The Impact of Metabolic Control on Cardiovascular Outcomes in Patients with Type 2 Diabetes and Chronic Multivessel Coronary Artery Disease: A Cohort Study

The Impact of Metabolic Control on Cardiovascular Outcomes in Patients with Type 2 Diabetes and Chronic Multivessel Coronary Artery Disease: A 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 The Impact of Metabolic Control on Cardiovascular Outcomes in Patients with Type 2 Diabetes and Chronic Multivessel Coronary Artery Disease: A Cohort Study Vitor Coutinho Andrade, Paulo Cury Rezende, Whady Hueb, Rosa Maria Rahmi Garcia, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7768266/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 11 Dec, 2025 Read the published version in Diabetology & Metabolic Syndrome → Version 1 posted 9 You are reading this latest preprint version Abstract Backgroud The long-term impact of metabolic control on cardiovascular outcomes in patients with type 2 diabetes mellitus and stable coronary artery disease remains uncertain. While some studies suggest benefits from multifactorial interventions, data specifically evaluating sustained control of key metabolic parameters are limited. Methods From 884 patients enrolled between 1995 and 2010, 718 were selected. Data were analyzed from July 2022 to July 2024. Patients were categorized into four groups based on the number of metabolic factors within target range (low-density lipoproteins (LDL-C) <100 mg/dL, glycated hemoglobin (HbA1C) <7.5%, triglycerides <150 mg/dL). The primary outcome was a composite of all-cause mortality, myocardial infarction, stroke, and unplanned myocardial revascularization. Multivariate Cox regression models were calculated adjusting for confounders including age, sex, smoking, ejection fraction, number of diseased vessels, and initial coronary artery disease treatment. Results Of 718 patients (mean [SD] age, 61 [8] years; 254 female [35,3%]), followed during 8 (± 3.4) years, 199 (27.8%) had all 3 metabolic factors controlled, 260 (36.2%) had 2 factors controlled, 175 (24.3%) one factor controlled, and 84 (11.7%) no factor controlled. The group with all factors controlled were older and more frequently male. A dose-response association was observed, with progressively higher event rates as fewer metabolic factors were controlled. Patients with no controlled factors had nearly threefold the risk of events compared to those with all within target levels (HR 2.87, 95% CI 1.81-4.54, p < 0,01) in adjusted analysis. Conclusions In patients with stable coronary artery disease and type 2 diabetes mellitus, inadequate control of metabolic factors was associated with higher risk of cardiovascular events over long-term follow-up. Trial registration: Retrospectively registered Type 2 diabetes mellitus Coronary artery disease Metabolic control Cardiovascular outcomes Figures Figure 1 Figure 2 BACKGROUND It is estimated that over 90% of events related to coronary artery disease (CAD) occur in individuals with at least one modifiable risk factor, such as elevated serum levels of low-density lipoproteins (LDL-C) and or glucose 1 . Although the causal association of these factors with the evolution of CAD remains controversial, some studies have suggested that the management of some of these factors could be associated with a reduction in cardiovascular event rates, particularly in patients with type 2 diabetes mellitus (T2DM) and high cardiovascular risk 2 – 4 , what could in turn, reinforce the causal relation between those factors and chronic coronary syndromes. However, there is a scarcity of studies that specifically investigated the impact of controlling strictly metabolic variables in patients with CAD and T2DM in a long-term follow-up. While some evidence supports that the simultaneous control of multiple risk factors may significantly be associated with a reduction in cardiovascular event rates 2 – 4 , the same cannot be confidently stated for the isolated management of individual metabolic factors. For instance, although epidemiological analyses suggest a correlation between chronic hyperglycemia and higher rates of cardiovascular disease 5–7 , most randomized clinical trials have failed to demonstrate a significant benefit of intensive glycemic control in reducing macrovascular events in T2DM patients 8–10 . Similarly, the association between triglyceride levels and cardiovascular disease remains uncertain. While some evidence suggests increased cardiovascular risk in patients with elevated triglycerides 11–13 , clinical trials assessing interventions to reduce triglycerides have yielded inconsistent results regarding cardiovascular outcomes 14–16 . Even in the case of LDL-C, for which scientific evidence suggests a consistent association with cardiovascular events 17 , there is ongoing debate about whether the magnitude of LDL-C reduction has a less pronounced impact in the context of chronic CAD 18 . These uncertainties underscore a critical gap in our understanding of the role of strictly metabolic factor control in reducing cardiovascular events. Because CAD is the result of a complex interaction of many factors, and that the metabolic ones are believed to play a crucial role in the progression and instability of atherosclerotic plaques, the hypothesis of this study is that the adequate control of multiple metabolic factors is associated with significant improvement in cardiovascular outcomes in a homogeneous cohort of patients with stable CAD and T2DM during long-term follow-up. METHODS Study Design and Population The study population consisted of patients with T2DM enrolled in the Medicine, Angioplasty, or Surgery Study (MASS) Registry at the Heart Institute, University of São Paulo, between June 1995 and March 2010. This retrospective study was granted an ethical waiver for review and informed consent by the Heart Institute’s Ethics Committee, University of São Paulo Medical School, in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. Patients were eligible for inclusion in the MASS Registry if they had multivessel CAD, stable angina or documented myocardial ischemia, preserved left ventricular function and were candidates for one of three treatment modalities: medical therapy, percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG). Clinical and laboratory data were prospectively collected and recorded in specific databases. Multivessel CAD was confirmed by coronary angiography, defined as obstructive lesions in at least two major coronary vessels with ≥ 70% stenosis. Left ventricular function was assessed by echocardiography, and only patients with an ejection fraction ≥ 0.35 were included. Exclusion criteria for the MASS Registry were recent acute coronary syndrome (within the past three months), serum creatinine levels > 2.0 mg/dL, hepatic dysfunction, active malignancy, or life expectancy < 2 years. For the present analysis, only T2DM patients were included, and were also excluded if they had incomplete data on cardiovascular outcomes or missing longitudinal measurements of LDL-C, glycated hemoglobin (HbA1c), or triglycerides. All patients received optimal medical therapy and were monitored through biannual outpatient visits at the Heart Institute, with the aim of achieving target treatment goals under close supervision. LDL-C, HbA1c, and triglyceride levels were measured annually, with diabetes and dyslipidemia management following international guidelines at the time. Measurement of LDL-C, HbA1c and Triglycerides Annual measurements of LDL-C, HbA1c, and triglyceride levels were recorded in a specific database. HbA1c levels were assessed using an immunoturbidimetric method certified by the National Glycohemoglobin Standardization Program (NGSP), with a reference range of 4.5% to 6.2%. Triglycerides levels were measured using an enzymatic colorimetric assay (Siemens Healthcare Diagnostics, Newark, USA), employing a biochromatic endpoint technique (510, 700 nm). Normal triglyceride levels were defined as less than 150 mg/dL, and the assay’s analytical sensitivity was 15 mg/dL. LDL-C levels were