Predictive Value of the Naples Prognostic Score on New-Onset Atrial Fibrillation in ST-Segment Elevation Myocardial Infarction Following Primary Percutaneous Coronary Intervention

By Yang Ling, Chen Liang, Renjie Wu, Jinfeng Wang

Affiliations

1. Department of Cardiology, Yijishan Hospital Affiliated to Wannan Medical College, Wuhu, China

doi: 10.29271/jcpsp.2025.07.819

ABSTRACT
Objective: To investigate the connection between Naples prognostic score (NPS) and new-onset atrial fibrillation (NOAF) in ST- segment elevation myocardial infarction (STEMI) cases following revascularisation.
Study Design: An observational study.
Place and Duration of the Study: Department of Cardiology, Yijishan Hospital, Affiliated to Wannan Medical College, Wuhu, China, from December 2016 to February 2023.
Methodology: The investigation recruited 683 consecutive STEMI patients after percutaneous coronary intervention (PCI), categorising them into two groups: NOAF group and sinus rhythm (SR) group. Analyses involving both multivariate logistic regression and receiver operating characteristic (ROC) curves were performed to evaluate the predictive capability of NPS for NOAF development. Additionally, the Kaplan-Meier method was employed to assess the differences in all-cause mortality between the two groups.
Results: Fifty-one (7.5%) patients of the present study developed NOAF during hospitalisation. NPS was found to be independently predictive of NOAF (NPS as continuous variable, odds ratio [OR], 2.207; 95% confidence interval [CI], 1.305-3.732; p <0.05; NPS as categorical variable, OR, 5.616; 95% CI, 1.252-25.198; p <0.05). The optimal NPS threshold for predicting NOAF development in STEMI patients post-PCI was greater than 2 (p <0.001). Furthermore, the all-cause mortality rate among individuals complicated with NOAF is significantly elevated in comparison to that of the SR group over a median follow-up duration of 44 months (Log-rank p <0.001).
Conclusion: NPS is independently predictive of NOAF among STEMI individuals who underwent PCI. Furthermore, NOAF is strongly linked to a poor prognosis after discharge.

Key Words: Naples prognostic score, New-onset atrial fibrillation, ST-segment elevation myocardial infarction, Prognosis.

INTRODUCTION

The emergence of new-onset atrial fibrillation (NOAF) in the context of ST-segment elevation myocardial infarction (STEMI) undergoing percutaneous coronary intervention (PCI) is a serious complication, with an estimated proportion varying from 2.8 to 14.2%.^1,2 Previous studies demonstrated that the development of NOAF is significantly correlated with adverse outcomes.^3,4
 

Recently, Naples prognostic score (NPS), a simple and practical assessment model that represents inflammatory and nutritional state, which consists of the value of serum albumin, total cholesterol (TC), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR), shows a significant correlation with unfavourable events in STEMI patients underwent inter- ventional therapy during hospitalisation and follow-up.^5,6

However, the relationship between this scoring system and NOAF remains unexplored. Accordingly, this study aimed to explore NPS at admission as an independent indicator of NOAF among STEMI cases after revascularisation.

METHODOLOGY

A total of 779 individuals diagnosed as STEMI at the Department of Cardiology, Yijishan Hospital Affiliated to Wannan Medical College, Wuhu, China, from December 2016 to February 2023, were enrolled in this retrospective cohort analysis. All participants received reperfusion therapy through stent implantation within 12 hours of the onset of symptoms. The diagnosis criteria of STEMI were strictly in accordance with the definition of myocardial infarction proposed in 2018.⁷ Participants who met at least one of the exclusion criteria, including those who previously suffered from various types of atrial fibrillation (AF) or malignancy, those who were subjected to PCI or coronary artery bypass grafting (CABG) before, participants presenting with valvular heart disease, individuals who experienced serious hepatic or renal insufficiency, those being treated for autoimmune or infectious disease, or patients who had been diagnosed with severe anaemia or malnutrition, were excluded. Additionally, patients with incomplete data during hospitalisation or follow-up were also eliminated. Following exclusion, 683 participants were enrolled in this study. This investigation was performed based on the guidelines put forth in the Declaration of Helsinki.

