Blood urea nitrogen to left ventricular ejection fraction ratio: a predictor of in-hospital outcomes in STEMI patients

Blood urea nitrogen to left ventricular ejection fraction ratio: a predictor of in-hospital outcomes in STEMI patients | 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 Blood urea nitrogen to left ventricular ejection fraction ratio: a predictor of in-hospital outcomes in STEMI patients Linfeng Xie, Jing Chen, Yuanzhu Li, Jian Shen, Xiang Li, Yuan Yang, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4552198/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Sep, 2025 Read the published version in BMC Cardiovascular Disorders → Version 1 posted 10 You are reading this latest preprint version Abstract Background The in-hospital mortality of ST-elevation myocardial infarction (STEMI) remains as high as 4–12%. Heart and kidney are closely linked, and both renal and cardiac function have been confirmed to be associated with the prognosis in patients with STEMI. This study intends to evaluate the prognostic value of blood urea nitrogen (BUN) to left ventricular ejection fraction (LVEF) ratio (BLR) in STEMI patients. Methods From January 2015 to January 2023, 2435 consecutive STEMI patients were enrolled. The primary endpoint was in-hospital all-cause mortality and the second endpoint was major adverse cardiovascular events (MACE) including cardiovascular death, nonfatal stroke, and nonfatal myocardial infarction. The predictive value of BLR was compared with BUN, LVEF, traditional markers and scores (GRACE score and TIMI score) by receiver operating characteristic (ROC) curves, the area under the curve (AUC) were compared by DeLong test. Then patients were divided into two groups based on the cut-off value of BLR determined by Youden index and compared the in-hospital mortality and MACE. The association between BLR and endpoints was investigated by Cox regression. Results Totally 2435 patients were included in our study, among which 90 (3.70%) patients died and 110 (4.52%) MACEs were collected. The non-survivors had significantly higher BUN level and lower LVEF value. The AUCs and DeLong test showed that the predictive value of BLR was significantly higher than BUN, LVEF, creatinine, NT-proBNP, and troponin I but was comparable to GRACE score and TIMI scores. The optimal cut-off value of BLR was 12.54 with a sensitivity of 75.6% and a specificity of 67.6%. The in-hospital mortality and MACE was significantly higher in high BLR group (8.23% vs. 1.37% for in-hospital mortality and 9.44% vs. 1.99% for in-hospital MACE, all p < 0.001). After multivariable adjustment, BLR ≥ 12.54 was still independently associated with higher in-hospital mortality (HR = 1.948, 95%CI 1.143, 3.318, p = 0.014) and MACE (HR = 1.720, 95%CI 1.066, 2.774, p = 0.026). Conclusion BLR is an important prognostic index to identify patients at high risk of in-hospital prognosis in STEMI patients and the prognostic value was comparable to or even higher traditional scores. Trial registration ChiCTR1900028516 (http//www.chictr.org.cn). Blood urea nitrogen Left ventricular ejection fraction ST-segment elevation myocardial infarction In-hospital prognosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction Worldwide, ischaemic heart disease is one of the most common causes of death and its incidence is still increasing [ 1 ] . Although the widespread use of reperfusion therapy, primary percutaneous coronary intervention (PCI), and modern antithrombotic therapy have significantly improved the long-term outcome in patients with acute ST-elevation myocardial infarction (STEMI) [ 2 – 4 ] , the in-hospital mortality of unselected patients with STEMI was still high, between 4–12% [ 5 ] . Therefore, after reperfusion treatment, it is important to identify patients at high risk of subsequent events such as reinfarction or death. Currently, several risk scores have been developed based on readily identifiable parameters in the acute phase of acute myocardial infarction (AMI) [ 6 ] , among which the TIMI score [ 7 ] and GRACE score [ 8 ] are widely used in clinical practice. However, their clinical use needs complex algorithms and the inclusion of multiple metrics. Previous studies have shown both renal function and cardiac function were associated with the outcome of STEMI patients [ 1 ] . Pathophysiologically, heart and kidneys are two closely related organs and interact with each other, so called cardiorenal syndrome (CRS) [ 9 ] . Therefore, combining renal and cardiac function together could provide more accurate prognostic value for patients with AMI. Blood urea nitrogen (BUN) is a surrogate of renal dysfunction and was shown to be superior to creatinine for the evaluation of prognosis in AMI patients [ 10 ] ; left ventricular ejection fraction (LVEF) is the most commonly used index to reflect the cardiac function [ 11 ] . In recently years, a new index, BUN to LVEF ratio (BLR), has been proposed to evaluate the outcome in patients with cardiovascular diseases [ 12 – 15 ] . However, no studies, to the best of our knowledge, have been explicitly designed to assess the short term prognostic value of BLR in STEMI patients. Accordingly, the present study aimed to test the utility of BLR as a simple but effective tool for risk stratification for STEMI patients. 2. Methods 2.1 Study design and patients This study was a retrospective, single-center study that involved 2435 patients who were diagnosed with STEMI from January 2015 and January 2023 with the aim to evaluate the prognostic value of BLR. The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University and complied with the Declaration of Helsinki. STEMI was defined as follows: chest pain or equivalent symptoms in combination with dynamic electrocardiographic changes consistent with STEMI, and increased serum troponin I (TnI). After admission, all patients received an overall evaluation. If there was no contraindication and the patients agreed, emergent coronary angiography and PCI were recommended. After the intervention procedure, patients were sent to the coronary care unit for electrocardiogram monitoring and further management was administered according to the guidelines [ 16 , 17 ] . The echocardiogram was performed within 24 hours after admission. Left ventricular volumes were measured by Simpson’s disk method and LVEF was calculated according to the American Society of Echocardiography protocol [ 18 ] . BUN were measured at admission, the reference range of our laboratory for BUN was 3.6–9.5 mmol/L (Ortho-Clinical Diagnostics,Inc, US). To ensure reliability and accuracy of the data, baseline characteristics, auxiliary examinations, and treatment were collected by experienced clinicians from the computerized patient record system. 2.2 Study endpoint The primary study endpoint of this study was in-hospital all-cause mortality and the second study endpoint was major adverse cardiovascular events (MACE) including cardiovascular mortality, nonfatal stroke, and nonfatal myocardial infarction (MI). 2.3 Calculation of TIMI score and GRACE score The calculation of TIMI score includes the following variables [ 7 ] : age, historical diabetes mellitus/hypertension or angina, systolic blood pressure, heart rate, Killip class, weight, anterior ST segment deviation or left bundle branch block, and time to treatment. The variables in GRACE score [ 8 ] includes age, Killip class, systolic blood pressure, ST segment deviation, cardiac arrest at admission, serum creatinine, raised cardiac markers, and heart rate. 2.4 Statistical analysis Continuous variables with normal distribution were presented in mean value and standard deviations, otherwise as the median value and inter-quartile range (25th and 75th), and two independent sample t-test or Mann-Whitney U test were used for the comparisons between groups respectively. Categorical variables were presented in numbers and percentages, and Chi-Square test test or Fisher test was employed. The prognostic value of BUN, LVEF, creatinine, N-terminal brain natriuretic peptide (NT-proBNP), TnI, GRACE score, TIMI score and BLR was evaluated by the receiver operating characteristic curve (ROC) and the area under the curve (AUC) for in-hospital mortality was calculated. The AUCs of those indexes were further compared by DeLong test. The optimal cut-off value of BLR was determined by Youden index, then patients were divided into two groups based on the cut-off value. Univariate and multivariate Cox regression models were constructed to confirm whether there was an independent relationship between BLR and clinical outcomes, based on the previous studies and taking the clinical relevance and model stability into consideration. The factors in the model included age, sex, admission systolic blood pressure, admission heart rate, lactate, NT-proBNP, TnI, Killip class > I, TIMI score and GRACE score, in which NT-proBNP and TnI were changed into categorical variables by the cut-off value of them determined by Youden index. A two-tailed p-value of < 0.05 was considered statistically significant and all statistical analyses were carried out using the SPSS statistical software, version 25.0 (IBM, USA), MedCalc statistical software 19.2.6, and GraphPad Prism 8.4.3. 3. Result From January 2015 to January 2023, a total of 2661 consecutive STEMI patients admitted, among which 226 patients had incomplete data or did not receive coronary angiography, the remaining 2435 patients were included in this study. The mean age of this cohort was 63 years (SD, 13) years and 1947 (80.0%) were male. During hospitalization, a total of 90 (3.70%) patients died and 110 (4.52%) MACEs occurred. Compared with survivors, non-survivors had a higher level of BUN (9.0 ± 4.9 vs. 6.2 ± 2.7 mmol/L, p < 0.001), lower LVEF (45 ± 11% vs. 54 ± 8%, p < 0.001) and higher BLR (12.46 (17.03, 22.57) vs. 10.68 (8.49, 13.61), p < 0.001). The ROC of BUN, LVEF, creatinine, NT-proBNP, TnI, GRACE score, TIMI score, and BLR for predicting in-hospital mortality and MACE were presented in Fig. 1 and Fig. 2 . The AUC of BUN, LVEF, creatinine, NT-proBNP, TnI, GRACE score, TIMI score and BLR for in-hospital mortality were 0.714, 0.741, 0.682, 0.712, 0.630, 0.784, 0.770, and 0.789, respectively; for MACE AUCs were 0.705, 0.698, 0.668, 0.704, 0.630, 0.771, 0.763, and 0.762, respectively, indicating BLR had highest prognostic power for in-hospital mortality and MACE. DeLong test showed that the predictive value of BLR was significantly higher than BUN, LVEF, creatinine, NT-proBNP, and TnI (all p 0.05). The optimal cut-off value of BLR for predicting in-hospital all-cause mortality was 12.54 determined by Yonden index with a sensitivity of 75.6% and a specificity of 67.6%. Then patients were divided into two groups, BLR < 12.54 and BLR ≥ 12.54 for further analysis. Table 1 showed the baseline characteristics and treatment of the 2 groups divided according to BLR cut-off value. Patients with higher BLR tended to be older (67 ± 12 vs. 61 ± 12 yeas, p < 0.001), had lower body mass index (23.74 ± 3.43 vs. 24.54 ± 3.43 kg/m 2 , p < 0.001), and had a higher proportion of previous MI (6.1% vs. 4.0%, p = 0.027), PCI (5.4% vs. 3.1%, p = 0.005), hypertension (59.2% vs. 49.3%, p < 0.001), diabetes (33.5% vs. 23.3%, p < 0.001), renal dysfunction (32.6% vs. 6.2%, p < 0.001), and previous stroke (6.8% vs. 4.4%, p = 0.010). At admission, more patients in higher BLR group presented with higher Killip class, lower blood pressure, higher heart rate, and cardiac shock (all p < 0.05). Table 1 Comparison of baseline characteristics divided by BLR Total (n = 2435) BLR ≥ 12.54 (n = 826) BLR < 12.54 (n = 1609) P value Demographics Age (years) 63 ± 13 67 ± 12 61 ± 12 < 0.001 Male (n, %) 1947 (80.0%) 650 (78.7%) 1297 (80.6%) 0.263 BMI (Kg/m 2 ) 24.27 ± 3.45 23.74 ± 3.43 24.54 ± 3.43 < 0.001 Co-morbidities (n, %) Previous MI 115 (4.7%) 50 (6.1%) 65 (4.0%) 0.027 Previous PCI 95 (3.9%) 45 (5.4%) 50 (3.1%) 0.005 Hypertension 1282 (52.6%) 489 (59.2%) 793 (49.3%) < 0.001 Diabetes mellitus 652 (26.8%) 277 (33.5%) 375 (23.3%) < 0.001 Dislipidemia 370 (15.2%) 116 (14.0%) 254 (15.8%) 0.257 Renal dysfunction a 368 (15.1%) 269 (32.6%) 99 (6.2%) < 0.001 Previous stroke 126 (5.2%) 56 (6.8%) 70 (4.4%) 0.010 Current smoker 1613 (66.2%) 529 (64.0%) 1084 (67.4%) 0.100 Clinical presentation (n, %) Cardiac arrest before admission 108 (4.4%) 38 (4.6%) 70 (4.4%) 0.777 Killip class < 0.001 I 1841 (75.6%) 534 (64.6%) 1307 (81.2%) II 278 (11.4%) 129 (15.6%) 149 (9.3%) III 55 (2.3%) 34 (4.1%) 21 (1.3%) IV 261 (10.7%) 129 (15.6%) 132 (8.2%) Cardiogenic shock 196 (8.0%) 144 (13.8%) 82 (5.1%) < 0.001 Admission vital signs Systolic blood pressure (mmHg) 125 ± 25 122 ± 26 127 ± 25 < 0.001 Diastolic blood pressure (mmHg) 78 ± 17 76 ± 17 79 ± 16 < 0.001 Heart rate (bpm) 82 ± 18 83 ± 20 82 ± 17 0.031 Location of MI (n, %) Anterior MI 1281 (52.6%) 428 (51.3%) 853 (53.0%) 0.575 Lateral MI 267 (11.0%) 104 (12.6%) 161 (10.1%) 0.066 Inferior MI 1200 (49.3%) 419 (50.7%) 781 (48.5%) 0.307 Right ventricle MI 262 (10.8%) 95 (11.5%) 167 (10.4%) 0.398 Posterior MI 324 (13.3%) 119 (14.4%) 205 (12.7%) 0.252 Culprit vessel (n, %) LM 12 (0.5%) 9 (1.1%) 3 (0.2%) 0.003 LAD 1265 (52.0%) 417 (50.5%) 848 (52.7%) 0.292 LCX 278 (11.4%) 93 (11.3%) 185 (11.5%) 0.857 RCA 940 (38.6%) 329 (39.8%) 611 (38.0%) 0.379 Laboratory findings Troponin I (ng/mL) 3.12 (0.30, 14.60) 4.24 (0.50, 18.10) 2.58 (0.25, 12.90) < 0.001 NT-proBNP (pg/mL) 137 (39, 505) 270 (79, 1155) 98 (31, 320) < 0.001 D-dimer (ng/mL) 285 (100, 659) 485 (189, 1020) 217 (100, 487) < 0.001 White blood cell counts (× 10 9 /L) 11.31 ± 3.87 11.68 ± 4.24 11.11 ± 3.65 < 0.001 Hemoglobin (g/L) 138 ± 19 134 ± 20 141 ± 19 < 0.001 Blood urea nitrogen (mmol/L) 6.3 ± 2.9 8.7 ± 3.8 5.1 ± 1.1 < 0.001 Creatinine (µmol/L) 75 (63, 90) 87 (71, 115) 71 (60, 82) < 0.001 LDL (mmol/L) 2.84 ± 0.93 2.72 ± 0.92 2.91 ± 0.93 < 0.001 HDL (mmol/L) 1.09 ± 0.31 1.12 ± 0.33 1.07 ± 0.29 < 0.001 Echocardiography findings LVEF (%) 54 ± 8 49 ± 9 56 ± 6 < 0.001 LVEDD (mm) 49 ± 5 50 ± 6 48 ± 4 < 0.001 Regional wall motion abnormality (n, %) 2092 (88.7%) 728 (91.4%) 1364 (87.4%) 0.005 Ventricular aneurysm (n, %) 105 (4.4%) 63 (7.9%) 42 (2.7%) < 0.001 Medication use in hospital (n, %) Aspirin 2358 (96.8%) 794 (96.1%) 1564 (97.2%) 0.150 P2Y12 receptor inhibitors 2404 (98.7%) 812 (98.3%) 1592 (98.9%) 0.183 Statins 2398 (98.5%) 803 (97.2%) 1595 (99.1%) < 0.001 β blockers 1323 (54.3%) 380 (46.0%) 943 (58.6%) < 0.001 ACEI/ARB 815 (33.5%) 218 (26.4%) 597 (37.1%) < 0.001 Anticoagulant drug 101 (4.1%) 49 (5.9%) 52 (3.2%) 0.002 PPI 2159 (88.7%) 754 (91.3%) 1405 (87.3%) 0.004 Percutaneous coronary intervention 2292 (94.1%) 773 (93.6%) 1519 (94.4%) 0.414 TIMI score 4.84 ± 2.52 5.73 ± 2.51 4.38 ± 2.40 < 0.001 GEACE score 128 (106, 155) 145 (120, 171) 120 (101, 145) < 0.001 BLR: Blood urea nitrogen to left ventricular ejection fraction ratio, BMI: body mass index, MI: myocardial infarction, PCI: percutaneous coronary intervention, LM: left main artery, LAD: left anterior descending artery, LCX: left circumfex artery, RCA: right coronary artery, NT-proBNP: N-terminal-pro-B-type-natriuretic-peptide, LDL: low-density lipoprotein, HDL: high-density lipoprotein, LVEF: left ventricular ejection fraction, LVEDD: left ventricular end-diastolic dimension, ACEI: angiotensin-converting enzyme inhibitor, ARB: angiotensin-converting receptor blocker, PPI: proton pump inhibitor). a:Renal dysfunction: estimate glomerular filtration rate 0.05). On coronary angiography, the distribution of culprit vessels were similar except that left main coronary artery was relatively more common in patients with higher BLR (1.1% vs. 0.2%, p = 0.003). The comparison of laboratory findings revealed that patients with higher BLR had a higher level of TnI, NT-proBNP, D-dimer, white blood cell counts, BUN, creatinine, and high-density lipoprotein, but had a lower level of hemoglobin and low-density lipoprotein (all p < 0.05). The echocardiography showed that patients in higher BLR group had lower LVEF (49 ± 9% vs. 56 ± 6%, p < 0.001), larger left ventricular end-diastolic dimension (50 ± 6 vs. 48 ± 4mm, p < 0.001), and more regional wall motion abnormality (91.4% vs. 87.4%, p = 0.005) ventricular aneurysm (7.9% vs. 2.7%, p < 0.001). During hospitalization, statins, β blockers, angiotensin-converting enzyme inhibitor/angiotensin-converting receptor blocker were more prescribed to patients with lower BLR, while proton pump inhibitor and anticoagulant drugs were more used in patients with higher BLR (all p 0.05). The mean TIMI score and GRACE score in patients with higher BLR was 5.73 and 145, respectively, and were significantly higher than in patients with lower BLR (all p < 0.001). Figure 3 showed the in-hospital outcomes between patients with high and low BLR. The in-hospital mortality and MACE were significantly higher in BLR ≥ 12.54 group (8.23% vs. 1.37% for in-hospital mortality, 9.44% vs. 1.99% for MACE, all p < 0.001). The cardiovascular mortality was significantly higher in high BLR group (8.11% vs. 1.31%, p < 0.001), while the nonfatal stroke and nonfatal MI were similar between the two groups (1.21% vs. 0.81%, p = 0.331 for nonfatal stroke and 0.36% vs. 0.06%, p = 0.227 for nonfatal MI, respectively). Figure 4 displays the K-M curves of the two group patients and it revealed the cumulative survival and free of MACE in patients with higher BLR were significantly lower than that in patients with lower BLR (all Log rank p < 0.001). Table 2 displayed the results from univirate and multivariate Cox regression for in-hospital mortality. As a continuous variable, BLR was positively associated increased risk of in-hospital all-cause mortality (HR = 1.061, 95%CI 1.047, 1.074, p < 0.001). As as a category variable and compared with BLR < 12.54, BLR ≥ 12.54 was associated with almost 5-fold increased risk of in-hospital all-cause mortality (HR = 4.773, 95%CI 2.935, 7.762, p < 0.001). After multivariate adjustment, BLR ≥ 12.54 was still an independent prognostic factor for in-hospital mortality (HR = 1.948, 95%CI 1.143, 3.318, p = 0.014). Other independent prognostic factors included heart rate (HR = 1.016, 95%CI 1.005, 1.026, p = 0.003), lactate (HR = 1.246, 95%CI 1.184, 1.312, p 265.5 pg/mL (HR = 2.139, 95%CI 1.284, 3.564, p = 0.004), and TNI > 4.50 ng/mL (HR = 1.733, 95%CI 1.079, 2.784, p = 0.023). Table 2 The univariate and multivariate Cox regression analysis of in-hospital mortality Predictors for in-hospital mortality Univariate analysis HR (95%CI) P Multivariate analysis HR (95%CI) P Age 1.051 (1.031, 1.071) < 0.001 Male 1.830 (1.183, 2.831) 0.007 Admission heart rate 1.026 (1.017, 1.035) < 0.001 1.016 (1.005, 1.026) 0.003 Admission SBP 0.985 (0.977, 0.992) < 0.001 Lactate 1.320 (1.266, 1.377) < 0.001 1.246 (1.184, 1.312) 265.5 3.361 (2.131, 5.303) 4.50 2.112 (1.371, 3.254) 0.001 1.733 (1.079, 2.784) 0.023 Killip Class > I 3.502 (2.286, 5.365) < 0.001 GRACE score 1.019 (1.015, 1.023) < 0.001 TIMI score 1.375 (1.271, 1.488) < 0.001 BLR (≥ 12.54) 4.773 (2.935, 7.762) < 0.001 1.948 (1.143, 3.318) 0.014 SBP: Systolic blood pressure; NT-proBNP: N-terminal-pro-B-type-natriuretic-peptide, BLR: blood urea nitrogen to left ventricular ejection fraction ratio. Table 3 showed the association of BLR with in-hospital MACE. Also, as a continuous variable, BLR was positively associated increased risk of in-hospital MACE (HR = 1.061, 95%CI 1.048, 1.073, p < 0.001). Compared with BLR < 12.54, BLR ≥ 12.54 was associated with almost 4-flold increased risk of in-hospital MACE (HR = 3.866, 95%CI 2.548, 5.865, p < 0.001). Similarly, BLR ≥ 12.54 was independently associated with increased risk of in-hospital MACE after multivariate adjustment (HR = 1.720, 95%CI 1.066, 2.774, p = 0.026). Other independent factors associated with in-hospital MACE included age (HR = 1.038, 95%CI 1.008, 1.068, p = 0.013), heart rate (HR = 1.019, 95%CI 1.009, 1.029, p < 0.001), lactate (HR = 1.225, 95%CI 1.166, 1.286, p 265.5 pg/mL (HR = 2.030, 95%CI 1.273, 3.239, p = 0.003), and TNI > 4.50 ng/mL (HR = 1.832, 95%CI 1.180, 2.844, p = 0.007). Table 3 The univariate and multivariate Cox regression analysis of in-hospital MACE Predictors for in-hospital mortality Univariate analysis HR (95%CI) P Multivariate analysis HR (95%CI) P Age 1.054 (1.036, 1.072) < 0.001 1.038 (1.008, 1.068) 0.013 Male 1.590 (1.061, 2.384) 0.025 Admission heart rate 1.026 (1.018, 1.035) < 0.001 1.019 (1.009, 1.029) < 0.001 Admission SBP 0.987 (0.980, 0.995) 0.001 Lactate 1.304 (1.253, 1.358) < 0.001 1.225 (1.166, 1.286) 265.5 3.335 (2.217, 5.017) 4.5 2.175 (1.471, 3.217) I 3.386 (2.307, 4.969) < 0.001 GRACE score 1.018 (1.014, 1.022) < 0.001 TIMI score 1.360 (1.267, 1.459) < 0.001 BLR (≥ 12.54) 3.866 (2.548, 5.865) < 0.001 1.720 (1.066, 2.774) 0.026 SBP: Systolic blood pressure; NT-proBNP: N-terminal-pro-B-type-natriuretic-peptide, BLR: blood urea nitrogen to left ventricular ejection fraction ratio. For a more detailed analysis of the association between BLR and in-hospital all-cause mortality and MACE in patients with different clinical profiling, subgroups were analyzed (Fig. 5 ). It revealed the effect of BLR on different subgroups were consistent except in anterior vs. non-anterior MI with more significant in patients with anterior MI compared with non-anterior MI (for in-hospital mortality, HR = 3.181, 95%CI 1.486, 6.807, p-interaction = 0.018; for MACE, HR = 2.507, 95%CI 1.300, 4.833, p-interaction = 0.027, respectively). 4. Discussion The main findings of the present study are as follows: firstly, in STEMI patients, higher BLR level was associated with higher in-hospital mortality and MACE incidence, and a BLR level higher than 12.54 was an independent risk factor for in-hospital all-cause mortality and MACE; secondly, the predictive value of BLR was significantly higher than BUN, LVEF, creatinine, NT-proBNP, and TnI and was comparable to GRACE score and TIMI scores; thirdly, the effects of BLR on different clinical profiles were consistent but more obvious in patients with anterior MI. Our present study demonstrated the possibility of BLR as a biomarker for prognostic evaluation in STEMI patients. Currently, TIMI score [ 7 ] and GRACE score [ 8 ] are the two scores widely used for risk stratification in patients with STEMI. However, the sophisticated algorithm of these risk scores limited their bedside use, e.g. TIMI score includes seven variables, age, blood pressure, heart rate and Killip class et., while GRACE score includes even more variables that need to be calculated through the calculator. More importantly, the predictive efficacy of these two scores is modest. Previous studies demonstrated that the AUCs of TIMI score and GRACE score for predicting the short-term outcome in patients with STEMI were 0.779 and 0.77, respectively [ 7 , 8 ] . In our study, the prognostic value of TIMI score and GRACE score was also modest with the AUCs of 0.770 and 0.784, respectively. Therefore, a simple and effective tool for risk stratification in patients with STEMI is urgently required. BLR was initially designed by Kiris et al. [ 13 ] , who used this index to evaluate the risk of contrast induced nephropathyin (CIN) in patients with acute coronary syndrome undergoing PCI and found out BLR was significantly higher in those who developed CIN, and as a continuous variable, BLR was independently associated significantly increased risk of CIN (OR 10.59, 95% CI 2.803–40.070, p = 0.001). Subsequent studies demonstrated that in patients with coronary artery disease, BLR was shown to be associated with all-cause mortality and decompensated heart failure incident in patients with stable angina pectoris, and the predictive value of BLR was superior to BUN or