The prognostic value of prognostic nutritional index and renal function indicators for mortality prediction in severe COVID-19 elderly patients: A retrospective study

1Citations
Citations of this article
5Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Identifying prognostic factors in elderly patients with severe coronavirus disease 2019 (COVID-19) is crucial for clinical management. Recent evidence suggests malnutrition and renal dysfunction are associated with poor outcome. This study aimed to develop a prognostic model incorporating prognostic nutritional index (PNI), estimated glomerular filtration rate (eGFR), and other parameters to predict mortality risk. This retrospective analysis included 155 elderly patients with severe COVID-19. Clinical data and outcomes were collected. Logistic regression analyzed independent mortality predictors. A joint predictor "L" incorporating PNI, eGFR, D-dimer, and lactate dehydrogenase (LDH) was developed and internally validated using bootstrapping. Decreased PNI (OR = 1.103, 95% CI: 0.78-1.169), decreased eGFR (OR = 0.964, 95% CI: 0.937-0.992), elevated D-dimer (OR = 1.001, 95% CI: 1.000-1.004), and LDH (OR = 1.005, 95% CI: 1.001-1.008) were independent mortality risk factors (all P < .05). The joint predictor "L" showed good discrimination (area under the curve [AUC] = 0.863) and calibration. The bootstrapped area under the curve was 0.858, confirming model stability. A combination of PNI, eGFR, D-dimer, and LDH provides useful prognostic information to identify elderly patients with severe COVID-19 at highest mortality risk for early intervention. Further external validation is warranted.

Cite

CITATION STYLE

APA

Cao, A., Luo, W., Wang, L., Wang, J., Zhou, Y., Huang, C., & Zhu, B. (2024). The prognostic value of prognostic nutritional index and renal function indicators for mortality prediction in severe COVID-19 elderly patients: A retrospective study. Medicine (United States), 103(20), E38213. https://doi.org/10.1097/MD.0000000000038213

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free