Every patient's clinical characteristic was extracted from the electronic medical record system of Yijishan Hospital. The value of estimated glomerular filtration rate (eGFR), measured based on a formula proposed for Chinese Patients,⁸ was used to assess the renal function. The calculation of body mass index (BMI) is executed by dividing the weight stated in kilograms by the square of the height stated in metres. The assessment of cardiac structure and function was accomplished through transthoracic echocardiography, which was performed within the first 24 hours of hospitalisation. NPS was calculated using the following variables, namely, serum albumin, TC, NLR, and LMR. Participants were categorised into two groups in accordance with their NPS values. Patients possessing NPS of 0,1,2, or 3,4 consisted of low and high NPS groups, respectively.

Those angiographic parameters, including culprit vessels, flow of thrombolysis in myocardial infarction (TIMI), coronary severity evaluated by SYNTAX score,⁹ as well as stent placements, were carefully assessed by other trained cardiologists blind to the current investigation. The patients who experienced an AF episode lasting more than 30 seconds recorded on electrocardiogram after PCI during hospitalisation were assigned to the NOAF group.

The following in-hospital adverse events, namely, cardiogenic shock, pulmonary oedema, usage of intra-aortic balloon pump (IABP), stroke, ventricular tachycardia or flutter (VT or VF), and mortality, consisted of secondary outcomes. The principal outcome was all-cause mortality throughout the follow-up interval. Follow-up information was collected from two colleagues via telephonic interview.

The normality of parametric variables was tested by Kolmogorov-Smirnov. Continuous data were expressed as mean ± standard deviation or median (interquartile range) with intergroup comparison using the Student’s t-test or Mann-Whitney U test. Numbers and frequencies were employed to depict categorical data, whereas the analysis of nonparametric variables across different groups was performed by the chi-square test or Fisher’s exact test. The independent indicators of NOAF were determined by the logistic regression analyses, including in the multivariate regression model variables exhibiting a p <0.1 in the univariate regression model. Notably, NPS was incorporated into the multivariate logistic regression model as a quantitative or categorical variable, respectively. The receiver operating characteristic (ROC) curve, characterised by the area under the curve (AUC), was harnessed to evaluate the predictive capacity of potential risk factors for estimating NOAF. The optimal cut-off level of NPS was established by the Youden’s index. The Kaplan-Meier method was carried out to analyse the follow-up information in the two groups, which were compared by the log-rank test. A value of p <0.05 was defined as having statistical significance. Statistical analyses in the current investigation were administrated with IBM SPSS version 23.0.

RESULTS

The final analysis enrolled 683 consecutive STEMI individuals who underwent PCI, of whom 51 (7.5%) experienced NOAF. Baseline characteristics of the SR vs. NOAF groups are depicted in (Table Ⅰ). Patients complicated with NOAF were older and had a higher likelihood of presenting with a Killip class ≥2 at admission. They also showed an increased prevalence of diabetes mellitus, larger left atrium, along with lower-left ventricular ejection fraction (LVEF) when compared to those in the SR group. The numbers of white blood cells, neutrophils, monocytes, and values of fasting glucose, high-density lipoprotein cholesterol (HDL-c), NPS, as well as SYNTAX scores were significantly higher among patients with NOAF, whereas lymphocyte and platelet counts, along with levels of eGFR, low-density lipoprotein cholesterol (LDL-c), and haemoglobin, were significantly lower in individuals with NOAF than those in the SR group. Besides that, the proportion of NPS >2 among NOAF patients was significantly higher compared with SR patients.

Table Ⅰ summarises the secondary outcomes of all patients during hospitalisation. Longer hospitalisation days was discovered in patients presenting with NOAF compared with non-NOAF patients.