determined using the Dimension RXL/EXL system (Siemens Healthcare, Newark, USA) with an analytical measurement range of 5 to 300 mg/dL. For triglyceride levels below 350 mg/dL, LDL-C was calculated using the Friedewald formula. When triglyceride levels were ≥ 350 mg/dL, direct LDL-C quantification was performed using a selective detergent-based photometric method. Clinical Events Patients were prospectively followed for the occurrence of cardiovascular events after enrollment in the MASS Registry. Event classification was based on the review of death certificates, family reports, and hospital records. The primary endpoint was a composite of all-cause mortality, MI, unplanned revascularization, or ischemic stroke. MI was defined as chest pain associated with electrocardiographic evidence of ischemia and elevated cardiac biomarkers, including creatine kinase-MB or troponin, above diagnostic thresholds. Stroke was defined as acute focal neurological deficit confirmed by brain imaging (computed tomography or magnetic resonance imaging). Revascularization procedures were indicated for patients who developed limiting angina or acute coronary syndrome, with suitable coronary anatomy for PCI or CABG. Statistical Analysis Data were analyzed between July 15, 2022, and July 15, 2024. Categorical variables are presented as absolute counts and percentages, while continuous variables are reported as means with standard deviations (SD). Comparisons between categorical variables were conducted using the χ² test or Fisher’s exact test. For continuous variables, ANOVA or Kruskal-Wallis tests were applied as appropriate. LDL-C, HbA1c, and triglyceride measurements were truncated prior to the occurrence of the first clinical endpoint. Patients were excluded from the analysis if they had fewer than three valid measurements of these biomarkers during follow-up, if the interval between measurements exceeded five years, or if clinical covariate data were missing. Patients were categorized into four groups based on the number of adequately controlled metabolic factors: LDL-C < 100 mg/dL, triglycerides < 150 mg/dL, and HbA1c < 7.5%. The reference group comprised patients with all three factors under control, while the remaining groups included patients with two, one, or no factors controlled. Event rates were estimated using the Kaplan-Meier method, and differences among the groups were assessed with the log-rank test. Cox proportional hazards regression was employed to model the time to the first occurrence of the composite primary endpoint, both unadjusted and adjusted for baseline covariates (age, sex, smoking status, left ventricular ejection fraction, number of diseased vessels, initial CAD treatment). All statistical tests were two-tailed, and significance was set at P < .05. Analyses were conducted using R version 4.2.2 (R Project for Statistical Computing). RESULTS The MASS Registry enrolled 884 patients with T2DM, multivessel CAD, and preserved left ventricular function. Of these, 152 patients (17.1%) were excluded due to fewer than three follow-up measurements of LDL-C, HbA1c, or triglycerides. Additionally, 11 patients (1.2%) had at least one interval between consecutive laboratory measurements of these markers exceeding 5 years, and 3 patients (0.3%) were excluded due to incomplete clinical follow-up data. The final study population comprised 718 patients, who were followed for a mean (SD) duration of 8.0 (± 3.4) years. These patients were grouped based on the number of metabolic factors within target range for further analysis (Fig. 1 ). In total, 5,562 LDL-C measurements were recorded, with an average of 7.7 (± 2.7) measurements per patient. Additionally, 4,974 HbA1c measurements were obtained, averaging 6.9 (± 2.4) measurements per patient, and 5,252 triglyceride measurements were recorded, averaging 7.3 (± 2.7) per patient. Of the 718 patients included in the final analysis, 199 (27.8%) had all three metabolic factors controlled. The number of patients with two, one, or no factors controlled was 260 (36.2%), 175 (24.3%), and 84 (11.7%), respectively. Baseline Characteristics The baseline characteristics of the 718 patients are shown in Table 1 . The group achieving control of all metabolic factors were older (63 years) compared to the group with no controlled factors (57 years). The majority of patients were male (64.6%), with a higher proportion of men in the group with better metabolic control (74% versus 54% in the group with no factors controlled). The prevalence of smoking was 7% in the group with all factors controlled, compared to 30% in the group with no factors controlled, with a progressive increase in smoking rates correlating with fewer controlled factors. Table 1 Baseline Characteristics of the Study Population Group A 1 n = 199 Group B 2 n = 260 Group C 3 n = 175 Group D 4 n = 84 p-value Demographic Profile Age, mean (SD), years 63 (± 8) 62 (± 7) 59 (± 9) 57 (± 8) p < 0.001 Male, n (%) 148 (74%) 170 (65%) 100 (57%) 46 (54%) p < 0.001 Current smoker, n (%) 14 (7%) 41 (17%) 43 (26%) 24 (30%) p < 0.001 Laboratory Values* Creatinine, mean (SD) 1.0 (± 0.2) 1.0 (± 0.3) 1.0 (± 0.3) 1.0 (± 0.3) p = 0.53 LDL-C, mean (SD) 107 (± 36) 112 (± 39) 129 (± 37) 145 (± 37) p = 0.03 HDL-C, mean (SD) 41 (± 10) 41 (± 10) 39 (± 10) 38 (± 7) p = 0.056 Triglycerides, mean (SD) 134 (± 55) 160 (± 90) 225 (± 119) 265 (± 128) p < 0.001 HbA1c, mean (SD), % 6.8 (± 1.0) 8.1 (± 1.9) 8.8 (± 2.0) 9.1 (± 1.6) p < 0.001 Medical History Hypertension, n (%) 149 (74%) 175 (72%) 130 (76%) 62 (76%) p = 0.78 Multivessel CAD, n (%) 114 (67%) 152 (67%) 115 (70%) 56 (70%) p = 0.83 LVEF, mean (SD), % 63 (± 8) 64 (± 8) 65 (± 7) 67 (± 7) p = 0.29 Treatment MT, n (%) 60 (30%) 87 (33%) 45 (26%) 19 (23%) p = 0.45 PCI, n (%) 49 (25%) 64 (25%) 47 (27%) 26 (31%) CABG, n (%) 89 (45%) 108 (42%) 83 (47%) 39 (46%) *Laboratory values are reported in mg/dL. 1 = All factors controlled; 2 = Two factors controlled; 3 = One factors controlled; 4 = No factors controlled Abbreviations: SD = standard deviation; LDL-C = low-density lipoprotein cholesterol; HDL-C = high-density lipoprotein cholesterol; HbA1c = glycated hemoglobin; CAD = coronary artery disease; LVEF = left ventricular ejection fraction; PCI = percutaneous coronary intervention; CABG = coronary artery bypass grafting. Renal function was preserved across all groups, and mean baseline HDL cholesterol levels were similar between groups. There were no statistically significant differences in the prevalence of arterial hypertension, presence of multivessel CAD, initial treatment strategies for CAD, or left ventricular function among the groups. The baseline characteristics of the study population are detailed in Table 1 . Cardiovascular events Among the 718 patients, 118 (16.4%) died during the follow-up period, with 48 deaths (40.7%) attributed to cardiovascular causes and 70 (59.3%) to non-cardiovascular causes. The annual all-cause mortality rate was 2.0%, while the annual cardiovascular mortality rate was 0.83%. Nonfatal acute MI occurred in 58 patients (8.0%), and 24 patients (3.3%) experienced a stroke. A total of 93 patients (12.9%) underwent unplanned myocardial revascularization, with 39 (5.4%) undergoing CABG and 54 (7.5%) undergoing PCI. The composite outcome of death, MI, stroke, or unplanned revascularization was observed in 293 patients (40.8%). Notably, 71 of these events occurred in the group with all risk factors controlled (representing 35.7% of the total cohort of this group), while 45 events occurred in the group with all factors uncontrolled (53.6% of this subgroup). Cardiovascular events and metabolic control In the Cox regression model, both unadjusted and adjusted analyses (adjusting for age, sex, left ventricular ejection fraction, smoking status, number of affected coronary vessels, and initial CAD treatment) showed an increasing risk of cardiovascular events as the number of uncontrolled metabolic factors were present. Patients with all factors uncontrolled had an 88% increased risk of the composite endpoint (all-cause death, non-fatal MI, non-fatal