In:
Medicine, Ovid Technologies (Wolters Kluwer Health), Vol. 103, No. 20 ( 2024-05-17), p. e38213-
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.
Type of Medium:
Online Resource
ISSN:
0025-7974
,
1536-5964
DOI:
10.1097/MD.0000000000038213
Language:
English
Publisher:
Ovid Technologies (Wolters Kluwer Health)
Publication Date:
2024
detail.hit.zdb_id:
2049818-4
Permalink