Similarly, patients complicated with NOAF experienced a significantly higher proportion of shock, pulmonary oedema, IABP use, stroke, VT or VF, and mortality relative to patients with SR.

The multivariable logistic regression model was employed to evaluate the potential risk indicators related to NOAF (as shown in Table II). The variables; including, age, history of hypertension or diabetes mellitus, Killip class ≥2, BMI, counts of white blood cells, neutrophils, lymphocytes, and monocytes, levels of haemoglobin, HDL-c, LDL-c, glucose, and albumin, along with eGFR, SYNTAX score, stent length, left atrium diameter, LVEF, as well as NPS, the usage of Beta-blockers, and NPS >2, based on univariate logistic regression, were associated with the occurrence of NOAF.

Figure 1: The receiver operating characteristic (ROC) curve of NPS as an indicator to estimate NOAF occurrence in PCI-treated cases with STEMI. (AUC: 0.662; 95% CI, 0.625-0.697; p <0.001).

Figure 2: The differences of the all-cause mortality in the two groups had been depicted by Kaplan-Meier survival cure, revealing that the NOAF group exhibited worse prognosis.

Table I: Comparison of baseline characteristics between the SR group and the NOAF group.

Variables	SR (n = 632)	NOAF (n = 51)	p-value
Age (years)	64 (53-73)	72 (67-77)	<0.001a
Male gender, n (%)	509 (80.5)	37 (72.5)	0.171b
Hypertension, n (%)	311 (49.2)	32 (62.7)	0.063b
Diabetes mellitus, n (%)	116 (18.4)	17 (33.3)	0.009b
Chronic obstructive pulmonary disease, n (%)	88 (13.9)	10 (19.6)	0.265b
Cigarette smoking, n (%)	315 (49.8)	22 (43.1)	0.357b
Drinking, n (%)	166 (26.3)	16 (31.4)	0.529b
Killip class ≥2, n (%)	101 (16.0)	25 (49.0)	<0.001b
BMI, kg/m2	24.9 (23.7-26.4)	25.3 (24.7-27.1)	0.067a
White blood cell, 109/L	10.9 (8.7-12.9)	13.1 (10.3 -15.7)	<0.001a
Neutrophil, 109/L	8.6 (6.6-10.7)	11.1 (8.3-13.3)	<0.001a
Lymphocyte, 109/L	1.2 (1.0-1.8)	0.9 (0.3-1.2)	<0.001a
Monocyte, 109/L	0.4 (0.3-0.6)	0.7 (0.4-1.0)	<0.001a
Haemoglobin, g/L	142 (130-155)	133 (122-142)	0.002a
Platelet, 109/L	181 (144-226)	158 (137-203)	0.041a
Total cholesterol, mg/dl	160.7 (138.1-189.5)	150.4 (123.7-177.5)	0.095a
High-density lipoprotein cholesterol, mmol/L	1.2 (1.0-1.3)	1.3 (1.2-1.4)	0.003a
Low-density lipoprotein cholesterol, mmol/L	2.4 (2.0-3.0)	2.1 (1.7-2.7)	0.009a
Glucose, mmol/L	5.6 (4.8-7.0)	7.4 (5.5-9.5)	<0.001a
Albumin, g/dL	3.67 ± 0.38	3.40 ± 0.37	<0.001c
Estimated glomerular filtration rate, mL/minute × 1.73 m2	111.7 (85.9-139.4)	88.7 (74.5-122.0)	0.004a
Peak creatine kinase, × 103U/L	1.6 (0.9-2.8)	1.8 (1.0-3.6)	0.261a
Culprit vessels, n (%)			0.495b
Left anterior descending coronary artery	345 (54.6)	27 (52.9)
Left circumflex coronary artery	50 (7.9)	2 (3.9)
Right coronary artery	237 (37.5)	22 (43.1)
TIMI 3 flow pre-PCI, n (%)	497 (78.6)	43 (84.3)	0.436b
Stent length, mm	29 (21-33)	29 (23-36)	0.066a
SYNTAX score	20 (14-24.5)	22 (16-27)	0.041a
Left atrial diameter, mm	35 (33-39)	41 (38-43)	<0.001a
Left ventricular ejection fraction, %	51 (46-57)	47 (44-55)	0.001a
ACEI/ARB usage, n (%)	323 (51.2)	27 (54.0)	0.814b
Beta-blockers usage, n (%)	428 (67.8)	23 (46.0)	0.002b
MRA usage, n (%)	110 (17.4)	21 (42.0)	<0.001b
Statins usage, n (%)	580 (91.8)	46 (90.2)	0.898b
Hospitalisation days	12 (10-14)	15 (11-18)	<0.001a
Cardiogenic shock, n (%)	61 (9.7)	16 (31.4)	<0.001b
Pulmonary oedema, n (%)	66 (10.4)	23 (45.1)	<0.001b
Intra-aortic balloon pump usage, n (%)	10 (1.6)	5 (9.8)	<0.001b
Stroke, n (%)	5 (0.8)	2 (3.9)	0.033b
Ventricular tachycardia or flutter, n (%)	19 (3.0)	7 (13.7)	<0.001b
Mortality, n (%)	15 (2.4)	7 (13.7)	<0.001b
NPS	2 (2-3)	4 (3-4)	<0.001a
NPS >2, n (%)	495 (78.3)	49 (96.1)	0.002b
SR, Sinus rhythm; NOAF, New-onset atrial fibrillation; BMI, Body mass index; TIMI, Thrombolysis in myocardial infarction; PCI, Percutaneous coronary intervention; SYNTAX, Synergy between percutaneous coronary intervention with taxus and cardiac surgery; ACEI, angiotensin-converting enzyme inhibitor; ARB, Angiotensin receptor blocker; MRA, Mineralocorticoid receptor antagonists; NPS, Naples prognostic score; p <0.05 as statistical significance; (a) Mann-Whitney test was used for skewed distribution; (b) The Chi-square or Fisher’s exact test was used for qualitative data; (c) T-test was used for normally distributed data.