stroke, or additional revascularization) compared to those with all factors controlled in the unadjusted analysis (HR 1.88, 95% CI 1.29–1.74, p < 0.01). This risk rose to 187% after adjustment for covariates in the multivariate analysis (HR 2.87, 95% CI 1.81–4.54, p < 0.01) (Tables 2 and 3 ). Table 2 Comparison of the Occurrence of Combined Cardiovascular Outcomes According to the Number of Controlled Factors – Unadjusted Analysis Metabolic Control Events (n, %) HR 95% CI p-value All factors controlled 71 (35.7%) 1.00 (reference) (reference) Two factors controlled 101 (38.8%) 1.13 0.83–1.53 0.41 One factor controlled 76 (43.4%) 1.34 0.97–1.86 0.07 No factors controlled 45 (53.6%) 1.88 1.29–2.74 < 0.01 Table 3 Comparison of the Occurrence of Combined Cardiovascular Outcomes According to the Number of Controlled Factors – Adjusted Analysis Metabolic Control Events (n, %) HR 95% CI p-value All factors controlled 71 (35.7%) 1.00 (reference) (reference) Two factors controlled 101 (38.8%) 1.17 0.81–1.68 0.39 One factor controlled 76 (43.4%) 1.64 1.12–2.40 0.01 No factors controlled 45 (53.6%) 2.87 1.81–4.54 < 0.01 The Kaplan-Meier curves demonstrated an early separation between groups starting at year two, with a marked increase in events observed among patients with a greater number of uncontrolled factors. This difference in event-free survival persisted throughout the follow-up period, as illustrated in Fig. 2 , emphasizing the association between metabolic control and cardiovascular outcomes. DISCUSSION This study showed a significant association between the number of uncontrolled metabolic factors and an increased risk of cardiovascular events in patients with stable CAD and T2DM over long-term follow-up. The analysis was adjusted for key baseline characteristics, including age, sex, smoking status, LVEF, extent of CAD, and initial CAD treatment. The results observed after multivariate adjustment highlights the independent nature of the findings Additionally, the homogeneity of this chronic CAD population regarding significant clinical characteristics that might influence clinical outcomes also strengths study findings. The cardiovascular events assessed in this study included a composite of death, non-fatal MI, non-fatal stroke, and unplanned myocardial revascularization, which we believe that are outcomes that can be linked to the progression of atherosclerosis. Poor control of LDL-C, HbA1c, and triglycerides could, theoretically, contribute to plaque instability, increasing the likelihood of acute atherosclerotic events. Despite the relatively low overall mortality in this high-risk population (CAD and T2DM), the presence of uncontrolled metabolic factors significantly heightened the risk of adverse events, underscoring the importance of optimal metabolic control. We observed a clear dose-response relationship, with fewer controlled factors leading to a progressive higher frequency of adverse outcomes. Specifically, patients with no controlled factors had almost twice the risk of cardiovascular events compared to those with all factors controlled. The strength of our findings is reinforced by several aspects of study design. Despite the retrospective nature, the cohort was systematically followed every six months with detailed data collection on metabolic factors. This minimized follow-up loss and ensured a high frequency of data collection for each metabolic parameter. The small number of patients with all factors uncontrolled highlights the rigor in managing these parameters, strengthening the validity of our results. Furthermore, a key strength of this study is the homogeneity of factors that could have confounded results - like LVEF, the extent of CAD, and initial treatment strategy. These factors were well-balanced across groups, ensuring that the differences in outcomes were likely attributable to the degree of metabolic control rather than other clinical variables. Our results are consistent with the “Comprehensive Cardiovascular Risk Factor Control Improves Survival The BARI 2D Trial” 4 , which showed that comprehensive risk factor control improves survival in patients with stable CAD and diabetes. However, while the authors of BARI 2D included both metabolic and non-metabolic factors such as smoking cessation and blood pressure control, our study focused exclusively on metabolic parameters. The HbA1c cut-off of ≥ 7.5% reflects a balance between strict glycemic control and the risk of hypoglycemia in this high-risk population. Previous studies 19–20 have shown a possible "J-curve" relationship between HbA1c and cardiovascular outcomes, where both high and low levels are associated with adverse events. Our choice of 7.5% mitigates the risk of hypoglycemia while identifying those with poor glycemic control. Similarly, despite lower LDL-C targets in contemporary practice, elevated LDL-C remains a critical predictor of cardiovascular events, reinforcing the importance of stringent control. Limitations This study has limitations. Although the research group performed rigorous follow-up, the retrospective nature of the analysis imposes inherent limitations. Additionally, while the study identifies the association between metabolic control and adverse outcomes, the underlying causes of poor metabolic control were not evaluated. It is possible that patients with uncontrolled factors had lower treatment adherence or, more plausibly, had more severe and resistant metabolic dysregulation. These issues were beyond the scope of the present analysis. Finally, in groups with one or two uncontrolled factors, we could not assess which specific factors were uncontrolled due to sample size limitations. Despite these limitations, our study suggests that in patients with stable CAD and T2DM, long-term metabolic control is associated with better cardiovascular outcomes. CONCLUSION In this study, inadequate control of metabolic factors was independently associated with a higher incidence of cardiovascular events in patients with stable CAD and T2DM over long-term follow-up. Abbreviations CABG coronary artery bypass grafting CAD stable coronary artery disease Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of the Instituto do Coração (InCor), Universidade de São Paulo, Brazil. Due to the retrospective nature of the study and use of de-identified data, the requirement for informed consent was waived by the ethics committee. Consent for publication Not applicable. Competing interests The authors declare that they have no competing interests. Authors’ information Not applicable. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution V.C.A. researched data and wrote the manuscript. P.C.R supervised the research and contributed to interpretation of results and statistical analysis. W.H. conceived this study, contributed to discussion and reviewed the manuscript. R.M.R.G. and A.C.R.A. contributed to discussion and reviewed the manuscript. T.L.S., M.F.S., M.O.L.R., M.S.T., C.V.S.J., J.A.F.R., and R.K.F. contributed to review the manuscript. All authors approved the final version of the manuscript. Acknowledgement The authors thank the clinical and administrative staff of the Instituto do Coração (InCor), Universidade de São Paulo, for their continued support in maintaining the MASS Registry database and facilitating long-term follow-up. No editorial, clerical, or statistical assistance was received for the preparation of this manuscript. Data Availability The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request. References Vasan RS, Sullivan LM, Wilson PW, et al. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med. 2005;142(6):393. Gaede P, Lund-Andersen H, Parving HH, et al. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med. 2008;358:580–91. Gaede P, Vedel P, Larsen N, et al. Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes. N Engl J Med. 2003;348:383–93. Bittner V, Bertolet M, Barraza Felix R, et al. Comprehensive Cardiovascular Risk Factor Control Improves Survival: The BARI 2D Trial. J Am Coll Cardiol. 2015;66(7):765. Additional Declarations No competing interests reported. 