R ver 4

The sample size was calculated based on a negative predictive value of 97.5%, as established previously [7 (link)]. The sensitivity, specificity, α error, β error, and prevalence rate were set as 84%, 88%, 0.05, 0.10, and 10%, respectively. The prevalence of AMI in adults who visit the ED for nontraumatic chest pain differs in the literature and is reported to range from 4% to 17% [3 (link),18 (link)]. The study sample size was calculated based on a 10% prevalence rate. However, based on a dropout rate of 10%, 8,814 participants will be ultimately required. This calculation is based on the “bdpv” library of R ver. 4.1.0 (R Foundation for Statistical Computing) and a corresponding study [19 (link)].

Descriptive statistics were used to summarize the variables in the study. The range and median were reported for continuous variables, and the frequency and proportion (%) were reported for categorical variables. For multiple group comparison, the Kruskal-Wallis rank sum test was used for continuous variables and the Fisher exact test for categorical variables. The Wilcoxon rank sum test was applied for pairwise comparison. A p-value of less than .05 was considered statistically significant. All statistical analyses were performed using R ver. 4.1.0 (R Foundation for Statistical Computing, Vienna, Austria).

Descriptive statistics, presented as percentages, were utilized to examine differences in demographic, clinical, and epidemiological characteristics among the 48 confirmed cases identified during the epidemiological investigation of this outbreak. Risk factors for infection were examined using univariate and multivariate logistic regression analyses, with adjustments for potential confounding variables of SARS-CoV-2 infection among the 80 attendees of the 3rd to 5th screenings. In line with the Republic of Korea vaccination policy at the time, minors (those under 19 years old) were not eligible for vaccination. Consequently, we categorized the study population into 2 groups based on this age cutoff. Contacts were classified based on the criteria for determining contacts of individuals with airborne-transmitted tuberculosis during flights. Specifically, attendees seated in the same row as the index case, as well as those in the 2 rows in front of and the single row behind that individual, were designated as close contacts. All other attendees were deemed casual contacts [20 ,21 ]. R ver. 4.1.0 (The R Foundation) was used for statistical analysis, and an alpha level of 0.05 was employed to determine statistical significance. Values were presented along with 95% confidence intervals (CIs).

We performed the Shapiro-Wilk test to determine if continuous variables followed a normal distribution, which showed a normal distribution. The average values and standard deviations are used to present these variables. On the other hand, categorical variables are presented them as counts and percentages (%). To compare groups, we performed PSM, based on the patient demographics (age, body mass index, and bone mineral density) and preoperative spinal condition (surgical level, pedicle diameter, and articular degeneration). Those factors are known to be associated with accuracy, ASD, and mechanical failure [20 (link)-23 (link)]. We used appropriate statistical methods such as analysis of variance and the chi-square test. Survival analysis and log-rank test were employed to account for the difference in follow-up periods between ASD rate and mechanical failure, ensuring an examination of the disparities in each group. We conducted Cox regression analyses not only for comparisons among groups but also for the entire patient cohort. We aimed to identify potential factors influencing radiological and clinical ASD, and mechanical failure by hazard ratios (HRs).
Statistical significance was defined as a 2-sided p-value less than 0.05. All statistical analyses were conducted using R ver. 4.1.0 (The R Foundation for Statistical Computing, Vienna, Austria).

Continuous variables were compared using the Student t-test or the Mann-Whitney U-test. Categorical variables were compared using the chi-square test or the Fisher exact test. Survival and cumulative incidence of recurrence by risk group were analyzed using Kaplan-Meier curves, and comparisons were made using the log-rank test. Univariable and multivariable analyses were conducted using a Cox proportional hazards regression model to identify prognostic factors that may affect survival. Risk factors for PCs were analyzed using binary logistic regression. Variables with a p-value ≤0.1 were included in the multivariable analyses. A p-value ≤0.05 was considered to indicate statistical significance. Statistical analyses were performed using IBM SPSS ver. 25.0 (IBM Corp., Armonk, NY, USA) and R ver. 4.1.0 (The R Foundation for Statistical Computing, Vienna, Austria; https://www.r-project.org/).