Major Adverse Cardiovascular Events Group Research Articles

Immune-inflammatory biomarkers for the occurrence of MACE in patients with myocardial infarction with non-obstructive coronary arteries.

Neutrophil-to-high-density lipoprotein cholesterol ratio (NHR), monocyte-to-high-density lipoprotein cholesterol ratio (MHR), lymphocyte-to-high-density lipoprotein cholesterol ratio (LHR), platelet-to-high-density lipoprotein cholesterol ratio (PHR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) have been identified as immune-inflammatory biomarkers associated with the prognosis of cardiovascular diseases. However, the relationship of these biomarkers with the prognosis of myocardial infarction with non-obstructive coronary arteries (MINOCA) remains unclear. Patients with MINOCA who underwent coronary angiography at the 920th Hospital of Joint Logistics Support Force were included in our study. Clinical baseline characteristics and laboratory testing data were collected from the hospital record system. The patients were divided into two groups on the basis of major adverse cardiovascular events (MACE) occurrence. Multiple logistic regression analysis was conducted to assess the relationship between NHR, MHR, LHR, PHR, SII, SIRI, AISI, and MACE. Receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of NHR, MHR, LHR, PHR, SII, SIRI, and AISI for MACE in patients with MINOCA. The accuracy of the prediction was indicated by the area under the curve (AUC) value. The study included 335 patients with MINOCA. (81 in the MACE group and 254 in the No-MACE group). The MACE group had higher levels of NHR, MHR, LHR, PHR, SII, SIRI, and AISI than the No-MACE group. Multiple logistic regression analysis adjusted for confounding factors indicated that the higher levels of NHR, MHR, PHR, SII, SIRI, and AISI were associated with the occurrence of MACE in patients with MINOCA (P < 0.001). The AUC values for NHR, MHR, PHR, SII, SIRI, and AISI were 0.695, 0.747, 0.674, 0.673, 0.688, and 0.676, respectively. The combination of NHR, MHR, PHR, SII, SIRI, and AISI improved the accuracy of predicting MACE in patients with MINOCA (AUC = 0.804). Higher levels of NHR, MHR, PHR, SII, SIRI, and AISI were associated with the occurrence of MACE, and the combination of NHR, MHR, PHR, SII, SIRI, and AISI improved the accuracy for predicting the incidence of MACE events in patients with MINOCA.

Estudio del índice de gravedad del síndrome metabólico como factor predictivo de un episodio cardiovascular mayor en mujeres premenopáusicas con lupus eritematoso sistémico

BackgroundPatients with systemic lupus erythematosus (SLE) have an increased risk of metabolic syndrome (MS) and cardiovascular (CV) disease. MS is evaluated binary, limiting the understanding of each component's severity individually. Therefore, severity scores for MS that evaluate them separately have been developed. This study aims to determine the prognosis between MS severity and the occurrence of major adverse cardiovascular events (MACE) in SLE patients. MethodsTen-year follow-up cohort study. Premenopausal>18-year-old women with a previous diagnosis of SLE were included. Patients with recent CV events, pregnancy, thyroid disease, and liposuction were excluded. The variables of interest were CV events; the confounding variables, and the MS severity indexes were examined. Hazard ratios and Kaplan-Meier survival curves were estimated through Cox regression. ResultsA total of 238 women were analyzed: 22 presented MACE, and 216 did not. MS prevalence, measured according to consensus and ATP-III criteria, was higher in MACE patients (50 and 40,95%, respectively). The MetSx-IMC severity index was higher within the MACE group. Cox analysis showed an increase in the MetSx-IMC associated with the risk of suffering MACE in a 1.107 ratio. ConclusionsThe MetSx-IMC severity index, contrary to the binary approaches, is recommended to evaluate MS as a predictor of MACE in SLE patients. Offering improved and more accurate prognosis in patients at risk of developing MCE.

Cardiac magnetic resonance-derived mitral annular plane systolic excursion: a robust indicator for risk stratification after myocardial infarction.

