The predictive value of prognostic nutritional index in patients with COVID-19

Authors

  • Naser N. Mohsin
  • Ekremah K. Shaker
  • Khalid S. Salih
  • Abdul Jabbar K. Ibrahim

DOI:

https://doi.org/10.51248/.v42i5.1932

Keywords:

PNI score, mortality, sensitivity, COVID-19

Abstract

Introduction and Aim: It is crucial to identify and start treating the COVID-19 patients who are most at risk of becoming seriously ill as soon as possible. There is some evidence that prognostic nutritional index (PNI) could predict the outcome of some diseases. The study objective was to determine whether PNI is a useful prognostic tool for predicting the outcome of COVID-19-positive patients.

 

Patients and Methods: At Al-Shifaa Hospital in Baghdad Medical City, a total of 160 patients with COVID-19 participated in a study that was designed as a cross-sectional. At the time of admission, information was collected on the patient's history, including clinical, laboratory, and demographic details. The PNI score was determined by 10 × serum albumin (g/dL) + 0.005 × total lymphocyte count (/mm3). Patients were followed up for survival.

 

Results: The mortality rate was 14.37%. Survived patients had a mean age of 55.85±16.03 years compared with 64.30 ±14.76 years for died patients with a significant difference. Diabetes was more common among died (39.13%) than survived patients (15.33%) with a significant difference. The median serum level of C-reactive protein (CRP), D-dimer and ferritin in deceased patients was 84 mg/L, 2208 ng/ml and 650 ng/ml, respectively compared with 48 mg/L, 858 ng/ml and 550 ng/ml in survived patients with highly significant differences. The mean PNI in survived and non-survived patients was 40.89±5.9 and 37.86±4.36, respectively with a significant difference. The area under the curve (AUC) for PNI was 0.888, 95%CI = 0.827 and 0.939, p = 0.002 At an ideal cutoff value of 39.08, the test's sensitivity and specificity are 80 % and 74 %, respectively.

 

Conclusion: The PNI score is an easy-to-use, speedy, and cost-effective tool that has the potential to be utilized on a routine basis to predict mortality in patients with COVID-19.

Author Biographies

Naser N. Mohsin

Laboratory Department, Medical City Campus, Ministry of Health, Baghdad, Iraq

Ekremah K. Shaker

Al-Rasheed University College, Baghdad, Iraq

Khalid S. Salih

Department of Physiology, College of Pharmacy, Tikrit University, Tikrit, Iraq

Abdul Jabbar K. Ibrahim

Al-Rasheed University College, Baghdad, Iraq

References

WHO Director-General’s Opening Remarks at the Media Briefing on COVID-19. 1 May 2020.allAfrica.com (English). https://www.who./ dg/speeches/detail/ who-director-general-s-opening-remarks-at-the-media-briefing-on-covid-19-11-march-2020.

Khodeir, M.M., Shabana, H.A., Alkhamiss, A.S., Rasheed, Z., Alsoghair, M., Alsagaby, S.A., et al., Early prediction keys for COVID-19 cases progression: A meta-analysis. J Infect Public Health. 2021;14(5):561-569. DOI: https://doi.org/10.1016/j.jiph.2021.03.001

Mehta, S. Nutritional status and COVID-19: an opportunity for lasting change? Clin Med (Lond) 2020;20(3):270-273. DOI: https://doi.org/10.7861/clinmed.2020-0187

Chandra, R. K., Nutrition and the immune system: An introduction. Am J Clin Nutr 1997; 66: 460S.3. DOI: https://doi.org/10.1093/ajcn/66.2.460S

Akbuga, K., Ferik, O.K., Yayla, K.G., Aslan, T., Eren, M., Karanfil, M., et al., Prognostic Nutritional Index as a New Prediction Tool for Coronary Collateral Development. Acta Cardiol Sin. 2022 Jan;38(1):21-26.

Chen, Q.J., Qu, H.J., Li, D.Z., Li, X.M., Zhu, J.J., Zieng, Y., et al., Prognostic nutritional index predicts clinical outcome in patients with acute ST-segment elevation myocardial infarction undergoing primary percutaneous coronary intervention. Sci Rep. 2017;7(1): 3285. DOI: https://doi.org/10.1038/s41598-017-03364-x

Pinato, D. J., North. P. V., Sharma, R. A novel, externally validated inflammation-based prognostic algorithm in hepatocellular carcinoma: the prognostic nutritional index (PNI). Bri J Cancer 2012;106(8):1439-1445. DOI: https://doi.org/10.1038/bjc.2012.92

Dong, X., Wang, B., Chen, S., Liu, J., Xia, Y., Wang, S., et al., Association between Prognostic Nutritional Index and Contrast-Associated Acute Kidney Injury in Patients Complicated with Chronic Kidney Disease and Coronary Artery Disease. J Interv Cardiol. 2021 Jul 5;2021: 2274430. DOI: https://doi.org/10.1155/2021/2274430

Borobia, A. M., Carcas, A. J., Arnalich, F., Alvarez-Sala, R., Monserrat-Villatoro, J., Quintana, M., et al., A cohort of patients with COVID-19 in a major teaching hospital in Europe. J Clin Med. 2020; 9:1733. DOI: https://doi.org/10.3390/jcm9061733

