Dual-Parameter IVUS Assessment of Coronary Calcification Stratifies the Risk of Adverse Events after PCI: A Retrospective Cohort Study

Dual-Parameter IVUS Assessment of Coronary Calcification Stratifies the Risk of Adverse Events after PCI: A Retrospective Cohort Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Dual-Parameter IVUS Assessment of Coronary Calcification Stratifies the Risk of Adverse Events after PCI: A Retrospective Cohort Study Shaowu Xiao, Mengya Zeng, Ying Liang, Yingying Mo, Yuewu Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8629286/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background The prognostic value of a dual-parameter intravascular ultrasound (IVUS) assessment that integrates both the calcium arc and length to grade coronary artery calcification (CAC) severity is not well established in patients undergoing percutaneous coronary intervention (PCI). Methods This single-center, retrospective study included 709 patients who underwent coronary angiography and preprocedural IVUS. Patients were stratified according to the maximum calcium arc and length as follows: no calcification (n = 417), mild calcification (arc ≤ 180° or length ≤ 5 mm, n = 168), and severe calcification (arc > 180° and length > 5 mm, n = 124). The primary endpoint was the composite of major adverse cardiovascular events (MACEs). Results Over a median follow-up of 18.6 months, 122 patients (17.2%) experienced MACEs. Each increase in CAC severity grade was independently associated with a greater risk of MACEs (adjusted hazard ratio [aHR] 1.30, 95% CI 1.04–1.63; P for trend = 0.021). Compared with patients with no calcification, those with severe calcification had a significantly greater risk of MACEs (aHR 1.67, 95% CI 1.06–2.65; p = 0.028) and target vessel revascularization (TVR) (aHR 2.45, 95% CI 1.28–4.68; p = 0.007). No significant increase in risk was observed for the mild calcification group. Conclusion Severe coronary calcification, defined by IVUS as an arc > 180° with a length > 5 mm, is a strong and independent predictor of adverse outcomes after PCI. This dual-parameter IVUS assessment provides a refined tool for preprocedural risk stratification. Coronary artery calcification Intravascular ultrasound Percutaneous coronary intervention Major adverse cardiovascular events Risk stratification Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Background Coronary artery calcification (CAC) is a well-established hallmark of advanced atherosclerosis, representing a complex, active process of mineral deposition within the arterial wall that is intimately linked to plaque burden, vulnerability, and overall cardiovascular risk. 1 Its presence and extent, traditionally assessed by coronary computed tomography angiography via the Agatston score, are powerful predictors of future cardiovascular events in both asymptomatic and symptomatic populations. 2 , 3 In the context of percutaneous coronary intervention (PCI), CAC presents a formidable technical challenge. This impedes optimal stent delivery, expansion, and apposition, leading to higher rates of procedural complications, such as stent underexpansion, malapposition, and dissection, which in turn are precursors for adverse outcomes such as in-stent restenosis (ISR) and stent thrombosis. 4 , 5 While coronary angiography remains the primary imaging modality for guiding PCI, it provides only a two-dimensional lumenogram and is notoriously limited in its ability to accurately characterize vessel wall pathology, particularly the depth, distribution, and thickness of calcification. 6 In contrast, intravascular ultrasound (IVUS) offers high-resolution, cross-sectional, in vivo visualization of the coronary vessel wall, enabling precise quantification of the calcification burden. 6 The standard IVUS metric for calcification is the maximum calcium arc, with a threshold of > 180° (or occasionally > 270°), which is often used to define "severe" calcium and is associated with difficulty in stent expansion. 7 However, calcification is a three-dimensional entity. A focal, short segment of intense calcium may behave differently during intervention than may a long, continuous sheet of calcium, even if both share a similar maximal arc. 8 Recent studies and expert consensus have therefore highlighted the importance of incorporating calcium length into the assessment, suggesting that the interplay between arc and length better captures the true procedural complexity and potential biological impact of a calcified lesion. 7 , 8 Despite these advances in imaging characterization, a critical knowledge gap persists. Most prognostic studies linking CAC to outcomes have focused on its mere presence or used single-parameter thresholds (e.g., arc alone), which fail to capture the three-dimensional complexity of calcification. 9 Therefore, the incremental prognostic value of a comprehensive dual-parameter (arc and length) stratification of CAC severity for predicting mid- to long-term clinical outcomes after PCI in a contemporary, real-world cohort receiving preprocedural IVUS guidance has not been fully established. Specifically, it remains unclear whether a graded risk exists across a spectrum from no calcification to mild and severe calcification, as defined by such composite criteria, and whether this risk is independent of traditional clinical and procedural factors. This study aimed to address this gap. We hypothesized that severe CAC, defined by stringent IVUS criteria requiring both a large arc (> 180°) and considerable length (> 5 mm), would be a stronger and independent predictor of major adverse cardiovascular events (MACEs) following PCI than would milder forms of calcification or its absence. By systematically investigating the associations between this detailed IVUS-based CAC severity stratification and clinical outcomes, we seek to provide a more refined tool for preprocedural risk assessment and to inform personalized management strategies for patients with calcified coronary lesions. 7 , 10 , 11 2. Methods 2.1 Study Design and Population This was a single-center, retrospective, observational cohort study conducted at the Department of Cardiology, The Second Affiliated Hospital of Hainan Medical University. The study protocol was reviewed and approved by the Hospital Ethics Committee (Approval No. LW2022035) and was conducted in strict accordance with the ethical principles of the Declaration of Helsinki. Given the retrospective nature of the analysis using deidentified data, the requirement for written informed consent from individual patients was waived by the ethics committee. The study population consisted of consecutive patients with known or suspected coronary artery disease who were admitted for elective or urgent PCI. To be included, patients must have undergone both diagnostic or guiding coronary angiography and a preintervention IVUS examination of at least one target lesion between January 1, 2023, and July 31, 2024. We retrospectively screened the hospital's catheterization laboratory database. The initial search identified 762 unique patient records where an IVUS procedure using a Boston Scientific imaging system was documented in conjunction with coronary angiography during the specified period. A comprehensive, manual review of electronic medical records was subsequently performed for all identified patients. On the basis of this review, 53 patients were excluded according to the following prespecified criteria: 1) poor-quality IVUS images precluding reliable calcium assessment (e.g., excessive noise, nonuniform rotational distortion, inadequate penetration) (n = 2); 2) missing unique patient identifiers necessary for accurate data linkage and follow-up (n = 9); and 3) duplicate records from multiple hospital admissions for the same index procedure (n = 42). After these exclusions were applied, 709 patients constituted the final analysis cohort. On the basis of the IVUS assessment of the target lesion, the study population was stratified into three mutually exclusive groups according to the dual-parameter CAC severity classification: 1) no calcification (n = 417, 58.8%); 2) mild calcification (n = 168, 23.7%); and 3) severe calcification (n = 124, 17.5%). A detailed flowchart illustrating the patient screening, exclusion, and enrollment process is provided in Fig. 1 . 2.2 Assessment of CAC Severity by IVUS Assessment of CAC severity was performed exclusively on the preintervention IVUS pullback of the target lesion intended for treatment. Automated IVUS pullback was performed at 1 mm/s (30 frames/s) via an iLab™ Polaris Multi-Modality Guidance System (Boston Scientific). Offline analysis was conducted via proprietary Image Viewer software (version 1.6). The analysis was carried out independently by two experienced interventional cardiologists, each with over 5 years of dedicated IVUS interpretation experience. Both analysts were blinded to all the clinical data, procedural details, and patient outcomes to minimize assessment bias. The target lesion was carefully reviewed frame-by-frame. Calcification was defined according to established IVUS criteria as a well-delineated, bright (hyperechoic) lesion located within the vessel wall, with acoustic shadowing that obscured the underlying arterial architecture and the adventitia. 12 For each calcified lesion, two key parameters were measured: 1) Maximum calcium arc: The largest angular extent of calcium measured in degrees (°) within a single cross-sectional frame anywhere along the lesion. 2) Calcium Length: The longitudinal extent of continuous or contiguous calcification measured in millimeters (mm) along the pullback. On the basis of the maximum calcium arc and calcium length, patients were stratified into three groups using predefined, dual-parameter criteria: 1) No calcification: no detectable calcium deposit was observed anywhere within the target lesion. 2) Mild calcification: the presence of calcium that does not meet the criteria for severe calcification. Specifically, this included lesions where the maximum calcium arc was ≤ 180° or where the calcium length was ≤ 5 mm. 3) Severe calcification: the presence of calcium meeting both of the following criteria: maximum calcium arc > 180° AND calcium length > 5 mm. 7 Representative IVUS images illustrating calcification are provided in Fig. 2 . This dual-parameter classification scheme was chosen to identify a subgroup with extensive, "high-burden" calcification that is likely to pose significant technical challenges. Any discrepancies in measurements or classification between the two primary analysts were resolved by joint rereview and consensus. In cases of persistent disagreement, a third senior interventional cardiologist was consulted for final adjudication. 2.3 Data collection Study data were systematically extracted from institutional electronic medical records and supplemented by structured telephone follow-ups conducted by trained coordinators via a standardized script. This multisource approach aimed to verify patient status, identify unreported hospitalizations, and ensure data completeness for endpoint ascertainment. The collected variables included demographics, medical history, laboratory parameters, clinical presentation, comorbidities, discharge medications, and detailed procedural characteristics. Sex-disaggregated data were collected for all baseline variables to enable sex-based analyses. 2.4 Study Endpoints and Follow-up Patients were followed from the index procedure until the occurrence of a primary endpoint event, death from any cause, loss to follow-up, or the administrative censoring date (September 30, 2025), whichever occurred first. The primary endpoint was the composite of MACEs, defined as the occurrence of any of the following: 1) cardiovascular death, 2) nonfatal myocardial infarction (MI), 3) ischemic stroke, 4) clinically driven target vessel revascularization (TVR), 5) hospitalization for heart failure, or 6) angiographically confirmed ISR. The secondary endpoints were the individual components of the primary composite endpoint, which were analyzed separately. Endpoint ascertainment was performed through a rigorous, multisource approach. First, the hospital's EMR system was interrogated for any records of readmission, emergency department visits, or outpatient clinic notes indicating a potential event. Second, data from the structured telephone follow-ups were integrated. All identified potential endpoint events were then submitted to an independent Clinical Events Committee (CEC) for blinded adjudication. The CEC comprised two experienced cardiologists and one neurologist (for stroke events) who was not involved in the patient's care or the IVUS analysis. The committee reviewed all available source documents (discharge summaries, procedure reports, lab results, and imaging reports) against prespecified, standardized definitions to confirm or reject each event and classify its type. Endpoint definitions adhered to contemporary consensus standards: Cardiovascular death: death due to acute MI, sudden cardiac death, heart failure, stroke, cardiovascular complications, cardiovascular hemorrhage, or other established cardiovascular causes. 13 Nonfatal MI: Diagnosis according to the Fourth Universal Definition of MI. 14 Ischemic stroke: A new focal neurological deficit of cerebrovascular origin lasting ≥ 24 hours or leading to death, confirmed by neurologist assessment and neuroimaging (CT/MRI). 15 TVR: Percutaneous intervention or surgical bypass of any segment within the entire major coronary vessel previously treated was repeated. Hospitalization for heart failure: An inpatient admission or urgent visit characterized by the requirement for intravenous diuretics due to new or worsening heart failure, with supporting objective evidence (e.g., pulmonary edema on X-ray, echocardiographic dysfunction, or elevated natriuretic peptides). 16 ISR: Luminal renarrowing ≥ 50% within the stent or its 5-mm margins on follow-up angiography is associated with recurrent symptoms or objective evidence of ischemia. 17 2.5 Statistical analysis Categorical variables are presented as numbers and percentages. Continuous variables were assessed for normality via the Shapiro‒Wilk test (significance level set at p < 0.05) and visual inspection of histograms. As most variables deviated from a normal distribution, they are summarized as medians with interquartile ranges (IQRs). Baseline characteristics across the three CAC severity groups (none, mild, severe) were compared via the Kruskal‒Wallis test for continuous variables and the chi‒square test (or Fisher’s exact test, where appropriate) for categorical variables. If a significant overall difference was detected (p < 0.05), post hoc pairwise comparisons were performed with a Bonferroni correction. The cumulative incidence of MACEs was estimated via the Kaplan‒Meier method, and differences between groups were compared via the log-rank test. To evaluate the independent associations between CAC severity and clinical outcomes, multivariable Cox proportional hazards regression models were employed. The proportional hazards assumption was assessed via Schoenfeld residual plots and was found to be satisfied. Two modeling strategies were used for determining CAC severity: Ordinal Model: CAC severity was treated as an ordinal variable (0 = no, 1 = mild, 2 = severe). The adjusted hazard ratio (aHR) represents the risk per-category increase, providing a test for trend. For the categorical model, CAC severity was treated as a nominal variable, with the "no" group as the reference. Separate aHRs were calculated for the "mild vs. no" and "severe vs. no" comparisons. Covariates for adjustment were selected a priori on the basis of established clinical relevance from the literature and their association with exposure or outcome in univariate analysis (p < 0.10). The adjustment set included age, sex, smoking, hypertension, dyslipidemia, diabetes mellitus, estimated glomerular filtration rate, hemoglobin A1c, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), lipoprotein(a), high-sensitivity C-reactive protein, and left ventricular ejection fraction. The specific covariates included in each final model are detailed in the respective table footnotes. The missing data were addressed as follows: the proportion of missing data for any individual variable was minimal (< 5%). On the basis of the pattern and mechanism, the data were assumed to be missing completely at random (MCAR). For continuous variables with missing values, imputation was performed using the median value of the respective CAC severity group (no, mild, or severe). The categorical variables had no missing data. A complete-case analysis was then applied for the regression modeling. A two-sided p value < 0.05 was considered statistically significant. All the statistical analyses were conducted via R software (version 4.5.2). During the preparation of this work, the authors used DeepSeek solely to refine the language and improve readability. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article. 3. Results 3.1 Baseline characteristics A total of 709 patients formed the final study cohort. The patients were stratified into three groups on the basis of preprocedural IVUS assessment: no calcification (n = 417, 58.8%), mild calcification (n = 168, 23.7%), and severe calcification (n = 124, 17.5%). The baseline demographic, clinical, and laboratory characteristics of the overall population and across the three groups are presented in Table 1 . Table 1 Baseline Characteristics According to Coronary Artery Calcification Severity Overall No Calcification Mild Calcification Severe Calcification P (n = 709) n = 417 (58.8%) n = 168 (23.7%) n = 124 (17.5%) value Patient demographics Age, years 65 (58, 71) 64 (57, 69) 66 (59, 72) 68 (61, 75) < 0.001 Gender, n (%) 0.279 Male 543 (76.6) 328 (78.7) 125 (74.4) 90 (72.6) Female 166 (23.4) 89 (21.3) 43 (25.6) 34 (27.4) Body mass index, kg/m² 23.8 (21.8, 25.7) 23.8 (21.7, 25.5) 23.8 (21.8, 26.0) 23.8 (22.1, 25.6) 0.996 SBP, mmHg 135 (121, 154) 135 (122, 153) 135 (120, 155) 136 (119, 156) 0.905 DBP, mmHg 79 (71, 89) 80 (71, 90) 78 (71, 88) 78 (71, 88) 0.455 Medical history, n (%) Smoking 207 (29.2) 127 (30.5) 53 (31.6) 27 (21.8) 0.130 Hypertension 420 (59.2) 229 (54.9) 104 (61.9) 87 (70.2) 0.007 Dyslipidemia 136 (19.2) 81 (19.4) 34 (20.2) 21 (16.9) 0.763 Diabetes mellitus 240 (33.9) 127 (30.5) 61 (36.3) 52 (41.9) 0.045 Prior myocardial infarction 134 (18.9) 76 (18.2) 36 (21.4) 22 (17.7) 0.627 Prior PCI 222 (31.3) 132 (31.7) 47 (28.0) 43 (34.7) 0.462 Laboratory uric acid, µmol/L 365 (309, 430) 365 (305, 419) 365 (302, 429) 369 (320, 449) 0.161 Hemoglobin A1c, % 6.3 (5.9, 7.1) 6.3 (5.8, 6.8) 6.3 (6.1, 7.2) 6.3 (6.0, 7.5) 0.016 eGFR, mL/min/1.73 m² 89.0 (72.0, 101.0) 92.3 (76.0, 104.0) 84.7 (70.0, 97.7) 82 (60.5, 94.0) < 0.001 Triglycerides, mmol/L 1.37 (0.97, 1.94) 1.37 (0.97, 1.92) 1.37 (0.99, 2.05) 1.34 (0.96, 1.97) 0.876 Total cholesterol, mmol/L 4.64 (3.71, 5.46) 4.64 (3.72, 5.47) 4.71 (3.92, 5.52) 4.26 (3.45, 5.35) 0.059 LDL-C, mmol/L 2.84 (2.15, 3.58) 2.88 (2.21, 3.61) 2.9 (2.31, 3.68) 2.51 (1.93, 3.37) 0.004 HDL-C, mmol/L 1.06 (0.90, 1.23) 1.08 (0.93, 1.26) 1.02 (0.85, 1.24) 1.02 (0.86, 1.19) 0.027 Lipoprotein (a), mg/dL 11.1 (4.3, 27.5) 8.4 (3.7, 21.9) 16.1 (6.4, 36.6) 13.7 (6.5, 29.5) < 0.001 CK-MB, U/L 13 (10, 24) 13 (10, 24) 14 (9, 23.25) 14 (9, 24.25) 0.895 Cardiac troponin I, ng/ml 0.01 (0.01, 0.99) 0.01 (0.01, 0.82) 0.01 (0.01, 1.32) 0.01 (0.01, 1.40) 0.222 NT-proBNP, pg/mL 210 (64, 963) 147 (52, 685) 312 (92, 1292) 338 (102, 1728) < 0.001 hs-CRP, mg/L 3.28 (1.15, 8.66) 3.05 (1.12, 6.25) 3.98 (1.43, 13.65) 3.92 (1.09, 10.61) 0.014 LVEF, % 61 (54, 66) 62 (56, 66) 61 (54, 65) 59 (48, 64) < 0.001 Clinical presentation, n (%) 0.212 STEMI 106 (15.0) 66 (15.8) 26 (15.5) 14 (11.3) 0.450 NSTEMI 113 (15.9) 59 (14.2) 29 (17.3) 25 (20.2) 0.239 Unstable angina 367 (51.8) 225 (54.0) 86 (51.2) 56 (45.2) 0.224 Stable angina 123 (17.3) 67 (16.1) 27 (16.1) 29 (23.4) 0.148 Comorbidities, n (%) Aortic valve calcification 44 (6.2) 14 (3.4) 17 (10.1) 13 (10.5) 0.001 NAVC 20 (2.8) 6 (1.4) 4 (2.4) 10 (8.1) 0.001 Aortic Stenosis 5 (0.7) 1 (0.2) 1 (0.6) 3 (2.4) 0.038 Discharge Medications, n (%) ACEI/ARB 417 (58.8) 231 (55.4) 108 (64.3) 78 (62.9) 0.084 Beta-blocker 473 (66.7) 267 (64.0) 112 (66.7) 94 (75.8) 0.051 statins 693 (97.7) 408 (97.8) 163 (97.0) 122 (98.4) 0.724 Dual antiplatelet therapy 643 (90.7) 375 (89.9) 157 (93.5) 111 (89.5) 0.367 Aspirin 659 (92.9) 384 (92.1) 162 (96.4) 113 (91.1) 0.122 Clopidogrel 390 (55.0) 215 (51.6) 98 (58.3) 77 (62.1) 0.072 Ticagrelor 301 (42.5) 189 (45.3) 66 (39.3) 46 (37.1) 0.170 Note:Data are presented as median (interquartile range) for continuous variables and number (%) for categorical variables. P values were calculated using the Kruskal‒Wallis test for continuous variables and the χ² test or Fisher's exact test for categorical variables, as appropriate. Abbreviations: ACE-I/ARBs, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; CK-MB, creatine kinase myocardial band; DBP, diastolic blood pressure; eGFR, glomerular filtration rate; HDL-C, high-density lipoprotein; hs-CRP, high-sensitivity C-reactive protein; LDL-C, low-density lipoprotein; LVEF, left ventricular ejection fraction; NAVC, Nonaortic valve calcification; NSTEMI, non-ST segment elevation acute myocardial infarction; NT-proBNP, N-terminal pro-B type natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; STEMI, ST segment elevation acute myocardial infarction. Compared with patients with mild CAC (66 [59–72] years) and no CAC (64 [57–69] years; p < 0.001), patients with severe CAC were significantly older (median age 68 [IQR 61–75] years). The distribution of sex was similar across groups (p = 0.279). The prevalence of traditional cardiovascular risk factors follows a gradient with increasing calcification severity. Hypertension was present in 70.2% of the patients in the severe CAC group, whereas it was present in 61.9% of those in the mild CAC group and 54.9% of those in the non-CAC group (p = 0.007). Diabetes mellitus was also more common in the severe CAC group (41.9%) than in the mild (36.3%) and no CAC (30.5%) groups (p = 0.045). There were no significant differences in smoking history, dyslipidemia, prior MI, or prior PCI across the groups. Notable differences were observed in key laboratory parameters. Renal function, as measured by the eGFR, progressively worsened with increasing CAC severity (median eGFRs: 92.3, 84.7, and 82.0 mL/min/1.73 m² for the no, mild, and severe groups, respectively; p < 0.001). Lipid profiles revealed that patients with severe CAC had significantly lower levels of LDL-C (p = 0.004) and HDL-C (p = 0.027), likely reflecting more intensive statin therapy or more advanced metabolic disease. The levels of lipoprotein(a), a genetically determined risk factor linked to atherosclerosis and calcification, were markedly greater in both calcified groups and highest in the mild CAC group (median 16.1 mg/dL) than in the non-CAC group (8.4 mg/dL; p < 0.001). Markers of hemodynamic stress and inflammation, NT-proBNP and hs-CRP, were also significantly elevated in the severe CAC group (both p < 0.001 and p = 0.014, respectively). The left ventricular ejection fraction was lowest in the severe CAC group (median 59% vs. 62% in the no CAC group; p < 0.001). Furthermore, extracoronary calcific comorbidities, including aortic valve calcification (10.5% vs. 3.4% without CAC) and nonaortic valve calcification (8.1% vs. 1.4%; both p = 0.001), were strikingly more common in the severe CAC group. The clinical presentation at the index hospitalization did not differ significantly across groups (p = 0.212), with unstable angina being the most common presentation. Discharge medications, including high-intensity statins and dual antiplatelet therapy, were similarly prescribed across groups, indicating comparable guideline-directed medical therapy post-PCI. 3.2 Procedural characteristics The detailed procedural characteristics are summarized in Table 2 . The left anterior descending artery was the most frequently assessed target vessel by IVUS across all groups (71.7% overall). There were no significant differences in the distribution of target vessels or in the prevalence of complex lesion morphologies such as bifurcations or ISR among the groups. However, chronic total occlusions were less common in the mild CAC group (1.2%) than in the no CAC group (5.8%, p = 0.038). Table 2 Procedural Characteristics of PCI According to Coronary Artery Calcification Severity Overall No Calcification Mild Calcification Severe Calcification P value (n = 709) n = 417 (58.8%) n = 168 (23.7%) n = 124 (17.5%) Target vessel assessed by IVUS, n (%) LM 147 (20.7) 87 (20.9) 37 (22.0) 23 (18.5) 0.765 LAD 508 (71.7) 293 (70.3) 118 (70.2) 97 (78.2) 0.202 LCX 103 (14.5) 66 (15.8) 26 (15.5) 11 (8.9) 0.143 RCA 162 (22.8) 93 (22.3) 44 (26.2) 25 (20.2) 0.440 Lesion characteristics, n(%) Bifurcation 30 (4.2) 19 (4.6) 8 (4.8) 3 (2.4) 0.541 Chronic total occlusion 30 (4.2) 24 (5.8) 2 (1.2) 4 (3.2) 0.038 In-stent restenosis 96 (13.5) 56 (13.4) 21 (12.5) 19 (15.3) 0.780 Procedural details, n(%) Treated with stent implantation 576 (81.2) 320 (76.7) 151 (89.9) 105 (84.7) 0.001 Single stent 225 (31.7) 150 (36.0) 46 (27.4) 29 (23.4) 0.012 Multiple stents 351 (49.5) 170 (40.8) 105 (62.5) 76 (61.3) < 0.001 Treated with DEB 96 (13.5) 60 (14.4) 17 (10.1) 19 (15.3) 0.321 Single DEB 73 (10.3) 42 (10.1) 14 (8.3) 17 (13.7) 0.319 Multiple DEB 23 (3.2) 18 (4.3) 3 (1.8) 2 (1.6) 0.156 Intraprocedural adjunctive therapy, n(%) Intraprocedural use of GPI 130 (18.3) 83 (19.9) 30 (17.9) 17 (13.7) 0.289 Intraprocedural use of IABP 17 (2.4) 7 (1.7) 4 (2.4) 6 (4.8) 0.130 Rotational atherectomy 24 (3.4) 1 (0.2) 2 (1.2) 21 (16.9) < 0.001 Note:Data are presented as number (percentage). P values were calculated using the χ² test or Fisher's exact test, as appropriate. Abbreviations: DEB, drug-eluting balloon; GPI, glycoprotein IIb/IIIa inhibitor; IABP, intra-aortic balloon pump; IVUS, intravascular ultrasound; LAD, left anterior descending artery; LCX, left circumflex artery;LM, left main coronary artery; PCI, percutaneous coronary intervention; RCA, right coronary artery. The surgical strategy differed markedly on the basis of calcification severity. The overall rate of stent implantation was 81.2%. Patients with any degree of calcification (mild or severe) were significantly more likely to be treated with stent implantation (89.9% and 84.7%, respectively) than were those with no CAC (76.7%, p = 0.001). Moreover, the use of multiple stents was substantially more common in the calcified groups (62.5% mild, 61.3% severe) than in the non-CAC group (40.8%, p < 0.001), suggesting longer or more complex disease in calcified segments. The use of drug-eluting balloons as a primary or adjunctive strategy did not differ significantly. As anticipated, the utilization of rotational atherectomy, a specific technique for modifying severe calcium, was overwhelmingly concentrated in the severe CAC group. Rotational atherectomy was used in 16.9% of patients with severe CAC, compared with only 1.2% in the mild CAC group and a negligible 0.2% in the no CAC group (p < 0.001). The use of other intraprocedural adjunctive therapies, such as glycoprotein IIb/IIIa inhibitors or intra-aortic balloon pump support, was similar across groups. 3.3 Associations between CAC Severity and Clinical Outcomes The median duration of clinical follow-up was 18.6 months (IQR 15.5–23.2 months). During this period, 122 patients (17.2% of the cohort) experienced the primary composite endpoint of MACEs. The unadjusted cumulative event rates are shown in the Kaplan‒Meier curve (Fig. 3 ), demonstrating a clear separation among the three groups, with the highest event rate in the severe CAC group. The Kaplan‒Meier curves for each secondary endpoint are presented in the supplementary figure. This risk stratification based on the dual-parameter IVUS criteria clearly differentiated the long-term prognosis among the three groups. The independent associations between CAC severity and clinical outcomes after multivariable adjustment for potential confounders are presented in Table 3 (ordinal analysis) and Table 4 (categorical analysis). Table 3 Association Between Coronary Artery Calcification Severity and Clinical Outcomes Event,n (%) Overall No Calcification Mild Calcification Severe Calcification aHR (95% CI) P for Trend (n = 709) n = 417 (58.8%) n = 168 (23.7%) n = 124 (17.5%) Primary Endpoint Composite MACEs 122 (17.2) 56 (13.4) 34 (20.2) 32 (25.8) 1.30 (1.04–1.63) 0.021 Secondary Endpoints Cardiovascular death 15 (2.1) 6 (1.4) 2 (1.2) 7 (5.6) 1.50 (0.83–2.72) 0.180 Nonfatal MI 3 (0.4) 0 2 (1.2) 1 (0.8) — — Stroke 15 (2.1) 5 (1.2) 4 (2.4) 6 (4.8) 1.88 (0.99–3.56) 0.054 TVR 57 (8.0) 26 (6.2) 14 (8.3) 17 (13.7) 1.55 (1.12–2.15) 0.008 Heart failure 12 (1.7) 3 (0.7) 3 (1.8) 6 (4.8) 1.65 (0.76–3.58) 0.201 In-stent restenosis 70 (9.9) 37 (8.9) 19 (11.3) 14 (11.3) 1.09 (0.80–1.48) 0.589 Note: Data are presented as number (percentage). Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) are presented for a per 1-grade increase in coronary artery calcification severity (modeled as an ordinal variable: no calcification = 0, mild = 1, severe = 2). The Cox proportional hazards model was adjusted for the following covariates: age, sex, smoking, hypertension, dyslipidemia, diabetes mellitus, estimated glomerular filtration rate, hemoglobin A1c, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipoprotein(a), high-sensitivity C-reactive protein, and left ventricular ejection fraction. The dash (—) indicates that the aHR was not estimated due to an insufficient number of events. Abbreviations: aHR, adjusted hazard ratio; CI, confidence interval; MACEs, major adverse cardiovascular events; MI, myocardial infarction; TVR, target vessel revascularization. Table 4 Associations Between Coronary Artery Calcification Severity Categories and Clinical Outcomes comparison aHR (95% CI) P value Primary Endpoint Composite MACEs Mild vs No 1.42 (0.92–2.20) 0.118 Severe vs No 1.67 (1.06–2.65) 0.028 Secondary Endpoints Cardiovascular death Mild vs No 0.48 (0.11–2.17) 0.343 Severe vs No 2.49 (0.89–6.91) 0.081 Nonfatal MI Mild vs No — — Severe vs No — — Stroke Mild vs No 1.88 (0.49–7.23) 0.355 Severe vs No 3.53 (0.98–12.71) 0.054 TVR Mild vs No 1.37 (0.70–2.68) 0.356 Severe vs No 2.45 (1.28–4.68) 0.007 Heart failure Mild vs No 2.31 (0.44–12.23) 0.324 Severe vs No 2.76 (0.56–13.60) 0.212 In-stent restenosis Mild vs No 1.21 (0.68–2.14) 0.519 Severe vs No 1.15 (0.60–2.19) 0.676 Note: The reference group is patients with no coronary artery calcification. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were derived from Cox proportional hazards models adjusted for the covariates listed in Table 3 . The dash (—) indicates that the aHR was not estimated due to an insufficient number of events. Abbreviations: aHR, adjusted hazard ratio; CI, confidence interval; MACEs, major adverse cardiovascular events; MI, myocardial infarction; TVR, target vessel revascularization. When CAC severity was modeled as an ordinal variable (none = 0, mild = 1, severe = 2), each incremental increase in calcification severity was independently associated with a 30% greater risk of composite MACEs (aHR 1.30, 95% confidence interval [CI] 1.04–1.63; P for trend = 0.021). This relationship was also significant for the risk of TVR, with an aHR of 1.55 (95% CI 1.12–2.15, p = 0.008) per severity grade increase. The risk ratio forest plot for each endpoint event is shown in Fig. 4 . In the categorical analysis using the non-CAC group as the reference (Table 4 , visualized in Fig. 5 ), the risk pattern was nuanced: Severe CAC vs. non-CAC: Patients with severe CAC had a 67% greater risk of experiencing composite MACEs (aHR 1.67, 95% CI 1.06–2.65; p = 0.028). Their risk of requiring repeat intervention was even more pronounced, with a 2.45-fold higher risk of TVR (aHR 2.45, 95% CI 1.28–4.68; p = 0.007). The risk of ischemic stroke was numerically elevated (aHR 3.53), with borderline significance (p = 0.054). Mild CAC vs. no CAC: In contrast, patients with mild calcification did not have a statistically significant increase in the risk of composite MACEs (HR 1.42, 95% CI 0.92–2.20; p = 0.118) or any of the individual secondary endpoints, including TVR (aHR 1.37, p = 0.356), compared with those with no calcification. The number of observed nonfatal myocardial infarction events was very low (n = 3 overall), precluding meaningful adjusted analysis for this specific endpoint. Risks for cardiovascular death, heart failure hospitalization, and ISR were not significantly different across groups in the categorical comparisons after multivariable adjustment. 4. Discussion 4.1 Main Findings This IVUS-guided cohort study provides robust, real-world evidence that a refined, dual-parameter assessment of CAC effectively stratifies post-PCI prognosis. Our principal finding is that severe calcification, defined by the coexistence of a maximal arc > 180° and a longitudinal length > 5 mm on preprocedural IVUS, is a potent and independent predictor of adverse clinical outcomes, most notably, a 2.45-fold increased risk of TVR. Conversely, mild calcification—failing to meet both criteria—did not confer a statistically significant elevation in composite event risk compared with noncalcified lesions. Importantly, when modeled ordinarily, each incremental grade in calcification severity was associated with a 30% higher risk of MACEs, underscoring a continuum of risk aligned with atherosclerotic burden. However, the categorical analysis reveals a critical threshold effect: excessive hazard is concentrated in the “severe” phenotype. This delineation moves beyond a simplistic binary (present/absent) assessment and advocates for a nuanced, severity-graded approach integral to a personalized interventional strategy. The mechanistic underpinnings of this risk are multifactorial and profound. Lesions meeting the severe criteria represent extensive, confluent calcific plates that create a long, noncompliant segment. 18 This architecture fundamentally challenges PCI mechanics: it impedes optimal balloon expansion, predisposes patients to asymmetric stent deployment, and increases the risk of stent underexpansion and malapposition—established precursors of stent failure, including restenosis and thrombosis. 19 , 20 The pronounced association with TVR directly reflects these technical pitfalls. In addition to mechanics, severe CAC may signify a more advanced, systemic atherosclerotic phenotype. 21 The elevated levels of lipoprotein(a), NT-proBNP, and hs-CRP, alongside a higher prevalence of extracoronary valvular calcification observed in this group, support this notion. The trend toward increased stroke risk, albeit requiring validation, further hints at a diffuse, high-risk vascular state prone to thromboembolic complications. 22 Thus, severe CAC identified by IVUS is not merely a local barrier to stent delivery but also a likely marker of aggressive, systemic vascular disease. 4.2 Comparison with Prior Studies and Contexts within the Field Our findings substantiate and significantly extend the existing knowledge on CAC. Prior studies have consistently linked IVUS-detected calcium, particularly arcs > 180° or > 270°, to procedural complexity and acute complications. 23 , 24 Observational data and trial subanalyses have associated such calcium with higher rates of target lesion failure. However, a key limitation has been the predominant focus on the calcium arc in isolation, which neglects its three-dimensional morphology. 9 , 11 Our work validates the evolving expert consensus that emphasizes integrating calcium length into clinical assessment. Biomechanical models and clinical experience suggest that long, continuous calcific sheets are more resistant to fracture and adequate preparation than focal nodules are. 25 By empirically demonstrating that the combination of arc and length identifies a subgroup at markedly elevated long-term risk, our dual-parameter model provides a more precise and clinically actionable risk stratification tool than either parameter alone. Our findings extend those of prior studies by demonstrating that a dual-parameter assessment that integrates both arc and length provides superior prognostic stratification compared with single-parameter (arc alone) approaches. While optical coherence tomography (OCT) offers superior resolution for measuring calcium thickness and discriminating superficial calcium from deep calcium, IVUS provides a more comprehensive assessment of calcium distribution and its relationship to the vessel wall. The ability of ultrasound to characterize the overall plaque architecture around calcific deposits is crucial for procedural planning. 26 Our proposed criteria complement the recently emphasized importance of “calcium modification” in complex PCI. They offer a practical, immediately applicable method to identify lesions that may benefit most from advanced plaque-modifying techniques (e.g., rotational/orbital atherectomy, intravascular lithotripsy) before stent deployment, aligning with the proactive strategy advocated in current best practices. 27 , 28 Furthermore, our results resonate with and reinforce findings from major trials underscoring the value of intravascular imaging-guided PCI. While pivotal trials such as ULTIMATE and RENOVATE-COMPLEX-PCI have demonstrated the clinical benefit of intravascular imaging (IVUS or OCT) guidance for PCI overall and for complex lesions, 29,30 our analyses focus on a specific, high-risk substrate—severe CAC—within that broad population. We provide granularity, showing that even under IVUS guidance, this lesion subset carries a residual high risk, thereby identifying an arena for further therapeutic refinement. The lack of significant risk elevation in the mild CAC group is a pivotal and reassuring finding, suggesting that standard contemporary PCI techniques under imaging guidance are sufficient for this subset, preventing overtreatment. 4.3 Clinical Implications and Future Directions The clinical translation of our findings is direct and impactful. The dual-parameter IVUS assessment provides a clear, preprocedural triage tool: Severe CACs (Arc > 180° & Length > 5 mm): This flags a high-risk lesion. Our data strongly support the routine consideration of dedicated calcium-modifying strategies (e.g., rotational/orbital atherectomy, intravascular lithotripsy) to achieve adequate lesion preparation prior to stenting. 31 This may improve stent expansion and apposition, with the goal of mitigating the identified excess TVR risk. Post-PCI, these patients warrant intensified surveillance, rigorous optimization of guideline-directed medical therapy (especially aggressive lipid lowering), and thorough patient education on symptom recognition. 32 For mild CAC, the absence of significant excess risk suggests that standard balloon angioplasty and stent implantation, guided by IVUS to ensure optimal results, 29 constitute an appropriate strategy. This prevents the unnecessary use of higher-cost and potentially higher-risk adjunctive technologies. For risk prediction, this stratification can be integrated into pre-PCI risk scores and patient counseling, setting realistic expectations regarding long-term prognosis. 32 Future research must build upon this foundation. First, prospective, multicenter validation of this dual-parameter classification is essential. Second, investigating its integrative value with other high-risk plaque features (e.g., thin-cap fibroatheroma, large lipid core) assessed by near-infrared spectroscopy or OCT could yield a comprehensive vulnerability profile. 33 Third, and most critically, randomized controlled trials are needed to determine whether a systematic, protocol-driven approach to severe CAC—mandating the use of specific calcium-modification technologies—can successfully abrogate the excess TVR risk we observed. 31 Such studies would move from risk stratification to evidence-based intervention, ultimately defining the optimal care pathway for this challenging patient cohort. 4.4 Limitations Several limitations merit consideration. The single-center, retrospective design inherently carries risks of unmeasured confounding and may affect generalizability, although our rigorous adjustment and adjudication processes mitigate some concerns. Treatment selection bias exists, as the use of rotational atherectomy is operator dependent; however, its pronounced use in the severe CAC group reinforces the clinical validity of our classification. The low event rates for certain individual endpoints (e.g., myocardial infarction) limit the power of those specific analyses. While the follow-up duration is clinically relevant for stent-related events, longer-term follow-up would clarify the durability of this risk. Finally, we did not account for other calcium characteristics, such as thickness or nodularity, which have been shown to correlate with procedural success and outcomes in more detailed imaging studies and may offer further prognostic refinement. 34 5. Conclusion In patients undergoing PCI, severe CAC, defined by preprocedural IVUS as a maximal arc > 180° coexisting with a length > 5 mm, is a powerful, independent determinant of adverse outcomes, particularly a nearly 2.5-fold increased risk of repeat revascularization. This practical dual-parameter assessment transcends simple detection to enable meaningful preprocedural risk stratification. It effectively distinguishes high-risk lesions that may necessitate specialized preparation and closer follow-up from lower-risk calcified lesions manageable with conventional techniques. By facilitating more precise and personalized therapeutic decision-making in the catheterization laboratory, this approach holds promise for improving the long-term prognosis of patients with this challenging coronary substrate. Abbreviations ACEI: Angiotensin-converting enzyme inhibitor; aHR: Adjusted hazard ratio; ARB: Angiotensin receptor blocker; CAC: Coronary artery calcification; CEC: Clinical Events Committee; CI: Confidence interval; CTO: Chronic total occlusion; DEB: Drug-eluting balloon; eGFR: Estimated glomerular filtration rate; EMR: Electronic medical record; GPI: Glycoprotein IIb/IIIa inhibitor; HDL-C: High-density lipoprotein cholesterol; hs-CRP: High-sensitivity C-reactive protein; IABP: Intra-aortic balloon pump; IQR: Interquartile range; ISR: In-stent restenosis; IVUS: Intravascular ultrasound; LAD: Left anterior descending artery; LCX: Left circumflex artery; LDL-C: Low-density lipoprotein cholesterol; LM: Left main coronary artery; LVEF: Left ventricular ejection fraction; MACE: Major adverse cardiovascular event; MI: Myocardial infarction; NAVC: Non-aortic valve calcification; NSTEMI: Non-ST-segment elevation myocardial infarction; NT-proBNP: N-terminal pro-B-type natriuretic peptide; OCT: Optical coherence tomography; PCI: Percutaneous coronary intervention; RCA: Right coronary artery; STEMI: ST-segment elevation myocardial infarction; TVR: Target vessel revascularization. Declarations Ethics approval and consent to participate The study was approved by the Ethics Committee of The Second Affiliated Hospital of Hainan Medical University (Approval No. LW2022035) and was conducted in accordance with the Declaration of Helsinki. The requirement for written informed consent was waived by the Ethics Committee for this retrospective analysis of deidentified data. Consent for publication Not applicable. Availability of data and materials The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. Competing interests The authors declare that they have no competing interests. Funding This study was supported by the National Natural Science Foundation of China (82360063), the Natural Science Foundation of Hainan Province (High Level Talents Project) (821RC1127), and the Key Research and Development Project of Hainan Province (Social Development) (ZDYF2022SHFZ070). Authors’ contributions SX: Conceptualization, methodology, software, formal analysis, investigation, data curation, writing – original draft, and visualization. MZ: Investigation, Resources, Validation, Writing – review & editing. YL: Investigation, Validation, Data curation, Visualization. YM: Investigation, Data curation. YC: Supervision, Project administration, Conceptualization, Writing – review & editing. Acknowledgments The authors thank Boston Scientific for providing technical support. We also thank our clinical colleagues, nursing staff, and independent clinical events committee for their assistance. References Onnis C, Virmani R, Kawai K, Nardi V, Lerman A, Cademartiri F, et al. Coronary Artery Calcification: Current Concepts and Clinical Implications. Circulation. 2024 Jan 16;149(3):251–66. Budoff MJ, Shaw LJ, Liu ST, Weinstein SR, Mosler TP, Tseng PH, et al. Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8629286","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591149892,"identity":"9cb955ef-ebb3-4ee5-b8a3-662d284819b6","order_by":0,"name":"Shaowu Xiao","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Shaowu","middleName":"","lastName":"Xiao","suffix":""},{"id":591149893,"identity":"ec782443-85d0-4f70-9b3e-2621589494c4","order_by":1,"name":"Mengya Zeng","email":"","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Mengya","middleName":"","lastName":"Zeng","suffix":""},{"id":591149894,"identity":"14e3f113-bb90-4db5-bad1-35f8c8a9dd7f","order_by":2,"name":"Ying Liang","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Ying","middleName":"","lastName":"Liang","suffix":""},{"id":591149895,"identity":"0b2ae846-7ecf-4dfc-a1a4-d53aac4d0a5e","order_by":3,"name":"Yingying Mo","email":"","orcid":"","institution":"Hainan Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yingying","middleName":"","lastName":"Mo","suffix":""},{"id":591149896,"identity":"24823561-9831-4bfb-bc54-1cc8870b3f42","order_by":4,"name":"Yuewu Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2klEQVRIiWNgGAWjYPACmwQGZgiLsYFILWmkazmcAGMR1sIvkWP4mLftfB5/O+/RDT8YbGQ3HGB+9gCfFskZOcbGvG23iyUO86Xd7GFIM95wgM3cAJ8Wgxs5ZtK5bbcTGw7zmN0GujBxwwEeNgl8Wuxv5Jj/zm07lzgfouU/YS0GEjlmzLltBxI3QLQcIKxF4syzYuk/55ITNwK13OwxSDaeeZjNDK8W/vbkjR9nlNklzjt/xuzGjwo72b7jzc/wamEQSEBxJxAz41UPsuYAIRWjYBSMglEw4gEAPKVKfdeIKVMAAAAASUVORK5CYII=","orcid":"","institution":"The Second Affiliated Hospital of Hainan Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yuewu","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2026-01-18 05:23:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8629286/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8629286/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102908713,"identity":"d97099e5-4fc5-4232-9cfe-7c90556644bc","added_by":"auto","created_at":"2026-02-18 09:52:01","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":95877,"visible":true,"origin":"","legend":"\u003cp\u003ePatient screening and study cohort flow diagram.\u003c/p\u003e\n\u003cp\u003eIVUS,intravascular ultrasound.