LVEF alone [ 12 ] . This finding was further confirmed in patients receiving coronary artery bypass grafting, and a remarkable elevated BLR predicted increased risk of long-term mortality and new-onset decompensated heart failure [ 14 ] . Recently, Ozkan et al. [ 15 ] found that in patients with acute heart failure, BLR was shown to be superior to BUN or LVEF for predicting the outcome. Those studies, taken together, suggested BLR could be served as a promising marker for risk stratification in patients with cardiovascular disease. Our present study extended previous findings, indicating BLR was a potential useful marker for risk stratification in patients with STEMI. In the setting of STEMI, a series of pathophysiological process, such as reduced cardiac output, systemic congestion, the activation of systemic vasoconstriction, diuretics use, and the administration of contrast media during revascularization could impair renal function [ 19 ] , which in turn, aggravates cardiac dysfunction via activation of renin-angiotensin-aldosterone system (RAAS) and finally CRS develops with a vicious cycle between renal and cardiac dysfunction [ 9 ] . Therefore, an adequate assessment of the cardiorenal interaction in the context of STEMI received PCI is of great importance. Our present study showed patients with higher BLR had more high risk clinical characteristics, such as older age, more morbidities and complications on admission, which were variables include in higher TIMI and GRACE scores; however, multivariate Cox regression suggested high BLR remained an independent risk factor for in-hospital mortality and MACE, indicating that BLR has independent predictive value in STEMI patients. Both BUN and creatinine reflect the renal function; however, BUN may increase before the elevation of creatinine or the decrease of glomerular filtration rate, because the overactivation of the sympathetic nervous system and RAAS could enhance the reabsorption of BUN in proximal tubular in the early stage of renal hypoperfusion [ 20 , 21 ] ; therefore, elevated BUN level not only reflects renal dysfunction but more importantly, indicates the neurohormonal activation, which has widely been demonstrated to be related with the prognosis in patients with AMI [ 22 – 24 ] . Actually, previous studies have confirmed the prognostic value of elevated BUN in patients with AMI [ 25 – 28 ] ; furthermore, the predictive value of BUN was shown to be superior to that of creatinine [ 10 ] . Therefore, as shown in the present study, the AUC of BUN was significantly higher than that of creatinine. LVEF is the most important index to describe the left heart systolic function, AMI usually causes the decrease of LVEF [ 29 ] , especially in the setting of anterior MI, which directly cause pump failure. Subgroup analysis in our present study also revealed the impact of BLR was more significant in patients with anterior MI compared with non-anterior MI, possibly due to the significant decrease in LVEF in patients with anterior MI. Similarly, LVEF is an independent factor associated with the prognosis in patients with STEMI [ 1 , 30 – 35 ] . Left ventricular dysfunction may develop at the onset of STEMI due to extensive myocardial necrosis or later during the process of ventricular remodelling [ 36 ] . BLR takes the two important prognostic factors together and in our present study, BLR exhibited superior predictive value compared with BUN or LVEF alone. Although the precise molecular mechanisms why BLR is associated with the short-term prognosis remains unknown, multiple neurohumoral and inflammatory pathways are involved in CRS. Firstly, left ventricular dysfunction causes prerenal hypoperfusion, which activates sympathetic nervous system, RAAS, and arginine vasopressin secretion, leading to fluid retention, increased preload, and worsening pump failure [ 37 ] . Secondly, when AMI occurs, a series of inflammatory biomarkers such as white blood cell, C-reactive protein, interleukin−6, reactive oxygen species are elevated [ 38 ] , which have direct cardiodepressant effects causing a reduction in LVEF [ 9 ] . What’s more, activated systemic inflammation could induce renal endothelial dysfunction and have been confirmed to be involved in the development of acute kidney injury after AMI and are associated with poor clinical outcome [ 39 , 40 ] . In addition, several other pathways that exacerbate cardiac or kidney injury, including activation of the sympathetic nervous system, imbalance in the proportion of reactive oxygen species/nitric oxide production, and persistent RAAS activation [ 41 ] , further induces both cardiac and renal dysfunction and causes a vicious cycle, leading to astounding morbidity and mortality. In contrast to other risk scores, BLR focused on the interaction between the two most important and commonly damaged organs (heart and kidney) after STEMI. Our present study shows the prognostic value of BLR was comparable to or even higher than that of TIMI score or GRACE score. Therefore, as a convenient, effective and low cost index, BLR provides a tool for risk stratification in patients with STEMI and should be taken into risk stratification model. Some limitations in our study should be addressed. First, as an retrospective observational study, some unmeasured and unknown confounding factors can not be well controlled. Second, we only analyzed the association between admission BLR with in-hospital outcome; however, the dynamic changes of BLR during hospitalization was unavailable. The dynamic change of BLR could provide more prognostic value. Third, patients with chronic kidney disease that could cause elevated BUN were not excluded although the effect was consistent between patients with and without chronic kidney disease in the subgroup analysis. Fourth, we only evaluated the association between BLR with short-term outcome, the prognostic value of BLR for long-term outcome remained unclear. Therefore, more studies are still needed to clarify the prognostic value of BLR in STEMI patients. 5. Conclusion Admission BLR provided important prognostic information for STEMI patients especially in patients with anterior MI and the predictive validity of BLR was comparable even better than traditional risk scores. An admission BLR higher than 12.54 was significantly associated with increased risk of in-hospital mortality and MACE. This easily accessible index might be promising for early risk stratification in STEMI. Declarations Ethics Approval and Consent to Participate: All methods were carried out in accordance with relevant guidelines and regulations. This study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the First Affiliated Hospital of Chongqing Medical University. All the participants were informed of the study content and signed informed consent. Competing interests: All authors have no conflicts of interest to declare. Funding/Support: Not Applicable Author Contribution L.F.X, B.H and S.X.L designed and performed this study; L.F.X contributed for data extraction, analyzed the data, and wrote the manuscript with support from B.H and S.X.L; J.C contributed for data extraction and analyzed the data; Y.Z.L contributed for data extraction and analyzed the data; J.S, X.L, Y.Y, G.L, and Y.C contributed for data extraction. Acknowledgements: Not Applicable Data Availability Statement: The data that supports the findings of this study are available from the corresponding author upon reasonable request. References Ibánez B, James S, Agewall S, et al. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation. Rev Esp Cardiol (Engl Ed). 2017;70(12):1082. 10.1016/j.rec.2017.11.010 . Townsend N, Wilson L, Bhatnagar P, Wickramasinghe K, Rayner M, Nichols M. 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Am Heart J. 2005;150(2):215–20. 10.1016/j.ahj.2004.09.027 . Lansky AJ, Goto K, Cristea E, et al. Clinical and angiographic predictors of short- and long-term ischemic events in acute coronary syndromes: results from the Acute Catheterization and Urgent Intervention Triage strategY (ACUITY) trial. Circ Cardiovasc Interv. 2010;3(4):308–16. 10.1161/CIRCINTERVENTIONS.109.887604 . Bedetti G, Gargani L, Sicari R, Gianfaldoni ML, Molinaro S, Picano E. Comparison of prognostic value of echographic [corrected] risk score with the Thrombolysis in Myocardial Infarction (TIMI) and Global Registry in Acute Coronary Events (GRACE) risk scores in acute coronary syndrome [published correction appears in Am J Cardiol. 2011;107(8):1253]. Am J Cardiol. 2010;106(12):1709–1716. 10.1016/j.amjcard.2010.08.024 . Morici N, Savonitto S, Murena E, et al. Causes of death in patients ≥ 75 years of age with non-ST-segment elevation acute coronary syndrome. Am J Cardiol. 2013;112(1):1–7. 10.1016/j.amjcard.2013.02.043 . Burns RJ, Gibbons RJ, Yi Q, et al. The relationships of left ventricular ejection fraction, end-systolic volume index and infarct size to six-month mortality after hospital discharge following myocardial infarction treated by thrombolysis. J Am Coll Cardiol. 2002;39(1):30–6. 10.1016/s0735-1097(01)01711-9 . White HD, Cross DB, Elliott JM, Norris RM, Yee TW. Long-term prognostic importance of patency of the infarct-related coronary artery after thrombolytic therapy for acute myocardial infarction. Circulation. 1994;89(1):61–7. 10.1161/01.cir.89.1.61 . Schrier RW, Abraham WT. Hormones and hemodynamics in heart failure. N Engl J Med. 1999;341(8):577–85. 10.1056/NEJM199908193410806 . Anzai A, Anzai T, Naito K, et al. Prognostic significance of acute kidney injury after reperfused ST-elevation myocardial infarction: synergistic acceleration of renal dysfunction and left ventricular remodeling. J Card Fail. 2010;16(5):381–9. 10.1016/j.cardfail.2009.12.020 . Ronco C, Haapio M, House AA, Anavekar N, Bellomo R. Cardiorenal syndrome. J Am Coll Cardiol. 2008;52(19):1527–39. 10.1016/j.jacc.2008.07.051 . Guerchicoff A, Stone GW, Mehran R, et al. Analysis of biomarkers for risk of acute kidney injury after primary angioplasty for acute ST-segment elevation myocardial infarction: results of the HORIZONS-AMI trial. Catheter Cardiovasc Interv. 2015;85(3):335–42. 10.1002/ccd.25620 . Haase M, Müller C, Damman K et al. Pathogenesis of cardiorenal syndrome type 1 in acute decompensated heart failure: workgroup statements from the eleventh consensus conference of the Acute Dialysis Quality Initiative (ADQI). Contrib Nephrol. 2013;182:99–116. 10.1159/000349969 . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Sep, 2025 Read the published version in BMC Cardiovascular Disorders → Version 1 posted Editorial decision: Revision requested 07 Aug, 2025 Reviews received at journal 16 Jun, 2025 Reviewers agreed at journal 16 Jun, 2025 Reviews received at journal 21 Aug, 2024 Reviewers agreed at journal 19 Aug, 2024 Reviewers invited by journal 25 Jul, 2024 Editor invited by journal 24 Jun, 2024 Editor assigned by journal 21 Jun, 2024 Submission checks completed at journal 21 Jun, 2024 First submitted to journal 08 Jun, 2024 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-4552198","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":324118787,"identity":"54dd26f7-8a83-426e-a78d-84957368a7fa","order_by":0,"name":"Linfeng Xie","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Linfeng","middleName":"","lastName":"Xie","suffix":""},{"id":324118788,"identity":"a694cf6c-9f08-4789-8526-d03160034488","order_by":1,"name":"Jing Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Chen","suffix":""},{"id":324118789,"identity":"1286df7b-2f74-4211-aa57-fafa98c1a182","order_by":2,"name":"Yuanzhu Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuanzhu","middleName":"","lastName":"Li","suffix":""},{"id":324118790,"identity":"db352030-c978-47b2-a079-7b430720085e","order_by":3,"name":"Jian Shen","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jian","middleName":"","lastName":"Shen","suffix":""},{"id":324118791,"identity":"20c84174-d0f2-412c-b656-f84fb438b2b0","order_by":4,"name":"Xiang Li","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiang","middleName":"","lastName":"Li","suffix":""},{"id":324118792,"identity":"f9fe8855-66e8-4922-9800-bc13321e20fc","order_by":5,"name":"Yuan Yang","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yuan","middleName":"","lastName":"Yang","suffix":""},{"id":324118793,"identity":"1a5deda9-6cca-48f7-84c3-97d5afded223","order_by":6,"name":"Gang Liu","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"Liu","suffix":""},{"id":324118794,"identity":"9b1b8fd8-800c-41a6-81e4-de1c9a30c6bc","order_by":7,"name":"Yintao Chen","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yintao","middleName":"","lastName":"Chen","suffix":""},{"id":324118795,"identity":"5c7f0354-d07a-4699-bb53-00b8c7da072f","order_by":8,"name":"Bi Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACAxDB2CDBw8/MfODAhx8kaJGRbG9LPDizh3gtDDYGZ84YH+ZgI0KLuUTys4dfd1jwMNzI+XCYgYdBnl/sAH4tljPSzI1lz0jwMM7I3XC4wILBcObsBAIOu5FgJi3ZJsHDLAHUMoOHIcHgNkEt6d/AWtgkch4c5mEjSkuOmeRHoBYenjMMRGo586ZMmhHoFwn2NgNgIEsQ4Zfj6dskf+6os7c/zPz4w4cfNvL80gS0gAAzD4ItQVg5CDASk0xGwSgYBaNgBAMAOahE2uNJaNUAAAAASUVORK5CYII=","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":true,"prefix":"","firstName":"Bi","middleName":"","lastName":"Huang","suffix":""},{"id":324118796,"identity":"3bf017fb-e140-4eaf-9bf1-6a48519a3c44","order_by":9,"name":"Suxin Luo","email":"","orcid":"","institution":"The First Affiliated Hospital of Chongqing Medical University","correspondingAuthor":false,"prefix":"","firstName":"Suxin","middleName":"","lastName":"Luo","suffix":""}],"badges":[],"createdAt":"2024-06-09 02:23:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4552198/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4552198/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12872-025-05180-y","type":"published","date":"2025-09-29T15:58:15+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":60615382,"identity":"f07bb16f-8786-4c68-9a41-ec06b0636d07","added_by":"auto","created_at":"2024-07-18 20:11:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":120706,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC of prognostic indexes for in-hospital mortality. (A) The ROC of BUN, LVEF and BLR for predicting in-hospital mortality. (B) The ROC of TNI, NT-proBNP, creatinine and BLR for predicting in-hospital mortality. (C) The ROC of GRACE score, TIMI score and BLR for predicting in-hospital mortality. (BUN: Blood urea nitrogen; LVEF: Left ventricular ejection fraction; BLR: Blood urea nitrogen to left ventricular ejection fraction ratio; TNI: Troponin I; NT-proBNP: N-Terminal Pro-Brain Natriuretic Peptide).\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4552198/v1/b422ba88ac4027e39bc4afa8.png"},{"id":60615385,"identity":"5f687437-d706-4e42-b40f-0db07f80b3d7","added_by":"auto","created_at":"2024-07-18 20:11:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124084,"visible":true,"origin":"","legend":"\u003cp\u003eThe ROC of prognostic indexes for MACE. (A) The ROC of BUN, LVEF and BLR for predicting in-hospital mortality. (B) The ROC of TNI, NT-proBNP, creatinine and BLR for predicting in-hospital mortality. (C) The ROC of GRACE score, TIMI score and BLR for predicting in-hospital mortality. (MACE: major adverse cardiovascular events, BUN: Blood urea nitrogen; LVEF: Left ventricular ejection fraction; BLR: Blood urea nitrogen to left ventricular ejection fraction ratio; TNI: Troponin I; NT-proBNP: N-Terminal Pro-Brain Natriuretic Peptide).\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4552198/v1/068316625cd3e26eae9f1a65.png"},{"id":60615383,"identity":"d70fed5a-e43a-4615-ac82-be96a17839da","added_by":"auto","created_at":"2024-07-18 20:11:59","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":46745,"visible":true,"origin":"","legend":"\u003cp\u003eThe in-hospital major adverse events of patients with BLR≥12.54 and \u0026lt;12.54. (BLR: Blood urea nitrogen to left ventricular ejection fraction ratio, MI: myocardial infarction, MACE: major adverse cardiovascular events).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4552198/v1/f33fef37313e45da60855c80.png"},{"id":60615386,"identity":"cc89cd4c-2ac3-42fc-8984-ffd97a0bd521","added_by":"auto","created_at":"2024-07-18 20:11:59","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":108710,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves for in-hospital all-cause mortality (A) and MACE (B) in STEMI patients (MACE: major adverse cardiovascular events, STEMI: ST-elevation myocardial infarction).\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4552198/v1/8c7a3be6e8a4013ea448857c.png"},{"id":60616390,"identity":"e29a6824-3bf3-4d72-ba7f-3ab8e9324b13","added_by":"auto","created_at":"2024-07-18 20:19:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":416985,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroups analysis of in-hospital mortality (A) and MACE (B) in STEMI patients (MACE: major adverse cardiovascular events, STEMI: ST-elevation myocardial infarction).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4552198/v1/8caee48d0912e268b61da23a.png"},{"id":92883883,"identity":"a97bbcc2-e964-4886-8c15-2c5e16f2d7a1","added_by":"auto","created_at":"2025-10-06 16:10:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1672098,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4552198/v1/c0a8e517-ad01-40bf-8779-dc106cda3bc4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Blood urea nitrogen to left ventricular ejection fraction ratio: a predictor of in-hospital outcomes in STEMI patients","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWorldwide, ischaemic heart disease is one of the most common causes of death and its incidence is still increasing\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Although the widespread use of reperfusion therapy, primary percutaneous coronary intervention (PCI), and modern antithrombotic therapy have significantly improved the long-term outcome in patients with acute ST-elevation myocardial infarction (STEMI)\u003csup\u003e[\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/sup\u003e, the in-hospital mortality of unselected patients with STEMI was still high, between 4\u0026ndash;12%\u003csup\u003e[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. Therefore, after reperfusion treatment, it is important to identify patients at high risk of subsequent events such as reinfarction or death. Currently, several risk scores have been developed based on readily identifiable parameters in the acute phase of acute myocardial infarction (AMI)\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e, among which the TIMI score\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e and GRACE score\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e are widely used in clinical practice. However, their clinical use needs complex algorithms and the inclusion of multiple metrics.\u003c/p\u003e \u003cp\u003ePrevious studies have shown both renal function and cardiac function were associated with the outcome of STEMI patients\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. Pathophysiologically, heart and kidneys are two closely related organs and interact with each other, so called cardiorenal syndrome (CRS)\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Therefore, combining renal and cardiac function together could provide more accurate prognostic value for patients with AMI. Blood urea nitrogen (BUN) is a surrogate of renal dysfunction and was shown to be superior to creatinine for the evaluation of prognosis in AMI patients\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e; left ventricular ejection fraction (LVEF) is the most commonly used index to reflect the cardiac function\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e. In recently years, a new index, BUN to LVEF ratio (BLR), has been proposed to evaluate the outcome in patients with cardiovascular diseases\u003csup\u003e[\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. However, no studies, to the best of our knowledge, have been explicitly designed to assess the short term prognostic value of BLR in STEMI patients. Accordingly, the present study aimed to test the utility of BLR as a simple but effective tool for risk stratification for STEMI patients.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study design and patients\u003c/h2\u003e \u003cp\u003eThis study was a retrospective, single-center study that involved 2435 patients who were diagnosed with STEMI from January 2015 and January 2023 with the aim to evaluate the prognostic value of BLR. The study protocol was approved by the Ethics Committee of the First Affiliated Hospital of Chongqing Medical University and complied with the Declaration of Helsinki.\u003c/p\u003e\u003cp\u003eSTEMI was defined as follows: chest pain or equivalent symptoms in combination with dynamic electrocardiographic changes consistent with STEMI, and increased serum troponin I (TnI). After admission, all patients received an overall evaluation. If there was no contraindication and the patients agreed, emergent coronary angiography and PCI were recommended. After the intervention procedure, patients were sent to the coronary care unit for electrocardiogram monitoring and further management was administered according to the guidelines\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe echocardiogram was performed within 24 hours after admission. Left ventricular volumes were measured by Simpson\u0026rsquo;s disk method and LVEF was calculated according to the American Society of Echocardiography protocol\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. BUN were measured at admission, the reference range of our laboratory for BUN was 3.6\u0026ndash;9.5 mmol/L (Ortho-Clinical Diagnostics,Inc, US). To ensure reliability and accuracy of the data, baseline characteristics, auxiliary examinations, and treatment were collected by experienced clinicians from the computerized patient record system.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Study endpoint\u003c/h2\u003e \u003cp\u003eThe primary study endpoint of this study was in-hospital all-cause mortality and the second study endpoint was major adverse cardiovascular events (MACE) including cardiovascular mortality, nonfatal stroke, and nonfatal myocardial infarction (MI).\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Calculation of TIMI score and GRACE score\u003c/h2\u003e \u003cp\u003eThe calculation of TIMI score includes the following variables\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e: age, historical diabetes mellitus/hypertension or angina, systolic blood pressure, heart rate, Killip class, weight, anterior ST segment deviation or left bundle branch block, and time to treatment. The variables in GRACE score\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e includes age, Killip class, systolic blood pressure, ST segment deviation, cardiac arrest at admission, serum creatinine, raised cardiac markers, and heart rate.