Association Between Phosphate and Long-term Outcome in CAD Patients Underwent Coronary Intervention

Association Between Phosphate and Long-term Outcome in CAD Patients Underwent Coronary Intervention | 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 Association Between Phosphate and Long-term Outcome in CAD Patients Underwent Coronary Intervention Tsung-Ying Tsai, Pai-Feng Hsu, Cheng-Hsueh Wu, Ya-Ling Yang, Su-Chan Chen, and 15 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-535266/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Introduction Phosphate has been linked to higher cardiovascular (CV) risk. However, whether phosphate is associated with poor outcomes for patients with coronary artery disease (CAD) after percutaneous coronary interventions (PCIs) remained undetermined. Methods 2,894 CAD patients (2,220 male, aged 71.6 ± 12.2), who received PCI at TVGH from 2006 to 2015, with phosphate measurement, were enrolled. The primary outcome was the composite of major adverse CV events [MACE, comprising of CV death, nonfatal MI, and nonfatal stroke] and heart failure hospitalization(HHF). The key secondary outcome was MACE. Results There was a J-curve association between phosphate and CV events after adjusted for comorbidities and renal function. Phosphate around 3.2 ± 0.1mg/dL was associated with the lowest CV risk. In Cox analysis, each 1 mg/dL increases in phosphate was associated with a higher risk of MACE+HHF (HR:1.12, 95% CI:1.05-1.21): CV death (HR: 1.37,95% CI: 1.22-1.55) and HHF (HR: 1.12, 95% CI: 1.02-1.23). Subgroup analyses showed more prominent association between phosphate and MACE+HHF in male, age > 65, bare-metal stents (BMSs), LVEF< 50%, eGFR 70 mg/dL, and emergent PCI. Conclusion Phosphate has a J-curve association with the risk of CV events in CAD patients undergoing PCI that was independent of comorbidities and renal function. Medical Genetics Coronary artery disease Phosphate percutaneous coronary intervention outcome Chronic kidney disease Figures Figure 1 Figure 2 Figure 3 1. Background The serum phosphate level is tightly regulated in order to maintain various aspects of human physiology, including energy metabolism, neurotransmission, endothelial function, bone formation, and cardiovascular (CV) function. 1 Although abnormal phosphate metabolism is considered the hallmark of chronic kidney disease (CKD), studies have shown that abnormal serum phosphate levels are associated with vascular calcification, atherosclerosis, all-cause, and CV mortality, regardless of renal function. 2–4 Phosphate was also reported to take part in the pathogenesis of the CV disease process. 5 Hormone and markers related to the regulation of phosphate metabolism, such as serum parathyroid hormone (PTH), alkaline phosphatase (ALKP), fibroblast growth factor 23 (FGF-23), and 1.25-(OH)2-D3 (VitD3) levels as all being linked to the development and progression of CV disease through vascular calcification or systemic inflammation. 6–8 Percutaneous coronary intervention (PCI) is the main method of coronary revascularization. However, the prognosis of patients with CKD undergoing PCI is unsatisfactory. 9–12 Previous studies have shown that increased serum levels of phosphate were associated with poor revascularization outcomes. 13 However, they only investigated patients undergoing regular dialysis with a short follow-up period. Furthermore, there is limited information about the interaction between serum phosphate and future adverse risk in situations, such as the choice of stent type, the underlying left ventricular ejection fraction (LVEF), and whether the patient presented with acute coronary syndrome (ACS). As such, we conducted this retrospective Asian CAD cohort study to assess the association of serum phosphate and future CV events in CAD patients with PCI. 2. Results 2.1 Patient demographics Among 8,794 consecutive patients who received PCI for CAD between 2006 to 2015, a total of 2,894 patients (2,220 male, aged 71.6 ± 12.2) with a baseline phosphate value recorded were enrolled. The demographic characteristics of the participants are shown in Table 1 . Serum phosphate ranged from 0.5 to 12.1 mg/dL (mean 3.6 ± 1.1 mg/dL). There were 270 (9.3%) patients with hypophosphatemia, defined as a phosphate level 4.5 mg/dL. Patients with a higher phosphate level were more likely to be younger and female. They also had a higher prevalence of DM and CKD, demonstrated in Table 1. Yet, patients within the second quartile of phosphate levels tended to have higher eGFR, lower serum calcium, and a lower prevalence of heart failure. There was a J-curved association between the eGFR and serum phosphate levels, as shown in supplement Figure 1 . In linear correlation analysis, age, female gender, HF, CKD, serum uric acid, calcium, and creatinine were significantly associated with serum phosphate levels, shown in supplement Table 1. 2.2 Clinical events During a median follow-up of 65.1 ± 32.1 months, 770 (25.8%) patients met the primary endpoint, while 443 (14.8%) patients met the key secondary endpoint of MACE. For the other secondary endpoints, there were 173 CV deaths, 91 nonfatal strokes, 211 nonfatal MIs, 416 HF hospitalizations, and 579 repeated revascularization procedures in the follow-up period. Compared with the 1 st , 3 rd , and 4 th quartiles of phosphate levels, patients within the second quartile phosphate level (between 3.0–3.4 mg/dL) had the lowest risk for the primary endpoint, MACE, CV death, and HF hospitalizations, demonstrated in Table 2. Kaplan-Meier curves and log-rank analyses also showed that patients in the second quartile of serum phosphate levels had a significantly lower risk for the primary endpoint and MACE ( Figures 1A and 1B ). Spline curve analysis showed a J-shaped relationship between serum phosphate levels and the odds of the primary endpoint, with MACE as the lowest point between phosphate levels of 3.0–3.4 mg/dL as well ( Figures 2A and 2B ). Table 2 showed an association between serum phosphate values and future CV risks, according to quartiles (the second quartile was the reference category) and continuous values. The unadjusted Cox-regression (model 1 of Table 2) showed there was a higher risk for the primary endpoint: MACE, CV death, MI, and HF hospitalization for every 1 mg/dl increase in serum phosphate. The unadjusted model (model 1 of Table 2) also showed the risk of the primary endpoint, with MACE significantly higher in patients in the first and fourth quartiles of the phosphate levels, while MI, CV death, and HF hospitalization was significantly higher in patients within the fourth quartile of phosphate levels. However, the risk of ischemic stroke and repeat revascularization was not associated with serum phosphate levels. After adjustment for age, gender, HTN, DM, smoking, and eGFR, Cox-regression (model 2 of Table 2) showed that there was a higher risk of the primary endpoint (HR: 1.18, 95% CI:1.11 - 1.26, p<0.001), MACE (HR: 1.13, 95% CI: 1.03–1.24), CV death (HR: 1.37,95% CI: 1.22-1.55), MI (HR:1.22, 95% CI:1.09 - 1.38), and HF-related hospitalization (HR: 1.12, 95% CI: 1.02-1.23) for every 1 mg/dl increase in serum phosphate. However, the higher risk was only seen in patients with phosphate levels in the fourth quartile after adjustment. 2.3 Subgroup analysis Results of the prespecified subgroup analysis were demonstrated in Table 3, showing the risk associated with the phosphate level, which appeared different for several subgroups. A J-shaped association between poor outcome and phosphate level was more pronounced among the male gender, age > 65 years, using BMS, LVEF< 50%, eGFR 70 mg/dL, and the presence of MI at enrollment. (Figure 3, supplement Figure 2) The association between CV risk and phosphate level appeared to be linear for those with CKD. 3. Discussion In this retrospective cohort study of 2,894 Asian patients with CAD undergoing PCI, we demonstrated that (1) serum phosphate is an independent risk factor of adverse clinical outcomes after PCI; (2) the association between phosphate level and clinical outcomes is J-shaped, with the lowest future CV event risk observed for phosphate levels at approximately 3.0-3.4 mg/dL. Even adjusted for comorbidities and renal function, the serum phosphate level is independently associated with future risk of CV mortality, major CV events, and HF hospitalization. (3) Subgroup analyses further show the association between serum phosphate level and CV risk as more prominent in the male gender, age > 65 years old, using BMS, LVEF < 50%, eGFR 70 mg/dL with the presence of MI at enrollment; this indicates the importance of phosphate serum level in determining future CV outcomes in high-risk patients after a coronary PCI. Phosphate homeostasis is essential for the maintenance of normal CV function. An abnormal phosphate balance and phosphate modulating hormones can damage the CV system. In cell and animal models, researchers found that phosphate plays a pivotal role in vascular calcification by inducing vascular smooth muscle cells (VSMCs) to undergo phenotypic changes in the osteochondrogenic phenotype. 14,15 Under the influence of phosphate, VSMCs lose the normal expression of calcification inhibitors and begin to express osteogenic markers. 16 A high phosphate level can also inhibit Vitamin D production. Without adequate vitamin D, the renin-angiotensin-aldosterone system activates in an unopposed manner, and results in dysregulated cardiomyocyte proliferation, inflammation, and atherosclerosis progression. 17,18 The association between phosphate exposure and calcification are both time- and dose-dependent, leading to diffuse medial calcification, the hallmark of CKD-related CV disease. 15 In addition to the cellular impact of phosphate to vessel walls, elevated serum phosphate is an independent risk factor for the development of CAD, progression of atherosclerotic plaques, MI, and CV death. 