The role of prognostic nutritional index in patients with non-ST segment elevation acute coronary syndrome

The Combination Effect of the Red Blood Cell Distribution Width and Prognostic Nutrition Index on the Prognosis in Patients Undergoing PCI

BACKGROUND

Inflammation and malnutrition are related to adverse clinical outcomes in patients with coronary artery disease (CAD). However, it is unclear whether there is a relationship between the PNI (prognostic nutritional index) and RDW (red blood cell distribution width) regarding the impact on the prognosis in patients with CAD undergoing percutaneous coronary intervention (PCI).

METHODS

A total of 5605 consecutive CAD patients undergoing PCI were selected retrospectively. The patients were stratified into four groups according to the PNI [high PNI (H-PNI) and low PNI (L-PNI)] and RDW [high RDW (H-RDW) and low RDW (L-RDW)]. The cutoff values of RDW and PNI were calculated using receiver-operating characteristic curve analysis. The primary endpoint was 1-year all-cause mortality (ACM). The secondary endpoint was major adverse cardiac cerebrovascular events (MACCEs), the composite of cardiac death (CD), the recurrence of MI, target lesion revascularization (TLR), and stroke. A Cox proportional hazards model was used to evaluate the association between the PNI, RDW, and clinical endpoints.

RESULTS

During 1-year follow-up, 235 (4.19%) patients died. In multivariate regression analysis, the L-PNI/H-RDW group was found to have the highest risk of 1-year ACM [hazard ratio (HR) = 8.85, 95% confidence interval (CI): 5.96-13.15, p = 0.020] with the H-PNI/L-RDW group as a reference, followed by the L-PNI/L-RDW (HR = 3.96, 95% CI: 2.60-6.00, p < 0.001) and H-RDW/H-PNI groups (HR = 3.00, 95% CI: 1.99-4.50, p < 0.001). Nomograms were developed to predict the probability of 1-year ACM and MACCEs.

CONCLUSIONS

CAD patients with L-PNI and H-RDW experienced the worst prognosis. The combination of PNI and RDW was a strong predictor of 1-year ACM. The coexistence of PNI and RDW appears to have a synergistic effect, providing further information for the risk stratification of CAD patients.

A new parameter in predicting contrast-induced nephropathy: Osaka prognostic score

OBJECTIVE

Nowadays, the frequency of complications is also increasing following the increasing frequency of coronary angiography and percutaneous coronary intervention. Contrast-induced nephropathy is one of the most common of these complications. This study aimed to investigate the relationship between the Osaka prognostic score, which has previously been shown to have prognostic importance in gastrointestinal malignancies, and the development of contrast-induced nephropathy.

METHODS

The study retrospectively examined the data of 1,498 patients who underwent coronary angiography and percutaneous coronary intervention due to acute coronary syndrome between 2018 and 2023. Demographic characteristics and laboratory findings were retrospectively collected from patients' charts and electronic medical records.

RESULTS

Osaka prognostic score (0.84±0.25 vs. 2.2±0.32, p<0.001) was higher in patients who developed contrast-induced nephropathy. Also, Osaka prognostic score [OR 2.161 95%CI (1.101-4.241), p<0.001] was found to be an independent risk factor along with age, diabetes mellitus, systolic pulmonary artery pressure, hemoglobin, hemoglobin, C-reactive protein, albumin, N-terminal brain natriuretic peptide, and systemic immune-inflammation index. The receiver operating characteristic curve showed that the optimal cutoff value of Osaka prognostic score to predict the development of contrast-induced nephropathy was 1.5, with a sensitivity of 83.4 and a specificity of 65.9% [area under the curve: 0.874 (95%CI: 0.850-0.897, p≤0.001)].

CONCLUSION

Osaka prognostic score may be an easily calculable, user-friendly, and useful parameter to predict the development of contrast-induced nephropathy in patients undergoing percutaneous coronary intervention after acute coronary syndromes.

Prognostic Nutritional Index is Associated with the Degree of Coronary Collateral Circulation in Stable Angina Patients with Chronic Total Occlusion

BACKGROUND

Coronary collateral circulation (CCC) can effectively improve myocardial blood supply to the area of CTO (chronic total coronary occlusion) and can, thus, improve the prognosis of patients with stable coronary syndrome (SCS). The degree of inflammation and some inflammation markers were associated with the development of collaterals.

OBJECTIVE

To investigate whether prognostic nutritional index (PNI) has an association with the development of CCC in patients with SCS.

METHODS

A total of 400 SCS patients with the presence of CTO in at least one major epicardial coronary artery were included in this study. The patients were divided into two groups according to the Rentrop score. Scores of 0 to 1 were considered poor developed CCC, and scores of 2 to 3 were accepted as good developed CCC. Statistical significance was set as a p-value < 0.05 for all analyses.

RESULTS

The mean age of the study cohort was 63±10 years; 273 (68.3%) were males. The poor-developed CCC group had a significantly lower PNI level compared with the good-developed CCC group (38.29±5.58 vs 41.23±3.85, p< 0.001). In the multivariate analysis, the PNI (odds ratio 0.870; 95% confidence interval 0.822-0.922; p< 0.001) was an independent predictor of poorly developed CCC.

CONCLUSION

The PNI can be used as one of the independent predictors of CCC formation. It was positively associated with the development of coronary collaterals in SCS patients with CTO.