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/bdf1f3b1764b8d3e71c93ed3.png"},{"id":102908709,"identity":"6750c033-1bd4-492f-9c28-dd59535fbd36","added_by":"auto","created_at":"2026-02-18 09:52:00","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":173924,"visible":true,"origin":"","legend":"\u003cp\u003eRepresentative intravascular ultrasound (IVUS) images showing different degrees of calcification. (A) No calcification. (B) Mild calcification. (C) Severe calcification. Figures from authors’ organization.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/2ef1fe117b2f6a01c054c48c.png"},{"id":102908711,"identity":"117f503b-920f-46ad-a4c9-a69215c08e7c","added_by":"auto","created_at":"2026-02-18 09:52:01","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":83713,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier Curves for the primary composite endpoint of MACEs.\u003c/p\u003e\n\u003cp\u003eMACEs, major adverse cardiovascular events.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/ca5276b9f215eaf34bec33c9.png"},{"id":102963533,"identity":"64031cdd-6c85-4ded-b8af-51c2167c3f7d","added_by":"auto","created_at":"2026-02-19 04:18:40","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":138815,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for the ordinal association between coronary artery calcification severity and clinical outcomes.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/81b7c0a134b81ae599b0786e.png"},{"id":102964467,"identity":"21a5d4d7-05c0-4a3e-ad6c-6f53c528d7a0","added_by":"auto","created_at":"2026-02-19 04:22:24","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":80320,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot for the categorical association between coronary artery calcification severity and MACEs.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/62a2623365f127da2d6de61b.png"},{"id":109156213,"identity":"423d2b15-b399-47b5-b8ef-636f4d61cc36","added_by":"auto","created_at":"2026-05-13 06:45:25","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1141816,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/a2c14ec1-f407-48ef-8328-1b68b967d4c6.pdf"},{"id":102908710,"identity":"7262c702-e14c-4b41-aad8-9d757d52521a","added_by":"auto","created_at":"2026-02-18 09:52:01","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":22250,"visible":true,"origin":"","legend":"","description":"","filename":"supplementaryfigure.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/993d4bb3a5bf94921b51b762.pdf"},{"id":102908714,"identity":"caa445f0-5cbe-4708-b52e-49a873d450f3","added_by":"auto","created_at":"2026-02-18 09:52:01","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":346183,"visible":true,"origin":"","legend":"","description":"","filename":"CentralIllustraction.png","url":"https://assets-eu.researchsquare.com/files/rs-8629286/v1/eba3c93cbb531bc16dcfdd3e.png"}],"financialInterests":"No competing interests reported.","formattedTitle":"Dual-Parameter IVUS Assessment of Coronary Calcification Stratifies the Risk of Adverse Events after PCI: A Retrospective Cohort Study","fulltext":[{"header":"1. Background","content":"\u003cp\u003eCoronary artery calcification (CAC) is a well-established hallmark of advanced atherosclerosis, representing a complex, active process of mineral deposition within the arterial wall that is intimately linked to plaque burden, vulnerability, and overall cardiovascular risk.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Its presence and extent, traditionally assessed by coronary computed tomography angiography via the Agatston score, are powerful predictors of future cardiovascular events in both asymptomatic and symptomatic populations.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e In the context of percutaneous coronary intervention (PCI), CAC presents a formidable technical challenge. This impedes optimal stent delivery, expansion, and apposition, leading to higher rates of procedural complications, such as stent underexpansion, malapposition, and dissection, which in turn are precursors for adverse outcomes such as in-stent restenosis (ISR) and stent thrombosis.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWhile coronary angiography remains the primary imaging modality for guiding PCI, it provides only a two-dimensional lumenogram and is notoriously limited in its ability to accurately characterize vessel wall pathology, particularly the depth, distribution, and thickness of calcification.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e In contrast, intravascular ultrasound (IVUS) offers high-resolution, cross-sectional, in vivo visualization of the coronary vessel wall, enabling precise quantification of the calcification burden.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e The standard IVUS metric for calcification is the maximum calcium arc, with a threshold of \u0026gt;\u0026thinsp;180\u0026deg; (or occasionally\u0026thinsp;\u0026gt;\u0026thinsp;270\u0026deg;), which is often used to define \"severe\" calcium and is associated with difficulty in stent expansion.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e However, calcification is a three-dimensional entity. A focal, short segment of intense calcium may behave differently during intervention than may a long, continuous sheet of calcium, even if both share a similar maximal arc.\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e Recent studies and expert consensus have therefore highlighted the importance of incorporating calcium length into the assessment, suggesting that the interplay between arc and length better captures the true procedural complexity and potential biological impact of a calcified lesion.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDespite these advances in imaging characterization, a critical knowledge gap persists. Most prognostic studies linking CAC to outcomes have focused on its mere presence or used single-parameter thresholds (e.g., arc alone), which fail to capture the three-dimensional complexity of calcification.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e Therefore, the incremental prognostic value of a comprehensive dual-parameter (arc and length) stratification of CAC severity for predicting mid- to long-term clinical outcomes after PCI in a contemporary, real-world cohort receiving preprocedural IVUS guidance has not been fully established. Specifically, it remains unclear whether a graded risk exists across a spectrum from no calcification to mild and severe calcification, as defined by such composite criteria, and whether this risk is independent of traditional clinical and procedural factors.\u003c/p\u003e \u003cp\u003eThis study aimed to address this gap. We hypothesized that severe CAC, defined by stringent IVUS criteria requiring both a large arc (\u0026gt;\u0026thinsp;180\u0026deg;) and considerable length (\u0026gt;\u0026thinsp;5 mm), would be a stronger and independent predictor of major adverse cardiovascular events (MACEs) following PCI than would milder forms of calcification or its absence. By systematically investigating the associations between this detailed IVUS-based CAC severity stratification and clinical outcomes, we seek to provide a more refined tool for preprocedural risk assessment and to inform personalized management strategies for patients with calcified coronary lesions.\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Population\u003c/h2\u003e \u003cp\u003eThis was a single-center, retrospective, observational cohort study conducted at the Department of Cardiology, The Second Affiliated Hospital of Hainan Medical University. The study protocol was reviewed and approved by the Hospital Ethics Committee (Approval No. LW2022035) and was conducted in strict accordance with the ethical principles of the Declaration of Helsinki. Given the retrospective nature of the analysis using deidentified data, the requirement for written informed consent from individual patients was waived by the ethics committee.\u003c/p\u003e \u003cp\u003eThe study population consisted of consecutive patients with known or suspected coronary artery disease who were admitted for elective or urgent PCI. To be included, patients must have undergone both diagnostic or guiding coronary angiography and a preintervention IVUS examination of at least one target lesion between January 1, 2023, and July 31, 2024.\u003c/p\u003e \u003cp\u003eWe retrospectively screened the hospital's catheterization laboratory database. The initial search identified 762 unique patient records where an IVUS procedure using a Boston Scientific imaging system was documented in conjunction with coronary angiography during the specified period. A comprehensive, manual review of electronic medical records was subsequently performed for all identified patients. On the basis of this review, 53 patients were excluded according to the following prespecified criteria: 1) poor-quality IVUS images precluding reliable calcium assessment (e.g., excessive noise, nonuniform rotational distortion, inadequate penetration) (n\u0026thinsp;=\u0026thinsp;2); 2) missing unique patient identifiers necessary for accurate data linkage and follow-up (n\u0026thinsp;=\u0026thinsp;9); and 3) duplicate records from multiple hospital admissions for the same index procedure (n\u0026thinsp;=\u0026thinsp;42). After these exclusions were applied, 709 patients constituted the final analysis cohort.\u003c/p\u003e \u003cp\u003eOn the basis of the IVUS assessment of the target lesion, the study population was stratified into three mutually exclusive groups according to the dual-parameter CAC severity classification: 1) no calcification (n\u0026thinsp;=\u0026thinsp;417, 58.8%); 2) mild calcification (n\u0026thinsp;=\u0026thinsp;168, 23.7%); and 3) severe calcification (n\u0026thinsp;=\u0026thinsp;124, 17.5%). A detailed flowchart illustrating the patient screening, exclusion, and enrollment process is provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Assessment of CAC Severity by IVUS\u003c/h2\u003e \u003cp\u003eAssessment of CAC severity was performed exclusively on the preintervention IVUS pullback of the target lesion intended for treatment. Automated IVUS pullback was performed at 1 mm/s (30 frames/s) via an iLab\u0026trade; Polaris Multi-Modality Guidance System (Boston Scientific). Offline analysis was conducted via proprietary Image Viewer software (version 1.6). The analysis was carried out independently by two experienced interventional cardiologists, each with over 5 years of dedicated IVUS interpretation experience. Both analysts were blinded to all the clinical data, procedural details, and patient outcomes to minimize assessment bias. The target lesion was carefully reviewed frame-by-frame.\u003c/p\u003e \u003cp\u003eCalcification was defined according to established IVUS criteria as a well-delineated, bright (hyperechoic) lesion located within the vessel wall, with acoustic shadowing that obscured the underlying arterial architecture and the adventitia.\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e For each calcified lesion, two key parameters were measured: 1) Maximum calcium arc: The largest angular extent of calcium measured in degrees (\u0026deg;) within a single cross-sectional frame anywhere along the lesion. 2) Calcium Length: The longitudinal extent of continuous or contiguous calcification measured in millimeters (mm) along the pullback.\u003c/p\u003e \u003cp\u003eOn the basis of the maximum calcium arc and calcium length, patients were stratified into three groups using predefined, dual-parameter criteria: 1) No calcification: no detectable calcium deposit was observed anywhere within the target lesion. 2) Mild calcification: the presence of calcium that does not meet the criteria for severe calcification. Specifically, this included lesions where the maximum calcium arc was \u0026le;\u0026thinsp;180\u0026deg; or where the calcium length was \u0026le;\u0026thinsp;5 mm. 3) Severe calcification: the presence of calcium meeting both of the following criteria: maximum calcium arc\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; AND calcium length\u0026thinsp;\u0026gt;\u0026thinsp;5 mm.\u003csup\u003e7\u003c/sup\u003e Representative IVUS images illustrating calcification are provided in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThis dual-parameter classification scheme was chosen to identify a subgroup with extensive, \"high-burden\" calcification that is likely to pose significant technical challenges. Any discrepancies in measurements or classification between the two primary analysts were resolved by joint rereview and consensus. In cases of persistent disagreement, a third senior interventional cardiologist was consulted for final adjudication.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data collection\u003c/h2\u003e \u003cp\u003eStudy data were systematically extracted from institutional electronic medical records and supplemented by structured telephone follow-ups conducted by trained coordinators via a standardized script. This multisource approach aimed to verify patient status, identify unreported hospitalizations, and ensure data completeness for endpoint ascertainment. The collected variables included demographics, medical history, laboratory parameters, clinical presentation, comorbidities, discharge medications, and detailed procedural characteristics. Sex-disaggregated data were collected for all baseline variables to enable sex-based analyses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Study Endpoints and Follow-up\u003c/h2\u003e \u003cp\u003ePatients were followed from the index procedure until the occurrence of a primary endpoint event, death from any cause, loss to follow-up, or the administrative censoring date (September 30, 2025), whichever occurred first.\u003c/p\u003e \u003cp\u003eThe primary endpoint was the composite of MACEs, defined as the occurrence of any of the following: 1) cardiovascular death, 2) nonfatal myocardial infarction (MI), 3) ischemic stroke, 4) clinically driven target vessel revascularization (TVR), 5) hospitalization for heart failure, or 6) angiographically confirmed ISR. The secondary endpoints were the individual components of the primary composite endpoint, which were analyzed separately.\u003c/p\u003e \u003cp\u003eEndpoint ascertainment was performed through a rigorous, multisource approach. First, the hospital's EMR system was interrogated for any records of readmission, emergency department visits, or outpatient clinic notes indicating a potential event. Second, data from the structured telephone follow-ups were integrated. All identified potential endpoint events were then submitted to an independent Clinical Events Committee (CEC) for blinded adjudication. The CEC comprised two experienced cardiologists and one neurologist (for stroke events) who was not involved in the patient's care or the IVUS analysis. The committee reviewed all available source documents (discharge summaries, procedure reports, lab results, and imaging reports) against prespecified, standardized definitions to confirm or reject each event and classify its type.\u003c/p\u003e \u003cp\u003eEndpoint definitions adhered to contemporary consensus standards:\u003c/p\u003e \u003cp\u003e \u003col\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eCardiovascular death: death due to acute MI, sudden cardiac death, heart failure, stroke, cardiovascular complications, cardiovascular hemorrhage, or other established cardiovascular causes.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eNonfatal MI: Diagnosis according to the Fourth Universal Definition of MI.