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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-7768266","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":531220345,"identity":"e40bbaa2-f55c-4096-ab92-2b7e6da975ef","order_by":0,"name":"Vitor Coutinho Andrade","email":"","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Vitor","middleName":"Coutinho","lastName":"Andrade","suffix":""},{"id":531220347,"identity":"0661e3cd-0cfc-446a-a383-772cc3a8fab0","order_by":1,"name":"Paulo Cury Rezende","email":"","orcid":"","institution":"Hospital das 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de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Stanislavovna","lastName":"Tairova","suffix":""},{"id":531220363,"identity":"bda6a213-42a6-410f-a24f-e988e9b07adc","order_by":9,"name":"Jose Antonio Franchini Ramires","email":"","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Jose","middleName":"Antonio Franchini","lastName":"Ramires","suffix":""},{"id":531220366,"identity":"94daa054-8bb0-491d-a180-790e994a49b1","order_by":10,"name":"Roberto Kalil Filho","email":"","orcid":"","institution":"Hospital das Clínicas HCFMUSP, Universidade de São Paulo","correspondingAuthor":false,"prefix":"","firstName":"Roberto","middleName":"Kalil","lastName":"Filho","suffix":""}],"badges":[],"createdAt":"2025-10-02 17:23:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7768266/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7768266/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s13098-025-02027-6","type":"published","date":"2025-12-11T15:58:17+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":93977663,"identity":"0149264c-93d4-4bac-b08e-0624824f4b1d","added_by":"auto","created_at":"2025-10-21 01:31:04","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":321900,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptDiabetolMetabolSyndr.docx","url":"https://assets-eu.researchsquare.com/files/rs-7768266/v1/2ff9d84226529404a1e41476.docx"},{"id":93978252,"identity":"21b5985f-0c14-4e75-965c-4d843a0a95c0","added_by":"auto","created_at":"2025-10-21 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01:23:04","extension":"xml","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":61119,"visible":true,"origin":"","legend":"","description":"","filename":"8987a442508a4e4c8043c1f09a48394b1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7768266/v1/b00f5c280c4ae4a890c72f58.xml"},{"id":93976916,"identity":"616792fc-69c4-4ddd-963a-24be4cc1b22c","added_by":"auto","created_at":"2025-10-21 01:23:04","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":72806,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7768266/v1/e255cf3c1eabfbf0218558c0.html"},{"id":93976909,"identity":"4e7eb6d8-e002-47a4-a5d9-4806e848b5e3","added_by":"auto","created_at":"2025-10-21 01:23:04","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":254844,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFlowchart of study population selection and grouping.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7768266/v1/39e67679128f829a7c92e6f3.jpeg"},{"id":93977659,"identity":"f5a1b8c8-88f2-4a64-9c3c-4ba3906cea79","added_by":"auto","created_at":"2025-10-21 01:31:04","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":211653,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKaplan-Meier Curve for Unadjusted Event-Free Survival Estimate\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7768266/v1/d02027ba6629a256466a29b4.png"},{"id":98244296,"identity":"c41c2dd9-23e8-424d-8460-1471466a270e","added_by":"auto","created_at":"2025-12-15 16:13:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1242853,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7768266/v1/031059bb-23a6-4b14-bb2f-d2cc0dc014fb.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The Impact of Metabolic Control on Cardiovascular Outcomes in Patients with Type 2 Diabetes and Chronic Multivessel Coronary Artery Disease: A Cohort Study","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eIt is estimated that over 90% of events related to coronary artery disease (CAD) occur in individuals with at least one modifiable risk factor, such as elevated serum levels of low-density lipoproteins (LDL-C) and or glucose\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Although the causal association of these factors with the evolution of CAD remains controversial, some studies have suggested that the management of some of these factors could be associated with a reduction in cardiovascular event rates, particularly in patients with type 2 diabetes mellitus (T2DM) and high cardiovascular risk\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, what could in turn, reinforce the causal relation between those factors and chronic coronary syndromes. However, there is a scarcity of studies that specifically investigated the impact of controlling strictly metabolic variables in patients with CAD and T2DM in a long-term follow-up.\u003c/p\u003e\u003cp\u003eWhile some evidence supports that the simultaneous control of multiple risk factors may significantly be associated with a reduction in cardiovascular event rates\u003csup\u003e\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e, the same cannot be confidently stated for the isolated management of individual metabolic factors. For instance, although epidemiological analyses suggest a correlation between chronic hyperglycemia and higher rates of cardiovascular disease\u003csup\u003e5\u0026ndash;7\u003c/sup\u003e, most randomized clinical trials have failed to demonstrate a significant benefit of intensive glycemic control in reducing macrovascular events in T2DM patients\u003csup\u003e8\u0026ndash;10\u003c/sup\u003e. Similarly, the association between triglyceride levels and cardiovascular disease remains uncertain. While some evidence suggests increased cardiovascular risk in patients with elevated triglycerides\u003csup\u003e11\u0026ndash;13\u003c/sup\u003e, clinical trials assessing interventions to reduce triglycerides have yielded inconsistent results regarding cardiovascular outcomes\u003csup\u003e14\u0026ndash;16\u003c/sup\u003e. Even in the case of LDL-C, for which scientific evidence suggests a consistent association with cardiovascular events\u003csup\u003e17\u003c/sup\u003e, there is ongoing debate about whether the magnitude of LDL-C reduction has a less pronounced impact in the context of chronic CAD\u003csup\u003e18\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThese uncertainties underscore a critical gap in our understanding of the role of strictly metabolic factor control in reducing cardiovascular events. Because CAD is the result of a complex interaction of many factors, and that the metabolic ones are believed to play a crucial role in the progression and instability of atherosclerotic plaques, the hypothesis of this study is that the adequate control of multiple metabolic factors is associated with significant improvement in cardiovascular outcomes in a homogeneous cohort of patients with stable CAD and T2DM during long-term follow-up.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Population\u003c/h2\u003e\u003cp\u003eThe study population consisted of patients with T2DM enrolled in the Medicine, Angioplasty, or Surgery Study (MASS) Registry at the Heart Institute, University of S\u0026atilde;o Paulo, between June 1995 and March 2010. This retrospective study was granted an ethical waiver for review and informed consent by the Heart Institute\u0026rsquo;s Ethics Committee, University of S\u0026atilde;o Paulo Medical School, in compliance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e\u003cp\u003ePatients were eligible for inclusion in the MASS Registry if they had multivessel CAD, stable angina or documented myocardial ischemia, preserved left ventricular function and were candidates for one of three treatment modalities: medical therapy, percutaneous coronary intervention (PCI), or coronary artery bypass grafting (CABG). Clinical and laboratory data were prospectively collected and recorded in specific databases.