Prognostic value of Geriatric Nutritional Risk Index and systemic immune-inflammatory index in elderly patients with acute coronary syndromes

The objective of this study was to evaluate the predictive value of the Geriatric Nutritional Risk Index (GNRI) combined with the Systemic Immunoinflammatory Index (SII) for the risk of major adverse cardiovascular events (MACE) following percutaneous coronary intervention in elderly patients with acute coronary syndrome (ACS). We retrospectively reviewed the medical records of 1202 elderly patients with acute coronary syndromes divided into MACE and non-MACE groups according to whether they had a MACE. The sensitivity analysis utilized advanced machine learning algorithms to preliminarily identify the critical role of GNRI versus SII in predicting MACE risk. We conducted a detailed analysis using a restricted cubic spline approach to investigate the nonlinear relationship between GNRI, SII, and MACE risk further. We constructed a clinical prediction model based on three key factors: GNRI, SII, and Age. To validate the accuracy and usefulness of this model, we compared it to the widely used GRACE score using subject work and recall curves. Additionally, we compared the predictive value of models and GRACE scores in assessing the risk of MACE using the Integrated Discriminant Improvement Index (IDI) and the Net Reclassification Index (NRI). This study included 827 patients. The GNRI scores were lower in the MACE group than in the non-MACE group, while the SII scores were higher in the MACE group (P < 0.001). The multifactorial analysis revealed a low GNRI (OR = 2.863, 95% CI: 2.026-4.047, P = 0.001), High SII (OR = 3.102, 95% CI: 2.213-4.348, P = 0.001). The area under the curve (AUC) for the predictive model was 0.778 (95% CI: 0.744-0.813, P = 0.001), while the AUC for the GRACE score was 0.744 (95% CI: 0.708-0.779, P = 0.001). NRI was calculated to be 0.5569, with NRI + at 0.1860 and NRI- at 0.3708. The IDI was found to be 0.0571, with a P-value of less than 0.001. These results suggest that the newly developed prediction model is more suitable for use with the population in this study than the GRACE score. The model constructed using GNRI and SII demonstrated good standardization and clinical impact, as evidenced by the standard, DCA, and clinical impact curves. The study shows that combining GNRI and SII can be a simple, cost-effective, and valuable way to predict the risk of MACE within one year in elderly acute coronary syndromes.

Prognostic nutritional index and prognosis of patients with coronary artery disease: A systematic review and meta-analysis

Background

This review assessed if prognostic nutritional index (PNI) can predict mortality and major adverse cardiac events (MACE) in coronary artery disease (CAD) patients.

Methods

PubMed, Web of Science, Scopus, and Embase were searched up to 1st November 2022 for all types of studies reporting adjusted associations between PNI and mortality or MACE in CAD patients. A random-effect meta-analysis was conducted for PNI as categorical or continuous variable. Subgroup analysis were conducted for multiple confounders.

Results

Fifteen studies with 22,521 patients were included. Meta-analysis found that low PNI was a significant predictor of mortality in CAD patients as compared to those with high PNI (HR: 1.67 95% CI: 1.39, 2.00 I2 = 95% p &lt; 0.00001). Increasing PNI scores were also associated with lower mortality (HR: 0.94 95% CI: 0.91, 0.97 I2 = 89% p = 0.0003). Meta-analysis demonstrated that patients with low PNI had significantly higher incidence of MACE (HR: 1.57 95% CI: 1.08, 2.28 I2 = 94% p = 0.02) and increasing PNI was associated with lower incidence of MACE (HR: 0.84 95% CI: 0.72, 0.92 I2 = 97% p = 0.0007). Subgroup analyses showed mixed results.

Conclusion

Malnutrition assessed by PNI can independently predict mortality and MACE in CAD patients. Variable PNI cut-offs and high inter-study heterogeneity are major limitations while interpreting the results. Further research focusing on specific groups of CAD and taking into account different cut-offs of PNI are needed to provide better evidence.

Systematic Review Registration

No CRD42022365913 https://www.crd.york.ac.uk/prospero/.

Relationship Between Prognostic Nutritional Index and Contrast-Associated Acute Kidney Injury in Patients With Non-ST Segment Elevation Myocardial Infarction Undergoing Coronary Angiography

Prognostic nutritional index (PNI), consisting of inflammatory-nutritional parameters, has been investigated in terms of outcomes and renal function in patients with coronary artery disease. The objective of this study is to assess the predictive power of the PNI in predicting the risk for developing contrast-associated acute kidney injury (CA-AKI), an important complication following coronary angiography in patients with non-ST-elevation myocardial infarction (NSTEMI). The study population (336 patients with the diagnosis of NSTEMI) was divided into two groups: patients with CA-AKI and patients without CA-AKI. The mean age of the whole population was 62.0 ± 12.7 (21-95) years. CA-AKI was detected in 68 (20%) patients. Prognostic nutritional index values were significantly (P < .001) lower in the CA-AKI (+) group. Low PNI values (cutoff < 48.5%) were independent predictors of CA-AKI with Odds ratio (OR): .913, 95% confidence interval (CI): .866-.962, P:.001, with a sensitivity 70.6% and specificity 69.4%. Prognostic nutritional index seems to be an easily assessable and promising scoring system that can be used in clinical practice for predicting the risk of developing CA-AKI.