To explore the predictive value of mitral annular plane systolic excursion (MAPSE) derived by cardiac magnetic resonance (CMR) for major adverse cardiovascular events (MACE) in postmyocardial infarction (MI) patients.Patients with MI who underwent 3.0 T CMR (Chinese Clinical Trial Registry, ChiCTR2200055158) were recruited retrospectively. CMR parameters included MAPSE and LVEF. Patients were followed up for MACE for more than 6 months and were separated into a No-MACE group and a MACE group.A total of 165 post-MI patients were included, and 103 patients were finally analyzed (61 patients belonged to the No-MACE group, and 42 patients belonged to the MACE group). The LVEF and MAPSE of the patients belonging to the No-MACE group were considerably higher than those of the patients belonging to the MACE group. Both LVEF and MAPSE were effective indicators of the occurrence of MACE after MI. The risk of MACE decreased as LVEF and MAPSE increased. For the risk prediction of MACE after MI, compared with model I (chi-square value 4.0 vs. 31.4, P < 0.001) and model II (chi-square value 22.7 vs. 31.4, P = 0.003), model III had a significant incremental predictive value. Moreover, the cutoff value of MAPSE was 9.70mm.CMR-derived MAPSE is an effective predictor of MACE occurrence in patients with MI, and MAPSE provided a significant incremental predictive value. Moreover, MAPSE could complement LVEF for superior risk stratification of MI patients.

Prognostic value of Geriatric Nutritional Risk Index and systemic immune-inflammatory index in elderly patients with acute coronary syndromes

The objective of this study was to evaluate the predictive value of the Geriatric Nutritional Risk Index (GNRI) combined with the Systemic Immunoinflammatory Index (SII) for the risk of major adverse cardiovascular events (MACE) following percutaneous coronary intervention in elderly patients with acute coronary syndrome (ACS). We retrospectively reviewed the medical records of 1202 elderly patients with acute coronary syndromes divided into MACE and non-MACE groups according to whether they had a MACE. The sensitivity analysis utilized advanced machine learning algorithms to preliminarily identify the critical role of GNRI versus SII in predicting MACE risk. We conducted a detailed analysis using a restricted cubic spline approach to investigate the nonlinear relationship between GNRI, SII, and MACE risk further. We constructed a clinical prediction model based on three key factors: GNRI, SII, and Age. To validate the accuracy and usefulness of this model, we compared it to the widely used GRACE score using subject work and recall curves. Additionally, we compared the predictive value of models and GRACE scores in assessing the risk of MACE using the Integrated Discriminant Improvement Index (IDI) and the Net Reclassification Index (NRI). This study included 827 patients. The GNRI scores were lower in the MACE group than in the non-MACE group, while the SII scores were higher in the MACE group (P < 0.001). The multifactorial analysis revealed a low GNRI (OR = 2.863, 95% CI: 2.026–4.047, P = 0.001), High SII (OR = 3.102, 95% CI: 2.213–4.348, P = 0.001). The area under the curve (AUC) for the predictive model was 0.778 (95% CI: 0.744–0.813, P = 0.001), while the AUC for the GRACE score was 0.744 (95% CI: 0.708–0.779, P = 0.001). NRI was calculated to be 0.5569, with NRI + at 0.1860 and NRI- at 0.3708. The IDI was found to be 0.0571, with a P-value of less than 0.001. These results suggest that the newly developed prediction model is more suitable for use with the population in this study than the GRACE score. The model constructed using GNRI and SII demonstrated good standardization and clinical impact, as evidenced by the standard, DCA, and clinical impact curves. The study shows that combining GNRI and SII can be a simple, cost-effective, and valuable way to predict the risk of MACE within one year in elderly acute coronary syndromes.

The Value of Combined Detection of Serum BNP, Cardiac Troponin-I and Dynamic Electrocardiogram in Early Clinical Diagnosis and Prognosis of Patients with Acute Myocardial Infarction.