\u003c/p\u003e\u003cp\u003eMultivessel CAD was confirmed by coronary angiography, defined as obstructive lesions in at least two major coronary vessels with \u0026ge;\u0026thinsp;70% stenosis. Left ventricular function was assessed by echocardiography, and only patients with an ejection fraction\u0026thinsp;\u0026ge;\u0026thinsp;0.35 were included. Exclusion criteria for the MASS Registry were recent acute coronary syndrome (within the past three months), serum creatinine levels\u0026thinsp;\u0026gt;\u0026thinsp;2.0 mg/dL, hepatic dysfunction, active malignancy, or life expectancy\u0026thinsp;\u0026lt;\u0026thinsp;2 years. For the present analysis, only T2DM patients were included, and were also excluded if they had incomplete data on cardiovascular outcomes or missing longitudinal measurements of LDL-C, glycated hemoglobin (HbA1c), or triglycerides.\u003c/p\u003e\u003cp\u003eAll patients received optimal medical therapy and were monitored through biannual outpatient visits at the Heart Institute, with the aim of achieving target treatment goals under close supervision. LDL-C, HbA1c, and triglyceride levels were measured annually, with diabetes and dyslipidemia management following international guidelines at the time.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eMeasurement of LDL-C, HbA1c and Triglycerides\u003c/h3\u003e\n\u003cp\u003eAnnual measurements of LDL-C, HbA1c, and triglyceride levels were recorded in a specific database. HbA1c levels were assessed using an immunoturbidimetric method certified by the National Glycohemoglobin Standardization Program (NGSP), with a reference range of 4.5% to 6.2%.\u003c/p\u003e\u003cp\u003eTriglycerides levels were measured using an enzymatic colorimetric assay (Siemens Healthcare Diagnostics, Newark, USA), employing a biochromatic endpoint technique (510, 700 nm). Normal triglyceride levels were defined as less than 150 mg/dL, and the assay\u0026rsquo;s analytical sensitivity was 15 mg/dL.\u003c/p\u003e\u003cp\u003eLDL-C levels were determined using the Dimension RXL/EXL system (Siemens Healthcare, Newark, USA) with an analytical measurement range of 5 to 300 mg/dL. For triglyceride levels below 350 mg/dL, LDL-C was calculated using the Friedewald formula. When triglyceride levels were \u0026ge;\u0026thinsp;350 mg/dL, direct LDL-C quantification was performed using a selective detergent-based photometric method.\u003c/p\u003e\n\u003ch3\u003eClinical Events\u003c/h3\u003e\n\u003cp\u003ePatients were prospectively followed for the occurrence of cardiovascular events after enrollment in the MASS Registry. Event classification was based on the review of death certificates, family reports, and hospital records. The primary endpoint was a composite of all-cause mortality, MI, unplanned revascularization, or ischemic stroke. MI was defined as chest pain associated with electrocardiographic evidence of ischemia and elevated cardiac biomarkers, including creatine kinase-MB or troponin, above diagnostic thresholds. Stroke was defined as acute focal neurological deficit confirmed by brain imaging (computed tomography or magnetic resonance imaging). Revascularization procedures were indicated for patients who developed limiting angina or acute coronary syndrome, with suitable coronary anatomy for PCI or CABG.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eData were analyzed between July 15, 2022, and July 15, 2024. Categorical variables are presented as absolute counts and percentages, while continuous variables are reported as means with standard deviations (SD). Comparisons between categorical variables were conducted using the χ\u0026sup2; test or Fisher\u0026rsquo;s exact test. For continuous variables, ANOVA or Kruskal-Wallis tests were applied as appropriate.\u003c/p\u003e\u003cp\u003eLDL-C, HbA1c, and triglyceride measurements were truncated prior to the occurrence of the first clinical endpoint. Patients were excluded from the analysis if they had fewer than three valid measurements of these biomarkers during follow-up, if the interval between measurements exceeded five years, or if clinical covariate data were missing.\u003c/p\u003e\u003cp\u003ePatients were categorized into four groups based on the number of adequately controlled metabolic factors: LDL-C\u0026thinsp;\u0026lt;\u0026thinsp;100 mg/dL, triglycerides\u0026thinsp;\u0026lt;\u0026thinsp;150 mg/dL, and HbA1c\u0026thinsp;\u0026lt;\u0026thinsp;7.5%. The reference group comprised patients with all three factors under control, while the remaining groups included patients with two, one, or no factors controlled.\u003c/p\u003e\u003cp\u003eEvent rates were estimated using the Kaplan-Meier method, and differences among the groups were assessed with the log-rank test. Cox proportional hazards regression was employed to model the time to the first occurrence of the composite primary endpoint, both unadjusted and adjusted for baseline covariates (age, sex, smoking status, left ventricular ejection fraction, number of diseased vessels, initial CAD treatment).\u003c/p\u003e\u003cp\u003eAll statistical tests were two-tailed, and significance was set at P\u0026thinsp;\u0026lt;\u0026thinsp;.05. Analyses were conducted using R version 4.2.2 (R Project for Statistical Computing).\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe MASS Registry enrolled 884 patients with T2DM, multivessel CAD, and preserved left ventricular function. Of these, 152 patients (17.1%) were excluded due to fewer than three follow-up measurements of LDL-C, HbA1c, or triglycerides. Additionally, 11 patients (1.2%) had at least one interval between consecutive laboratory measurements of these markers exceeding 5 years, and 3 patients (0.3%) were excluded due to incomplete clinical follow-up data. The final study population comprised 718 patients, who were followed for a mean (SD) duration of 8.0 (\u0026plusmn;\u0026thinsp;3.4) years. These patients were grouped based on the number of metabolic factors within target range for further analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn total, 5,562 LDL-C measurements were recorded, with an average of 7.7 (\u0026plusmn;\u0026thinsp;2.7) measurements per patient. Additionally, 4,974 HbA1c measurements were obtained, averaging 6.9 (\u0026plusmn;\u0026thinsp;2.4) measurements per patient, and 5,252 triglyceride measurements were recorded, averaging 7.3 (\u0026plusmn;\u0026thinsp;2.7) per patient.\u003c/p\u003e\u003cp\u003eOf the 718 patients included in the final analysis, 199 (27.8%) had all three metabolic factors controlled. The number of patients with two, one, or no factors controlled was 260 (36.2%), 175 (24.3%), and 84 (11.7%), respectively.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eBaseline Characteristics\u003c/h2\u003e\u003cp\u003eThe baseline characteristics of the 718 patients are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The group achieving control of all metabolic factors were older (63 years) compared to the group with no controlled factors (57 years). The majority of patients were male (64.6%), with a higher proportion of men in the group with better metabolic control (74% versus 54% in the group with no factors controlled). The prevalence of smoking was 7% in the group with all factors controlled, compared to 30% in the group with no factors controlled, with a progressive increase in smoking rates correlating with fewer controlled factors.