Comparison of Systemic Immune-Inflammation Index and Naples Prognostic Score for Prediction Coronary Artery Severity Patients Undergoing Coronary Computed Tomographic Angiography

The impact of the Naples Prognostic Score on the short- and long-term prognosis of patients undergoing transcatheter aortic valve implantation

BACKGROUND

Preoperative systemic inflammation and nutritional status have been shown to affect prognosis in patients undergoing transcatheter aortic valve implantation (TAVI). In this study, we investigated the effect of the Naples Prognostic Score (NPS), which consists of four different parameters including these two components on short- and long-term prognosis in patients undergoing TAVI.

METHODS

In 343 patients (mean age 78.1 ± 8.4 years, 51.3% female) who underwent TAVI, the NPS score was calculated from the blood tests obtained before the procedure and the study population was divided into three according to the NPS value: those with 0 and 1 were divided into Group-1, those with 2 into Group-2, and those with 3 and 4 into Group-3. The relationship between NPS group and in-hospital adverse events and long-term survival was evaluated.

RESULTS

Systolic pulmonary artery pressure, STS score, presence of chronic lung disease and being in NPS Group-3 [adjusted odds ratio (adjOR): 3.93, 95% confidence interval (CI) (1.02-15.17), P  = 0.047] were found to be independent predictors of in-hospital mortality. According to the multivariate Cox-regression model, both Group-2 NPS [adjusted hazard ratio (adjHR): 4.81, 95% CI (1.09-21.14), P  = 0.037] and Group-3 NPS [adjHR: 10.1, 95% CI (2.31-43.36), P  = 0.002] was an independent predictor of 2-year all-cause mortality after TAVI. There was no significant difference in perioperative adverse events between the groups except for postprocedural acute kidney injury. According to receiver-operating characteristic analysis, the optimal predictive value of NPS for in-hospital and long-term mortality was 2.5.

CONCLUSION

In patients who will be candidates for TAVI, NPS is a simple and effective tool for determining both short- and long-term prognosis.

Predicting coronary artery severity in patients undergoing coronary computed tomographic angiography: Insights from pan-immune inflammation value and atherogenic index of plasma

BACKGROUND AND AIMS

Coronary computed tomographic angiography (CCTA) is pivotal in diagnosing coronary artery disease (CAD). We explored the link between CAD severity and two biomarkers, Pan-Immune Inflammation Value (PIV) and Atherogenic Index of Plasma (AIP), in stable CAD patients.

METHODS AND RESULTS

A retrospective observational study of 409 CCTA patients with stable angina pectoris. Logistic regression identified predictors of severe CAD, stratified by CAD-RADS score. Receiver Operating Characteristic (ROC) curves evaluated predictive performance. PIV and AIP were significant predictors of severe CAD (PIV: OR 1.002, 95% CI: 1.000-1.004, p < 0.021; AIP: OR 0.963, 95% CI: 0.934-0.993, p < 0.04). AUC values for predicting severe CAD were 0.563 (p < 0.001) for PIV and 0.625 (p < 0.05) for AIP. Combined with age, AUC improved to 0.662 (p < 0.02).

CONCLUSIONS

PIV and AIP were associated with severe CAD, with AIP demonstrating superior predictive capability. Incorporating AIP into risk assessment could enhance CAD prediction, offering a cost-effective and accessible method for identifying individuals at high risk of coronary atherosclerosis.

Correlations Between Acute Coronary Syndrome and Novel Inflammatory Markers (Systemic Immune-Inflammation Index, Systemic Inflammation Response Index, and Aggregate Index of Systemic Inflammation) in Patients with and without Diabetes or Prediabetes

Purpose

Type 2 diabetes mellitus (DM) is a recognized independent risk factor for both chronic coronary syndrome (CCS) and its complication, acute coronary syndrome (ACS). Patients with DM and prediabetes (preDM) face an increased ACS risk. Inflammation plays a significant role in the pathogenesis of both CCS and ACS. This study delves into novel inflammatory markers, such as the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI, also known as SIIRI or PIV), to explore their relationship with ACS and CCS in patients that have been or have not been diagnosed with DM or preDM.