Acute myocardial infarction (AMI) is a prevalent cardiovascular disease resulting from myocardial ischemia and necrosis due to coronary artery occlusion. AMI is characterized by a sudden onset and high mortality, underscoring the significance of early diagnosis and treatment for improving patient prognosis. This study endeavors to assess the utility of a combined assessment involving serum brain natriuretic peptide (BNP), cardiac troponin-I (cTnI), and dynamic electrocardiogram (ECG) in the early clinical diagnosis and prognosis prediction of AMI. This paper constitutes a retrospective study. All enrolled patients underwent dynamic ECG examination. The study compared the serum levels of BNP and cTnI, along with pertinent dynamic ECG parameters [turbulence slope (TS) and standard deviation (SDNN) of the 24-hour interval between normal atrial depolarization and ventricular depolarization (R-R)], between the observation group (AMI patients) and the control group (patients with unstable angina (UA)). To evaluate the early diagnostic potential of AMI, we utilized receiver operating characteristic (ROC) curves to analyze serum BNP, cTnI, dynamic ECG, and their combined utility. Furthermore, a follow-up period of 6 months was conducted for AMI patients to record major adverse cardiovascular events (MACE). In the observation group, the serum levels of BNP and cTnI were significantly higher than those in the control group (p < 0.001), while dynamic ECG parameters, specifically TS and SDNN, were significantly lower in the observation group compared to the control group (p < 0.001). The results obtained from the ROC curve analysis revealed that the area under the curve (AUC) for BNP, cTnI, dynamic ECG, and their combination in early AMI diagnosis were 0.838, 0.887, 0.874, and 0.974, respectively. The 95% confidence intervals (CI) were 0.781~0.884, 0.836~0.926, 0.822~0.915, and 0.942~0.991, respectively. Sensitivity values were 64.29%, 82.14%, 91.07%, and 88.39%, and specificity values were 91.00%, 88.00%, 70.00%, and 98.00%, respectively. Significantly, the combination of all three markers demonstrated superior efficacy in early AMI diagnosis compared to any single index (p < 0.05). During the 6-month follow-up of 112 AMI patients, 22 experienced MACE. The MACE group exhibited notably higher serum BNP and cTnI levels compared to the non-MACE group. Additionally, dynamic electrocardiogram parameters TS and SDNN demonstrated a significant decrease (p < 0.05) in the MACE group. The combined assessment of serum BNP, cTnI, and dynamic electrocardiogram enhances the early clinical diagnostic potential for AMI and holds value in assessing the prognosis of AMI patients.

The Predictive Value of Hemoglobin to Red Cell Blood Distribution Width Ratio Combined with Serum Sodium for MACE of Acute Heart Failure with Preserved Ejection Fraction in Elderly Patients.

To investigate the predictive value of hemoglobin (Hb) to red blood cell distribution width (RDW) (Hb/RDW) ratio in combination with serum sodium for major adverse cardiovascular events (MACE) in elderly acute heart failure patients with preserved ejection fraction at 30 days after discharge. 130 elderly acute heart failure patients with preserved ejection fraction were enrolled and followed up at 30 days after discharge. They were classified into the MACE group (n=11) and none-MACE group (n=119). On the day of admission, clinical baseline characteristics were measured and results from laboratory tests were gathered. The correlation and predictive value of Hb/RDW and serum sodium with the occurrence of MACE at 30 days after discharge in acute heart failure patients with preserved ejection fraction in the elderly were analyzed. Spearman correlation analysis showed that the occurrence of MACE was negatively correlated with Hb/RDW, serum sodium (r=-0.209, r=0.291, p<0.05) and Hb/RDW (OR=0.484, 95% CI:0.254, 0.922), serum sodium (OR=0.779, 95% CI:0.646,0.939) were independent risk factors (p<0.05) analyzed by multifactorial logistic. Receiver operating characteristic curves (ROC) analysis showed that the area under the curve (AUC) for the prediction of MACE by Hb/RDW was 0.73, with an optimal threshold of 9.28, sensitivity 81.80%, specificity 70.60%, positive predictive value (PPV) 20.50%, negative predictive value (NPV) 97.70%; the AUC of serum sodium for predicting the occurrence of MACE was 0.76, with an optimal threshold of 140.35 mmol/L, sensitivity 90.90%, specificity 57.10%, PPV 16.40%, NPV 98.60%; and the AUC of Hb/RDW combined serum sodium to predict the occurrence of MACE was 0.83, with sensitivity 90.90%, specificity 78.20%, PPV 27.80% and NPV 98.90%. Hb/RDW and serum sodium had negative correlation with MACE and were independent risk factors of 30-day MACE; Hb/RDW combined with serum sodium can predict 30-day MACE occurrence in elderly acute heart failure patients with preserved ejection fraction.

Effect of quantitative parameters of contrast-enhanced ultrasound on the long-term prognosis of patients with chronic coronary syndrome.