\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 of the Study Population\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=\"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=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\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\u003eGroup A\u003csup\u003e1\u003c/sup\u003e\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;199\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eGroup B\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;260\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eGroup C\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;175\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eGroup D\u003csup\u003e4\u003c/sup\u003e\u003c/p\u003e\u003cp\u003en\u0026thinsp;=\u0026thinsp;84\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDemographic Profile\u003c/p\u003e\u003cp\u003eAge, mean (SD), years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63 (\u0026plusmn;\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e62 (\u0026plusmn;\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59 (\u0026plusmn;\u0026thinsp;9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e57 (\u0026plusmn;\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e148 (74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e170 (65%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100 (57%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e46 (54%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCurrent smoker, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 (17%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43 (26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24 (30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLaboratory Values*\u003c/p\u003e\u003cp\u003eCreatinine, mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.0 (\u0026plusmn;\u0026thinsp;0.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.0 (\u0026plusmn;\u0026thinsp;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.0 (\u0026plusmn;\u0026thinsp;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.0 (\u0026plusmn;\u0026thinsp;0.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDL-C, mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e107 (\u0026plusmn;\u0026thinsp;36)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e112 (\u0026plusmn;\u0026thinsp;39)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e129 (\u0026plusmn;\u0026thinsp;37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e145 (\u0026plusmn;\u0026thinsp;37)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHDL-C, mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (\u0026plusmn;\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e41 (\u0026plusmn;\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39 (\u0026plusmn;\u0026thinsp;10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38 (\u0026plusmn;\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.056\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTriglycerides, mean (SD)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e134 (\u0026plusmn;\u0026thinsp;55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160 (\u0026plusmn;\u0026thinsp;90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e225 (\u0026plusmn;\u0026thinsp;119)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e265 (\u0026plusmn;\u0026thinsp;128)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHbA1c, mean (SD), %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.8 (\u0026plusmn;\u0026thinsp;1.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.1 (\u0026plusmn;\u0026thinsp;1.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.8 (\u0026plusmn;\u0026thinsp;2.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.1 (\u0026plusmn;\u0026thinsp;1.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMedical History\u003c/p\u003e\u003cp\u003eHypertension, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e149 (74%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e175 (72%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e130 (76%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62 (76%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.78\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMultivessel CAD, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e114 (67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e152 (67%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e115 (70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e56 (70%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.83\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLVEF, mean (SD), %\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e63 (\u0026plusmn;\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (\u0026plusmn;\u0026thinsp;8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e65 (\u0026plusmn;\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e67 (\u0026plusmn;\u0026thinsp;7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTreatment\u003c/p\u003e\u003cp\u003eMT, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e60 (30%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87 (33%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e45 (26%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19 (23%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u0026thinsp;=\u0026thinsp;0.45\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePCI, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e49 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (25%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47 (27%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26 (31%)\u003c/p\u003e\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\u003eCABG, n (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e89 (45%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e108 (42%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e83 (47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e39 (46%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003e*Laboratory values are reported in mg/dL.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003csup\u003e\u003cem\u003e1\u003c/em\u003e\u003c/sup\u003e \u003cem\u003e= All factors controlled;\u003c/em\u003e \u003csup\u003e\u003cem\u003e2\u003c/em\u003e\u003c/sup\u003e \u003cem\u003e= Two factors controlled;\u003c/em\u003e \u003csup\u003e\u003cem\u003e3\u003c/em\u003e\u003c/sup\u003e \u003cem\u003e= One factors controlled;\u003c/em\u003e \u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e \u003cem\u003e= No factors controlled\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"6\"\u003e\u003cem\u003eAbbreviations: SD\u0026thinsp;=\u0026thinsp;standard deviation; LDL-C\u0026thinsp;=\u0026thinsp;low-density lipoprotein cholesterol; HDL-C\u0026thinsp;=\u0026thinsp;high-density lipoprotein cholesterol; HbA1c\u0026thinsp;=\u0026thinsp;glycated hemoglobin; CAD\u0026thinsp;=\u0026thinsp;coronary artery disease; LVEF\u0026thinsp;=\u0026thinsp;left ventricular ejection fraction; PCI\u0026thinsp;=\u0026thinsp;percutaneous coronary intervention; CABG\u0026thinsp;=\u0026thinsp;coronary artery bypass grafting.\u003c/em\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eRenal function was preserved across all groups, and mean baseline HDL cholesterol levels were similar between groups. There were no statistically significant differences in the prevalence of arterial hypertension, presence of multivessel CAD, initial treatment strategies for CAD, or left ventricular function among the groups. The baseline characteristics of the study population are detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eCardiovascular events\u003c/h3\u003e\n\u003cp\u003eAmong the 718 patients, 118 (16.4%) died during the follow-up period, with 48 deaths (40.7%) attributed to cardiovascular causes and 70 (59.3%) to non-cardiovascular causes. The annual all-cause mortality rate was 2.0%, while the annual cardiovascular mortality rate was 0.83%. Nonfatal acute MI occurred in 58 patients (8.0%), and 24 patients (3.3%) experienced a stroke. A total of 93 patients (12.9%) underwent unplanned myocardial revascularization, with 39 (5.4%) undergoing CABG and 54 (7.5%) undergoing PCI.\u003c/p\u003e\u003cp\u003eThe composite outcome of death, MI, stroke, or unplanned revascularization was observed in 293 patients (40.8%). Notably, 71 of these events occurred in the group with all risk factors controlled (representing 35.7% of the total cohort of this group), while 45 events occurred in the group with all factors uncontrolled (53.6% of this subgroup).