\u003csup\u003e14\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eIschemic stroke: A new focal neurological deficit of cerebrovascular origin lasting\u0026thinsp;\u0026ge;\u0026thinsp;24 hours or leading to death, confirmed by neurologist assessment and neuroimaging (CT/MRI).\u003csup\u003e15\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eTVR: Percutaneous intervention or surgical bypass of any segment within the entire major coronary vessel previously treated was repeated.\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eHospitalization for heart failure: An inpatient admission or urgent visit characterized by the requirement for intravenous diuretics due to new or worsening heart failure, with supporting objective evidence (e.g., pulmonary edema on X-ray, echocardiographic dysfunction, or elevated natriuretic peptides).\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003cspan\u003e \u003cli\u003e \u003cp\u003eISR: Luminal renarrowing\u0026thinsp;\u0026ge;\u0026thinsp;50% within the stent or its 5-mm margins on follow-up angiography is associated with recurrent symptoms or objective evidence of ischemia.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/li\u003e \u003c/span\u003e \u003c/ol\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Statistical analysis\u003c/h2\u003e \u003cp\u003eCategorical variables are presented as numbers and percentages. Continuous variables were assessed for normality via the Shapiro‒Wilk test (significance level set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and visual inspection of histograms. As most variables deviated from a normal distribution, they are summarized as medians with interquartile ranges (IQRs). Baseline characteristics across the three CAC severity groups (none, mild, severe) were compared via the Kruskal‒Wallis test for continuous variables and the chi‒square test (or Fisher\u0026rsquo;s exact test, where appropriate) for categorical variables. If a significant overall difference was detected (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), post hoc pairwise comparisons were performed with a Bonferroni correction.\u003c/p\u003e \u003cp\u003eThe cumulative incidence of MACEs was estimated via the Kaplan‒Meier method, and differences between groups were compared via the log-rank test. To evaluate the independent associations between CAC severity and clinical outcomes, multivariable Cox proportional hazards regression models were employed. The proportional hazards assumption was assessed via Schoenfeld residual plots and was found to be satisfied.\u003c/p\u003e \u003cp\u003eTwo modeling strategies were used for determining CAC severity:\u003c/p\u003e \u003cp\u003eOrdinal Model: CAC severity was treated as an ordinal variable (0\u0026thinsp;=\u0026thinsp;no, 1\u0026thinsp;=\u0026thinsp;mild, 2\u0026thinsp;=\u0026thinsp;severe). The adjusted hazard ratio (aHR) represents the risk per-category increase, providing a test for trend.\u003c/p\u003e \u003cp\u003eFor the categorical model, CAC severity was treated as a nominal variable, with the \"no\" group as the reference. Separate aHRs were calculated for the \"mild vs. no\" and \"severe vs. no\" comparisons.\u003c/p\u003e \u003cp\u003eCovariates for adjustment were selected a priori on the basis of established clinical relevance from the literature and their association with exposure or outcome in univariate analysis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.10). The adjustment set included age, sex, smoking, hypertension, dyslipidemia, diabetes mellitus, estimated glomerular filtration rate, hemoglobin A1c, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), lipoprotein(a), high-sensitivity C-reactive protein, and left ventricular ejection fraction. The specific covariates included in each final model are detailed in the respective table footnotes.\u003c/p\u003e \u003cp\u003eThe missing data were addressed as follows: the proportion of missing data for any individual variable was minimal (\u0026lt;\u0026thinsp;5%). On the basis of the pattern and mechanism, the data were assumed to be missing completely at random (MCAR). For continuous variables with missing values, imputation was performed using the median value of the respective CAC severity group (no, mild, or severe). The categorical variables had no missing data. A complete-case analysis was then applied for the regression modeling.\u003c/p\u003e \u003cp\u003eA two-sided p value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant. All the statistical analyses were conducted via R software (version 4.5.2).\u003c/p\u003e \u003cp\u003eDuring the preparation of this work, the authors used DeepSeek solely to refine the language and improve readability. After using this tool, the authors reviewed and edited the content as needed and take full responsibility for the content of the published article.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Baseline characteristics\u003c/h2\u003e \u003cp\u003eA total of 709 patients formed the final study cohort. The patients were stratified into three groups on the basis of preprocedural IVUS assessment: no calcification (n\u0026thinsp;=\u0026thinsp;417, 58.8%), mild calcification (n\u0026thinsp;=\u0026thinsp;168, 23.7%), and severe calcification (n\u0026thinsp;=\u0026thinsp;124, 17.5%). The baseline demographic, clinical, and laboratory characteristics of the overall population and across the three groups are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline Characteristics According to Coronary Artery Calcification Severity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMild Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSevere Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;709)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;417 (58.8%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;168 (23.7%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;124 (17.5%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003evalue\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePatient demographics\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge, years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e65 (58, 71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64 (57, 69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (59, 72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e68 (61, 75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGender, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e543 (76.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e328 (78.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e125 (74.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90 (72.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e166 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index, kg/m\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e23.8 (21.8, 25.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.8 (21.7, 25.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.8 (21.8, 26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23.8 (22.1, 25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.996\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSBP, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e135 (121, 154)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e135 (122, 153)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e135 (120, 155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e136 (119, 156)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDBP, mmHg\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (71, 89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (71, 90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78 (71, 88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78 (71, 88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.455\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMedical history, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e207 (29.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53 (31.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e27 (21.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e420 (59.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e229 (54.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (61.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e87 (70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDyslipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e136 (19.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e21 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (33.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e127 (30.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (41.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.045\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior myocardial infarction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134 (18.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76 (18.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (21.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22 (17.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.627\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrior PCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e222 (31.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e132 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e47 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.462\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLaboratory\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003euric acid, \u0026micro;mol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e365 (309, 430)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e365 (305, 419)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e365 (302, 429)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e369 (320, 449)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin A1c, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3 (5.9, 7.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.3 (5.8, 6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.3 (6.1, 7.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.3 (6.0, 7.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eeGFR, mL/min/1.73 m\u0026sup2;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e89.0 (72.0, 101.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92.3 (76.0, 104.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.7 (70.0, 97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82 (60.5, 94.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriglycerides, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.37 (0.97, 1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37 (0.97, 1.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.37 (0.99, 2.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.34 (0.96, 1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal cholesterol, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.64 (3.71, 5.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.64 (3.72, 5.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.71 (3.92, 5.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.26 (3.45, 5.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.059\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL-C, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.84 (2.15, 3.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.88 (2.21, 3.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.9 (2.31, 3.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.51 (1.93, 3.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL-C, mmol/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06 (0.90, 1.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.08 (0.93, 1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 (0.85, 1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.02 (0.86, 1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLipoprotein (a), mg/dL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.1 (4.3, 27.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.4 (3.7, 21.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.1 (6.4, 36.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.7 (6.5, 29.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCK-MB, U/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e13 (10, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (10, 24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (9, 23.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (9, 24.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.895\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac troponin I, ng/ml\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.01 (0.01, 0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.01 (0.01, 0.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01 (0.01, 1.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.01 (0.01, 1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-proBNP, pg/mL\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e210 (64, 963)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e147 (52, 685)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e312 (92, 1292)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e338 (102, 1728)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ehs-CRP, mg/L\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.28 (1.15, 8.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.05 (1.12, 6.25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.98 (1.43, 13.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.92 (1.09, 10.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF, %\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61 (54, 66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (56, 66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61 (54, 65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59 (48, 64)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eClinical presentation, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSTEMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e106 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e14 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.450\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNSTEMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e113 (15.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59 (14.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnstable angina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e367 (51.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e225 (54.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86 (51.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e56 (45.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.224\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStable angina\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e123 (17.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (16.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e29 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidities, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic valve calcification\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNAVC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (2.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10 (8.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAortic Stenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (0.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDischarge Medications, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e417 (58.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e231 (55.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e108 (64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78 (62.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.084\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBeta-blocker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e473 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267 (64.