Ultrasound is one of the most commonly used examination methods in patients with coronary artery disease (CAD) and is valuable in evaluating patient prognosis. Although contrast-enhanced ultrasound (CEUS) can assess more in depth the vascular lesions of patients, there is still a lack of relevant research on the value of quantitative parameters of CEUS in predicting the long-term prognosis of patients with chronic coronary syndrome (CCS), thus, we designed this study. From January 2016 to December 2017, a total of 473 patients with CCS admitted to Yueyang People's Hospital were retrospectively enrolled. The patients were followed up for five years. According to whether the patients had major adverse cardiovascular events (MACE), patients were divided into the MACE group (n=113) and the control group (n=360). The CEUS was performed to detect the myocardial perfusion status. The value of quantitative parameters of CEUS in predicting the MACE in patients with CCS was analyzed using the receiver operating characteristic (ROC) curve. Peak intensity of contrast agent at platform stage, rising rate of microbubble reperfusion, and left ventricular ejection fraction (LVEF) were found to be valuable in predicting the risk of MACE in patients with CCS. Among them, the peak intensity of contrast agent at platform stage had the highest predictive value, and the area under the curve (AUC) was 0.860 [95% confidence interval (CI): 0.827-0.894, P<0.001]. Multivariate logistics regression analysis showed that the peak intensity of contrast agent at platform stage <4.54 dB and rising rate of microbubble reperfusion <0.275 s were independent risk factors of MACE in patients with CCS. The relative risks were 12.238 (95% CI: 6.632-22.585) and 5.724 (95% CI: 3.149-10.405), respectively. Quantitative parameters of CEUS can be used as predictors of MACE in patients with CCS, and strengthening the management of such high-risk patients may be beneficial to reduce the incidence of MACE.

Comparative analysis of four nutritional scores predicting the incidence of MACE in older adults with acute coronary syndromes after PCI

To determine the most appropriate nutritional assessment tool for predicting the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI from four nutritional assessment tools including PNI, GNRI, CONUT, and BMI. Consecutive cases diagnosed with acute coronary syndrome (ACS) and underwent percutaneous coronary intervention (PCI) in the Department of Cardiovascular Medicine of the Air force characteristic medical center from 1 January 2020 to 1 April 2022 were retrospectively collected. The basic clinical characteristics and relevant test and examination indexes were collected uniformly, and the cases were divided into the MACE group (174 cases) and the non-MACE group (372 cases) according to whether a major adverse cardiovascular event (MACE) had occurred within 1 year. Predictive models were constructed to assess the nutritional status of patients with the Prognostic Nutritional Index (PNI), Geriatric Nutritional Risk Index (GNRI), Controlling nutritional status (CONUT) scores, and Body Mass Index (BMI), respectively, and to analyze their relationship with prognosis. The incremental value of the four nutritional assessment tools in predicting risk was compared using the Integrated Discriminant Improvement (IDI) and the net reclassification improvement (NRI). The predictive effect of each model on the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI was assessed using area under the ROC curve (AUC), calibration curves, decision analysis curves, and clinical impact curves; comparative analyses were performed. Among the four nutritional assessment tools, the area under the curve (AUC) was significantly higher for the PNI (AUC: 0.798, 95%CI 0.755–0.840 P < 0.001) and GNRI (AUC: 0.760, 95%CI 0.715–0.804 P < 0.001) than for the CONUT (AUC: 0.719,95%CI 0.673–0.765 P < 0.001) and BMI (AUC: 0.576, 95%CI 0.522–0.630 P < 0.001). The positive predictive value (PPV) of PNI: 67.67% was better than GNRI, CONUT, and BMI, and the negative predictive value (NPV): of 83.90% was better than CONUT and BMI and similar to the NPV of GNRI. The PNI, GNRI, and CONUT were compared with BMI, respectively. The PNI had the most significant improvement in the Integrated Discriminant Improvement Index (IDI) (IDI: 0.1732, P < 0.001); the PNI also had the most significant improvement in the Net Reclassification Index (NRI) (NRI: 0.8185, P < 0.001). In addition, of the four nutritional assessment tools used in this study, the PNI was more appropriate for predicting the occurrence of major adverse cardiovascular events (MACE) within 1 year in elderly ACS patients undergoing PCI.