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables with normal distribution were presented in mean value and standard deviations, otherwise as the median value and inter-quartile range (25th and 75th), and two independent sample t-test or Mann-Whitney U test were used for the comparisons between groups respectively. Categorical variables were presented in numbers and percentages, and Chi-Square test test or Fisher test was employed. The prognostic value of BUN, LVEF, creatinine, N-terminal brain natriuretic peptide (NT-proBNP), TnI, GRACE score, TIMI score and BLR was evaluated by the receiver operating characteristic curve (ROC) and the area under the curve (AUC) for in-hospital mortality was calculated. The AUCs of those indexes were further compared by DeLong test. The optimal cut-off value of BLR was determined by Youden index, then patients were divided into two groups based on the cut-off value. Univariate and multivariate Cox regression models were constructed to confirm whether there was an independent relationship between BLR and clinical outcomes, based on the previous studies and taking the clinical relevance and model stability into consideration. The factors in the model included age, sex, admission systolic blood pressure, admission heart rate, lactate, NT-proBNP, TnI, Killip class\u0026thinsp;\u0026gt;\u0026thinsp;I, TIMI score and GRACE score, in which NT-proBNP and TnI were changed into categorical variables by the cut-off value of them determined by Youden index. A two-tailed p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant and all statistical analyses were carried out using the SPSS statistical software, version 25.0 (IBM, USA), MedCalc statistical software 19.2.6, and GraphPad Prism 8.4.3.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cp\u003eFrom January 2015 to January 2023, a total of 2661 consecutive STEMI patients admitted, among which 226 patients had incomplete data or did not receive coronary angiography, the remaining 2435 patients were included in this study. The mean age of this cohort was 63 years (SD, 13) years and 1947 (80.0%) were male. During hospitalization, a total of 90 (3.70%) patients died and 110 (4.52%) MACEs occurred.\u003c/p\u003e \u003cp\u003eCompared with survivors, non-survivors had a higher level of BUN (9.0\u0026thinsp;\u0026plusmn;\u0026thinsp;4.9 vs. 6.2\u0026thinsp;\u0026plusmn;\u0026thinsp;2.7 mmol/L, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lower LVEF (45\u0026thinsp;\u0026plusmn;\u0026thinsp;11% vs. 54\u0026thinsp;\u0026plusmn;\u0026thinsp;8%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and higher BLR (12.46 (17.03, 22.57) vs. 10.68 (8.49, 13.61), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The ROC of BUN, LVEF, creatinine, NT-proBNP, TnI, GRACE score, TIMI score, and BLR for predicting in-hospital mortality and MACE were presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The AUC of BUN, LVEF, creatinine, NT-proBNP, TnI, GRACE score, TIMI score and BLR for in-hospital mortality were 0.714, 0.741, 0.682, 0.712, 0.630, 0.784, 0.770, and 0.789, respectively; for MACE AUCs were 0.705, 0.698, 0.668, 0.704, 0.630, 0.771, 0.763, and 0.762, respectively, indicating BLR had highest prognostic power for in-hospital mortality and MACE. DeLong test showed that the predictive value of BLR was significantly higher than BUN, LVEF, creatinine, NT-proBNP, and TnI (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05), but was comparable to GRACE score and TIMI scores (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The optimal cut-off value of BLR for predicting in-hospital all-cause mortality was 12.54 determined by Yonden index with a sensitivity of 75.6% and a specificity of 67.6%. Then patients were divided into two groups, BLR\u0026thinsp;\u0026lt;\u0026thinsp;12.54 and BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 for further analysis.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e showed the baseline characteristics and treatment of the 2 groups divided according to BLR cut-off value. Patients with higher BLR tended to be older (67\u0026thinsp;\u0026plusmn;\u0026thinsp;12 vs. 61\u0026thinsp;\u0026plusmn;\u0026thinsp;12 yeas, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), had lower body mass index (23.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.43 vs. 24.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.43 kg/m\u003csup\u003e2\u003c/sup\u003e, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and had a higher proportion of previous MI (6.1% vs. 4.0%, p\u0026thinsp;=\u0026thinsp;0.027), PCI (5.4% vs. 3.1%, p\u0026thinsp;=\u0026thinsp;0.005), hypertension (59.2% vs. 49.3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), diabetes (33.5% vs. 23.3%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), renal dysfunction (32.6% vs. 6.2%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and previous stroke (6.8% vs. 4.4%, p\u0026thinsp;=\u0026thinsp;0.010). At admission, more patients in higher BLR group presented with higher Killip class, lower blood pressure, higher heart rate, and cardiac shock (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eComparison of baseline characteristics divided by BLR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2435)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;826)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eBLR\u0026thinsp;\u0026lt;\u0026thinsp;12.54\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;1609)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eDemographics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63\u0026thinsp;\u0026plusmn;\u0026thinsp;13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e61\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1947 (80.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e650 (78.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1297 (80.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.263\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI (Kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.27\u0026thinsp;\u0026plusmn;\u0026thinsp;3.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.74\u0026thinsp;\u0026plusmn;\u0026thinsp;3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCo-morbidities (n, %)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e115 (4.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50 (6.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65 (4.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.027\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious PCI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e95 (3.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1282 (52.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e489 (59.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e793 (49.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiabetes mellitus\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e652 (26.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e277 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e375 (23.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDislipidemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e370 (15.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e254 (15.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.257\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRenal dysfunction\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e368 (15.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e269 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevious stroke\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126 (5.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (6.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.010\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent smoker\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1613 (66.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e529 (64.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1084 (67.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.100\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eClinical presentation (n, %)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiac arrest before admission\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e108 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (4.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip class\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1841 (75.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e534 (64.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1307 (81.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149 (9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIII\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21 (1.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e261 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129 (15.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e132 (8.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCardiogenic shock\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196 (8.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e144 (13.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82 (5.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eAdmission vital signs\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSystolic blood pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e125\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e122\u0026thinsp;\u0026plusmn;\u0026thinsp;26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e127\u0026thinsp;\u0026plusmn;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDiastolic blood pressure (mmHg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u0026thinsp;\u0026plusmn;\u0026thinsp;16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeart rate (bpm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e82\u0026thinsp;\u0026plusmn;\u0026thinsp;18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82\u0026thinsp;\u0026plusmn;\u0026thinsp;17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eLocation of MI (n, %)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnterior MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1281 (52.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e428 (51.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e853 (53.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.575\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLateral MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e267 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104 (12.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e161 (10.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.066\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eInferior MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1200 (49.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e419 (50.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e781 (48.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.307\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRight ventricle MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e262 (10.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePosterior MI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e324 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e205 (12.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.252\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eCulprit vessel (n, %)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (0.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (1.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (0.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLAD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1265 (52.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e417 (50.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e848 (52.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.292\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLCX\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e185 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.857\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRCA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e940 (38.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e329 (39.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e611 (38.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.379\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eLaboratory findings\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTroponin I (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.12 (0.30, 14.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.24 (0.50, 18.