2,4,5,19,20 Phosphate dysregulation was observed to be associated with atrial fibrillation, left ventricular hypertrophy, heart failure, and stroke. 21–24 Moreover, many studies show the association between poor CV outcomes and phosphates, which are significant for patients without CKD, as the link extends beyond the commonly-recognized abnormal zone. 4,20 The Framingham offspring registry and the Cholesterol and Recurrent Events Study (CARE) registry show that for patients with normal renal function, phosphate levels > 3.5 mg/dL correlate with a higher risk of CV events. 4,25 In the current study, subgroup analysis demonstrated the association of serum phosphate levels and future adverse outcomes in patients who underwent PCI; this showed that the J-shaped relationship was more significant in the male gender, age > 65 years, using BMS, LVEF<50%, eGFR 70 mg/dL and the presence of MI at enrollment. Aronson et al. reported an independent association between serum phosphate, all-cause mortality, and heart failure in patients after acute myocardial infarction (AMI). The risk for mortality appears to increase with serum phosphate levels within the normal range and becomes even more prominent in the presence of CKD. Our current study expanded the association to all CAD patients, including those receiving elective PCI. 26 It also coincided with Kestenbaum’s observation that serum phosphate levels > 3.5 mg/dl were associated with a significantly increased risk of death. 27 Furthermore, our study reported a significant association between serum phosphate levels, higher risk of HF hospitalization, and total CV events (especially those using BMS, LVEF<50%, eGFR 70 mg/dL and the presence of MI at enrollment); this suggests that higher phosphate carries a generally higher risk in high-risk patients. There is limited information explaining why a more prominent association between phosphate level and risk of total CV events was observed with BMSs than DESs. Although DES and BMS were reported to have no significant difference in the outcome of CV death or MI, DES use reduces the risk of revascularization and stent thrombosis. 28 Moreover, Sung et al. reviewed 966 patients receiving PCI in Taiwan and reported that DES was related to better outcomes (reducing MI and mortality) than BMS. 29 This may suggest that elevated serum phosphate adds more risk for vulnerable patients. A similar association between serum phosphate and future risk in the heart failure population was observed [42]. Our subgroup analysis provides insight about patients with high CV risk at baseline, particularly vulnerable to the additional risk from phosphate imbalance, and how intervention can reduce CV risk with DES use, while lipid lowering may mitigate these problems. Our study has several limitations. First, this study was designed as a retrospective observation cohort: the timing and indication for phosphate level collection was not controlled. There is also potential for selection bias, as phosphate levels were probably only checked in patients with certain characteristics, such as renal function alteration or electrolyte imbalance. Second, we could only recruit patients receiving PCI, thus the association between phosphate and coronary artery bypass graft (CABG) was not explored. Third, we were unable to collect all information about medications and patient diets - which may have significantly affected phosphate levels. In conclusion, our study showed that high serum phosphate levels are significantly associated with poor outcomes in CAD patients receiving PCI. The association between phosphate level and clinical outcome is J-shaped, with the lowest future CV risk observed for levels around 3.0-3.4 mg/dL after adjustment for comorbidities and renal function. The association between serum phosphate level and CV risk was more obvious in the male gender, age > 65 years, using BMS, LVEF<50%, eGFR 70 mg/dL, and the presence of MI at enrollment, indicating the importance of serum level of phosphate in determining future CV outcomes in vulnerable patients after PCI. 4. Methods We retrospectively reviewed patients who had received PCI for CAD from 2006 to 2015 at the Taipei Veterans General Hospital. Patients with a measured serum phosphate level at enrollment, who underwent successful PCI, were enrolled. The demographic characteristics, biochemical data, procedural details, and clinical outcomes of these patients were collected from the electronic medical record review. This study followed the Declaration of Helsinki and was approved by the Internal Research Board of Taipei Veterans General Hospital (IRB No. 2016-03-014CC). It was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research. The patient data used in this study was untraceable and anonymous before entering the analysis. According to the Internal Research Board of Taipei Veterans General Hospital, patient informed consent formed was not required. PCI procedures were performed in conformity with the 2010 ESC/EACTS guidelines on myocardial revascularization. 30 In brief, coronary angiography was performed with standard procedures. Unfractionated heparin was administered to achieve an activated clotting time of > 300 s. After successful wire-crossing, lesion modification was usually performed by balloon dilatations. Rotablations were performed for heavily calcified or balloon-uncrossable lesions. Following dilatation and/or lesion modification, a stent was deployed for most lesions. Successful PCI was defined as residual stenosis < 30% with thrombolysis in MI (TIMI), grade 3 flow at the end of the procedure. Following the procedures, all patients received aspirin (100 mg/d) indefinitely and a P2Y12 inhibitor for at least one month if a bare-metal stent (BMS) was deployed, or at least one year if a drug-eluting stent (DES) was deployed. All patients were observed for a minimum of 8 hours and then discharged under stable conditions. Baseline information such as body mass index (BMI) and smoking status were collected. We obtained a detailed medical history for comorbid conditions such as hypertension (HTN), diabetes mellites (DM), dyslipidemia, stroke, chronic kidney disease (CKD), heart failure (HF), and the medication history transcribed from electronic medical records. Procedure details of the PCI, including indication for the procedure (ACS or elective), the type of deployed stents (BMSs or DESs), were collected from the procedure notes. Biochemical parameters, including serum phosphate, serum calcium, serum creatinine, uric acid, hemoglobin, low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C), were measured using a TBA-c16000 automatic analyzer (Toshiba Medical Systems, Tochigi, Japan) following an overnight fast before the index procedure. The ejection fraction from the left ventriculography and echocardiographic study were also evaluated when available. The primary endpoint was the composite of CV deaths, nonfatal MIs, nonfatal strokes, or HF hospitalizations. The key secondary outcome was major adverse CV events [MACE, defined as the composite of CV deaths, nonfatal MIs, and nonfatal strokes]. Other secondary outcomes included the individual components of MACE, HF hospitalizations, and repeat revascularization. The data was expressed as mean ± standard deviation for continuous variables and mean ± 95% confidence interval (CI) for categorical variables. Demographic characteristics and biochemical variables were compared using the Student’s t-test and the Mann–Whitney U test to compare continuous variables when appropriate, with chi-square tests used for categorical variables. The association between the serum phosphate level and clinical and biochemical variables was evaluated sequentially with multiple linear regression. To evaluate the association between serum phosphate and clinical outcomes, the serum phosphate was categorized into four quartiles. Survival to the primary and secondary endpoints of the four groups was compared with the stepwise Cox proportional hazards models, while backward selection was used to calculate hazard ratios (HRs) and 95% CI for serum phosphate categories. To adjust for confounding variables, a second Cox hazard ratio was performed with adjustment for age, gender, hypertension, DM, smoking status, and estimated glomerular filtration rate (eGFR). Subgroup and sensitivity analyses were also performed. Prespecified subgroups in these analyses were defined according to age ( 65 years of age or older), gender, DM, hypertension (HTN), smoking, BMI (< 22kg/m 2 , or 22kg/m 2 or more), LDL (< 70 mg/dL, 70 mg/dL or more), HDL (< 40 mg/dL, 40 mg/dL or more), ACS, eGFR (< 60 ml/min/1.73 2 , 60 ml/min/1.73 2 or more), LVEF (< 50%, 50% or more), DES use, and dialysis status. Statistical significance was set as P < 0.05. All statistical analyses were carried out with SPSS 20.0 software (IBM, Inc. Chicago, IL, USA) Declarations Funding: Research foundation of cardiovascular medicine, Taiwan. No. 107-02-006 Disclosure Statement: The authors have nothing to disclose. References Weisinger, J. R. &Bellorín-Font, E. Magnesium and phosphorus. Lancet vol. 352 391–396 (1998). Larsson, T. E. et al. Conjoint effects of serum calcium and phosphate on risk of total, cardiovascular, and noncardiovascular mortality in the community. Arterioscler. Thromb. Vasc. Biol. 30 , 333–339 (2010). Shin, S. et al. 