Abstract 17461: Major Cardiovascular Events and Liver Disease in Patients With Truncating Variants in APOB and PSCK9

Introduction: Truncated variants in the genes ApoB and PSCK9 have been shown to be associated with low levels of low-density lipoprotein cholesterol (LDL-C), however, there is concern about the increased risk of liver disease. Using Intermountain Health’s HerediGene Population Study, a population-based genetic study, we sought to understand the impact of these variants on major adverse cardiovascular events (MACE) and liver disease. Methods: Of the 32,159 sequenced patients (pts), 58 (0.18%) had a truncating variant in ApoB (n=49) and PCSK9 (n=10). Among those with a truncating variant, we compared the demographics, LDL-C levels, statin use, and disease by MACE (including, myocardial infarction [MI], heart failure (HF) hospitalization, stroke, peripheral artery disease, and carotid artery disease). Results: MACE occurred in 32% of pts, with HF hospitalization followed by MI being the most frequent. The rates of MACE were similar for pts with ApoB (n=15, 30.6%) and PCSK9 (n= 4, 40%). Differences in demographics and clinical characteristics stratified by MACE are shown in the Table. LDL-C levels were low in both groups, with approximately half having an LDL-C &lt;70 mg/dL. Hypertension was more common in the MACE group (95% vs 50%). Both groups had high rates of liver disease (47%) compared to the general patient population (9%). Renal failure was also common among these pts (36%). Only 2 of the deaths (both in the MACE group) were cardiovascular-related, 1 due to stroke and 1 due to heart failure. Conclusion: Low LDL-C was associated with truncated variants in the ApoB and PSCK9 genes. However, these patients still had a high rate of MACE, which was driven mainly by hypertensive diseases. Frequency of liver disease and renal failure was high, which may also be attributed to hypertension. While this is a small sample, these findings suggest that continued screening for cardiovascular disease is needed despite low LDL-C, with liver disease screening also needing to be performed.

Comparison of machine-learning models for the prediction of 1-year adverse outcomes of patients undergoing primary percutaneous coronary intervention for acute ST-elevation myocardial infarction.

Acute ST-elevation myocardial infarction (STEMI) is a leading cause of mortality and morbidity worldwide, and primary percutaneous coronary intervention (PCI) is the preferred treatment option. Machine learning (ML) models have the potential to predict adverse clinical outcomes in STEMI patients treated with primary PCI. However, the comparative performance of different ML models for this purpose is unclear. This study used a retrospective registry-based design to recruit consecutive hospitalized patients diagnosed with acute STEMI and treated with primary PCI from 2011 to 2019, at Tehran Heart Center, Tehran, Iran. Four ML models, namely Gradient Boosting Machine (GBM), Distributed Random Forest (DRF), Logistic Regression (LR), and Deep Learning (DL), were used to predict major adverse cardiovascular events (MACE) during 1-year follow-up. A total of 4514 patients (3498 men and 1016 women) were enrolled, with MACE occurring in 610 (13.5%) subjects during follow-up. The mean age of the population was 62.1 years, and the MACE group was significantly older than the non-MACE group (66.2 vs. 61.5 years, p < .001). The learning process utilized 70% (n = 3160) of the total population, and the remaining 30% (n = 1354) served as the testing data set. DRFand GBM models demonstrated the best performance in predicting MACE, with an area under the curve of 0.92 and 0.91, respectively. ML-based models, such as DRF and GBM, can effectively identify high-risk STEMI patients for adverse events during follow-up. These models can be useful for personalized treatment strategies, ultimately improving clinical outcomes and reducing the burden of disease.

Association between Major Adverse Cardiovascular Events and the Liver Fibrosis Score in Patients with and without Coronary Artery Disease: From the FU-CCTA Registry.