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e112 (66.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94 (75.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.051\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003estatins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e693 (97.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e408 (97.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e163 (97.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e122 (98.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.724\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDual antiplatelet therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e643 (90.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e375 (89.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e157 (93.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111 (89.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.367\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e659 (92.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e384 (92.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162 (96.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e113 (91.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eClopidogrel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e390 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e215 (51.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (58.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e77 (62.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTicagrelor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e301 (42.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e189 (45.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e66 (39.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e46 (37.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.170\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"1\" nameend=\"c7\" namest=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote:Data are presented as median (interquartile range) for continuous variables and number (%) for categorical variables. P values were calculated using the Kruskal‒Wallis test for continuous variables and the χ\u0026sup2; test or Fisher's exact test for categorical variables, as appropriate. \u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: ACE-I/ARBs, angiotensin-converting enzyme inhibitors/angiotensin receptor blockers; CK-MB, creatine kinase myocardial band; DBP, diastolic blood pressure; eGFR, glomerular filtration rate; HDL-C, high-density lipoprotein; hs-CRP, high-sensitivity C-reactive protein; LDL-C, low-density lipoprotein; LVEF, left ventricular ejection fraction; NAVC, Nonaortic valve calcification; NSTEMI, non-ST segment elevation acute myocardial infarction; NT-proBNP, N-terminal pro-B type natriuretic peptide; PCI, percutaneous coronary intervention; SBP, systolic blood pressure; STEMI, ST segment elevation acute myocardial infarction.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCompared with patients with mild CAC (66 [59\u0026ndash;72] years) and no CAC (64 [57\u0026ndash;69] years; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), patients with severe CAC were significantly older (median age 68 [IQR 61\u0026ndash;75] years). The distribution of sex was similar across groups (p\u0026thinsp;=\u0026thinsp;0.279). The prevalence of traditional cardiovascular risk factors follows a gradient with increasing calcification severity. Hypertension was present in 70.2% of the patients in the severe CAC group, whereas it was present in 61.9% of those in the mild CAC group and 54.9% of those in the non-CAC group (p\u0026thinsp;=\u0026thinsp;0.007). Diabetes mellitus was also more common in the severe CAC group (41.9%) than in the mild (36.3%) and no CAC (30.5%) groups (p\u0026thinsp;=\u0026thinsp;0.045). There were no significant differences in smoking history, dyslipidemia, prior MI, or prior PCI across the groups.\u003c/p\u003e \u003cp\u003eNotable differences were observed in key laboratory parameters. Renal function, as measured by the eGFR, progressively worsened with increasing CAC severity (median eGFRs: 92.3, 84.7, and 82.0 mL/min/1.73 m\u0026sup2; for the no, mild, and severe groups, respectively; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Lipid profiles revealed that patients with severe CAC had significantly lower levels of LDL-C (p\u0026thinsp;=\u0026thinsp;0.004) and HDL-C (p\u0026thinsp;=\u0026thinsp;0.027), likely reflecting more intensive statin therapy or more advanced metabolic disease. The levels of lipoprotein(a), a genetically determined risk factor linked to atherosclerosis and calcification, were markedly greater in both calcified groups and highest in the mild CAC group (median 16.1 mg/dL) than in the non-CAC group (8.4 mg/dL; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Markers of hemodynamic stress and inflammation, NT-proBNP and hs-CRP, were also significantly elevated in the severe CAC group (both p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and p\u0026thinsp;=\u0026thinsp;0.014, respectively). The left ventricular ejection fraction was lowest in the severe CAC group (median 59% vs. 62% in the no CAC group; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Furthermore, extracoronary calcific comorbidities, including aortic valve calcification (10.5% vs. 3.4% without CAC) and nonaortic valve calcification (8.1% vs. 1.4%; both p\u0026thinsp;=\u0026thinsp;0.001), were strikingly more common in the severe CAC group.\u003c/p\u003e \u003cp\u003eThe clinical presentation at the index hospitalization did not differ significantly across groups (p\u0026thinsp;=\u0026thinsp;0.212), with unstable angina being the most common presentation. Discharge medications, including high-intensity statins and dual antiplatelet therapy, were similarly prescribed across groups, indicating comparable guideline-directed medical therapy post-PCI.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Procedural characteristics\u003c/h2\u003e \u003cp\u003eThe detailed procedural characteristics are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The left anterior descending artery was the most frequently assessed target vessel by IVUS across all groups (71.7% overall). There were no significant differences in the distribution of target vessels or in the prevalence of complex lesion morphologies such as bifurcations or ISR among the groups. However, chronic total occlusions were less common in the mild CAC group (1.2%) than in the no CAC group (5.8%, p\u0026thinsp;=\u0026thinsp;0.038).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e Procedural Characteristics of PCI According to Coronary Artery Calcification Severity\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMild Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSevere Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;709)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;417 (58.8%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;168 (23.7%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;124 (17.5%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTarget vessel assessed by IVUS, n (%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e147 (20.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e87 (20.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e37 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e23 (18.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.765\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e508 (71.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e293 (70.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e118 (70.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e97 (78.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.202\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e103 (14.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e66 (15.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e26 (15.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e11 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162 (22.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e93 (22.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44 (26.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e25 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.440\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLesion characteristics, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBifurcation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (4.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.541\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic total occlusion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e30 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24 (5.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.038\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-stent restenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e56 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e21 (12.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.780\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eProcedural details, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreated with stent implantation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e576 (81.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e320 (76.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e151 (89.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e105 (84.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle stent\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e225 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e150 (36.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e46 (27.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e29 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.012\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple stents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e351 (49.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e170 (40.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e105 (62.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e76 (61.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTreated with DEB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e96 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e60 (14.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e17 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e19 (15.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.321\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSingle DEB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e73 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.319\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiple DEB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e23 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2 (1.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIntraprocedural adjunctive therapy, n(%)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraprocedural use of GPI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e130 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e83 (19.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e30 (17.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.289\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntraprocedural use of IABP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e17 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e0.130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRotational atherectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e24 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1 (0.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e21 (16.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eNote:Data are presented as number (percentage). \u003cem\u003eP\u003c/em\u003e values were calculated using the χ\u0026sup2; test or Fisher's exact test, as appropriate.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"6\"\u003eAbbreviations: DEB, drug-eluting balloon; GPI, glycoprotein IIb/IIIa inhibitor; IABP, intra-aortic balloon pump; IVUS, intravascular ultrasound; LAD, left anterior descending artery; LCX, left circumflex artery;LM, left main coronary artery; PCI, percutaneous coronary intervention; RCA, right coronary artery.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe surgical strategy differed markedly on the basis of calcification severity. The overall rate of stent implantation was 81.2%. Patients with any degree of calcification (mild or severe) were significantly more likely to be treated with stent implantation (89.9% and 84.7%, respectively) than were those with no CAC (76.7%, p\u0026thinsp;=\u0026thinsp;0.001). Moreover, the use of multiple stents was substantially more common in the calcified groups (62.5% mild, 61.3% severe) than in the non-CAC group (40.8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), suggesting longer or more complex disease in calcified segments. The use of drug-eluting balloons as a primary or adjunctive strategy did not differ significantly.\u003c/p\u003e \u003cp\u003eAs anticipated, the utilization of rotational atherectomy, a specific technique for modifying severe calcium, was overwhelmingly concentrated in the severe CAC group. Rotational atherectomy was used in 16.9% of patients with severe CAC, compared with only 1.2% in the mild CAC group and a negligible 0.2% in the no CAC group (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The use of other intraprocedural adjunctive therapies, such as glycoprotein IIb/IIIa inhibitors or intra-aortic balloon pump support, was similar across groups.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Associations between CAC Severity and Clinical Outcomes\u003c/h2\u003e \u003cp\u003eThe median duration of clinical follow-up was 18.6 months (IQR 15.5\u0026ndash;23.2 months). During this period, 122 patients (17.2% of the cohort) experienced the primary composite endpoint of MACEs. The unadjusted cumulative event rates are shown in the Kaplan‒Meier curve (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), demonstrating a clear separation among the three groups, with the highest event rate in the severe CAC group. The Kaplan‒Meier curves for each secondary endpoint are presented in the supplementary figure. This risk stratification based on the dual-parameter IVUS criteria clearly differentiated the long-term prognosis among the three groups.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe independent associations between CAC severity and clinical outcomes after multivariable adjustment for potential confounders are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e (ordinal analysis) and Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e (categorical analysis).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociation Between Coronary Artery Calcification Severity and Clinical Outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eEvent,n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOverall\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMild Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSevere Calcification\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eaHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for Trend\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;709)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;417 (58.8%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;168 (23.7%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;124 (17.5%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary Endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eComposite MACEs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122 (17.