Table II: Uni- and multi-variate logistic models for risk factors.
 

Variable	Univariate analysis			Multivariate analysisa			Multivariate analysisb
	OR	95% CI	p-value	OR	95% CI	p-value	OR	95% CI	p-value
Age	1.065	1.037-1.094	<0.001	1.043	1.009-1.078	0.012	1.046	1.012-1.080	0.007
Male gender	0.639	0.335-1.218	0.174
Hypertension	1.738	0.965-3.132	0.066
Diabetes mellitus	2.224	1.201-4.118	0.011
Smoking	0.763	0.429-1.358	0.358
Drinking	1.283	0.692-2.379	0.428
Killip class ≥2	0.198	0.110-0.356	<0.001	3.235	1.541-6.789	0.002	3.243	1.553-6.772	0.002
BMI	1.144	0.981-1.335	0.087
White blood cell	1,168	1.090-1.251	<0.001
Neutrophil	1.125	1.054-1.201	<0.001
Lymphocyte	0.201	0.103-0.394	<0.001
Monocyte	11.871	4.867-28.519	<0.001
Haemoglobin	0.976	0.959-0.993	0.006
Platelet	0.999	0.995-1.004	0.828
Total cholesterol	0.995	0.989-1.002	0.162
High-density lipoprotein cholesterol	4.664	1.588-13.697	0.005
Low-density lipoprotein cholesterol	0.673	0.456-0.994	0.047
Glucose	1.131	1.061-1.207	<0.001	1.088	1.001-1.182	0.047	1.090	1.004-1.183	0.039
Albumin	0.134	0.059-0.307	<0.001
Estimated glomerular filtration rate	0.987	0.978-0.996	0.006
Creatine kinase	1.003	0.987-1.019	0.159
Culprit vessel LAD*	0.843	0.469-1.516	0.569
Culprit vessel LCX*	0.431	0.098-1.892	0.265
TIMI 3 flow pre-PCI	1.460	0.670-3.179	0.341
Stent length	1.021	1.003-1.039	0.024
SYNTAX score	1.056	1.015-1.098	0.007
Left atrial diameter	1.115	1.052-1.183	<0.001	1.077	1.006-1.153	0.033	1.084	1.012-1.161	0.022
Left ventricular ejection fraction	0.937	0.903-0.973	0.001
ACEI/ARB usage	1.119	0.628-1.995	0.702
Beta-blockers usage	0.404	0.226-0.722	0.002
MRA usage	3.430	1.886-6.237	<0.001
Statin usage	0.825	0.314-2.166	0.696
NPS (continuous)	2.599	1.587-4.258	<0.001	2.207	1.305-3.732	0.003
NPS >2 (categorical)	6.781	1.628-28.236	0.009				5.616	1.252-25.198	0.024
COPD, Chronic obstructive pulmonary disease; BMI, Body mass index; LAD, Left anterior descending coronary artery; LCX, Left circumflex coronary artery; RCA, Right coronary artery; TIMI, Thrombolysis in myocardial infarction; PCI, Percutaneous coronary intervention; SYNTAX, Synergy between percutaneous coronary intervention with taxus and cardiac surgery; ACEI, Angiotensin-converting enzyme inhibitor; ARB, Angiotensin receptor blocker; MRA, Mineralocorticoid receptor antagonists; NPS, Naples prognostic score. aNPS as a continuous variable; bNPS as a categorical variable; *Compared with culprit vessel RCA; p <0.05 as statistical significance; The multivariate logistic models were used to assess predictive data, including, age, Killip class <2, glucose, left atrial diameter, and NPS.