Patients and Methods

This study included data of 493 patients with chest pain undergoing coronary angiography. They were categorized into four groups: 1) without DM/preDM and with CCS; 2) with both DM/preDM and CCS; 3) without DM/preDM and with ACS, 4) with both DM/preDM and ACS. Standard methods of statistical analysis were used to reveal possible differences between groups and to find the most influential ACS risk factors in groups with DM/preDM and without DM/preDM.

Results

The analysis showed no significant differences in SII, SIRI, or AISI between the respective patient groups. A logistic regression analysis generated a model incorporating SII, high-density lipoprotein, and low-density lipoprotein levels as the influential ACS risk factors for patients with DM/preDM. The model demonstrated 71.0% accuracy, 37.0% sensitivity, and 89.4% specificity.

Conclusion

The findings suggest that the aforementioned inflammatory markers may have potential for distinguishing DM/preDM patients at higher risk of ACS at a low financial cost. However, further comprehensive and well-designed research is required to validate their clinical utility.

Clinical implication of the Naples prognostic score on transcatheter aortic valve replacement in patients with severe aortic stenosis

BACKGROUND

One of the hallmarks of frailty in patients with severe aortic stenosis (AS) is malnutrition, for which one of the most up-to-date scoring systems is the Naples prognostic score (NPS). This study sought to investigate the predictive role of the NPS in determining mortality in patients undergoing transcatheter aortic valve replacement (TAVR) under long-term follow-up.

METHODS

A total of 430 consecutive patients with symptomatic severe AS who underwent TAVR were included retrospectively. The primary endpoint of the study was the long-term all-cause mortality. The study population was divided into two groups according to the NPS value, including Group 1 (NPS 0-2) and Group 2 (NPS 3-4).

RESULTS

The all-cause mortality occurred in 250 patients (62.5%) patients during a follow-up time of 40.6 (22.0-69.4) months. During the follow-up period, all-cause mortality was higher in Group 2 compared with Group 1 (87.9% vs. 42.9%, p < 0.001). Older age (p < 0.001), chronic obstructive pulmonary disease (p = 0.015), left ventricular ejection fraction (p = 0.021), and being in Group 2 (high NPS) (hazard ratio: 7.058, 95% confidence interval: 5.174-9.629, p < 0.001) were found to be independent predictors of all-cause mortality at long-term follow-up.

CONCLUSION

The NPS as a malnutrition and inflammation marker in patients with severe aortic stenosis who underwent TAVR provides valuable information for all-cause mortality under long-term follow-up.

Naples Prognostic Score and Clinical Outcomes in Pulmonary Arterial Hypertension Patients

Objectives

Pulmonary arterial hypertension (PAH) is a specific form of pulmonary hypertension characterized by an increased mean pulmonary arterial pressure. Risk stratification is crucial in managing PAH, using various clinical, laboratory, and imaging parameters. The Naples prognostic score (NPS), incorporating nutritional and inflammatory markers, has demonstrated prognostic value in other conditions but not in PAH. The goal of this study was to appraise the importance of NPS as a prognostic indicator for patients with PAH.

Methods

This retrospective study involved 101 PAH patients. Echocardiographic, laboratory, and right heart catheterization data were collected. Statistical analyses compared variables between survivors and non-survivors, and multivariate logistic regression identified mortality risk factors.

Results

Among the 101 patients, 18 died within the follow-up period. The mortality group showed elevated levels of B-type natriuretic peptide (BNP) and significantly higher median NPS. Patients were categorized based on their NPS scores, revealing higher mortality in Group 2. Multivariate logistic regression identified age and BNP levels as independent predictors of mortality. The inclusion of NPS in the model further reinforced its association with mortality.

Conclusion

The study suggests that NPS is linked to poor outcomes in PAH patients. NPS, a straightforward and easily calculated score, holds the potential to predict the clinical trajectory of PAH, offering advantages for risk assessment in this population.