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e34 (20.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e32 (25.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.30 (1.04\u0026ndash;1.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Endpoints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiovascular death\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (1.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e7 (5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.50 (0.83\u0026ndash;2.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.180\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNonfatal MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3 (0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e15 (2.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e4 (2.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.88 (0.99\u0026ndash;3.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26 (6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e17 (13.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.55 (1.12\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.008\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3 (1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.65 (0.76\u0026ndash;3.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIn-stent restenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70 (9.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37 (8.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e19 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e14 (11.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.09 (0.80\u0026ndash;1.48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.589\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eNote: Data are presented as number (percentage). Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) are presented for a per 1-grade increase in coronary artery calcification severity (modeled as an ordinal variable: no calcification\u0026thinsp;=\u0026thinsp;0, mild\u0026thinsp;=\u0026thinsp;1, severe\u0026thinsp;=\u0026thinsp;2). The Cox proportional hazards model was adjusted for the following covariates: age, sex, smoking, hypertension, dyslipidemia, diabetes mellitus, estimated glomerular filtration rate, hemoglobin A1c, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, lipoprotein(a), high-sensitivity C-reactive protein, and left ventricular ejection fraction. The dash (\u0026mdash;) indicates that the aHR was not estimated due to an insufficient number of events.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eAbbreviations: aHR, adjusted hazard ratio; CI, confidence interval; MACEs, major adverse cardiovascular events; MI, myocardial infarction; TVR, target vessel revascularization.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations Between Coronary Artery Calcification Severity Categories and Clinical Outcomes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecomparison\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eaHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary Endpoint\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eComposite MACEs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.42 (0.92\u0026ndash;2.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.118\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.67 (1.06\u0026ndash;2.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.028\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary Endpoints\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCardiovascular death\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.48 (0.11\u0026ndash;2.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.343\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.49 (0.89\u0026ndash;6.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.081\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNonfatal MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eStroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.88 (0.49\u0026ndash;7.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.355\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.53 (0.98\u0026ndash;12.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eTVR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37 (0.70\u0026ndash;2.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.356\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.45 (1.28\u0026ndash;4.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHeart failure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.31 (0.44\u0026ndash;12.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.324\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.76 (0.56\u0026ndash;13.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.212\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIn-stent restenosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMild vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.21 (0.68\u0026ndash;2.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.519\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSevere vs No\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.15 (0.60\u0026ndash;2.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.676\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eNote: The reference group is patients with no coronary artery calcification. Adjusted hazard ratios (aHRs) with 95% confidence intervals (CIs) were derived from Cox proportional hazards models adjusted for the covariates listed in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The dash (\u0026mdash;) indicates that the aHR was not estimated due to an insufficient number of events.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eAbbreviations: aHR, adjusted hazard ratio; CI, confidence interval; MACEs, major adverse cardiovascular events; MI, myocardial infarction; TVR, target vessel revascularization.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWhen CAC severity was modeled as an ordinal variable (none\u0026thinsp;=\u0026thinsp;0, mild\u0026thinsp;=\u0026thinsp;1, severe\u0026thinsp;=\u0026thinsp;2), each incremental increase in calcification severity was independently associated with a 30% greater risk of composite MACEs (aHR 1.30, 95% confidence interval [CI] 1.04\u0026ndash;1.63; P for trend\u0026thinsp;=\u0026thinsp;0.021). This relationship was also significant for the risk of TVR, with an aHR of 1.55 (95% CI 1.12\u0026ndash;2.15, p\u0026thinsp;=\u0026thinsp;0.008) per severity grade increase. The risk ratio forest plot for each endpoint event is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn the categorical analysis using the non-CAC group as the reference (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, visualized in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), the risk pattern was nuanced:\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eSevere CAC vs. non-CAC: Patients with severe CAC had a 67% greater risk of experiencing composite MACEs (aHR 1.67, 95% CI 1.06\u0026ndash;2.65; p\u0026thinsp;=\u0026thinsp;0.028). Their risk of requiring repeat intervention was even more pronounced, with a 2.45-fold higher risk of TVR (aHR 2.45, 95% CI 1.28\u0026ndash;4.68; p\u0026thinsp;=\u0026thinsp;0.007). The risk of ischemic stroke was numerically elevated (aHR 3.53), with borderline significance (p\u0026thinsp;=\u0026thinsp;0.054).\u003c/p\u003e \u003cp\u003eMild CAC vs. no CAC: In contrast, patients with mild calcification did not have a statistically significant increase in the risk of composite MACEs (HR 1.42, 95% CI 0.92\u0026ndash;2.20; p\u0026thinsp;=\u0026thinsp;0.118) or any of the individual secondary endpoints, including TVR (aHR 1.37, p\u0026thinsp;=\u0026thinsp;0.356), compared with those with no calcification.\u003c/p\u003e \u003cp\u003eThe number of observed nonfatal myocardial infarction events was very low (n\u0026thinsp;=\u0026thinsp;3 overall), precluding meaningful adjusted analysis for this specific endpoint. Risks for cardiovascular death, heart failure hospitalization, and ISR were not significantly different across groups in the categorical comparisons after multivariable adjustment.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Main Findings\u003c/h2\u003e \u003cp\u003eThis IVUS-guided cohort study provides robust, real-world evidence that a refined, dual-parameter assessment of CAC effectively stratifies post-PCI prognosis. Our principal finding is that severe calcification, defined by the coexistence of a maximal arc\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; and a longitudinal length\u0026thinsp;\u0026gt;\u0026thinsp;5 mm on preprocedural IVUS, is a potent and independent predictor of adverse clinical outcomes, most notably, a 2.45-fold increased risk of TVR. Conversely, mild calcification\u0026mdash;failing to meet both criteria\u0026mdash;did not confer a statistically significant elevation in composite event risk compared with noncalcified lesions. Importantly, when modeled ordinarily, each incremental grade in calcification severity was associated with a 30% higher risk of MACEs, underscoring a continuum of risk aligned with atherosclerotic burden. However, the categorical analysis reveals a critical threshold effect: excessive hazard is concentrated in the \u0026ldquo;severe\u0026rdquo; phenotype. This delineation moves beyond a simplistic binary (present/absent) assessment and advocates for a nuanced, severity-graded approach integral to a personalized interventional strategy.\u003c/p\u003e \u003cp\u003eThe mechanistic underpinnings of this risk are multifactorial and profound. Lesions meeting the severe criteria represent extensive, confluent calcific plates that create a long, noncompliant segment.\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e This architecture fundamentally challenges PCI mechanics: it impedes optimal balloon expansion, predisposes patients to asymmetric stent deployment, and increases the risk of stent underexpansion and malapposition\u0026mdash;established precursors of stent failure, including restenosis and thrombosis.\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e The pronounced association with TVR directly reflects these technical pitfalls. In addition to mechanics, severe CAC may signify a more advanced, systemic atherosclerotic phenotype.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e The elevated levels of lipoprotein(a), NT-proBNP, and hs-CRP, alongside a higher prevalence of extracoronary valvular calcification observed in this group, support this notion. The trend toward increased stroke risk, albeit requiring validation, further hints at a diffuse, high-risk vascular state prone to thromboembolic complications.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Thus, severe CAC identified by IVUS is not merely a local barrier to stent delivery but also a likely marker of aggressive, systemic vascular disease.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Comparison with Prior Studies and Contexts within the Field\u003c/h2\u003e \u003cp\u003eOur findings substantiate and significantly extend the existing knowledge on CAC. Prior studies have consistently linked IVUS-detected calcium, particularly arcs\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; or \u0026gt;\u0026thinsp;270\u0026deg;, to procedural complexity and acute complications.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e Observational data and trial subanalyses have associated such calcium with higher rates of target lesion failure. However, a key limitation has been the predominant focus on the calcium arc in isolation, which neglects its three-dimensional morphology.\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Our work validates the evolving expert consensus that emphasizes integrating calcium length into clinical assessment. Biomechanical models and clinical experience suggest that long, continuous calcific sheets are more resistant to fracture and adequate preparation than focal nodules are.\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e By empirically demonstrating that the combination of arc and length identifies a subgroup at markedly elevated long-term risk, our dual-parameter model provides a more precise and clinically actionable risk stratification tool than either parameter alone.\u003c/p\u003e \u003cp\u003eOur findings extend those of prior studies by demonstrating that a dual-parameter assessment that integrates both arc and length provides superior prognostic stratification compared with single-parameter (arc alone) approaches. While optical coherence tomography (OCT) offers superior resolution for measuring calcium thickness and discriminating superficial calcium from deep calcium, IVUS provides a more comprehensive assessment of calcium distribution and its relationship to the vessel wall. The ability of ultrasound to characterize the overall plaque architecture around calcific deposits is crucial for procedural planning.\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Our proposed criteria complement the recently emphasized importance of \u0026ldquo;calcium modification\u0026rdquo; in complex PCI. They offer a practical, immediately applicable method to identify lesions that may benefit most from advanced plaque-modifying techniques (e.g., rotational/orbital atherectomy, intravascular lithotripsy) before stent deployment, aligning with the proactive strategy advocated in current best practices.\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e,\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFurthermore, our results resonate with and reinforce findings from major trials underscoring the value of intravascular imaging-guided PCI. While pivotal trials such as ULTIMATE and RENOVATE-COMPLEX-PCI have demonstrated the clinical benefit of intravascular imaging (IVUS or OCT) guidance for PCI overall and for complex lesions,\u003csup\u003e29,30\u003c/sup\u003e our analyses focus on a specific, high-risk substrate\u0026mdash;severe CAC\u0026mdash;within that broad population. We provide granularity, showing that even under IVUS guidance, this lesion subset carries a residual high risk, thereby identifying an arena for further therapeutic refinement. The lack of significant risk elevation in the mild CAC group is a pivotal and reassuring finding, suggesting that standard contemporary PCI techniques under imaging guidance are sufficient for this subset, preventing overtreatment.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Clinical Implications and Future Directions\u003c/h2\u003e \u003cp\u003eThe clinical translation of our findings is direct and impactful. The dual-parameter IVUS assessment provides a clear, preprocedural triage tool:\u003c/p\u003e \u003cp\u003eSevere CACs (Arc\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; \u0026amp; Length\u0026thinsp;\u0026gt;\u0026thinsp;5 mm): This flags a high-risk lesion. Our data strongly support the routine consideration of dedicated calcium-modifying strategies (e.g., rotational/orbital atherectomy, intravascular lithotripsy) to achieve adequate lesion preparation prior to stenting.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e This may improve stent expansion and apposition, with the goal of mitigating the identified excess TVR risk. Post-PCI, these patients warrant intensified surveillance, rigorous optimization of guideline-directed medical therapy (especially aggressive lipid lowering), and thorough patient education on symptom recognition.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor mild CAC, the absence of significant excess risk suggests that standard balloon angioplasty and stent implantation, guided by IVUS to ensure optimal results,\u003csup\u003e29\u003c/sup\u003e constitute an appropriate strategy. This prevents the unnecessary use of higher-cost and potentially higher-risk adjunctive technologies.