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Med. 375 , 1242–1252 (2016). Sung, S. H. et al. Comparison of clinical outcomes in patients undergoing coronary intervention with drug-eluting stents or bare-metal stents: A nationwide population study. Acta Cardiol. Sin. 33 , 10–19 (2017). Sousa-Uva, M. et al. 2018 ESC/EACTS Guidelines on myocardial revascularization The Task Force on myocardial revascularization of the European Society of Cardiology (ESC) and European Association for Cardio-Thoracic Surgery (EACTS) Developed with the special contribution of th. doi:10.1093/eurheartj/ehy394. Tables Table 1 Baseline clinical characteristics among quartiles of serum phosphate Overall (n=2894) 1 st quartile (IP 0~3mg/dL) (n=765) 2 nd quartile (IP 3~3.4mg/dL) (n=790) 3 rd quartile (IP 3.5~4mg/dL) (n=762) 4 th quartile (IP>4mg/dL) (n=667) p value p for trend IP 3.56±1.08 2.49±0.41 3.21±0.14 3.72±0.17 5.01±1.16 <.0001 <.0001 Male Gender (n, %) 2220 (74.4) 627 (82.0) 639 (80.9) 559 (73.4) 395 (59.2) <0.001 <.0001 Age(y/o) 71.59±12.20 74.54±11.20 71.28±12.00 71.16±12.52 69.08±12.52 <0.001 <.0001 BMI 25.06±3.98 24.69±3.92 25.24±3.98 25.10±3.74 25.21±4.27 0.040 0.031 Smoking (n, %) 1149 (38.5) 314 (41.1) 317 (40.1) 296 (38.9) 222 (33.3) 0.0136 0.004 Dyslipidemia (n, %) 696 (23.3) 115 (15.0) 95 (12.0) 78 (10.2) 84 (12.6) 0.0413 <.0001 Diabetes (n, %) 1341 (44.9) 298 (39.0) 336 (42.5) 337 (44.2) 370 (55.5) <.0001 <.0001 Hypertension (n, %) 2543 (85.2) 653 (85.4) 682 (86.3) 647 (84.9) 561 (84.1) 0.6829 0.403 Heart failure (n, %) 593 (19.9) 148 (19.4) 124 (15.7) 141 (18.5) 180 (27.0) <.0001 <.0001 Stroke (n, %) 230 (7.7) 52 (6.8) 47 (6.0) 75 (9.8) 56 (8.4) 0.0218 0.028 CKD (n, %) 351 (11.8) 66 (8.6) 67 (8.5) 69 (9.1) 149 (22.3) <.0001 <.0001 ACS (n, %) 1318 (44.2) 144(18.8) 178(22.5) 163(21.4) 153(22.9) 0.929 0.654 Table 1 cont. Baseline clinical characteristics among quartiles of serum phosphate Overall (n=2894) 1 st quartile (IP 0~3mg/dL) (n=765) 2 nd quartile (IP 3~3.4mg/dL) (n=790) 3 rd quartile (IP 3.5~4mg/dL) (n=762) 4 th quartile (IP>4mg/dL) (n=667) p value p for trend Creatinine 2.06±2.23 1.63±1.48 1.59±1.40 1.69±1.66 3.39±3.35 <.0001 <.0001 eGFR 53.20±29.34 56±24 59.14±29.76 57.04±28.21 38.17±30.38 <.0001 <.0001 Hemoglobin 12.23±2.12 12.34±2.05 12.64±2.05 12.44±2.01 11.38±2.19 <.0001 <.0001 Uric acid 6.60±2.08 6.19±2.01 6.49±1.96 6.66±1.99 7.13±2.30 <.0001 <.0001 Calcium 8.90±0.72 9±0.76 8.91±0.61 8.96±0.69 8.97±0.87 <.0001 <.0001 HDL 42.20±12.47 41.87±12.34 43.10±12.53 42.29±12.59 41.38±12.36 0.070 0.3337 LDL 104.10±34.76 102.11±35.24 103.34±32.51 107.06±34.72 103.78±36.70 0.042 0.053 Beta blockers 1246 (41.8%) 289 (37.8%) 329 (41.7%) 336 (44.1%) 292 (43.8%) 0.05 0.011 Statins 1386 (46.4%) 327 (42.8%) 376 (48.0%) 402 (52.8%) 281 (42.1%) <.0001 0.489 ACEI/ARB 1378 (46.2%) 348(45.5%) 386(48.9%) 338(44.4%) 306(45.9%) 0.099 0.245 ACEI/ARB= angiotensin converting enzyme inhibitor/ angiotensin receptor blockers; CKD=Chronic kidney disease, HDL= High density lipoprotein-cholesterol; LDL= low density lipoprotein-cholesterol Table 2 Association between serum phosphate level in quartiles and clinical outcomes Unadjusted (model 1) Adjusted* (model 2) Events, n (%) HR (95% CI) p value HR (95% CI) p value Primary endpoint Q1(0~3mg/dL) 190 (24.8) 1.28(1.04 - 1.57) 0.021 1.15(0.93 - 1.41) 0.194 Q2(3~3.4mg/dL) 173 (21.9) Reference -- Reference -- Q3(3.5~4 mg/dL) 193 (25.3) 1.20(0.98 - 1.47) 0.084 1.15(0.94 - 1.41) 0.185 Q4(>4 mg/dL) 214 (32.1) 1.89(1.54 - 2.31) 0.000 1.55(1.25 - 1.92) 0.000 Cont. -- 1.18(1.11 - 1.26) 0.000 1.12(1.05 - 1.21) 0.001 MACE Q1(0~3mg/dL) 116 (15.2) 1.40(1.07 - 1.84) 0.015 1.31(1.00 - 1.72) 0.053 Q2(3~3.4mg/dL) 95 (12.0) Reference -- Reference -- Q3(3.5~4 mg/dL) 107 (14.0) 1.21(0.91 - 1.59) 0.185 1.16(0.88 - 1.53) 0.292 Q4(>4 mg/dL) 125 (18.7) 1.94(1.49 - 2.54) 0.000 1.53(1.15 - 2.03) 0.004 Cont. -- 1.21(1.11 - 1.31) 0.000 1.13(1.03 - 1.24) 0.007 MI Q1(0~3mg/dL) 54 (7.1) 1.39(0.94 - 2.07) 0.101 1.37(0.92 - 2.04) 0.118 Q2(3~3.4mg/dL) 45 (5.7) Reference -- Reference -- Q3(3.5~4 mg/dL) 50 (6.6) 1.18(0.79 - 1.77) 0.419 1.15(0.76 - 1.72) 0.510 Q4(>4 mg/dL) 62 (9.3) 2.11(1.43 - 3.09) 0.000 1.51(1.00 - 2.27) 0.049 Cont. -- 1.22(1.09 - 1.38) 0.001 1.07(0.94 - 1.23) 0.298 Stroke Q1(0~3mg/dL) 29 (3.8) 1.54(0.88 - 2.67) 0.129 1.47(0.84 - 2.57) 0.177 Q2(3~3.4mg/dL) 22 (2.8) Reference -- Reference -- Q3(3.5~4 mg/dL) 25 (3.3) 1.22(0.69 - 2.16) 0.505 1.21(0.68 - 2.15) 0.521 Q4(>4 mg/dL) 15 (2.3) 1.06(0.55 - 2.05) 0.861 1.03(0.52 - 2.05) 0.935 Cont. -- 0.98(0.78 - 1.23) 0.842 0.99(0.78 - 1.26) 0.934 CV death Q1(0~3mg/dL) 36 (4.7) 1.22(0.76 - 1.97) 0.406 1.07(0.66 - 1.73) 0.780 Q2(3~3.4mg/dL) 32 (4.1) Reference -- Reference -- Q3(3.5~4 mg/dL) 40 (5.3) 1.31(0.82 - 2.09) 0.251 1.24(0.78 - 1.97) 0.372 Q4(>4 mg/dL) 65 (9.8) 2.73(1.79 - 4.17) 0.000 2.17(1.39 - 3.39) 0.001 Cont. -- 1.38(1.25 - 1.53) 0.000 1.37(1.22 - 1.55) 0.000 HF Q1(0~3mg/dL) 101 (13.2) 1.20(0.91 - 1.59) 0.200 1.03(0.78 - 1.36) 0.832 Q2(3~3.4mg/dL) 96 (12.2) Reference -- Reference -- Q3(3.5~4 mg/dL) 106 (13.9) 1.17(0.89 - 1.54) 0.272 1.11(0.84 - 1.46) 0.464 Q4(>4 mg/dL) 113 (16.9) 1.77(1.35 - 2.33) 0.000 1.51(1.13 - 2.01) 0.005 Cont. -- 1.15(1.05 - 1.26) 0.002 1.12(1.02 - 1.23) 0.023 Revascularization Q1(0~3mg/dL) 148 (19.4) 1.05(0.84 - 1.31) 0.676 1.09(0.87 - 1.36) 0.476 Q2(3~3.4mg/dL) 160 (20.3) Reference -- Reference -- Q3(3.5~4 mg/dL) 163 (21.4) 1.09(0.88 - 1.36) 0.435 1.09(0.87 - 1.35) 0.449 Q4(>4 mg/dL) 108 (16.2) 0.97(0.76 - 1.24) 0.831 0.93(0.72 - 1.20) 0.568 Cont. -- 1.00(0.92 - 1.09) 0.977 0.97(0.89 - 1.07) 0.541 MI= myocardial infraction, HF=hospitalization for decompensated heart failure, MACE=major adverse cardiovascular events including cardiovascular deaths, nonfatal stroke and nonfatal MI. Adjusted*(Model 2) was adjusted for Age, Gender, HTN, DM, Smoking and eGFR. Table 3 Additional Declarations No competing interests reported. Supplementary Files ScientificreportSupp.docx SupplementFigure1.tif SupplementFigure2.tif Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Major revision 09 Aug, 2021 Reviews received at journal 25 Jul, 2021 Reviewers agreed at journal 25 Jul, 2021 Reviewers invited by journal 01 Jun, 2021 Editor assigned by journal 01 Jun, 2021 Editor invited by journal 19 May, 2021 Submission checks completed at journal 19 May, 2021 First submitted to journal 17 May, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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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-535266","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":27813382,"identity":"b4e14591-52f3-48b9-bf03-70fed5d8fe44","order_by":0,"name":"Tsung-Ying Tsai","email":"","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Tsung-Ying","middleName":"","lastName":"Tsai","suffix":""},{"id":27813383,"identity":"2e5d47d2-eb38-40ae-abc2-693d2c56ef18","order_by":1,"name":"Pai-Feng Hsu","email":"","orcid":"","institution":"Taipei Veterans General 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Leu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8klEQVRIiWNgGAWjYBACAwbGBmYQg4+BgfEBkObhI1oLGwMDswFICxthLUClUC1sElAGfmDOf7jtcUHNHbs29h6zyq85djJsDMwPH93Ao8VyRmK78Yxjz5LbeM6Y3Zbdlgx0GJuxcQ4+h91gbJPmYTuczCaRY3ZbchszUAsPmzReLecPArX8A2qRf2NWLLmtnggtBxLbpHnbDtuxSfCYMX7cdpgILTeAWmb2HU5g40krlmbcdpyHjZmQX84ffyZd8O2wPT/74Y0ff26rBjKaHz7GpwUGEhuABDMPiMlMhHIQsAcRjD+IVD0KRsEoGAUjCwAAXaxC4T87/SMAAAAASUVORK5CYII=","orcid":"","institution":"Taipei Veterans General Hospital","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Hsin-Bang","middleName":"","lastName":"Leu","suffix":""}],"badges":[],"createdAt":"2021-05-17 15:14:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-535266/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-535266/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":9398595,"identity":"2505b00b-bda3-42c1-b564-e2dc3d94ad2a","added_by":"auto","created_at":"2021-05-20 17:01:22","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":490573,"visible":true,"origin":"","legend":"A: The Kaplan-Meier curve for survival to the primary outcome divided by quartiles of serum phosphate level. P values are for the overall comparison among the groups using the log rank test. IP=serum phosphate.\nB: The Kaplan-Meier curve for survival to MACE divided by quartiles of serum phosphate level. P values are for the overall comparison among the groups using the log rank test. MACE=major adverse cardiovascular events.","description":"","filename":"Figure1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/d0f375847559bc030faac8d1.jpg"},{"id":9398583,"identity":"61738462-df3c-4715-9941-613a5a2ee663","added_by":"auto","created_at":"2021-05-20 17:01:18","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":541758,"visible":true,"origin":"","legend":"A: Cubic spline analysis. The plot describes the relationship between serum phosphate as a continuous variable and the probability of the primary endpoint. The grey area indicates the 95% confidence interval.\nB: Cubic spline analysis. The plot describes the relationship between serum phosphate as a continuous variable and the probability of MACE. The grey area indicates the 95% confidence interval. MACE=major adverse cardiovascular events.","description":"","filename":"Figure2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/c701268182913903b71a1fb0.jpg"},{"id":9398586,"identity":"8bee30ec-dfde-460c-ab40-562a9990f8f8","added_by":"auto","created_at":"2021-05-20 17:01:19","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":183446,"visible":true,"origin":"","legend":"Prespecified subgroup analysis showing the relationship between serum phosphate quartile and the probability of the primary endpoint in different subgroups. The risk associated with phosphate level appeared more pronounced for male patients, patients received BMS, patients without CKD and patients with low EF. DES=drug eluted stents, BMS=bare metal stents, CKD=chronic kidney disease, EF=left ventricular ejection fraction.","description":"","filename":"Figure3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/1b088be6a035a5edff766b38.jpg"},{"id":13694018,"identity":"989527cd-ab66-4bb3-946e-22b8a736e811","added_by":"auto","created_at":"2021-09-17 12:51:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":682090,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/1d84a5a5-8171-409c-b3d9-fc8c323dac1b.pdf"},{"id":9398582,"identity":"108dda4f-de1e-4aa1-a219-b2272be2e957","added_by":"auto","created_at":"2021-05-20 