Platelet-to-Lymphocyte Ratio as a Predictor of Atrial Fibrillation in STEMI Patients

Introduction

ST-segment elevation myocardial infarction (STEMI) remains one of the leading causes of death worldwide [1]. Atrial fibrillation (AF) is the most common clinically significant supraventricular arrhythmia in STEMI [2]. It has been reported that the incidence of new-onset AF (NOAF) during hospitalization is 6.9–7.9% in patients undergoing percutaneous coronary intervention (PCI) [3–5]. Notably, the occurrence of any type of AF in patients with acute myocardial infarction increases the risk of adverse cardiovascular events [1]. When STEMI and AF coexist, they pose a threat to patients and also present a challenge to physicians in terms of treatment. Evidence from real-world scenarios indicates that the triple-antithrombotic therapy advocated by existing guidelines has problems, including a heightened risk of bleeding and poor patient compliance [6]. Therefore, it is necessary to explore the risk factors of NOAF after STEMI to optimize risk stratification.

Inflammatory response plays an important role in myocardial infarction and AF. Previous studies have shown that myocardial infarction can lead to atrial inflammation and increase the risk of developing AF [7,8]. Platelets are a key component in the processes of inflammation and thrombosis [9–11]. A decrease in lymphocyte count is associated with a higher mortality rate in patients with acute myocardial infarction [12,13]. The platelet-to-lymphocyte ratio (PLR) is a new biomarker of inflammatory response. Previous studies have shown that an elevated PLR is an independent risk factor for no-reflow and increased mortality after PCI in patients with acute myocardial infarction [14,15]. Gungor et al [16] found that the preoperative PLR level is independently associated with the risk of AF after CABG. In addition, PLR has been proven to be an independent predictor of AF recurrence after radiofrequency ablation, and there is a linear dose–response relationship with the risk of AF recurrence [17]. However, the relationship between PLR and NOAF in STEMI patients remains unclear. This study aimed to explore the predictive value of PLR for NOAF after PCI in STEMI patients.

Material and Methods

STUDY POPULATION:

In this retrospective observational study conducted at a single center, patients diagnosed with STEMI at Suining County People’s Hospital from January 2022 to October 2024 were recruited consecutively. The diagnostic criteria for STEMI were troponin levels elevated beyond the 99th percentile of the reference value’s upper limit on at least 1 occasion and new ST-segment elevation emerged at the J point in 2 neighboring leads [18]. This study received approval from the Ethics Committee of Suining County People’s Hospital (NO. LL-2023-042). Because there was no risk to patients, the requirement of informed consent was waived. The inclusion criteria were: successful PCI (TIMI ≥2) within 12 hours after the onset of symptoms, continuous electrocardiogram monitoring during hospitalization (≥36 hours), and complete clinical data. The exclusion criteria were: age less than 18 years old, history of atrial fibrillation or atrial flutter, history of myocardial infarction, severe renal insufficiency (estimated glomerular filtration rate [eGFR] <30 mL·min−1·1.73 m−2), malignant or inflammatory diseases, severe valvular heart disease, and thyroid dysfunction. After applying the inclusion and exclusion criteria, 654 patients were included in this study (Figure 1).

CLINICAL DATA ASSESSMENT:

We collected all the baseline clinical information of the enrolled patients from electronic records, including sex, age, body mass index (BMI), smoking, and past medical history. We recorded use of certain medications (aspirin, P2Y12 inhibitor, statins, β-blockers, angiotensin-converting-enzyme inhibitor, and angiotensin II receptor blocker) prior to NOAF during hospitalization. We also recorded the use of anti-arrhythmic drugs by the patients before the onset of STEMI. The platelet and lymphocyte counts were measured and recorded in the Emergency Department before primary PCI. PLR was defined as the ratio of platelets to lymphocytes. The peak levels of C-reactive protein (CRP), troponin I (TNI), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) during hospitalization were also recorded. AF was defined as single-lead electrocardiogram (≥30 s) or 12-lead electrocardiogram shows the disappearance of P waves, which are replaced by fibrillatory waves (f waves) with irregular size, morphology, and duration, and the RR intervals are all irregular. NOAF was defined as new-onset AF after admission in patients with no previous history of AF [19]. The infarct-related artery (IRA) was recorded according to the results of coronary angiography (CAG).

