Purpose. This study was aimed at investigating whether the platelet-to-neutrophil ratio (PNR) is independently related to the prognosis of patients with ST-elevation myocardial infarction (STEMI) after successful primary percutaneous coronary intervention (pPCI). Methods. This was a secondary analysis of data retrieved from the DATADRYAD database, which was a prospective cohort study. A total of 464 STEMI patients who underwent successful pPCI were recruited between January 2010 and October 2014. The target-independent variable, PNR, was measured at the baseline. The dependent variable in the current study was the occurrence of major adverse cardiovascular events (MACEs) during the 30-month follow-up. Results. Two patients were excluded from the final analysis because their platelet counts were unavailable. The average age of the 462 participants was years, and approximately 76.6% were male. After adjusting for age, sex, anterior wall myocardial infarction (MI), history of MI, apelin-12, apelin-12 change rate, left ventricular end-diastolic diameter, peak cardiac troponin I, pathological Q wave, Killip classification grade, fasting blood glucose, albumin, GENSINI score, and estimated glomerular filtration rate, a nonlinear relationship was found between the PNR and MACEs in the included cohort. The threshold value of the PNR for MACEs was 23.1. Over this cutoff value, the incidence rate of MACEs increased by 43% per 10-unit change in PNR (95% CI: 1.16–1.75, ). Conclusion. There was a threshold relationship between PNR and MACEs in patients with STEMI who underwent successful pPCI. The incidence of MACEs was positively associated with the PNR when the PNR exceeded 23.1.

Background: Low voltage areas (LVAs) on left atrial (LA) voltage mapping correlate with atrial fibrosis. However, there is no uniform standard for the definition of LVAs, or mapping techniques and mapping rhythms, so that the predictive value of left atrial LVAs for recurrence of atrial fibrillation (AF) is uncertain. This study aimed to explore the relationship between the presence of pre-ablation left atrial LVAs and the risk of recurrent AF after catheter ablation. Methods: The databases of PubMed, Embase, Web of science, Cochrane library, Scopus, Wanfang Datebase, China National Knowledge Infrastructure, China Biology Medicine and China Scientific Journal Datebase were searched from inception to 31 July 2023. Relevant studies regarding left atrial LVAs prior to ablation to predict postoperative recurrence of AF were identified and analyzed. The efficacy endpoints were defined as the recurrence of atrial arrhythmia lasting over 30 s. Results: A total of 12 studies with 1070 patients were included. We found the presence of pre-ablation left atrial LVAs correlated with the risk of recurrent AF after ablation (hazard ratio (HR) = 2.87, 95% confidence interval (CI): 2.33–3.52). The presence of pre-ablation left atrial LVAs can predict the risk of recurrent AF after ablation both in the follow-up duration ≤12 months group and follow-up duration >12 months group (follow-up duration ≤12 months: HR = 2.93, 95% CI: 2.20–3.90; follow-up duration >12 months: HR = 2.80, 95% CI: 2.09–3.77). The presence of pre-ablation left atrial LVAs correlated with the risk of recurrent AF after ablation in paroxysmal AF (HR = 2.89, 95% CI: 1.97–4.24). Conclusions: The presence of pre-ablation left atrial LVAs correlate with the risk of recurrent AF after catheter ablation.

Atrial fibrosis is an independent predictor of the recurrence of atrial fibrillation (AF) after catheter ablation. Low-voltage areas (LVA) measured during catheter ablation for AF are a commonly used surrogate for the presence of atrial fibrosis. LVA are associated with clinical outcomes and comorbidities and have links to triggering sites for AF. Several trials have shown promising data of targeting ablation in LVA, however the results have been mixed. This article will review the role of LVA in the prediction of adverse events in AF patients, including stroke, how to predict the presence of LVA, and the impact of LVA ablation on the recurrence of AF.

Background: The aim of this work was to investigate left atrial electrophysiological properties for their ability to predict the recurrence of atrial fibrillation (AF) following pulmonary vein isolation (PVI). Methods: The study comprised 53 patients with AF [62 (interquartile range (IQR): 52–68) years old; 47.2% females]. High-density, three-dimensional electro-anatomic mapping using PentaRay was conducted during sinus rhythm in the left atrium (LA) immediately after PVI. LA conduction time, conduction velocity in predefined anterior and posterior routes, low voltage area percentage and distribution were assessed. Results: The AF recurrence group had longer LA conduction time compared to the non-recurrence group [11 (IQR: 10–12) ms vs. 9 (IQR: 8–10) ms, p = 0.001). The percent low voltage area was greater in the recurrence group than the non-recurrence group [31.2 (IRQ: 7.1–49.3)% vs. 7.7 (IQR: 4.3–15.2)%, p = 0.008]. Multivariate Cox regression revealed that LA conduction time independently predicted AF recurrence following ablation over a median follow-up of 235 days [IQR: 154–382 days; hazard ratio (HR): 2.37, 95% confidence interval (CI): 1.08–5.23, p = 0.031]. The optimal cut-off for LA conduction time was 98 ms [area under curve (AUC): 0.926, sensitivity: 0.833, specificity: 0.894, p < 0.01]. Kaplan–Meier analysis revealed that patients with a conduction time >98 ms had a higher rate of AF recurrence following ablation (p < 0.001). Conclusions: Patients with longer LA conduction time after PVI had more frequent AF recurrence.

A patient in their 50s was admitted with recurrent abdominal pain and syncope after drinking alcohol. They had this problem for 2 years but experienced worsening on admission. The patient was a smoker and had alcohol overconsumption for about 20 years. The average alcohol intake was 250 g/wk. They had hypertension diagnosed 3 months prior to admission. On admission, high-sensitivity troponin I was 0.01 ng/mL (to convert to μg/L, multiply by 1) and serum potassium was 4.6 mEq/L (to convert to mmol/L, multiply by 1), both of which were in normal range. The patient’s Holter was shown in the Figure.