The liver fibrosis score reflects the degree of hepatic scarring and has been reported to be associated with cardiovascular disease. Using a coronary artery computed tomography angiography registry at the Fukuoka University Hospital (FU-CCTA registry), we investigated the association between major adverse cardiovascular events (MACEs) and the liver fibrosis score (fibrosis-4 index (FIB-4I)) in 612 patients who underwent CCTA to screen for coronary artery disease and performed a prognosis survey for up to 5 years. The primary endpoint was MACEs (all-cause mortality, acute myocardial infarction, ischemic stroke, coronary revascularization). FIB-4I in all patients and in patients with hypertension (HTN) was significantly higher in the MACE group than in the non-MACE group. The event-free survival rate of MACEs targeting only patients with HTN was significantly lower in patients with a high risk of liver fibrosis (FIB-4I values of 2.67 or higher) than in those with a low or intermediate risk (less than 2.67). However, no significant difference was observed in all patients or in patients without HTN. Finally, FIB-4I and body mass index were independent factors associated with MACEs in patients with HTN. In conclusion, the liver fibrosis score may be an independent predictor of MACEs in hypertensive patients undergoing CCTA.

Prognostic value of coronary CT angiography for the prediction of all-cause mortality and non-fatal myocardial infarction: a propensity score analysis.

To explore the relationship between comprehensive assessment of coronary atherosclerosis by coronary CT angiography (CCTA) and all-cause mortality and non-fatal myocardial infarction in the Chinese population. Sixty-three patients from the prospective long-term study who experienced major adverse cardiovascular events (MACE) during the follow-up were included. No-MACE patients were 1:1 propensity-matched. Various qualitative and quantitative CCTA parameters, such as coronary artery calcium score (CACS), high-risk plaque, coronary artery disease (CAD) severity, number of obstructive vessels, segment involvement score (SIS), segment stenosis score (SSS), computed tomography-adapt Leaman score (CT-LeSc), and peri-coronary adipose tissue (PCAT) CT attenuation, were compared between both groups. Cox regression analysis was performed to determine the association between CCTA parameters and MACE. The MACE group had higher CACS, more high-risk plaques, more obstructive CAD, more obstructive vessels, higher PCAT CT attenuation, and higher coronary atherosclerotic burden (SIS: 5.76 ± 3.36 vs. 2.84 ± 3.07; SSS: 11.06 ± 8.41 vs. 3.94 ± 4.78; CT-LeSc: 11.25 ± 6.57 vs. 5.49 ± 5.82) than the control group (all p < 0.05). On multivariable analysis, hazard ratios were 1.058 for the SSS (p = 0.004), and 2.152 for the obstructive CAD. When the burden of coronary atherosclerosis was defined as the CT-LeSc, hazard ratios were 1.057 for the CT-LeSc (p = 0.036), and 2.272 for the obstructive CAD. The SSS, CT-LeSc, and presence of obstructive CAD were independently associated with the all-cause mortality and non-fatal myocardial infarction in the suspected CADs in the Chinese population.

PTH Predicts the in-Hospital MACE After Primary Percutaneous Coronary Intervention for Acute ST-Segment Elevation Myocardial Infarction.

To investigate the correlation between serum parathyroid hormone (PTH) levels and in-hospital major adverse cardiovascular events (MACE) in patients with acute ST-segment elevation myocardial infarction (STEMI) after primary percutaneous coronary intervention (PCI), and establish a risk prediction model based on parameters such as PTH for in-hospital MACE. This observational retrospective study consecutively enrolled 340 patients who underwent primary PCI for STEMI between January 2016 and December 2020, divided into a MACE group (n=92) and a control group (n=248). The least absolute shrinkage and selection operator (LASSO) and logistic regression analyses were used to determine the risk factors for MACE after primary PCI. The rms package in R-studio statistical software was used to construct a nomogram, to detect the line chart C-index, and to draw a calibration curve. The decision curve analysis (DCA) method was used to evaluate the clinical application value and net benefit. Correlation analysis revealed that PTH level positively correlated with the occurrence of in-hospital MACE. Receiver operating characteristic curve analyses revealed that PTH had a good predictive value for in-hospital MACE. Multivariate logistic regression analysis indicated that Killip class II-IV, and FBG were independently associated with in-hospital MACE after primary PCI. A nomogram model was constructed using the above parameters. The model C-index was 0.894 and the calibration curve indicated that the model was well calibrated. The DCA curve suggested that the nomogram model was better than TIMI score model in terms of net clinical benefit. Serum PTH levels in patients with STEMI are associated with in-hospital MACE after primary PCI, and the nomogram risk prediction model based on PTH demonstrated good predictive ability with obvious clinical practical value.