\u003c/p\u003e \u003cp\u003eFor risk prediction, this stratification can be integrated into pre-PCI risk scores and patient counseling, setting realistic expectations regarding long-term prognosis.\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFuture research must build upon this foundation. First, prospective, multicenter validation of this dual-parameter classification is essential. Second, investigating its integrative value with other high-risk plaque features (e.g., thin-cap fibroatheroma, large lipid core) assessed by near-infrared spectroscopy or OCT could yield a comprehensive vulnerability profile.\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e Third, and most critically, randomized controlled trials are needed to determine whether a systematic, protocol-driven approach to severe CAC\u0026mdash;mandating the use of specific calcium-modification technologies\u0026mdash;can successfully abrogate the excess TVR risk we observed.\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e Such studies would move from risk stratification to evidence-based intervention, ultimately defining the optimal care pathway for this challenging patient cohort.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Limitations\u003c/h2\u003e \u003cp\u003eSeveral limitations merit consideration. The single-center, retrospective design inherently carries risks of unmeasured confounding and may affect generalizability, although our rigorous adjustment and adjudication processes mitigate some concerns. Treatment selection bias exists, as the use of rotational atherectomy is operator dependent; however, its pronounced use in the severe CAC group reinforces the clinical validity of our classification. The low event rates for certain individual endpoints (e.g., myocardial infarction) limit the power of those specific analyses. While the follow-up duration is clinically relevant for stent-related events, longer-term follow-up would clarify the durability of this risk. Finally, we did not account for other calcium characteristics, such as thickness or nodularity, which have been shown to correlate with procedural success and outcomes in more detailed imaging studies and may offer further prognostic refinement.\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn patients undergoing PCI, severe CAC, defined by preprocedural IVUS as a maximal arc\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; coexisting with a length\u0026thinsp;\u0026gt;\u0026thinsp;5 mm, is a powerful, independent determinant of adverse outcomes, particularly a nearly 2.5-fold increased risk of repeat revascularization. This practical dual-parameter assessment transcends simple detection to enable meaningful preprocedural risk stratification. It effectively distinguishes high-risk lesions that may necessitate specialized preparation and closer follow-up from lower-risk calcified lesions manageable with conventional techniques. By facilitating more precise and personalized therapeutic decision-making in the catheterization laboratory, this approach holds promise for improving the long-term prognosis of patients with this challenging coronary substrate.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eACEI: Angiotensin-converting enzyme inhibitor; aHR: Adjusted hazard ratio; ARB: Angiotensin receptor blocker; CAC: Coronary artery calcification; CEC: Clinical Events Committee; CI: Confidence interval; CTO: Chronic total occlusion; DEB: Drug-eluting balloon; eGFR: Estimated glomerular filtration rate; EMR: Electronic medical record; GPI: Glycoprotein IIb/IIIa inhibitor; HDL-C: High-density lipoprotein cholesterol; hs-CRP: High-sensitivity C-reactive protein; IABP: Intra-aortic balloon pump; IQR: Interquartile range; ISR: In-stent restenosis; IVUS: Intravascular ultrasound; LAD: Left anterior descending artery; LCX: Left circumflex artery; LDL-C: Low-density lipoprotein cholesterol; LM: Left main coronary artery; LVEF: Left ventricular ejection fraction; MACE: Major adverse cardiovascular event; MI: Myocardial infarction; NAVC: Non-aortic valve calcification; NSTEMI: Non-ST-segment elevation myocardial infarction; NT-proBNP: N-terminal pro-B-type natriuretic peptide; OCT: Optical coherence tomography; PCI: Percutaneous coronary intervention; RCA: Right coronary artery; STEMI: ST-segment elevation myocardial infarction; TVR: Target vessel revascularization.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e\n\u003cp\u003eThe study was approved by the Ethics Committee of The Second Affiliated Hospital of Hainan Medical University (Approval No. LW2022035) and was conducted in accordance with the Declaration of Helsinki. The requirement for written informed consent was waived by the Ethics Committee for this retrospective analysis of deidentified data.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e\n\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis study was supported by the National Natural Science Foundation of China (82360063), the Natural Science Foundation of Hainan Province (High Level Talents Project) (821RC1127), and the Key Research and Development Project of Hainan Province (Social Development) (ZDYF2022SHFZ070).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSX: Conceptualization, methodology, software, formal analysis, investigation, data curation, writing \u0026ndash; original draft, and visualization. MZ: Investigation, Resources, Validation, Writing \u0026ndash; review \u0026amp; editing. YL: Investigation, Validation, Data curation, Visualization. YM: Investigation, Data curation. YC: Supervision, Project administration, Conceptualization, Writing \u0026ndash; review \u0026amp; editing.\u003c/p\u003e\n\u003ch2\u003eAcknowledgments\u003c/h2\u003e\n\u003cp\u003eThe authors thank Boston Scientific for providing technical support. We also thank our clinical colleagues, nursing staff, and independent clinical events committee for their assistance.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eOnnis C, Virmani R, Kawai K, Nardi V, Lerman A, Cademartiri F, et al. Coronary Artery Calcification: Current Concepts and Clinical Implications. Circulation. 2024 Jan 16;149(3):251\u0026ndash;66.\u003c/li\u003e\n\u003cli\u003eBudoff MJ, Shaw LJ, Liu ST, Weinstein SR, Mosler TP, Tseng PH, et al. Long-term prognosis associated with coronary calcification: observations from a registry of 25,253 patients. J Am Coll Cardiol. 2007 May 8;49(18):1860\u0026ndash;70.\u003c/li\u003e\n\u003cli\u003eDetrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008 Mar 27;358(13):1336\u0026ndash;45.\u003c/li\u003e\n\u003cli\u003eNg P, Maehara A, Kirtane AJ, McEntegart M, Jaffer FA, Doshi D, et al. Management of Coronary Stent Underexpansion. J Am Coll Cardiol. 2025 Feb 18;85(6):625\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eBai H, Zhang B, Sun Y, Wang X, Luan B, Zhang X. Research advances in the etiology of in-stent restenosis of coronary arteries. Front Cardiovasc Med. 2025;12:1585102.\u003c/li\u003e\n\u003cli\u003eMintz GS, Matsumura M, Ali Z, Maehara A. Clinical Utility of Intravascular Imaging: Past, Present, and Future. 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J Coll Physicians Surg--Pak JCPSP. 2023 Dec;33(12):1355\u0026ndash;60.\u003c/li\u003e\n\u003cli\u003eSaito Y, Kobayashi Y, Fujii K, Sonoda S, Tsujita K, Hibi K, et al. CVIT 2025 clinical expert consensus document on intravascular ultrasound. Cardiovasc Interv Ther. 2025 Apr;40(2):211\u0026ndash;25.\u003c/li\u003e\n\u003cli\u003eDoan KH, Liu TL, Yun WS, Kim YS, Yun KH, Oh SK, et al. Intravascular Ultrasound Guided Intervention in Calcified Coronary Lesions Showed Good Clinical Outcomes during One Year Follow-Up. J Clin Med. 2023 June 15;12(12):4073.\u003c/li\u003e\n\u003cli\u003ePu J, Mintz GS, Biro S, Lee JB, Sum ST, Madden SP, et al. Insights into echo-attenuated plaques, echolucent plaques, and plaques with spotty calcification: Novel findings from comparisons among intravascular ultrasound, near-infrared spectroscopy, and pathological histology in 2,294 human coronary artery segments. J Am Coll Cardiol. 2014 June 3;63(21):2220\u0026ndash;33.\u003c/li\u003e\n\u003cli\u003eMarkwerth P, Bajanowski T, Tzimas I, Dettmeyer R. Sudden cardiac death-update. Int J Legal Med. 2021 Mar;135(2):483\u0026ndash;95.\u003c/li\u003e\n\u003cli\u003eThygesen K, Alpert JS, Jaffe AS, Chaitman BR, Bax JJ, Morrow DA, et al. Fourth Universal Definition of Myocardial Infarction (2018). Circulation. 2018;138(20):e618\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eHua X, Liu M, Wu S. Definition, prediction, prevention and management of patients with severe ischemic stroke and large infarction. Chin Med J (Engl). 2023 Dec 20;136(24):2912\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eMetra M, Tomasoni D, Adamo M, Bayes-Genis A, Filippatos G, Abdelhamid M, et al. Worsening of chronic heart failure: Definition, epidemiology, management and prevention. A clinical consensus statement by the heart failure association of the european society of cardiology. Eur J Heart Fail. 2023 June;25(6):776\u0026ndash;91.\u003c/li\u003e\n\u003cli\u003eGiacoppo D, Mazzone PM, Capodanno D. Current management of in-stent restenosis. J Clin Med. 2024 Apr 19;13(8):2377.\u003c/li\u003e\n\u003cli\u003eScalamogna M, Kuna C, Voll F, Aytekin A, Lahu S, Kessler T, et al. Modified balloons to prepare severely calcified coronary lesions before stent implantation: a systematic review and meta-analysis of randomized trials. Clin Res Cardiol Off J Ger Card Soc. 2024 July;113(7):995\u0026ndash;1005.\u003c/li\u003e\n\u003cli\u003eMintz GS, Popma JJ, Pichard AD, Kent KM, Satler LF, Chuang YC, et al. Patterns of calcification in coronary artery disease. A statistical analysis of intravascular ultrasound and coronary angiography in 1155 lesions. Circulation. 1995 Apr 1;91(7):1959\u0026ndash;65.\u003c/li\u003e\n\u003cli\u003eFrizzell J, Kereiakes DJ. Calcified plaque modification during percutaneous coronary revascularization. Prog Cardiovasc Dis. 2025;88:39\u0026ndash;52.\u003c/li\u003e\n\u003cli\u003eKutikhin AG, Feenstra L, Kostyunin AE, Yuzhalin AE, Hillebrands JL, Krenning G. Calciprotein Particles: Balancing Mineral Homeostasis and Vascular Pathology. Arterioscler Thromb Vasc Biol. 2021 May 5;41(5):1607\u0026ndash;24.\u003c/li\u003e\n\u003cli\u003eNgamdu KS, Kalra DK. Risk of Stroke, Dementia, and Cognitive Decline with Coronary and Arterial Calcification. J Clin Med. 2024 July 22;13(14):4263.\u003c/li\u003e\n\u003cli\u003eKirtane AJ, G\u0026eacute;n\u0026eacute;reux P, Lewis B, Shlofmitz RA, Dohad S, Choudary J, et al. Orbital atherectomy versus balloon angioplasty before drug-eluting stent implantation in severely calcified lesions eligible for both treatment strategies (ECLIPSE): a multicenter, open-label, randomized trial. Lancet Lond Engl. 2025 Apr 12;405(10486):1240\u0026ndash;51.\u003c/li\u003e\n\u003cli\u003eZhang M, Matsumura M, Usui E, Noguchi M, Fujimura T, Fall KN, et al. 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Percutaneous Coronary Interventions for Calcified Lesions: A Systematic Review with Meta-analyses of Randomized Trials. Interv Cardiol Lond Engl. 2025;20:e31.\u003c/li\u003e\n\u003cli\u003eZhang J, Gao X, Kan J, Ge Z, Han L, Lu S, et al. Intravascular Ultrasound Versus Angiography-Guided Drug-Eluting Stent Implantation: The ULTIMATE Trial. J Am Coll Cardiol. 2018 Dec 18;72(24):3126\u0026ndash;37.\u003c/li\u003e\n\u003cli\u003eLee JM, Choi KH, Song YB, Lee JY, Lee SJ, Lee SY, et al. Intravascular Imaging-Guided or Angiography-Guided Complex PCI. N Engl J Med. 2023 May 4;388(18):1668\u0026ndash;79.\u003c/li\u003e\n\u003cli\u003eSung JG, Lo ST, Lam H. Contemporary Interventional Approach to Calcified Coronary Artery Disease. Korean Circ J. 2023 Feb;53(2):55\u0026ndash;68.\u003c/li\u003e\n\u003cli\u003eByrne RA, Rossello X, Coughlan JJ, Barbato E, Berry C, Chieffo A, et al. 2023 ESC Guidelines for the management of acute coronary syndromes. Eur Heart J. 2023 Oct 12;44(38):3720\u0026ndash;826.\u003c/li\u003e\n\u003cli\u003eMuller J, Madder R. OCT-NIRS Imaging for Detection of Coronary Plaque Structure and Vulnerability. Front Cardiovasc Med. 2020;7:90.\u003c/li\u003e\n\u003cli\u003eNozoe M, Nishioka S, Oi K, Suematsu N, Kubota T. Effects of Patient Background and Treatment Strategy on Clinical Outcomes After Coronary Intervention for Calcified Nodule Lesions. Circ Rep. 2021 Dec 10;3(12):699\u0026ndash;706.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Coronary artery calcification, Intravascular ultrasound, Percutaneous coronary intervention, Major adverse cardiovascular events, Risk stratification","lastPublishedDoi":"10.21203/rs.3.rs-8629286/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8629286/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe prognostic value of a dual-parameter intravascular ultrasound (IVUS) assessment that integrates both the calcium arc and length to grade coronary artery calcification (CAC) severity is not well established in patients undergoing percutaneous coronary intervention (PCI).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis single-center, retrospective study included 709 patients who underwent coronary angiography and preprocedural IVUS. Patients were stratified according to the maximum calcium arc and length as follows: no calcification (n\u0026thinsp;=\u0026thinsp;417), mild calcification (arc\u0026thinsp;\u0026le;\u0026thinsp;180\u0026deg; or length\u0026thinsp;\u0026le;\u0026thinsp;5 mm, n\u0026thinsp;=\u0026thinsp;168), and severe calcification (arc\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; and length\u0026thinsp;\u0026gt;\u0026thinsp;5 mm, n\u0026thinsp;=\u0026thinsp;124). The primary endpoint was the composite of major adverse cardiovascular events (MACEs).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOver a median follow-up of 18.6 months, 122 patients (17.2%) experienced MACEs. Each increase in CAC severity grade was independently associated with a greater risk of MACEs (adjusted hazard ratio [aHR] 1.30, 95% CI 1.04\u0026ndash;1.63; P for trend\u0026thinsp;=\u0026thinsp;0.021). Compared with patients with no calcification, those with severe calcification had a significantly greater risk of MACEs (aHR 1.67, 95% CI 1.06\u0026ndash;2.65; p\u0026thinsp;=\u0026thinsp;0.028) and target vessel revascularization (TVR) (aHR 2.45, 95% CI 1.28\u0026ndash;4.68; p\u0026thinsp;=\u0026thinsp;0.007). No significant increase in risk was observed for the mild calcification group.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSevere coronary calcification, defined by IVUS as an arc\u0026thinsp;\u0026gt;\u0026thinsp;180\u0026deg; with a length\u0026thinsp;\u0026gt;\u0026thinsp;5 mm, is a strong and independent predictor of adverse outcomes after PCI. This dual-parameter IVUS assessment provides a refined tool for preprocedural risk stratification.\u003c/p\u003e","manuscriptTitle":"Dual-Parameter IVUS Assessment of Coronary Calcification Stratifies the Risk of Adverse Events after PCI: A Retrospective Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-18 09:51:52","doi":"10.21203/rs.3.rs-8629286/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1e07b307-163b-4db7-8456-711366ee1159","owner":[],"postedDate":"February 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-05-13T06:44:27+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-18 09:51:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8629286","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8629286","identity":"rs-8629286","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}