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.58 (0.25, 12.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-proBNP (pg/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e137 (39, 505)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e270 (79, 1155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98 (31, 320)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD-dimer (ng/mL)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e285 (100, 659)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e485 (189, 1020)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e217 (100, 487)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite blood cell counts (\u0026times; 10\u003csup\u003e9\u003c/sup\u003e /L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11.31\u0026thinsp;\u0026plusmn;\u0026thinsp;3.87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.68\u0026thinsp;\u0026plusmn;\u0026thinsp;4.24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.11\u0026thinsp;\u0026plusmn;\u0026thinsp;3.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHemoglobin (g/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e138\u0026thinsp;\u0026plusmn;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134\u0026thinsp;\u0026plusmn;\u0026thinsp;20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e141\u0026thinsp;\u0026plusmn;\u0026thinsp;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlood urea nitrogen (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.3\u0026thinsp;\u0026plusmn;\u0026thinsp;2.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7\u0026thinsp;\u0026plusmn;\u0026thinsp;3.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u0026thinsp;\u0026plusmn;\u0026thinsp;1.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine (\u0026micro;mol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75 (63, 90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (71, 115)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71 (60, 82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.72\u0026thinsp;\u0026plusmn;\u0026thinsp;0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDL (mmol/L)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07\u0026thinsp;\u0026plusmn;\u0026thinsp;0.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eEchocardiography findings\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEF (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54\u0026thinsp;\u0026plusmn;\u0026thinsp;8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLVEDD (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49\u0026thinsp;\u0026plusmn;\u0026thinsp;5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50\u0026thinsp;\u0026plusmn;\u0026thinsp;6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48\u0026thinsp;\u0026plusmn;\u0026thinsp;4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegional wall motion abnormality (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2092 (88.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e728 (91.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1364 (87.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVentricular aneurysm (n, %)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (4.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (7.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (2.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eMedication use in hospital (n, %)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAspirin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2358 (96.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e794 (96.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1564 (97.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eP2Y12 receptor inhibitors\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2404 (98.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e812 (98.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1592 (98.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.183\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2398 (98.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e803 (97.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1595 (99.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eβ blockers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1323 (54.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e380 (46.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e943 (58.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eACEI/ARB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e815 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e218 (26.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e597 (37.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAnticoagulant drug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101 (4.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePPI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2159 (88.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e754 (91.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1405 (87.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePercutaneous coronary intervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2292 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e773 (93.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1519 (94.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.414\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;2.52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.73\u0026thinsp;\u0026plusmn;\u0026thinsp;2.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;2.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGEACE score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e128 (106, 155)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e145 (120, 171)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e120 (101, 145)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eBLR: Blood urea nitrogen to left ventricular ejection fraction ratio, BMI: body mass index, MI: myocardial infarction, PCI: percutaneous coronary intervention, LM: left main artery, LAD: left anterior descending artery, LCX: left circumfex artery, RCA: right coronary artery, NT-proBNP: N-terminal-pro-B-type-natriuretic-peptide, LDL: low-density lipoprotein, HDL: high-density lipoprotein, LVEF: left ventricular ejection fraction, LVEDD: left ventricular end-diastolic dimension, ACEI: angiotensin-converting enzyme inhibitor, ARB: angiotensin-converting receptor blocker, PPI: proton pump inhibitor).\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003ea:Renal dysfunction: estimate glomerular filtration rate\u0026lt;\u0026thinsp;60mL/(min*1.73^2)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe location of MI on electrocardiogram was similar between the two groups (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). On coronary angiography, the distribution of culprit vessels were similar except that left main coronary artery was relatively more common in patients with higher BLR (1.1% vs. 0.2%, p\u0026thinsp;=\u0026thinsp;0.003). The comparison of laboratory findings revealed that patients with higher BLR had a higher level of TnI, NT-proBNP, D-dimer, white blood cell counts, BUN, creatinine, and high-density lipoprotein, but had a lower level of hemoglobin and low-density lipoprotein (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The echocardiography showed that patients in higher BLR group had lower LVEF (49\u0026thinsp;\u0026plusmn;\u0026thinsp;9% vs. 56\u0026thinsp;\u0026plusmn;\u0026thinsp;6%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), larger left ventricular end-diastolic dimension (50\u0026thinsp;\u0026plusmn;\u0026thinsp;6 vs. 48\u0026thinsp;\u0026plusmn;\u0026thinsp;4mm, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and more regional wall motion abnormality (91.4% vs. 87.4%, p\u0026thinsp;=\u0026thinsp;0.005) ventricular aneurysm (7.9% vs. 2.7%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). During hospitalization, statins, β blockers, angiotensin-converting enzyme inhibitor/angiotensin-converting receptor blocker were more prescribed to patients with lower BLR, while proton pump inhibitor and anticoagulant drugs were more used in patients with higher BLR (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.05). The percentage of PCI was comparable between the two groups (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The mean TIMI score and GRACE score in patients with higher BLR was 5.73 and 145, respectively, and were significantly higher than in patients with lower BLR (all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e showed the in-hospital outcomes between patients with high and low BLR. The in-hospital mortality and MACE were significantly higher in BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 group (8.23% vs. 1.37% for in-hospital mortality, 9.44% vs. 1.99% for MACE, all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The cardiovascular mortality was significantly higher in high BLR group (8.11% vs. 1.31%, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while the nonfatal stroke and nonfatal MI were similar between the two groups (1.21% vs. 0.81%, p\u0026thinsp;=\u0026thinsp;0.331 for nonfatal stroke and 0.36% vs. 0.06%, p\u0026thinsp;=\u0026thinsp;0.227 for nonfatal MI, respectively). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e displays the K-M curves of the two group patients and it revealed the cumulative survival and free of MACE in patients with higher BLR were significantly lower than that in patients with lower BLR (all Log rank p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e displayed the results from univirate and multivariate Cox regression for in-hospital mortality. As a continuous variable, BLR was positively associated increased risk of in-hospital all-cause mortality (HR\u0026thinsp;=\u0026thinsp;1.061, 95%CI 1.047, 1.074, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). As as a category variable and compared with BLR\u0026thinsp;\u0026lt;\u0026thinsp;12.54, BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 was associated with almost 5-fold increased risk of in-hospital all-cause mortality (HR\u0026thinsp;=\u0026thinsp;4.773, 95%CI 2.935, 7.762, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After multivariate adjustment, BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 was still an independent prognostic factor for in-hospital mortality (HR\u0026thinsp;=\u0026thinsp;1.948, 95%CI 1.143, 3.318, p\u0026thinsp;=\u0026thinsp;0.014). Other independent prognostic factors included heart rate (HR\u0026thinsp;=\u0026thinsp;1.016, 95%CI 1.005, 1.026, p\u0026thinsp;=\u0026thinsp;0.003), lactate (HR\u0026thinsp;=\u0026thinsp;1.246, 95%CI 1.184, 1.312, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), NT-proBNP\u0026thinsp;\u0026gt;\u0026thinsp;265.5 pg/mL (HR\u0026thinsp;=\u0026thinsp;2.139, 95%CI 1.284, 3.564, p\u0026thinsp;=\u0026thinsp;0.004), and TNI\u0026thinsp;\u0026gt;\u0026thinsp;4.50 ng/mL (HR\u0026thinsp;=\u0026thinsp;1.733, 95%CI 1.079, 2.784, p\u0026thinsp;=\u0026thinsp;0.023).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe univariate and multivariate Cox regression analysis of in-hospital mortality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors for in-hospital mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003cp\u003eHR (95%CI) P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003cp\u003eHR (95%CI) P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.051 (1.031, 1.071)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.830 (1.183, 2.831)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission heart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.026 (1.017, 1.