17:01:18","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":73686,"visible":true,"origin":"","legend":"","description":"","filename":"ScientificreportSupp.docx","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/daefef4dddda2249c185876e.docx"},{"id":9398808,"identity":"a46f6fc9-eb7b-4185-afe8-f43b8fd75d9b","added_by":"auto","created_at":"2021-05-20 17:04:19","extension":"tif","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":173880,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFigure1.tif","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/e9b04792c9800742ac99c6d2.tif"},{"id":9398807,"identity":"5048a498-1761-461c-abff-7be50e1b46c8","added_by":"auto","created_at":"2021-05-20 17:04:18","extension":"tif","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":93938,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementFigure2.tif","url":"https://assets-eu.researchsquare.com/files/rs-535266/v1/f764e6b85b1c4e343df11235.tif"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAssociation Between Phosphate and Long-term Outcome in CAD Patients Underwent Coronary Intervention\u003c/p\u003e","fulltext":[{"header":"1. Background","content":"\u003cp\u003eThe serum phosphate level is tightly regulated in order to maintain various aspects of human physiology, including energy metabolism, neurotransmission, endothelial function, bone formation, and cardiovascular (CV) function. \u003csup\u003e1\u003c/sup\u003e Although abnormal phosphate metabolism is considered the hallmark of chronic kidney disease (CKD), studies have shown that abnormal serum phosphate levels are associated with vascular calcification, atherosclerosis, all-cause, and CV mortality, regardless of renal function. \u003csup\u003e2\u0026ndash;4\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003ePhosphate was also reported to take part in the pathogenesis of the CV disease process. \u003csup\u003e5\u003c/sup\u003e Hormone and markers related to the regulation of phosphate metabolism, such as serum parathyroid hormone (PTH), alkaline phosphatase (ALKP), fibroblast growth factor 23 (FGF-23), and 1.25-(OH)2-D3 (VitD3) levels as all being linked to the development and progression of CV disease through vascular calcification or systemic inflammation. \u003csup\u003e6\u0026ndash;8\u003c/sup\u003e Percutaneous coronary intervention (PCI) is the main method of coronary revascularization. However, the prognosis of patients with CKD undergoing PCI is unsatisfactory. \u003csup\u003e9\u0026ndash;12\u003c/sup\u003e Previous studies have shown that increased serum levels of phosphate were associated with poor revascularization outcomes. \u003csup\u003e13\u003c/sup\u003e However, they only investigated patients undergoing regular dialysis with a short follow-up period. Furthermore, there is limited information about the interaction between serum phosphate and future adverse risk in situations, such as the choice of stent type, the underlying left ventricular ejection fraction (LVEF), and whether the patient presented with acute coronary syndrome (ACS). As such, we conducted this retrospective Asian CAD cohort study to assess the association of serum phosphate and future CV events in CAD patients with PCI.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cp\u003e\u003cstrong\u003e2.1 Patient demographics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong 8,794 consecutive patients who received PCI for CAD between 2006 to 2015, a total of 2,894 patients (2,220 male, aged 71.6 \u0026plusmn; 12.2) with a baseline phosphate value recorded were enrolled. The demographic characteristics of the participants are shown in \u003cstrong\u003eTable 1\u003c/strong\u003e. Serum phosphate ranged from 0.5 to 12.1 mg/dL (mean 3.6 \u0026plusmn; 1.1 mg/dL). There were 270 (9.3%) patients with hypophosphatemia, defined as a phosphate level \u0026lt; 2.5 mg/dL while 356 (12.3%) patients had hyperphosphatemia, defined as phosphate level \u0026gt; 4.5 mg/dL. Patients with a higher phosphate level were more likely to be younger and female. They also had a higher prevalence of DM and CKD, demonstrated in Table 1. Yet, patients within the second quartile of phosphate levels tended to have higher eGFR, lower serum calcium, and a lower prevalence of heart failure. There was a J-curved association between the eGFR and serum phosphate levels, as shown in \u003cstrong\u003esupplement Figure 1\u003c/strong\u003e. In linear correlation analysis, age, female gender, HF, CKD, serum uric acid, calcium, and creatinine were significantly associated with serum phosphate levels, shown in\u003cstrong\u003e supplement Table 1.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.2 Clinical events\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDuring a median follow-up of 65.1 \u0026plusmn; 32.1 months, 770 (25.8%) patients met the primary endpoint, while 443 (14.8%) patients met the key secondary endpoint of MACE. For the other secondary endpoints, there were 173 CV deaths, 91 nonfatal strokes, 211 nonfatal MIs, 416 HF hospitalizations, and 579 repeated revascularization procedures in the follow-up period. Compared with the 1\u003csup\u003est\u003c/sup\u003e, 3\u003csup\u003erd\u003c/sup\u003e\u003csub\u003e,\u003c/sub\u003e and 4\u003csup\u003eth\u003c/sup\u003e quartiles of phosphate levels, patients within the second quartile phosphate level (between 3.0\u0026ndash;3.4 mg/dL) had the lowest risk for the primary endpoint, MACE, CV death, and HF hospitalizations, demonstrated in Table 2. Kaplan-Meier curves and log-rank analyses also showed that patients in the second quartile of serum phosphate levels had a significantly lower risk for the primary endpoint and MACE (\u003cstrong\u003eFigures 1A and 1B\u003c/strong\u003e). Spline curve analysis showed a J-shaped relationship between serum phosphate levels and the odds of the primary endpoint, with MACE as the lowest point between phosphate levels of 3.0\u0026ndash;3.4 mg/dL as well (\u003cstrong\u003eFigures 2A and 2B\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e showed an association between serum phosphate values and future CV risks, according to quartiles (the second quartile was the reference category) and continuous values. The unadjusted Cox-regression (model 1 of Table 2) showed there was a higher risk for the primary endpoint: MACE, CV death, MI, and HF hospitalization for every 1 mg/dl increase in serum phosphate. The unadjusted model (model 1 of Table 2) also showed the risk of the primary endpoint, with MACE significantly higher in patients in the first and fourth quartiles of the phosphate levels, while MI, CV death, and HF hospitalization was significantly higher in patients within the fourth quartile of phosphate levels. However, the risk of ischemic stroke and repeat revascularization was not associated with serum phosphate levels. After adjustment for age, gender, HTN, DM, smoking, and eGFR, Cox-regression (model 2 of Table 2) showed that there was a higher risk of the primary endpoint (HR: 1.18, 95% CI:1.11 - 1.26, p\u0026lt;0.001), MACE (HR: 1.13, 95% CI: 1.03\u0026ndash;1.24), CV death (HR: 1.37,95% CI: 1.22-1.55), MI (HR:1.22, 95% CI:1.09 - 1.38), and HF-related hospitalization (HR: 1.12, 95% CI: 1.02-1.23) for every 1 mg/dl increase in serum phosphate. However, the higher risk was only seen in patients with phosphate levels in the fourth quartile after adjustment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e2.3 Subgroup analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eResults of the prespecified subgroup analysis were demonstrated in Table 3, showing the risk associated with the phosphate level, which appeared different for several subgroups. A J-shaped association between poor outcome and phosphate level was more pronounced among the male gender, age \u0026gt; 65 years, using BMS, LVEF\u0026lt; 50%, eGFR\u0026lt; 60, LDL \u0026gt; 70 mg/dL, and the presence of MI at enrollment. (Figure 3, supplement Figure 2) The association between CV risk and phosphate level appeared to be linear for those with CKD.\u003c/p\u003e"},{"header":"3. Discussion","content":"\u003cp\u003eIn this retrospective cohort study of 2,894 Asian patients with CAD undergoing PCI, we demonstrated that (1) serum phosphate is an independent risk factor of adverse clinical outcomes after PCI; (2) the association between phosphate level and clinical outcomes is J-shaped, with the lowest future CV event risk observed for phosphate levels at approximately 3.0-3.4 mg/dL. Even adjusted for comorbidities and renal function, the serum phosphate level is independently associated with future risk of CV mortality, major CV events, and HF hospitalization. (3) Subgroup analyses further show the association between serum phosphate level and CV risk as more prominent in the male gender, age \u0026gt; 65 years old, using BMS, LVEF \u0026lt; 50%, eGFR\u0026lt; 60, LDL \u0026gt; 70 mg/dL with the presence of MI at enrollment; this indicates the importance of phosphate serum level in determining future CV outcomes in high-risk patients after a coronary PCI.