Junior GLG de, Braga F, Jorge JK, et al. Prognostic Value of Troponin-T and B-Type Natriuretic Peptide in Patients Hospitalized for COVID-19. Arq Bras Cardiol. 2020;115(4):660-666. doi:10.36660/abc.20200385
• 28. Usuda D, Sangen R, Hashimoto Y, Muranaka E, Iinuma Y, Kanda T. Validation of a B-type natriuretic peptide as a prognostic marker in pneumonia patients: a prospective cohort study. BMJ Open. 2016;6(2):e010440. doi:10.1136/bmjopen-2015-010440
• 29. Turgay Yıldırım Ö, Kaya Ş. The atherogenic index of plasma as a predictor of mortality in patients with COVID-19. Heart & Lung. 2021;50(2):329-333. doi:10.1016/j.hrtlng.2021.01.016
• 30. Papageorgiou N, Sohrabi C, Merino DP, et al. High sensitivity troponin and COVID-19 outcomes. Acta Cardiologica. 2021;0(0):1-8. doi:10.1080/00015385.2021.1887586
• 31. Aladağ N, Atabey RD. The role of concomitant cardiovascular diseases and cardiac biomarkers for predicting mortality in critical COVID-19 patients. Acta Cardiologica. 2021;76(2):132-139. doi:10.1080/00015385.2020.1810914
• 32. Wang D, Hu B, Hu C, et al. Clinical Characteristics of 138 Hospitalized Patients With 2019 Novel Coronavirus-Infected Pneumonia in Wuhan, China. JAMA. 2020;323(11):1061-1069. doi:10.1001/jama.2020.1585
• 33. Tang N, Li D, Wang X, Sun Z. Abnormal coagulation parameters are associated with poor prognosis in patients with novel coronavirus pneumonia. J Thromb Haemost. 2020;18(4):844-847. doi:10.1111/jth.14768
• 34. Wu C, Chen X, Cai Y, et al. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA Internal Medicine. 2020;180(7):934-943. doi:10.1001/jamainternmed.2020.0994
• 35. Andreini D, Conte E, Mushtaq S, et al. Extent of lung involvement over severity of cardiac disease for the prediction of adverse outcome in COVID-19 patients with cardiovascular disease. Int J Cardiol. 2021;323:292-294. doi:10.1016/j.ijcard.2020.10.006
• 36. Jobs A, Simon R, de Waha S, et al. Pneumonia and inflammation in acute decompensated heart failure: a registry-based analysis of 1939 patients. Eur Heart J Acute Cardiovasc Care. 2018;7(4):362-370. doi:10.1177/2048872617700874
• 37. Li J, Ye H, Zhao L. B-type natriuretic peptide in predicting the severity of community-acquired pneumonia. World J Emerg Med. 2015;6(2):131-136. doi:10.5847/wjem.j.1920-8642.2015.02.008
• 38. Falcone M, Corrao S, Venditti M, Serra P, Licata G. Performance of PSI, CURB-65, and SCAP scores in predicting the outcome of patients with community-acquired and healthcare-associated pneumonia. Intern Emerg Med. 2011;6(5):431-436. doi:10.1007/s11739-011-0521-y
• 39. Post F, Weilemann LS, Messow CM, Sinning C, Münzel T. B-type natriuretic peptide as a marker for sepsis-induced myocardial depression in intensive care patients. Crit Care Med. 2008;36(11):3030-3037. doi:10.1097/CCM.0b013e31818b9153
• 40. Yap LB, Mukerjee D, Timms PM, Ashrafian H, Coghlan JG. Natriuretic peptides, respiratory disease, and the right heart. Chest. 2004;126(4):1330-1336. doi:10.1378/chest.126.4.1330
• 41. Ceriani E, Marceca A, Lanfranchi A, et al. Early echocardiographic findings in patients hospitalized for COVID-19 pneumonia: a prospective, single center study. Intern Emerg Med. Published online May 21, 2021. doi:10.1007/s11739-021-02733-9
• 42. Mishra A, Lal A, Sahu KK, George AA, Martin K, Sargent J. An Update on Pulmonary Hypertension in Coronavirus Disease-19 (COVID-19). Acta Biomed. 2020;91(4):e2020155. doi:10.23750/abm.v91i4.10698