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.016 (1.005, 1.026)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission SBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.985 (0.977, 0.992)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.320 (1.266, 1.377)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.246 (1.184, 1.312)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-proBNP\u0026thinsp;\u0026gt;\u0026thinsp;265.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.361 (2.131, 5.303)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.139 (1.284, 3.564)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTroponin I\u0026thinsp;\u0026gt;\u0026thinsp;4.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.112 (1.371, 3.254)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.733 (1.079, 2.784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.023\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip Class\u0026thinsp;\u0026gt;\u0026thinsp;I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.502 (2.286, 5.365)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGRACE score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.019 (1.015, 1.023)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.375 (1.271, 1.488)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBLR (\u0026ge;\u0026thinsp;12.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4.773 (2.935, 7.762)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.948 (1.143, 3.318)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSBP: Systolic blood pressure; NT-proBNP: N-terminal-pro-B-type-natriuretic-peptide, BLR: blood urea nitrogen to left ventricular ejection fraction ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e showed the association of BLR with in-hospital MACE. Also, as a continuous variable, BLR was positively associated increased risk of in-hospital MACE (HR\u0026thinsp;=\u0026thinsp;1.061, 95%CI 1.048, 1.073, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Compared with BLR\u0026thinsp;\u0026lt;\u0026thinsp;12.54, BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 was associated with almost 4-flold increased risk of in-hospital MACE (HR\u0026thinsp;=\u0026thinsp;3.866, 95%CI 2.548, 5.865, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Similarly, BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 was independently associated with increased risk of in-hospital MACE after multivariate adjustment (HR\u0026thinsp;=\u0026thinsp;1.720, 95%CI 1.066, 2.774, p\u0026thinsp;=\u0026thinsp;0.026). Other independent factors associated with in-hospital MACE included age (HR\u0026thinsp;=\u0026thinsp;1.038, 95%CI 1.008, 1.068, p\u0026thinsp;=\u0026thinsp;0.013), heart rate (HR\u0026thinsp;=\u0026thinsp;1.019, 95%CI 1.009, 1.029, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), lactate (HR\u0026thinsp;=\u0026thinsp;1.225, 95%CI 1.166, 1.286, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), NT-proBNP\u0026thinsp;\u0026gt;\u0026thinsp;265.5 pg/mL (HR\u0026thinsp;=\u0026thinsp;2.030, 95%CI 1.273, 3.239, p\u0026thinsp;=\u0026thinsp;0.003), and TNI\u0026thinsp;\u0026gt;\u0026thinsp;4.50 ng/mL (HR\u0026thinsp;=\u0026thinsp;1.832, 95%CI 1.180, 2.844, p\u0026thinsp;=\u0026thinsp;0.007).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eThe univariate and multivariate Cox regression analysis of in-hospital MACE\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictors for in-hospital mortality\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eUnivariate analysis\u003c/p\u003e \u003cp\u003eHR (95%CI) P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eMultivariate analysis\u003c/p\u003e \u003cp\u003eHR (95%CI) P\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.054 (1.036, 1.072)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.038 (1.008, 1.068)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.013\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.590 (1.061, 2.384)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.025\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission heart rate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.026 (1.018, 1.035)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.019 (1.009, 1.029)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdmission SBP\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.987 (0.980, 0.995)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLactate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.304 (1.253, 1.358)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.225 (1.166, 1.286)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNT-proBNP\u0026thinsp;\u0026gt;\u0026thinsp;265.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.335 (2.217, 5.017)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2.030 (1.273, 3.239)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTroponin I\u0026thinsp;\u0026gt;\u0026thinsp;4.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2.175 (1.471, 3.217)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.832 (1.180, 2.844)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKillip Class\u0026thinsp;\u0026gt;\u0026thinsp;I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.386 (2.307, 4.969)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGRACE score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.018 (1.014, 1.022)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTIMI score\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.360 (1.267, 1.459)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBLR (\u0026ge;\u0026thinsp;12.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3.866 (2.548, 5.865)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1.720 (1.066, 2.774)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.026\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eSBP: Systolic blood pressure; NT-proBNP: N-terminal-pro-B-type-natriuretic-peptide, BLR: blood urea nitrogen to left ventricular ejection fraction ratio.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eFor a more detailed analysis of the association between BLR and in-hospital all-cause mortality and MACE in patients with different clinical profiling, subgroups were analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). It revealed the effect of BLR on different subgroups were consistent except in anterior vs. non-anterior MI with more significant in patients with anterior MI compared with non-anterior MI (for in-hospital mortality, HR\u0026thinsp;=\u0026thinsp;3.181, 95%CI 1.486, 6.807, p-interaction\u0026thinsp;=\u0026thinsp;0.018; for MACE, HR\u0026thinsp;=\u0026thinsp;2.507, 95%CI 1.300, 4.833, p-interaction\u0026thinsp;=\u0026thinsp;0.027, respectively).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"4. Discussion","content":" \u003cp\u003eThe main findings of the present study are as follows: firstly, in STEMI patients, higher BLR level was associated with higher in-hospital mortality and MACE incidence, and a BLR level higher than 12.54 was an independent risk factor for in-hospital all-cause mortality and MACE; secondly, the predictive value of BLR was significantly higher than BUN, LVEF, creatinine, NT-proBNP, and TnI and was comparable to GRACE score and TIMI scores; thirdly, the effects of BLR on different clinical profiles were consistent but more obvious in patients with anterior MI. Our present study demonstrated the possibility of BLR as a biomarker for prognostic evaluation in STEMI patients.\u003c/p\u003e \u003cp\u003eCurrently, TIMI score\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e and GRACE score\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e are the two scores widely used for risk stratification in patients with STEMI. However, the sophisticated algorithm of these risk scores limited their bedside use, e.g. TIMI score includes seven variables, age, blood pressure, heart rate and Killip class et., while GRACE score includes even more variables that need to be calculated through the calculator. More importantly, the predictive efficacy of these two scores is modest. Previous studies demonstrated that the AUCs of TIMI score and GRACE score for predicting the short-term outcome in patients with STEMI were 0.779 and 0.77, respectively\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. In our study, the prognostic value of TIMI score and GRACE score was also modest with the AUCs of 0.770 and 0.784, respectively. Therefore, a simple and effective tool for risk stratification in patients with STEMI is urgently required.\u003c/p\u003e \u003cp\u003eBLR was initially designed by Kiris et al.\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e, who used this index to evaluate the risk of contrast induced nephropathyin (CIN) in patients with acute coronary syndrome undergoing PCI and found out BLR was significantly higher in those who developed CIN, and as a continuous variable, BLR was independently associated significantly increased risk of CIN (OR 10.59, 95% CI 2.803\u0026ndash;40.070, p\u0026thinsp;=\u0026thinsp;0.001). Subsequent studies demonstrated that in patients with coronary artery disease, BLR was shown to be associated with all-cause mortality and decompensated heart failure incident in patients with stable angina pectoris, and the predictive value of BLR was superior to BUN or LVEF alone\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. This finding was further confirmed in patients receiving coronary artery bypass grafting, and a remarkable elevated BLR predicted increased risk of long-term mortality and new-onset decompensated heart failure\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. Recently, Ozkan et al.\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e found that in patients with acute heart failure, BLR was shown to be superior to BUN or LVEF for predicting the outcome. Those studies, taken together, suggested BLR could be served as a promising marker for risk stratification in patients with cardiovascular disease. Our present study extended previous findings, indicating BLR was a potential useful marker for risk stratification in patients with STEMI.\u003c/p\u003e \u003cp\u003eIn the setting of STEMI, a series of pathophysiological process, such as reduced cardiac output, systemic congestion, the activation of systemic vasoconstriction, diuretics use, and the administration of contrast media during revascularization could impair renal function\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e, which in turn, aggravates cardiac dysfunction via activation of renin-angiotensin-aldosterone system (RAAS) and finally CRS develops with a vicious cycle between renal and cardiac dysfunction\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Therefore, an adequate assessment of the cardiorenal interaction in the context of STEMI received PCI is of great importance. Our present study showed patients with higher BLR had more high risk clinical characteristics, such as older age, more morbidities and complications on admission, which were variables include in higher TIMI and GRACE scores; however, multivariate Cox regression suggested high BLR remained an independent risk factor for in-hospital mortality and MACE, indicating that BLR has independent predictive value in STEMI patients.