\u003c/p\u003e\n\u003cp\u003ePhosphate homeostasis is essential for the maintenance of normal CV function. An abnormal phosphate balance and phosphate modulating hormones can damage the CV system. In cell and animal models, researchers found that phosphate plays a pivotal role in vascular calcification by inducing vascular smooth muscle cells (VSMCs) to undergo phenotypic changes in the osteochondrogenic phenotype. \u003csup\u003e14,15\u003c/sup\u003e Under the influence of phosphate, VSMCs lose the normal expression of calcification inhibitors and begin to express osteogenic markers. \u003csup\u003e16\u003c/sup\u003e A high phosphate level can also inhibit Vitamin D production. Without adequate vitamin D, the renin-angiotensin-aldosterone system activates in an unopposed manner, and results in dysregulated cardiomyocyte proliferation, inflammation, and atherosclerosis progression. \u003csup\u003e17,18\u003c/sup\u003e The association between phosphate exposure and calcification are both time- and dose-dependent, leading to diffuse medial calcification, the hallmark of CKD-related CV disease. \u003csup\u003e15\u003c/sup\u003e In addition to the cellular impact of phosphate to vessel walls, elevated serum phosphate is an independent risk factor for the development of CAD, progression of atherosclerotic plaques, MI, and CV death. \u003csup\u003e2,4,5,19,20\u003c/sup\u003e Phosphate dysregulation was observed to be associated with atrial fibrillation, left ventricular hypertrophy, heart failure, and stroke. \u003csup\u003e21\u0026ndash;24\u003c/sup\u003e Moreover, many studies show the association between poor CV outcomes and phosphates, which are significant for patients without CKD, as the link extends beyond the commonly-recognized abnormal zone. \u003csup\u003e4,20\u003c/sup\u003e The Framingham\u0026nbsp;offspring registry and the Cholesterol and Recurrent Events Study (CARE)\u0026nbsp;registry show that for patients with normal renal function, phosphate levels \u0026gt; 3.5 mg/dL correlate with a higher risk of CV events. \u003csup\u003e4,25\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eIn the current study, subgroup analysis demonstrated the association of serum phosphate levels and future adverse outcomes in patients who underwent PCI; this showed that the J-shaped relationship was more significant in the male gender, age \u0026gt; 65 years, using BMS, LVEF\u0026lt;50%, eGFR\u0026lt; 60, LDL \u0026gt; 70 mg/dL and the presence of MI at enrollment. Aronson et al. reported an independent association between serum phosphate, all-cause mortality, and heart failure in patients after acute myocardial infarction (AMI). The risk for mortality appears to increase with serum phosphate levels within the normal range and becomes even more prominent in the presence of CKD. Our current study expanded the association to all CAD patients, including those receiving elective PCI. \u003csup\u003e26\u003c/sup\u003e It also coincided with Kestenbaum\u0026rsquo;s observation that serum phosphate levels \u0026gt; 3.5 mg/dl were associated with a significantly increased risk of death. \u003csup\u003e27\u003c/sup\u003e Furthermore, our study reported a significant association between serum phosphate levels, higher risk of HF hospitalization, and total CV events (especially those using BMS, LVEF\u0026lt;50%, eGFR\u0026lt; 60, LDL \u0026gt; 70 mg/dL and the presence of MI at enrollment); this suggests that higher phosphate carries a generally higher risk in high-risk patients. There is limited information explaining why a more prominent association between phosphate level and risk of total CV events was observed with BMSs than DESs. Although DES and BMS were reported to have no significant difference in the outcome of CV death or MI, DES use reduces the risk of revascularization and stent thrombosis. \u003csup\u003e28\u003c/sup\u003e Moreover, Sung et al. reviewed 966 patients receiving PCI in Taiwan and reported that DES was related to better outcomes (reducing MI and mortality) than BMS. \u003csup\u003e29\u003c/sup\u003e This may suggest that elevated serum phosphate adds more risk for vulnerable patients. A similar association between serum phosphate and future risk in the heart failure population was observed [42]. Our subgroup analysis provides insight about patients with high CV risk at baseline, particularly vulnerable to the additional risk from phosphate imbalance, and how intervention can reduce CV risk with DES use, while lipid lowering may mitigate these problems.\u003c/p\u003e\n\u003cp\u003eOur study has several limitations. First, this study was designed as a retrospective observation cohort: the timing and indication for phosphate level collection was not controlled. There is also potential for selection bias, as phosphate levels were probably only checked in patients with certain characteristics, such as renal function alteration or electrolyte imbalance. Second, we could only recruit patients receiving PCI, thus the association between phosphate and coronary artery bypass graft (CABG) was not explored. Third, we were unable to collect all information about medications and patient diets - which may have significantly affected phosphate levels.\u003c/p\u003e\n\u003cp\u003eIn conclusion, our study showed that high serum phosphate levels are significantly associated with poor outcomes in CAD patients receiving PCI. The association between phosphate level and clinical outcome is J-shaped, with the lowest future CV risk observed for levels around 3.0-3.4 mg/dL after adjustment for comorbidities and renal function. The association between serum phosphate level and CV risk was more obvious in the male gender, age \u0026gt; 65 years, using BMS, LVEF\u0026lt;50%, eGFR \u0026lt; 60, LDL \u0026gt; 70 mg/dL, and the presence of MI at enrollment, indicating the importance of serum level of phosphate in determining future CV outcomes in vulnerable patients after PCI.\u003c/p\u003e"},{"header":"4. Methods","content":"\u003cp\u003eWe retrospectively reviewed patients who had received PCI for CAD from 2006 to 2015 at the Taipei Veterans General Hospital. Patients with a measured serum phosphate level at enrollment, who underwent successful PCI, were enrolled. The demographic characteristics, biochemical data, procedural details, and clinical outcomes of these patients were collected from the electronic medical record review. This study followed the Declaration of Helsinki and was approved by the Internal Research Board of Taipei Veterans General Hospital (IRB No. 2016-03-014CC).\u003c/p\u003e\n\u003cp\u003eIt was not appropriate or possible to involve patients or the public in the design, or conduct, or reporting, or dissemination plans of our research. The patient data used in this study was untraceable and anonymous before entering the analysis. According to the Internal Research Board of Taipei Veterans General Hospital, patient informed consent formed was not required.\u003c/p\u003e\n\u003cp\u003ePCI procedures were performed in conformity with the 2010 ESC/EACTS guidelines on myocardial revascularization. \u003csup\u003e30\u003c/sup\u003e In brief, coronary angiography was performed with standard procedures. Unfractionated heparin was administered to achieve an activated clotting time of \u0026gt; 300 s. After successful wire-crossing, lesion modification was usually performed by balloon dilatations. Rotablations were performed for heavily calcified or balloon-uncrossable lesions. Following dilatation and/or lesion modification, a stent was deployed for most lesions. Successful PCI was defined as residual stenosis \u0026lt; 30% with thrombolysis in MI (TIMI), grade 3 flow at the end of the procedure. Following the procedures, all patients received aspirin (100 mg/d) indefinitely and a P2Y12 inhibitor for at least one month if a bare-metal stent (BMS) was deployed, or at least one year if a drug-eluting stent (DES) was deployed. All patients were observed for a minimum of 8 hours and then discharged under stable conditions.\u003c/p\u003e\n\u003cp\u003eBaseline information such as body mass index (BMI) and smoking status were collected. We obtained a detailed medical history for comorbid conditions such as hypertension (HTN), diabetes mellites (DM), dyslipidemia, stroke, chronic kidney disease (CKD), heart failure (HF), and the medication history transcribed from electronic medical records. Procedure details of the PCI, including indication for the procedure (ACS or elective), the type of deployed stents (BMSs or DESs), were collected from the procedure notes. Biochemical parameters, including serum phosphate, serum calcium, serum creatinine, uric acid, hemoglobin, low-density lipoprotein-cholesterol (LDL-C), and high-density lipoprotein-cholesterol (HDL-C), were measured using a TBA-c16000 automatic analyzer (Toshiba Medical Systems, Tochigi, Japan) following an overnight fast before the index procedure. The ejection fraction from the left ventriculography and echocardiographic study were also evaluated when available.\u003c/p\u003e\n\u003cp\u003eThe primary endpoint was the composite of CV deaths, nonfatal MIs, nonfatal strokes, or HF hospitalizations. The key secondary outcome was major adverse CV events [MACE, defined as the composite of CV deaths, nonfatal MIs, and nonfatal strokes]. Other secondary outcomes included the individual components of MACE, HF hospitalizations, and repeat revascularization.\u003c/p\u003e\n\u003cp\u003eThe data was expressed as mean \u0026plusmn; standard deviation for continuous variables and mean \u0026plusmn; 95% confidence interval (CI) for categorical variables. Demographic characteristics and biochemical variables were compared using the Student\u0026rsquo;s t-test and the Mann\u0026ndash;Whitney U test to compare continuous variables when appropriate, with chi-square tests used for categorical variables. The association between the serum phosphate level and clinical and biochemical variables was evaluated sequentially with multiple linear regression. To evaluate the association between serum phosphate and clinical outcomes, the serum phosphate was categorized into four quartiles. Survival to the primary and secondary endpoints of the four groups was compared with the stepwise Cox proportional hazards models, while backward selection was used to calculate hazard ratios (HRs) and 95% CI for serum phosphate categories. To adjust for confounding variables, a second Cox hazard ratio was performed with adjustment for age, gender, hypertension, DM, smoking status, and estimated glomerular filtration rate (eGFR). Subgroup and sensitivity analyses were also performed. Prespecified subgroups in these analyses were defined according to age (\u0026lt; 65 years of age, or \u0026gt; 65 years of age or older), gender, DM, hypertension (HTN), smoking, BMI (\u0026lt; 22kg/m\u003csup\u003e2\u003c/sup\u003e, or 22kg/m\u003csup\u003e2\u003c/sup\u003e or more), LDL (\u0026lt; 70 mg/dL, 70 mg/dL or more), HDL (\u0026lt; 40 mg/dL, 40 mg/dL or more), ACS, eGFR (\u0026lt; 60 ml/min/1.73\u003csup\u003e2\u003c/sup\u003e, 60 ml/min/1.73\u003csup\u003e2 \u003c/sup\u003eor more), LVEF (\u0026lt; 50%, 50% or more), DES use, and dialysis status. Statistical significance was set as P \u0026lt; 0.05. All statistical analyses were carried out with SPSS 20.0 software (IBM, Inc. Chicago, IL, USA)\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003eResearch foundation of cardiovascular medicine, Taiwan. No. 107-02-006\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDisclosure Statement: \u003c/strong\u003eThe authors have nothing to disclose.