\u003c/p\u003e\n\u003ch3\u003eCardiovascular events and metabolic control\u003c/h3\u003e\n\u003cp\u003eIn the Cox regression model, both unadjusted and adjusted analyses (adjusting for age, sex, left ventricular ejection fraction, smoking status, number of affected coronary vessels, and initial CAD treatment) showed an increasing risk of cardiovascular events as the number of uncontrolled metabolic factors were present.\u003c/p\u003e\u003cp\u003ePatients with all factors uncontrolled had an 88% increased risk of the composite endpoint (all-cause death, non-fatal MI, non-fatal stroke, or additional revascularization) compared to those with all factors controlled in the unadjusted analysis (HR 1.88, 95% CI 1.29\u0026ndash;1.74, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). This risk rose to 187% after adjustment for covariates in the multivariate analysis (HR 2.87, 95% CI 1.81\u0026ndash;4.54, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) (Tables\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\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\u003eComparison of the Occurrence of Combined Cardiovascular Outcomes According to the Number of Controlled Factors \u0026ndash; Unadjusted Analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetabolic Control\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvents (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAll factors controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71 (35.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTwo factors controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101 (38.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.83\u0026ndash;1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOne factor controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e76 (43.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97\u0026ndash;1.86\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNo factors controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45 (53.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.29\u0026ndash;2.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\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\u003eComparison of the Occurrence of Combined Cardiovascular Outcomes According to the Number of Controlled Factors \u0026ndash; Adjusted Analysis\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMetabolic Control\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEvents (n, %)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHR\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e95% CI\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003ep-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAll factors controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e71 (35.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.00 (reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(reference)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTwo factors controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e101 (38.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.81\u0026ndash;1.68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.39\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eOne factor controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e76 (43.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.12\u0026ndash;2.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNo factors controlled\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e45 (53.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.81\u0026ndash;4.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eThe Kaplan-Meier curves demonstrated an early separation between groups starting at year two, with a marked increase in events observed among patients with a greater number of uncontrolled factors. This difference in event-free survival persisted throughout the follow-up period, as illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, emphasizing the association between metabolic control and cardiovascular outcomes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study showed a significant association between the number of uncontrolled metabolic factors and an increased risk of cardiovascular events in patients with stable CAD and T2DM over long-term follow-up. The analysis was adjusted for key baseline characteristics, including age, sex, smoking status, LVEF, extent of CAD, and initial CAD treatment. The results observed after multivariate adjustment highlights the independent nature of the findings Additionally, the homogeneity of this chronic CAD population regarding significant clinical characteristics that might influence clinical outcomes also strengths study findings.\u003c/p\u003e\u003cp\u003eThe cardiovascular events assessed in this study included a composite of death, non-fatal MI, non-fatal stroke, and unplanned myocardial revascularization, which we believe that are outcomes that can be linked to the progression of atherosclerosis. Poor control of LDL-C, HbA1c, and triglycerides could, theoretically, contribute to plaque instability, increasing the likelihood of acute atherosclerotic events. Despite the relatively low overall mortality in this high-risk population (CAD and T2DM), the presence of uncontrolled metabolic factors significantly heightened the risk of adverse events, underscoring the importance of optimal metabolic control.\u003c/p\u003e\u003cp\u003eWe observed a clear dose-response relationship, with fewer controlled factors leading to a progressive higher frequency of adverse outcomes. Specifically, patients with no controlled factors had almost twice the risk of cardiovascular events compared to those with all factors controlled.\u003c/p\u003e\u003cp\u003eThe strength of our findings is reinforced by several aspects of study design. Despite the retrospective nature, the cohort was systematically followed every six months with detailed data collection on metabolic factors. This minimized follow-up loss and ensured a high frequency of data collection for each metabolic parameter. The small number of patients with all factors uncontrolled highlights the rigor in managing these parameters, strengthening the validity of our results.\u003c/p\u003e\u003cp\u003eFurthermore, a key strength of this study is the homogeneity of factors that could have confounded results - like LVEF, the extent of CAD, and initial treatment strategy. These factors were well-balanced across groups, ensuring that the differences in outcomes were likely attributable to the degree of metabolic control rather than other clinical variables.\u003c/p\u003e\u003cp\u003eOur results are consistent with the \u003cem\u003e\u0026ldquo;Comprehensive Cardiovascular Risk Factor Control Improves Survival The BARI 2D Trial\u0026rdquo;\u003c/em\u003e\u003csup\u003e\u003cem\u003e4\u003c/em\u003e\u003c/sup\u003e, which showed that comprehensive risk factor control improves survival in patients with stable CAD and diabetes. However, while the authors of BARI 2D included both metabolic and non-metabolic factors such as smoking cessation and blood pressure control, our study focused exclusively on metabolic parameters.\u003c/p\u003e\u003cp\u003eThe HbA1c cut-off of \u0026ge;\u0026thinsp;7.5% reflects a balance between strict glycemic control and the risk of hypoglycemia in this high-risk population. Previous studies\u003csup\u003e19\u0026ndash;20\u003c/sup\u003e have shown a possible \"J-curve\" relationship between HbA1c and cardiovascular outcomes, where both high and low levels are associated with adverse events. Our choice of 7.5% mitigates the risk of hypoglycemia while identifying those with poor glycemic control. Similarly, despite lower LDL-C targets in contemporary practice, elevated LDL-C remains a critical predictor of cardiovascular events, reinforcing the importance of stringent control.\u003c/p\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study has limitations. Although the research group performed rigorous follow-up, the retrospective nature of the analysis imposes inherent limitations. Additionally, while the study identifies the association between metabolic control and adverse outcomes, the underlying causes of poor metabolic control were not evaluated. It is possible that patients with uncontrolled factors had lower treatment adherence or, more plausibly, had more severe and resistant metabolic dysregulation. These issues were beyond the scope of the present analysis. Finally, in groups with one or two uncontrolled factors, we could not assess which specific factors were uncontrolled due to sample size limitations.