Souris, M., Gonzale, J. P. COVID-19: Spatial analysis of hospital case-fatality rate in France. PLoS ONE 2020;15(12): e0243606. DOI: https://doi.org/10.1371/journal.pone.0243606

Chen, Y., Zhao, M., Wu, Y., Zang, S. Epidemiological analysis of the early 38 fatalities in Hubei, China, of the coronavirus disease 2019. J Glob Health 2020;10(1):011004. DOI: https://doi.org/10.7189/jogh.10.011004

Docherty, A. B., Harrison, E. M., Green, C. A., Hardwick, H. E., Pius, R., Norman, L., et al: Features of 20 133 UK patients in hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: prospective observational cohort study. BMJ 2020;369:m1985. DOI: https://doi.org/10.1136/bmj.m1985

Wasityastuti, W., Dhamarjati, A.S.S. Immunosenescence and the susceptibility of the elderly to coronavirus disease 2019 (COVID-19). Expert Opin Ther Targets. 2020; 40:199-202. DOI: https://doi.org/10.36497/jri.v40i3.115

Qin, C., Zhou, L., Hu, Z., Zhang, S., Yang, S., Tao. Y., et al. Dysregulation of immune response in patients with COVID-19 in Wuhan, China. Clin Infect Dis. 2020; 71:762-768. DOI: https://doi.org/10.1093/cid/ciaa248

Guan, W. J., Liang, W. H., Zhao, Y., Liang, H. R., Chen, Z. S., Li, Y. M., et al. Comorbidity and its impact on 1,590 patients with Covid-19 in China: a nationwide analysis. Eur Respir J. 2020;55. DOI: https://doi.org/10.1183/13993003.01227-2020

Ssentongo, P., Ssentongo, A. E., Heilbrunn, E. S., Ba, D. M., Chinchilli, V. M. Association of cardiovascular disease and 10 other pre-existing comorbidities with COVID-19 mortality: A systematic review and meta-analysis. PLoS One 2020;26;15(8): e0238215. DOI: https://doi.org/10.1371/journal.pone.0238215

Dahan, S., Segal, G., Katz, I., Hellou, T., Tietel, M., Bryk, G., et al. Ferritin as markers of severity of COVID-19 patients: a fatal correlation. JAMJ 2020;22: 494-500.

Kernan, K. F., Carcillo, J. A. Hyperferritinemia and inflammation. Int Immunol. 2017;29(9):401-409. DOI: https://doi.org/10.1093/intimm/dxx031

Rostami, M., Mansouritorghabeh, H. D-dimer level in COVID-19 infection: a systematic review. Expert Rev Hematol. 2020; 13: 1265-1275. DOI: https://doi.org/10.1080/17474086.2020.1831383

Gungor, B., Atici, A., Baycan, O. F., Alici, G., Ozturk, F., Tugrul, S., et al., Elevated D-dimer levels on admission are associated with severity and increased risk of mortality in COVID-19: A systematic review and meta-analysis. Am J Emerg Med. 2021; 39: 173-179. DOI: https://doi.org/10.1016/j.ajem.2020.09.018

Bansal, A., Singh, A. D., Jain, V., Aggarwal, M., Gupta, S., Padappayil, R. P., et al., The association of D-dimers with mortality, intensive care unit admission or acute respiratory distress syndrome in patients hospitalized with coronavirus disease 2019 (COVID-19): A systematic review and meta-analysis. Heart Lung. 2021; 50: 9-12. DOI: https://doi.org/10.1016/j.hrtlng.2020.08.024

Cinar, T., Hayiroglu, M.I., Cicek, V., Kiliç, S., Asal, S., Yavuz, S., et al., Is prognostic nutritional index a predictive marker for estimating all-cause in-hospital mortality in COVID-19 patients with cardiovascular risk factors? Heart Lung. 2021 Mar-Apr;50(2):307-312. DOI: https://doi.org/10.1016/j.hrtlng.2021.01.006

Wei, W., Wu, X., Jin, C., Mu, T., Gu, G., Min, M., et al. Predictive Significance of the Prognostic Nutritional Index (PNI) in Patients with Severe COVID-19. J Immunol Res. 2021 Jul 9; 2021: 9917302. DOI: https://doi.org/10.1155/2021/9917302

Hu, X., Deng, H., Wang, Y., Chen, L., Gu, X., Wang, X. Predictive value of the prognostic nutritional index for the severity of coronavirus disease 2019. Nutrition. 2021 Apr; 84:111123. DOI: https://doi.org/10.1016/j.nut.2020.111123

Wang, Z., Yang, B., Li, Q., Wen, L., Zhang, R. Clinical features of 69 cases with coronavirus disease 2019 in Wuhan, China. Clin Infect Dis. 2020; 71:769-777. DOI: https://doi.org/10.1093/cid/ciaa272

Soeters, P. B., Wolfe, R. R., Shenkin, A. Hypoalbuminemia: pathogenesis and clinical significance. J Parenter Enteral Nutr. 2019; 43:181-193. DOI: https://doi.org/10.1002/jpen.1451

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Published

2022-11-14

How to Cite

1.
N. Mohsin N, K. Shaker E, S. Salih K, Jabbar K. Ibrahim A. The predictive value of prognostic nutritional index in patients with COVID-19. Biomedicine [Internet]. 2022 Nov. 14 [cited 2022 Nov. 27];42(5):992-8. Available from: https://biomedicineonline.org/home/article/view/1932

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