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWeisinger, J. R. \u0026amp;Bellor\u0026iacute;n-Font, E. Magnesium and phosphorus. \u003cem\u003eLancet\u003c/em\u003e vol. 352 391\u0026ndash;396 (1998).\u003c/li\u003e\n\u003cli\u003eLarsson, T. E. \u003cem\u003eet al.\u003c/em\u003e Conjoint effects of serum calcium and phosphate on risk of total, cardiovascular, and noncardiovascular mortality in the community. \u003cem\u003eArterioscler. Thromb. Vasc. Biol.\u003c/em\u003e\u003cstrong\u003e30\u003c/strong\u003e, 333\u0026ndash;339 (2010).\u003c/li\u003e\n\u003cli\u003eShin, S. \u003cem\u003eet al.\u003c/em\u003e Impact of serum calcium and phosphate on coronary atherosclerosis detected by cardiac computed tomography. \u003cem\u003eEur. 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The Relation between Serum Phosphorus Levels and Clinical Outcomes after Acute Myocardial Infarction. \u003cem\u003ePLoS One\u003c/em\u003e\u003cstrong\u003e8\u003c/strong\u003e, (2013).\u003c/li\u003e\n\u003cli\u003eKestenbaum, B. \u003cem\u003eet al.\u003c/em\u003e Serum phosphate levels and mortality risk among people with chronic kidney disease. \u003cem\u003eJ. Am. Soc. Nephrol.\u003c/em\u003e\u003cstrong\u003e16\u003c/strong\u003e, 520\u0026ndash;528 (2005).\u003c/li\u003e\n\u003cli\u003eB\u0026oslash;naa, K. H. \u003cem\u003eet al.\u003c/em\u003e Drug-Eluting or Bare-Metal Stents for Coronary Artery Disease. \u003cem\u003eN. Engl. J. Med.\u003c/em\u003e\u003cstrong\u003e375\u003c/strong\u003e, 1242\u0026ndash;1252 (2016).\u003c/li\u003e\n\u003cli\u003eSung, S. H. \u003cem\u003eet al.\u003c/em\u003e Comparison of clinical outcomes in patients undergoing coronary intervention with drug-eluting stents or bare-metal stents: A nationwide population study. \u003cem\u003eActa Cardiol. Sin.\u003c/em\u003e\u003cstrong\u003e33\u003c/strong\u003e, 10\u0026ndash;19 (2017).\u003c/li\u003e\n\u003cli\u003eSousa-Uva, M. \u003cem\u003eet al.\u003c/em\u003e 2018 ESC/EACTS Guidelines on myocardial revascularization The Task Force on myocardial revascularization of the European Society of Cardiology (ESC) and European Association for Cardio-Thoracic Surgery (EACTS) Developed with the special contribution of th. doi:10.1093/eurheartj/ehy394.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\" width=\"1021\"\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 Baseline clinical characteristics among quartiles of serum phosphate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003eOverall\u003c/p\u003e\n\u003cp\u003e(n=2894)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e1\u003csup\u003est\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP 0~3mg/dL) (n=765)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e2\u003csup\u003end\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP 3~3.4mg/dL)\u003c/p\u003e\n\u003cp\u003e(n=790)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e3\u003csup\u003erd\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP 3.5~4mg/dL)\u003c/p\u003e\n\u003cp\u003e(n=762)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e4\u003csup\u003eth\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP\u0026gt;4mg/dL)\u003c/p\u003e\n\u003cp\u003e(n=667)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ep for trend\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eIP\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e3.56\u0026plusmn;1.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e2.49\u0026plusmn;0.41\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e3.21\u0026plusmn;0.14\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e3.72\u0026plusmn;0.17\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e5.01\u0026plusmn;1.16\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eMale Gender (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e2220 (74.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e627 (82.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e639 (80.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e559 (73.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e395 (59.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eAge(y/o)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e71.59\u0026plusmn;12.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e74.54\u0026plusmn;11.20\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e71.28\u0026plusmn;12.00\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e71.16\u0026plusmn;12.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e69.08\u0026plusmn;12.52\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eBMI\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e25.06\u0026plusmn;3.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e24.69\u0026plusmn;3.92\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e25.24\u0026plusmn;3.98\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e25.10\u0026plusmn;3.74\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e25.21\u0026plusmn;4.27\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.040\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.031\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eSmoking (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e1149 (38.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e314 (41.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e317 (40.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e296 (38.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e222 (33.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0136\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eDyslipidemia (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e696 (23.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e115 (15.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e95 (12.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e78 (10.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e84 (12.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0413\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eDiabetes (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e1341 (44.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e298 (39.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e336 (42.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e337 (44.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e370 (55.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eHypertension (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e2543 (85.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e653 (85.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e682 (86.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e647 (84.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e561 (84.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.6829\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.403\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eHeart failure (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e593 (19.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e148 (19.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e124 (15.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e141 (18.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e180 (27.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eStroke (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e230 (7.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e52 (6.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e47 (6.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e75 (9.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e56 (8.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.0218\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.028\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eCKD (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e351 (11.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e66 (8.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e67 (8.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e69 (9.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e149 (22.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eACS (n, %)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e1318 (44.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e144(18.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e178(22.5)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e163(21.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e153(22.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.929\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.654\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\" width=\"1021\"\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1 cont. Baseline clinical characteristics among quartiles of serum phosphate\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003eOverall\u003c/p\u003e\n\u003cp\u003e(n=2894)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e1\u003csup\u003est\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP 0~3mg/dL) (n=765)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e2\u003csup\u003end\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP 3~3.4mg/dL)\u003c/p\u003e\n\u003cp\u003e(n=790)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e3\u003csup\u003erd\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP 3.5~4mg/dL)\u003c/p\u003e\n\u003cp\u003e(n=762)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e4\u003csup\u003eth\u003c/sup\u003e quartile\u003c/p\u003e\n\u003cp\u003e(IP\u0026gt;4mg/dL)\u003c/p\u003e\n\u003cp\u003e(n=667)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003ep for trend\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eCreatinine\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e2.06\u0026plusmn;2.23\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e1.63\u0026plusmn;1.48\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e1.59\u0026plusmn;1.40\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e1.69\u0026plusmn;1.66\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e3.39\u0026plusmn;3.35\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eeGFR\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e53.20\u0026plusmn;29.