Eligibility Criteria
151,607 inpatients with data about Lp(a) levels from January 2017 to July 2021 were retrospectively collected at the Second Affiliated Hospital of Nanchang University, Jiangxi Province. Among these, 2,110 patients with unknown AF status, 12,707 cancer patients, 26,866 kidney dysfunction patients, and 16,465 patients with pregnancy, infection, and poisoning were excluded. Among the 96,089 patients who met the criteria, the patients with AF were selected as the case group, and the control group was 1:2 matched with the propensity score matching (PSM) method by the following items: sex, age, smoking, drinking, CHD, and hypertension status. Finally, the case group included 4,511 AF patients, and the control group included 9,022 non-AF patients (Figure 1).
Definition and Measurement of AF and Other Diseases
The patient's data were derived from their medical records; AF patients were identified as AF by a professional cardiologist based on the electrocardiogram. The diagnostic criteria for AF were no apparent P wave repetition and irregular RR intervals were detected on electrocardiography (ECG) [12]. We defined the first diagnosis day of AF as the onset day. A CHD diagnosis was made when satisfying at least one coronary artery or its major branch had stenosis > 50% on coronary angiography [13].
Clinical and Laboratory Analyses
General information was collected, containing age, sex, body mass index (BMI), alcohol comsumption, smoking, systolic blood pressure (SBP), and diastolic blood pressure (DBP). Measurement of Lp(a) concentration: After fasting for over 8 hours, we collected the patient’s fresh serum and used the Lp(a) Assay Kit (Latex-Enhanced Immunoturbidimetric Method, Beijing Antu Inc, China, LOT:10723C11) to measure Lp(a) levels, where 0 to 3000 mg/dL is the standard reference range for Lp(a). The experimental principle of the Lp(a) kit is as follows: Lp(a) reacts with the mouse anti-human lipoprotein(a) monoclonal antibody present on the latex particles. Then the agglomeration of latex particles increases the turbidity in the solution. The calibration curve of absorbance and concentration was established by measuring a series of calibrators. By comparison with the established calibration curve, the Lp(a) concentration of the samples can be identified.
The laboratory data of albumin, apolipoprotein (Apo(A)), apolipoprotein B (Apo(B)), blood glucose, C-reactive protein (CRP), creatine, high-density lipoprotein cholesterol (HDL-C), homocysteine (HCY), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), and uric acid were recorded.
Statistical Analyses
Statistical analyses were performed with IBM SPSS statistical software, version 21.0 (SPSS Inc., Chicago, Illinois), and R software, version 4.1.1. The level of significance was 0.05. PASS, version 15.0, was used for the estimation of the required sample size.
The AF group and non-AF control group were 1:2 matched using the PSM method for balancing covariates. PSM is a statistical method used to ensure that study participants are comparable on clinical measures and reduce bias. PSM determines whether the variable is a responder or a confounder when creating a regression model. The propensity scores for each subject were estimated to range from 0 to 1, indicating how the subjects should be divided into treatment groups.
In the baseline analysis, the median and quantile deviation were used to describe the continuous data because almost all of the data were skewed. For categorical variables, the number and percentage of cases were used to describe the data. All patients were equally sent into four groups by Lp(a) quantiles: quantile 1 (Q1), under 8.71 mg/dL; quantile 2 (Q2), 8.71-16.54 mg/dL; quantile 3 (Q3), 16.54-32.42 mg/dL; and quantile 4 (Q4), higher than 32.42 mg/dL. Binary logistic regression models were used to evaluate the correlation, and the risk prediction equation and odds ratio with the confidence interval for each factor were calculated by SPSS. Model 1 is the unadjusted analysis model. Model 2 uses BMI and SBP for adjustment. Model 3 was further adjusted for TG, CRP, HCY, blood glucose, and statin status. Subgroup analyses were designed to evaluate the influences of age (≤ 65 years and >65 years), sex (men and women), CHD, hypertension status, and T2DM status on the relationship between Lp(a) and AF.