\u003c/p\u003e \u003cp\u003eBoth BUN and creatinine reflect the renal function; however, BUN may increase before the elevation of creatinine or the decrease of glomerular filtration rate, because the overactivation of the sympathetic nervous system and RAAS could enhance the reabsorption of BUN in proximal tubular in the early stage of renal hypoperfusion\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]\u003c/sup\u003e; therefore, elevated BUN level not only reflects renal dysfunction but more importantly, indicates the neurohormonal activation, which has widely been demonstrated to be related with the prognosis in patients with AMI\u003csup\u003e[\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Actually, previous studies have confirmed the prognostic value of elevated BUN in patients with AMI\u003csup\u003e[\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e; furthermore, the predictive value of BUN was shown to be superior to that of creatinine\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. Therefore, as shown in the present study, the AUC of BUN was significantly higher than that of creatinine. LVEF is the most important index to describe the left heart systolic function, AMI usually causes the decrease of LVEF\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, especially in the setting of anterior MI, which directly cause pump failure. Subgroup analysis in our present study also revealed the impact of BLR was more significant in patients with anterior MI compared with non-anterior MI, possibly due to the significant decrease in LVEF in patients with anterior MI. Similarly, LVEF is an independent factor associated with the prognosis in patients with STEMI\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR31 CR32 CR33 CR34\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Left ventricular dysfunction may develop at the onset of STEMI due to extensive myocardial necrosis or later during the process of ventricular remodelling\u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]\u003c/sup\u003e. BLR takes the two important prognostic factors together and in our present study, BLR exhibited superior predictive value compared with BUN or LVEF alone.\u003c/p\u003e \u003cp\u003eAlthough the precise molecular mechanisms why BLR is associated with the short-term prognosis remains unknown, multiple neurohumoral and inflammatory pathways are involved in CRS. Firstly, left ventricular dysfunction causes prerenal hypoperfusion, which activates sympathetic nervous system, RAAS, and arginine vasopressin secretion, leading to fluid retention, increased preload, and worsening pump failure\u003csup\u003e[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. Secondly, when AMI occurs, a series of inflammatory biomarkers such as white blood cell, C-reactive protein, interleukin\u0026minus;6, reactive oxygen species are elevated\u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e, which have direct cardiodepressant effects causing a reduction in LVEF\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. What\u0026rsquo;s more, activated systemic inflammation could induce renal endothelial dysfunction and have been confirmed to be involved in the development of acute kidney injury after AMI and are associated with poor clinical outcome\u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. In addition, several other pathways that exacerbate cardiac or kidney injury, including activation of the sympathetic nervous system, imbalance in the proportion of reactive oxygen species/nitric oxide production, and persistent RAAS activation\u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]\u003c/sup\u003e, further induces both cardiac and renal dysfunction and causes a vicious cycle, leading to astounding morbidity and mortality.\u003c/p\u003e \u003cp\u003eIn contrast to other risk scores, BLR focused on the interaction between the two most important and commonly damaged organs (heart and kidney) after STEMI. Our present study shows the prognostic value of BLR was comparable to or even higher than that of TIMI score or GRACE score. Therefore, as a convenient, effective and low cost index, BLR provides a tool for risk stratification in patients with STEMI and should be taken into risk stratification model.\u003c/p\u003e \u003cp\u003eSome limitations in our study should be addressed. First, as an retrospective observational study, some unmeasured and unknown confounding factors can not be well controlled. Second, we only analyzed the association between admission BLR with in-hospital outcome; however, the dynamic changes of BLR during hospitalization was unavailable. The dynamic change of BLR could provide more prognostic value. Third, patients with chronic kidney disease that could cause elevated BUN were not excluded although the effect was consistent between patients with and without chronic kidney disease in the subgroup analysis. Fourth, we only evaluated the association between BLR with short-term outcome, the prognostic value of BLR for long-term outcome remained unclear. Therefore, more studies are still needed to clarify the prognostic value of BLR in STEMI patients.\u003c/p\u003e "},{"header":"5. Conclusion","content":" \u003cp\u003eAdmission BLR provided important prognostic information for STEMI patients especially in patients with anterior MI and the predictive validity of BLR was comparable even better than traditional risk scores. An admission BLR higher than 12.54 was significantly associated with increased risk of in-hospital mortality and MACE. This easily accessible index might be promising for early risk stratification in STEMI.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate:\u003c/strong\u003e All methods were carried out in accordance with relevant guidelines and regulations. This study was conducted in accordance with the Declaration of Helsinki and approved by the ethics committee of the First Affiliated Hospital of Chongqing Medical University. All the participants were informed of the study content and signed informed consent.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e All authors have no conflicts of interest to declare.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding/Support:\u003c/strong\u003e Not Applicable\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eL.F.X, B.H and S.X.L designed and performed this study; L.F.X contributed for data extraction, analyzed the data, and wrote the manuscript with support from B.H and S.X.L; J.C contributed for data extraction and analyzed the data; Y.Z.L contributed for data extraction and analyzed the data; J.S, X.L, Y.Y, G.L, and Y.C contributed for data extraction.\u003c/p\u003e\u003ch2\u003eAcknowledgements:\u003c/h2\u003e \u003cp\u003eNot Applicable\u003c/p\u003e\u003ch2\u003eData Availability Statement:\u003c/h2\u003e \u003cp\u003eThe data that supports the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eIb\u0026aacute;nez B, James S, Agewall S, et al. 2017 ESC Guidelines for the management of acute myocardial infarction in patients presenting with ST-segment elevation. 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Contrib Nephrol. 2013;182:99\u0026ndash;116. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1159/000349969\u003c/span\u003e\u003cspan address=\"10.1159/000349969\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Blood urea nitrogen, Left ventricular ejection fraction, ST-segment elevation myocardial infarction, In-hospital prognosis","lastPublishedDoi":"10.21203/rs.3.rs-4552198/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4552198/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe in-hospital mortality of ST-elevation myocardial infarction (STEMI) remains as high as 4\u0026ndash;12%. Heart and kidney are closely linked, and both renal and cardiac function have been confirmed to be associated with the prognosis in patients with STEMI. This study intends to evaluate the prognostic value of blood urea nitrogen (BUN) to left ventricular ejection fraction (LVEF) ratio (BLR) in STEMI patients.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eFrom January 2015 to January 2023, 2435 consecutive STEMI patients were enrolled. The primary endpoint was in-hospital all-cause mortality and the second endpoint was major adverse cardiovascular events (MACE) including cardiovascular death, nonfatal stroke, and nonfatal myocardial infarction. The predictive value of BLR was compared with BUN, LVEF, traditional markers and scores (GRACE score and TIMI score) by receiver operating characteristic (ROC) curves, the area under the curve (AUC) were compared by DeLong test. Then patients were divided into two groups based on the cut-off value of BLR determined by Youden index and compared the in-hospital mortality and MACE. The association between BLR and endpoints was investigated by Cox regression.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eTotally 2435 patients were included in our study, among which 90 (3.70%) patients died and 110 (4.52%) MACEs were collected. The non-survivors had significantly higher BUN level and lower LVEF value. The AUCs and DeLong test showed that the predictive value of BLR was significantly higher than BUN, LVEF, creatinine, NT-proBNP, and troponin I but was comparable to GRACE score and TIMI scores. The optimal cut-off value of BLR was 12.54 with a sensitivity of 75.6% and a specificity of 67.6%. The in-hospital mortality and MACE was significantly higher in high BLR group (8.23% vs. 1.37% for in-hospital mortality and 9.44% vs. 1.99% for in-hospital MACE, all p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). After multivariable adjustment, BLR\u0026thinsp;\u0026ge;\u0026thinsp;12.54 was still independently associated with higher in-hospital mortality (HR\u0026thinsp;=\u0026thinsp;1.948, 95%CI 1.143, 3.318, p\u0026thinsp;=\u0026thinsp;0.014) and MACE (HR\u0026thinsp;=\u0026thinsp;1.720, 95%CI 1.066, 2.774, p\u0026thinsp;=\u0026thinsp;0.026).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBLR is an important prognostic index to identify patients at high risk of in-hospital prognosis in STEMI patients and the prognostic value was comparable to or even higher traditional scores.\u003c/p\u003e\u003ch2\u003eTrial registration\u003c/h2\u003e \u003cp\u003eChiCTR1900028516 (http//www.chictr.org.cn).\u003c/p\u003e","manuscriptTitle":"Blood urea nitrogen to left ventricular ejection fraction ratio: a predictor of in-hospital outcomes in STEMI patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-18 20:11:54","doi":"10.21203/rs.3.rs-4552198/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-07T09:23:43+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-06-16T07:04:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"196846675352498608758040091594327613858","date":"2025-06-16T06:32:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-08-21T16:11:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"156142945627546093109571034817255025561","date":"2024-08-19T15:02:20+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-07-25T08:04:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-24T07:53:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-21T14:32:03+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-21T14:31:23+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cardiovascular Disorders","date":"2024-06-09T02:09:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cardiovascular-disorders","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcar","sideBox":"Learn more about [BMC Cardiovascular Disorders](http://bmccardiovascdisord.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcar/default.aspx","title":"BMC Cardiovascular Disorders","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"87a60ed2-ebb4-4af5-9270-e209c4a2627e","owner":[],"postedDate":"July 18th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-10-06T16:04:48+00:00","versionOfRecord":{"articleIdentity":"rs-4552198","link":"https://doi.org/10.1186/s12872-025-05180-y","journal":{"identity":"bmc-cardiovascular-disorders","isVorOnly":false,"title":"BMC Cardiovascular Disorders"},"publishedOn":"2025-09-29 15:58:15","publishedOnDateReadable":"September 29th, 2025"},"versionCreatedAt":"2024-07-18 20:11:54","video":"","vorDoi":"10.1186/s12872-025-05180-y","vorDoiUrl":"https://doi.org/10.1186/s12872-025-05180-y","workflowStages":[]},"version":"v1","identity":"rs-4552198","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4552198","identity":"rs-4552198","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}