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e56\u0026plusmn;24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e59.14\u0026plusmn;29.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e57.04\u0026plusmn;28.21\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e38.17\u0026plusmn;30.38\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eHemoglobin\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e12.23\u0026plusmn;2.12\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e12.34\u0026plusmn;2.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e12.64\u0026plusmn;2.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e12.44\u0026plusmn;2.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e11.38\u0026plusmn;2.19\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eUric acid\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e6.60\u0026plusmn;2.08\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e6.19\u0026plusmn;2.01\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e6.49\u0026plusmn;1.96\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e6.66\u0026plusmn;1.99\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e7.13\u0026plusmn;2.30\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eCalcium\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e8.90\u0026plusmn;0.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e9\u0026plusmn;0.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e8.91\u0026plusmn;0.61\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e8.96\u0026plusmn;0.69\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e8.97\u0026plusmn;0.87\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eHDL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e42.20\u0026plusmn;12.47\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e41.87\u0026plusmn;12.34\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e43.10\u0026plusmn;12.53\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e42.29\u0026plusmn;12.59\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e41.38\u0026plusmn;12.36\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.070\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.3337\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eLDL\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e104.10\u0026plusmn;34.76\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e102.11\u0026plusmn;35.24\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e103.34\u0026plusmn;32.51\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e107.06\u0026plusmn;34.72\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e103.78\u0026plusmn;36.70\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.042\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.053\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eBeta blockers\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e1246 (41.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e289 (37.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e329 (41.7%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e336 (44.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e292 (43.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.05\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.011\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eStatins\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e1386 (46.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e327 (42.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e376 (48.0%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e402 (52.8%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e281 (42.1%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e\u0026lt;.0001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.489\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd width=\"180\"\u003e\n\u003cp\u003eACEI/ARB\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"130\"\u003e\n\u003cp\u003e1378 (46.2%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e348(45.5%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e386(48.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e338(44.4%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"135\"\u003e\n\u003cp\u003e306(45.9%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.099\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd width=\"85\"\u003e\n\u003cp\u003e0.245\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr\u003e\n\u003ctd colspan=\"8\" width=\"1021\"\u003e\n\u003cp\u003eACEI/ARB= angiotensin converting enzyme inhibitor/ angiotensin receptor blockers; CKD=Chronic kidney disease, HDL= High density lipoprotein-cholesterol; LDL= low density lipoprotein-cholesterol\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" width=\"0\"\u003e\n\u003ctbody\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"7\" width=\"680\"\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Association between serum phosphate level in quartiles and clinical outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"208\"\u003e\n\u003cp\u003eUnadjusted (model 1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"227\"\u003e\n\u003cp\u003eAdjusted* (model 2)\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 59px;\"\u003e\n\u003ctd style=\"height: 59px;\" width=\"151\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003eEvents,\u003c/p\u003e\n\u003cp\u003en (%)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"132\"\u003e\n\u003cp\u003eHR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"76\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"142\"\u003e\n\u003cp\u003eHR (95% CI)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 59px;\" width=\"85\"\u003e\n\u003cp\u003ep value\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"161\"\u003e\n\u003cp\u003e\u003cstrong\u003ePrimary endpoint\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"5\" width=\"520\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e190 (24.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.28(1.04 - 1.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.021\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.15(0.93 - 1.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.194\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e173 (21.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e193 (25.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.20(0.98 - 1.47)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.084\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.15(0.94 - 1.41)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.185\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e214 (32.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.89(1.54 - 2.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.55(1.25 - 1.92)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.18(1.11 - 1.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.12(1.05 - 1.21)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003eMACE\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e116 (15.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.40(1.07 - 1.84)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.015\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.31(1.00 - 1.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.053\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e95 (12.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e107 (14.0)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.21(0.91 - 1.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.185\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.16(0.88 - 1.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.292\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e125 (18.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.94(1.49 - 2.54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.53(1.15 - 2.03)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.004\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.21(1.11 - 1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.13(1.03 - 1.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.007\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003eMI\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e54 (7.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.39(0.94 - 2.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.101\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.37(0.92 - 2.04)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.118\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e45 (5.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e50 (6.6)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.18(0.79 - 1.77)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.419\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.15(0.76 - 1.72)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.510\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e62 (9.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e2.11(1.43 - 3.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.51(1.00 - 2.27)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.049\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.22(1.09 - 1.38)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.07(0.94 - 1.