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Updated: Sep 13, 2025

Cutoff Value of Phase Angle by Bioelectrical Impedance Analysis at Admission as a Prognostic Factor in Patients with Acute Heart Failure
Published on: June 10, 2025
Association between geriatric nutritional risk index and In-Hospital mortality in acute aortic dissection patients: a
Lingyu Lin1,2, Sailan Li1,2, Yanchun Peng3
1Department of Cardiovascular Surgery, Fujian Medical University Union Hospital, Fuzhou, 350001, Fujian Province, China.
Background:
The impact of the geriatric nutritional risk index (GNRI) on the prognosis of patients with acute Stanford type A aortic dissection (AAAD) remains unclear. This study sought to explore the predictive value of GNRI for in-hospital mortality in patients with AAAD.
Methods:
We conducted a retrospective analysis of patients who underwent surgery for AAAD from January 2014 to December 2022. Based on the median GNRI score, patients were stratified into high GNRI (> 103.7) and low GNRI (≤ 103.7) groups. Multivariate logistic regression analysis was used to assess the association between GNRI and in-hospital mortality.
Results:
A total of 936 patients were included, with a mean age of 52.7 ± 11.6 years. The mean GNRI was 103.8 ± 11.3, and patients were stratified into low GNRI (n = 472, 50.4%) and high GNRI (n = 464, 49.6%) groups. The low GNRI group had a significantly higher in-hospital mortality rate than the high GNRI group (23.1% vs. 17.5%, P = 0.032). Multivariate logistic regression identified GNRI ≤ 103.7 as an independent risk factor for in-hospital mortality (OR = 2.037, 95%CI:1.110-3.740, P = 0.022). CPB time (OR = 1.005, 95%CI: 1.001-1.009, P = 0.022), and lactate levels (OR = 1.221, 95%CI: 1.144-1.302, P < 0.001) were also independent risk factors for in-hospital mortality. The AUC of the logistic model was 0.811.
Conclusion:
The GNRI is a validated nutritional assessment tool, and AAAD patients with a GNRI ≤ 103.7 havesignificantly higher in-hospital mortality rate. These findings highlight the importance of preoperative nutritional assessment and optimization to improve outcomes for AAAD patients.
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