\u003c/p\u003e\u003cp\u003eDespite these limitations, our study suggests that in patients with stable CAD and T2DM, long-term metabolic control is associated with better cardiovascular outcomes.\u003c/p\u003e\u003c/div\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn this study, inadequate control of metabolic factors was independently associated with a higher incidence of cardiovascular events in patients with stable CAD and T2DM over long-term follow-up.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCABG\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003ecoronary artery bypass grafting\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003eCAD\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003estable coronary artery disease\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003cp\u003e This study was approved by the Ethics Committee of the Instituto do Cora\u0026ccedil;\u0026atilde;o (InCor), Universidade de S\u0026atilde;o Paulo, Brazil. Due to the retrospective nature of the study and use of de-identified data, the requirement for informed consent was waived by the ethics committee.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eAuthors\u0026rsquo; information\u003c/h2\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eV.C.A. researched data and wrote the manuscript. P.C.R supervised the research and contributed to interpretation of results and statistical analysis. W.H. conceived this study, contributed to discussion and reviewed the manuscript. R.M.R.G. and A.C.R.A. contributed to discussion and reviewed the manuscript. T.L.S., M.F.S., M.O.L.R., M.S.T., C.V.S.J., J.A.F.R., and R.K.F. contributed to review the manuscript. All authors approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors thank the clinical and administrative staff of the Instituto do Cora\u0026ccedil;\u0026atilde;o (InCor), Universidade de S\u0026atilde;o Paulo, for their continued support in maintaining the MASS Registry database and facilitating long-term follow-up. No editorial, clerical, or statistical assistance was received for the preparation of this manuscript.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eVasan RS, Sullivan LM, Wilson PW, et al. Relative importance of borderline and elevated levels of coronary heart disease risk factors. Ann Intern Med. 2005;142(6):393.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaede P, Lund-Andersen H, Parving HH, et al. Effect of a multifactorial intervention on mortality in type 2 diabetes. N Engl J Med. 2008;358:580\u0026ndash;91.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGaede P, Vedel P, Larsen N, et al. Multifactorial intervention and cardiovascular disease in patients with type 2 diabetes. N Engl J Med. 2003;348:383\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBittner V, Bertolet M, Barraza Felix R, et al. Comprehensive Cardiovascular Risk Factor Control Improves Survival: The BARI 2D Trial. J Am Coll Cardiol. 2015;66(7):765.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Type 2 diabetes mellitus, Coronary artery disease, Metabolic control, Cardiovascular outcomes","lastPublishedDoi":"10.21203/rs.3.rs-7768266/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7768266/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackgroud\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe long-term impact of metabolic control on cardiovascular outcomes in patients with type 2 diabetes mellitus and stable coronary artery disease remains uncertain. While some studies suggest benefits from multifactorial interventions, data specifically evaluating sustained control of key metabolic parameters are limited.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom 884 patients enrolled between 1995 and 2010, 718 were selected. Data were analyzed from July 2022 to July 2024. Patients were categorized into four groups based on the number of metabolic factors within target range (low-density lipoproteins (LDL-C) \u0026lt;100 mg/dL, glycated hemoglobin (HbA1C) \u0026lt;7.5%, triglycerides \u0026lt;150 mg/dL).\u003c/p\u003e\n\u003cp\u003eThe primary outcome was a composite of all-cause mortality, myocardial infarction, stroke, and unplanned myocardial revascularization. Multivariate Cox regression models were calculated adjusting for confounders including age, sex, smoking, ejection fraction, number of diseased vessels, and initial coronary artery disease treatment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOf 718 patients (mean [SD] age, 61 [8] years; 254 female [35,3%]), followed during 8 (± 3.4) years, 199 (27.8%) had all 3 metabolic factors controlled, 260 (36.2%) had 2 factors controlled, 175 (24.3%) one factor controlled, and 84 (11.7%) no factor controlled. The group with all factors controlled were older and more frequently male. A dose-response association was observed, with progressively higher event rates as fewer metabolic factors were controlled. Patients with no controlled factors had nearly threefold the risk of events compared to those with all within target levels (HR 2.87, 95% CI 1.81-4.54, p \u0026lt; 0,01) in adjusted analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn patients with stable coronary artery disease and type 2 diabetes mellitus, inadequate control of metabolic factors was associated with higher risk of cardiovascular events over long-term follow-up.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRetrospectively registered\u003c/p\u003e","manuscriptTitle":"The Impact of Metabolic Control on Cardiovascular Outcomes in Patients with Type 2 Diabetes and Chronic Multivessel Coronary Artery Disease: A Cohort Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-21 01:22:59","doi":"10.21203/rs.3.rs-7768266/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-10-17T12:28:15+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-17T08:45:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-13T21:40:08+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"10252278590441238181961627989681739554","date":"2025-10-09T21:42:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156850561948389295369324962530326010080","date":"2025-10-09T17:30:55+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-07T09:50:34+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-06T05:17:21+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-10-06T05:16:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Diabetology \u0026 Metabolic Syndrome","date":"2025-10-02T17:21:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"diabetology-and-metabolic-syndrome","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"dims","sideBox":"Learn more about [Diabetology \u0026 Metabolic Syndrome](http://dmsjournal.biomedcentral.com/)","snPcode":"13098","submissionUrl":"https://submission.nature.com/new-submission/13098/3","title":"Diabetology \u0026 Metabolic Syndrome","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a937bd87-5e63-474e-ac4d-5df3cd050c38","owner":[],"postedDate":"October 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-12-15T16:07:39+00:00","versionOfRecord":{"articleIdentity":"rs-7768266","link":"https://doi.org/10.1186/s13098-025-02027-6","journal":{"identity":"diabetology-and-metabolic-syndrome","isVorOnly":false,"title":"Diabetology \u0026 Metabolic Syndrome"},"publishedOn":"2025-12-11 15:58:17","publishedOnDateReadable":"December 11th, 2025"},"versionCreatedAt":"2025-10-21 01:22:59","video":"","vorDoi":"10.1186/s13098-025-02027-6","vorDoiUrl":"https://doi.org/10.1186/s13098-025-02027-6","workflowStages":[]},"version":"v1","identity":"rs-7768266","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7768266","identity":"rs-7768266","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}