# Association of Prognostic Nutritional Index and New-Onset Atrial Fibrillation in Patients Undergoing Surgical Aortic Valve Replacement: A Silent Predictor in Perioperative Outcomes?

## TL;DR

This study shows that a nutritional score called PNI can predict new-onset atrial fibrillation after heart surgery, especially in younger patients.

## Contribution

The study identifies PNI as a novel independent predictor of postoperative atrial fibrillation in surgical aortic valve replacement patients.

## Key findings

- PNI was independently associated with new-onset atrial fibrillation in both univariate and multivariate analyses.
- Patients in the lowest PNI tertile had a significantly higher risk of developing atrial fibrillation.
- PNI remained a strong predictor in patients under 70 years old, where age lost significance.

## Abstract

Background: New-onset postoperative atrial fibrillation (NOAF) is the most prevalent arrythmia after cardiac surgery with a significant clinical and economic impact. Therefore, simple and practical biomarkers for NOAF prediction remain a clinical priority. Increasing evidence indicates that malnutrition is linked to postoperative complications, including the onset of atrial fibrillation. The Prognostic Nutritional Index (PNI), which reflects the immunonutritional and inflammatory status through serum albumin concentration and lymphocyte count, has emerged as a reliable prognostic indicator in cardiovascular disease. The present study aimed to investigate the association between PNI and the development of NOAF in patients undergoing surgical aortic valve replacement (SAVR). Methods: A total of 241 consecutive patients who underwent AVR for severe aortic stenosis or regurgitation were enrolled in this study. The population was stratified into two groups according to the development of NOAF (NOAF group) or the lack thereof (no NOAF group). Results: In both univariate and multivariate logistic regression analyses adjusted for several established NOAF determinants, age and PNI, both as continuous variables, were independently associated with NOAF in both univariate (OR = 1.03; CI 95% = 1.01–1.06, p = 0.009, and OR = 0.9; CI 95% = 0.8–0.9, p = 0.01, respectively) and multivariate models (OR = 1.02; CI 95% = 1.01–1.06, p = 0.05, and OR = 0.9; CI 95% = 0.8–0.9, p = 0.03, respectively). When PNI was analyzed by tertiles, patients in the lowest tertile (PNI < 41.5) showed a significantly higher risk of developing NOAF at both univariate (OR = 1.9; CI 95% = 1.2–2.8, p = 0.004) and multivariate analysis (OR = 1.6; CI 95% = 1–2.6, p = 0.03), whereas age lost statistical significance (OR = 1.0; 95% CI = 0.9–1.05; p = 0.06). Furthermore, when the study population was divided into two groups based on the median age (70 years), PNI values differed significantly between NOAF and no NOAF patients only in patients under 70 years (p = 0.01). In this younger subgroup, PNI remained an independent predictor of NOAF, both when considered as a continuous variable (OR = 0.86; CI 95% = 0.74–0.98, p = 0.02), and nominal variable (PNI < 41.5, OR = 0.88; CI 95% = 0.80–0.97, p = 0.01). Conclusions: Overall, these findings identify PNI as an independent predictor of NOAF following SAVR, particularly in patients younger than 70 years. This study underlines the potential clinical value of preoperative nutritional assessment for risk stratification. Incorporating nutritional parameters such as PNI into current predictive models may enhance the accuracy of prognostic evaluation and support targeted perioperative management strategies.