Statistical Analysis
diabetes, chronic kidney disease, dyslipidemia
ISCHEMIC STROKE, PERIPHERAL VASCULAR DISEASE, DYSLIPIDEMIA, REGRESSION, HEART FAILURE, HYPERTENSION, DIABETES
Categorical variables were reported as frequencies and percentages, and continuous variables were reported as medians with interquartile ranges. Distributions of biomarker concentrations were displayed in empirical cumulative distribution function plots.Differences in biomarker concentration distributions between MINOCA and MI‐CAD at baseline and at 1 month later were investigated using Mann‐Whitney tests. To study these differences adjusting for potential confounders, we performed linear regression analyses using ln‐transformed concentrations of hs‐cTnT, NT‐proBNP, hs‐CRP, and GDF‐15 as response variables. The concentrations are presented as geometric means and were calculated using the antilogs of the model‐adjusted means of the ln‐transformed data; thus, the comparisons between MINOCA and MI‐CAD are presented as adjusted geometric mean ratios. A geometric mean ratio >1 corresponds to a higher biomarker concentration in MINOCA, and a geometric mean ratio <1 corresponds to a higher biomarker concentration in MI‐CAD. The analyses were adjusted in 2 models. Model 1 was unadjusted at baseline, whereas at 1‐month follow‐up, it was adjusted for randomized treatment (clopidogrel versus ticagrelor) and corresponding biomarker concentration at baseline. Model 2 was additionally adjusted for baseline clinical characteristics (age, sex, body mass index, current smoking, hypertension, dyslipidemia [medical history or lipid treatment at admission], diabetes, chronic kidney disease [medical history], MI type [STEMI/NSTEMI], previous MI, previous ischemic stroke, previous heart failure, and peripheral vascular disease). Additional adjustment was made at baseline for hours from the onset of symptoms to blood sampling, and at 1‐month follow‐up for revascularization during index hospitalization. A further analysis was done with adjustment for medications at follow‐up (antiplatelets, P2YTo visualize temporal biomarker concentration changes in MINOCA and MI‐CAD during hospital stay, linear regression models including time from symptom onset, MINOCA/MI‐CAD classification, and MI type (STEMI/NSTEMI), as well as all pairwise interactions between the 3, were fitted. Time was modeled as a restricted cubic spline, with 4 knots placed at the 5th, 35th, 65th, and 95th sample percentiles, to allow for nonlinear associations (for details, see Data Differences between MINOCA and MI‐CAD in delta changes of biomarker concentrations from baseline to 1 month later were assessed using Mann‐Whitney tests.There were a few missing biomarker values that were not accounted for in the statistical analyses. In all tests, a statement of statistical significance implies a 2‐sided 