STATISTICAL ANALYSIS:

All data were statistically analyzed using SPSS (version 27.0, Chicago, USA) and R (version 4.3.1; R Foundation for Statistical Computing). The Kolmogorov-Smirnov test was used to assess normal distribution. Continuous variables with a normal distribution are expressed as mean±standard deviation and analyzed using the t test. Continuous variables with a non-normal distribution are expressed as medians (Q25, Q75) and were analyzed using the Mann-Whitney U test. Categorical variables are expressed as counts and percentages and were analyzed using the χ² test. To eliminate the interference of multicollinearity among variables, potential risk factors (P<0.05) discovered through univariate logistic regression analysis were incorporated into the multivariate logistic regression analysis model via the forward stepwise approach. To investigate the dose–response association between the PLR and NOAF, restricted cubic splines (RCS) analysis was used. The predictive value of PLR for NOAF was evaluated by the receiver-operating characteristic curve (ROC). Statistical significance was defined as a P value less than 0.05.

Results

BASELINE CHARACTERISTICS:

A total of 745 STEMI patients who met the inclusion criteria were initially selected. Among them, 91 patients who met the exclusion criteria were removed. Finally, 654 STEMI patients were included in this study. Females accounted for 28.44% of the patients, and the average age was 63.37±12.91 years old. The incidence of NOAF during hospitalization was 53/654 (8.1%). The comparison of baseline characteristics between the 2 groups of patients is shown in Table 1. Compared with the group without NOAF, patients in the NOAF group had higher levels of PLR, neutrophil count, lymphocyte count, Killip class, CRP, and NT-proBNP, a higher proportion of intra-aortic balloon pump (IABP) use, and a lower left ventricular ejection fraction (LVEF), and the differences were all statistically significant (P<0.05) (Table 1). Among the patients with NOAF, 1 patient received electrical cardioversion, 37 patients received anti-arrhythmic treatment excluding β-blockers, and 19 patients received anticoagulant treatment during hospitalization (Table 2).

LOGISTIC REGRESSION ANALYSIS FOR NOAF:

Univariate logistic regression analysis revealed that the occurrence of NOAF was associated with LVEF, IABP, neutrophil count, lymphocyte count, CRP, PLR, Killip >1, and NT-proBNP (P<0.05) (Table 3). The above variables (except for lymphocyte count) were included in the multivariate logistic regression using the forward stepwise method, and the results showed that LVEF (OR=0.900, 95% CI: 0.865~0.937, P<0.001), NT-proBNP (OR=1.525, 95% CI: 1.173~1.982, P=0.002), and PLR (OR=1.003, 95% CI: 1.001~1.006, P=0.004) were independent factors affecting the occurrence of NOAF in patients with STEMI (Table 4). The RCS results suggested a linear dose–response relationship between PLR and NOAF, indicating that greater PLR was associated with a higher risk of NOAF (Figure 2).

ROC ANALYSIS OF NOAF DURING HOSPITALIZATION:

The ROC analysis of LVEF, NT-proBNP, and PLR for predicting the occurrence of NOAF during hospitalization is shown in Table 3 and Figure 3. According to the ROC results, the areas under the curve of LVEF, NT-proBNP, and PLR for predicting the occurrence of NOAF during hospitalization were 0.746, 0.697, and 0.653, respectively, and the corresponding P values were all less than 0.05, showing statistically significant differences. Among them, the cut-off value of PLR for predicting NOAF was 212.11, with a corresponding sensitivity of 50.9% and a specificity of 76.5%. After combining LVEF, NT-proBNP, and PLR, the ROC results showed that the area under the curve for predicting the occurrence of NOAF during hospitalization was 0.778 (Table 5, Figure 3).

Discussion

LIMITATIONS:

Several limitations should be acknowledged in this study. First, this was a single-center retrospective study, and there may be some unrecognized confounding factors in the obtained data, which may have led to bias. The use of multicenter designs or larger sample sizes in the future will provide practical avenues for ongoing research. Second, although the results of this study prove that elevated PLR is related to NOAF after PCI in STEMI patients, basic research may be required to elucidate the specific mechanism of action. Third, due to the lack of long-term electrocardiogram monitoring of patients before admission, some previous medical histories of AF may have been overlooked, especially for cryptogenic AF. On the other hand, during the readmission period, we did not conduct continuous electrocardiogram monitoring for all patients, which may have led to some patients with NOAF being overlooked. Fourth, this study only explored the relationship between PLR and NOAF in STEMI patients undergoing primary PCI, so some of our conclusions may not be directly applicable to other diseases.

Conclusions

Elevated PLR is an independent risk factor for NOAF after PCI in STEMI patients, and there is a linear dose–response relationship between PLR and NOAF. This finding suggests that the PLR could be a valuable marker for evaluating the inflammatory status in patients with STEMI and forecasting the risk categorization of NOAF. However, placing these results in a broader clinical practice context can prevent over-generalization, and they should be applied with caution before more extensive validation studies are conducted.

Data Availability Statement

The datasets used and/or analyzed in the current study are available from the corresponding author on reasonable request.