Furthermore, NPS, as either a continuous or categorical variable, has been suggested as an independent indicator of NOAF among STEMI individuals post-PCI according to multivariable regression analysis.

An ROC curve was constructed for NPS in Figure 1, which predicted NOAF among patients with STEMI post-PCI (AUC: 0.662, 95% CI: 0.625-0.697, p <0.001). Additionally, the ROC curve demonstrated that an optimum cut-off value of NPS >2 determines NOAF with 72.5% sensitivity and 55.9% specificity. Furthermore, the survival probability of SR and NOAF patients after a median 44-month follow-up period was 89.8% and 68.2%, respectively. Kaplan-Meier survival curve analysis displayed the long-term mortality among NOAF patients was significantly higher in comparison to that observed in patients with SR (Log-rank p <0.001, Figure 2).

DISCUSSION

This study demonstrated that NPS serves as an independent predictor for assessing NOAF in individuals with STEMI who are undergoing revascularisation. In addition, patients with NOAF are more prone to exhibit adverse clinical outcomes during hospitalisation and follow-up in comparison with patients in the SR group. It is the first analysis to investigate the correlation between NPS and NOAF among cases with STEMI who underwent interventional treatment.

Virtually, it is acknowledged that NOAF is one of the most prevalent phenomena in the context of STEMI during the era of PCI, and reported that the incidence of the development of NOAF might vary from 2.8 to 14.2% draw from prior studies.^1,2 The result in the present investigation, with NOAF occurring in 7.5% of STEMI patients, is in accordance with the findings from the previous literature. Besides that, the positive correlation between NOAF and a poor prognosis among patients with STEMI post-PCI has been posited in previous studies. A survey conducted by Luo et al. proved that NOAF is significantly correlated to ischaemic stroke in STEMI patients after adjusting for potential ischaemic stroke risk factors.⁴ Additionally, Fauchier et al., fulfilled a large and nationwide analysis of 797,212 individuals diagnosed with acute myocardial infarction and found that the rate of major cardiovascular adverse outcomes in individuals who exhibited NOAF was significantly increased, in comparison to cases with SR or previous atrial fibrillation, thus revealing a significant association between NOAF and prognostic end- points.¹⁰ The present investigation also displayed that patients in NOAF group had increased rates of in-hospital adverse events and all-cause death over a long-term follow-up, which corresponds to prior studies. Accordingly, it is of utmost importance for clinicians to identify the candidates who are prone to develop NOAF in STEMI patients after initial revascularisation.