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.298\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003eStroke\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"6\" width=\"529\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e29 (3.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.54(0.88 - 2.67)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.129\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.47(0.84 - 2.57)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.177\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e22 (2.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e25 (3.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.22(0.69 - 2.16)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.505\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.21(0.68 - 2.15)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.521\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e15 (2.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.06(0.55 - 2.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.861\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.03(0.52 - 2.05)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.935\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e0.98(0.78 - 1.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.842\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e0.99(0.78 - 1.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.934\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003eCV death\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"6\" width=\"529\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e36 (4.7)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.22(0.76 - 1.97)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.406\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.07(0.66 - 1.73)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.780\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e32 (4.1)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e40 (5.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.31(0.82 - 2.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.251\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.24(0.78 - 1.97)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.372\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e65 (9.8)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e2.73(1.79 - 4.17)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e2.17(1.39 - 3.39)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.001\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.38(1.25 - 1.53)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.37(1.22 - 1.55)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003eHF\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e101 (13.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.20(0.91 - 1.59)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.200\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.03(0.78 - 1.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.832\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e96 (12.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e106 (13.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.17(0.89 - 1.54)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.272\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.11(0.84 - 1.46)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.464\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e113 (16.9)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.77(1.35 - 2.33)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.000\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.51(1.13 - 2.01)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.005\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.15(1.05 - 1.26)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.002\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.12(1.02 - 1.23)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.023\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003e\u003cstrong\u003eRevascularization\u003c/strong\u003e\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ1(0~3mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e148 (19.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.05(0.84 - 1.31)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.676\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.09(0.87 - 1.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.476\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ2(3~3.4mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e160 (20.3)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003eReference\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ3(3.5~4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e163 (21.4)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.09(0.88 - 1.36)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.435\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e1.09(0.87 - 1.35)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.449\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eQ4(\u0026gt;4 mg/dL)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e108 (16.2)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e0.97(0.76 - 1.24)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.831\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e0.93(0.72 - 1.20)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.568\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003ctr style=\"height: 35px;\"\u003e\n\u003ctd style=\"height: 35px;\" width=\"151\"\u003e\n\u003cp\u003eCont.\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" colspan=\"2\" width=\"94\"\u003e\n\u003cp\u003e--\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"132\"\u003e\n\u003cp\u003e1.00(0.92 - 1.09)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"76\"\u003e\n\u003cp\u003e0.977\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"142\"\u003e\n\u003cp\u003e0.97(0.89 - 1.07)\u003c/p\u003e\n\u003c/td\u003e\n\u003ctd style=\"height: 35px;\" width=\"85\"\u003e\n\u003cp\u003e0.541\u003c/p\u003e\n\u003c/td\u003e\n\u003c/tr\u003e\n\u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMI= myocardial infraction, HF=hospitalization for decompensated heart failure, MACE=major adverse cardiovascular events including cardiovascular deaths, nonfatal stroke and nonfatal MI.\u003c/p\u003e\n\u003cp\u003eAdjusted*(Model 2) was adjusted for Age, Gender, HTN, DM, Smoking and eGFR.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cimg 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alt=\"\" /\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Coronary artery disease, Phosphate, percutaneous coronary intervention, outcome, Chronic kidney disease","lastPublishedDoi":"10.21203/rs.3.rs-535266/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-535266/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eIntroduction\u003c/p\u003e\u003cp\u003ePhosphate has been linked to higher cardiovascular (CV) risk. However, whether phosphate is associated with poor outcomes for patients with coronary artery disease (CAD) after percutaneous coronary interventions (PCIs) remained undetermined. \u003c/p\u003e\u003cp\u003eMethods \u003c/p\u003e\u003cp\u003e2,894 CAD patients (2,220 male, aged 71.6 ± 12.2), who received PCI at TVGH from 2006 to 2015, with phosphate measurement, were enrolled. The primary outcome was the composite of major adverse CV events [MACE, comprising of CV death, nonfatal MI, and nonfatal stroke] and heart failure hospitalization(HHF). The key secondary outcome was MACE. \u003c/p\u003e\u003cp\u003eResults\u003c/p\u003e\u003cp\u003eThere was a J-curve association between phosphate and CV events after adjusted for comorbidities and renal function. Phosphate around 3.2 ± 0.1mg/dL was associated with the lowest CV risk. In Cox analysis, each 1 mg/dL increases in phosphate was associated with a higher risk of MACE+HHF (HR:1.12, 95% CI:1.05-1.21): CV death (HR: 1.37,95% CI: 1.22-1.55) and HHF (HR: 1.12, 95% CI: 1.02-1.23). Subgroup analyses showed more prominent association between phosphate and MACE+HHF in male, age \u0026gt; 65, bare-metal stents (BMSs), LVEF\u0026lt; 50%, eGFR \u0026lt;60, LDL \u0026gt;70 mg/dL, and emergent PCI.\u003c/p\u003e\u003cp\u003eConclusion\u003c/p\u003e\u003cp\u003ePhosphate has a J-curve association with the risk of CV events in CAD patients undergoing PCI that was independent of comorbidities and renal function.\u003c/p\u003e","manuscriptTitle":"Association Between Phosphate and Long-term Outcome in CAD Patients Underwent Coronary Intervention","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-05-20 17:00:53","doi":"10.21203/rs.3.rs-535266/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Major revision","date":"2021-08-09T17:57:13+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2021-07-25T13:43:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"aa61d7f7-6712-4aef-ad0a-1448e0cc0584","date":"2021-07-25T05:36:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-06-01T12:19:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-06-01T12:05:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2021-05-19T09:17:13+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2021-05-19T05:12:29+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2021-05-17T15:10:52+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ff65545f-ecd3-49dd-ab2b-36492a145309","owner":[],"postedDate":"May 20th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":4448077,"name":"Medical Genetics"}],"tags":[],"updatedAt":"2021-09-21T13:59:11+00:00","versionOfRecord":[],"versionCreatedAt":"2021-05-20 17:00:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-535266","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-535266","identity":"rs-535266","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}