The aetiology causing the development of NOAF in the setting of STEMI during PCI era is multifactorial and complex. It is well-acknowledged that inflammation exerts a crucial function in the entire physiopathological mechanism of STEMI. Considering the inflammatory process in the emergence and progression of atrial fibrillation,¹¹ the relationship between a series of inflammatory parameters and NOAF among STEMI individuals post-PCI has been investigated. Additionally, the previous investigation revealed that the systemic inflammatory response index is recognised as an independent predictor for NOAF development in STEMI cases after interventional reperfusion, with the predictability for NOAF exceeding that of NLR or monocyte-to-lymphocyte ratio.¹² Additionally, a small prospective cohort investigation carried out by Van Beek et al. demonstrated that hypoalbuminaemia is a significant NOAF predictor for individuals in the intensive care unit.¹³ Noticeably, 985 consecutive STEMI cases who underwent PCI from the southwest China were enrolled and analysed in an observational study. The inverse association between hyper- cholesterolaemia and NOAF had been displayed according to their observation.¹⁴ It is noteworthy that a wide series of demographic, clinical, or laboratory biomarkers are proven to be correlated to NOAF, nevertheless, more comprehensive and practical indicators for forecasting NOAF among patients with STEMI after interventional therapy are still required.

NPS, which is a composite of inflammatory and nutritional parameters, encompassing NLR, LMR, serum albumin, and TC, has been demonstrated to be related to both in-hospital and follow-up adverse endpoints in STEMI individuals after PCI. A multicentre and retrospective trial of 2,280 STEMI patients who underwent PCI has determined that NPS can independently predict the decreasing LVEF after adjusting for risk factors.¹⁵ A retrospective analysis of 1,887 individuals with STEMI following PCI was analysed and revealed that NPS is significantly associated with major adverse outcomes during hospitalisation and follow-up.⁵ However, no previous investigations have determined the relationship between NPS and NOAF among STEMI cases who underwent PCI. The current results discovered that the level of NPS or proportion of NPS >2 in patients with NOAF was significantly higher in comparison with that among patients with SR. Furthermore, NPS, as either a continuous or a categorical variable, was identified as an independent predictor of NOAF after incorporating potential risk variables. This study is the inaugural assessment of the link between NPS and NOAF in individuals who have undergone interventional treatment.

Several limitations should be noted in this investigation. First, the causal association between NOAF and NPS is impossible to be proven because of the nature of the retrospective analysis. Besides that, the present study is restricted to Chinese patients with relatively small samples, limiting its generality. Additionally, several potential residual covariables may still be present. Finally, the incidence of NOAF development might be affected because of previously unidentified AF. Accordingly, it is necessary to conduct a multicentre prospective trial in the future.

CONCLUSION

NPS, a relatively practical and easily calculated scoring system, can be used to independently estimate the development of NOAF for STEMI cases receiving PCI. Moreover, NOAF in STEMI patients presents a higher proportion of all- cause mortality compared to individuals with SR over a long-term follow-up.

ETHICAL  APPROVAL:
This study was approved by the Institutional Review Board of Yijishan Hospital Affiliated of Wannan Medical College and conducted in accordance with the Declaration of Helsinki (IRB-2021-013).

PATIENTS’ CONSENT:
Informed consent was provided by all patients.

COMPETING  INTEREST:
The authors declared no conflict of interest.

AUTHORS’ CONTRIBUTION:
YL: Data collection and drafting of the manuscript.
CL, RW: Literature review and data collection.
JW: Design, analysis, and interpretation of the work.
All authors approved the final version of the manuscript to be published.

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