Cystatin C as a Predictor of Major Adverse Cardiovascular Event in Patients with Acute Myocardial Infarction Without Cardiogenic Shock and Renal Impairment After Coronary Intervention.

To prove that cystatin C is a predictor of major adverse cardiovascular events (MACE) after percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI), either with ST-segment Elevation (AMI-EST) or without ST-segment elevation (AMI-NEST), without cardiogenic shock or renal impairment. This was an observational cohort study. Samples were obtained from AMI patients who underwent PCI between February 2022 and March 2022 at the Intensive Cardiovascular Care Unit. Cystatin C levels were measured before PCI. MACE were observed within 6 months. Comparisons between normally distributed continuous data were performed using the t-test; Mann-Whitney test was used for non-normally distributed data. Categorical data were compared using the chi-squared test. The cut-off point of cystatin C levels to predict MACE was analyzed using Receiver Operating Characteristics (ROC). The participants were 40 AMI patients, consisting of 32 patients (80%) with AMI-EST and eight patients (20%) diagnosed with AMI-NEST, who were evaluated for the occurrence of MACE within 6 months after PCI. Ten patients (25%) developed MACE during follow-up [(MACE (+)], and the rest were in the MACE (-) group. Cystatin C levels were significantly higher in the MACE (+) group (p=0.021). ROC analysis revealed a cystatin C level of 1.21 mg/dL; cystatin C > 1.21 is associated with MACE risk, showing a significant relationship with the odds ratio value reaching 26.00, with 95% CI (3.99-169.24). Cystatin C level is an independent predictor of MACE in patients with AMI without cardiogenic shock or renal impairment after PCI.

Analysis of Risk Factors for Major Adverse Cardiovascular Events in Patients with Coronary Stent Restenosis after Revascularization

Background: To investigate the risk factors for myocardial infarction, recurrent in-stent restenosis (ISR) and target vessel revascularization (TVR) in patients with coronary ISR within 4 years after revascularization. Methods: A total of 1884 patients who were hospitalized at Fuwai Hospital for ISR and successfully treated with coronary intervention between January 2017 and December 2018 were included to determine whether there were myocardial infarction, recurrent ISR, TVR and other major adverse cardiovascular events (MACEs) within 4 years after intervention. The patients were divided into the MACE group (215 patients) and the non-MACE group (1669 patients). The clinical data of patients in the two groups were compared, and the risk factors for postoperative MACEs in the ISR patients were obtained by multivariate logistic regression analysis. The receiver operating characteristic (ROC) curve was used to determine the optimal prediction threshold for postoperative MACEs in ISR patients. The difference in survival curves between the two groups was compared using Kaplan‒Meier survival analysis. Results: The albumin (43.42 ± 4.77 vs. 44.17 ± 4.46, p = 0.021), direct bilirubin (2.5 (2, 3.5) vs. 2.8 (2.07, 3.73), p = 0.036) and free triiodothyronine (FT3) (2.85 ± 0.43 vs. 2.92 ± 0.42, p = 0.019) levels in the MACE group were significantly lower than those in the non-MACE group, and there was a significant negative correlation between albumin and FT3 and MACEs. The results of univariate and multivariate logistic regression analyses revealed that FT3 was an independent predictor of postoperative MACEs in ISR patients (Odds Ratio (OR) = 0.626, 95% CI: 0.429–0.913, p = 0.015). The ROC curve analysis determined that an FT3 value of 2.785 pmol/L was the optimal prediction threshold. According to the threshold, ISR patients were divided into the FT3 &lt;2.785 group and the FT3 ≥2.785 group. The Kaplan‒Meier analysis revealed that the postoperative recurrence rate of MACEs of the FT3 &lt;2.785 group was substantially greater than that of the FT3 ≥2.785 group (Hazard Ratio (HR) = 0.76, 95% CI: 0.58–0.994, p = 0.044). Conclusions: FT3 can be used as an independent predictor of postoperative myocardial infarction, recurrent ISR and TVR in ISR patients. When FT3 is &lt;2.785 pmol/L, the incidence of postoperative myocardial infarction, recurrent ISR and TVR in ISR patients increases significantly.

Risk prediction model for major adverse cardiovascular events (MACE) during hospitalization in patients with coronary heart disease based on myocardial energy metabolic substrate.

The early attack of coronary heart disease (CHD) is very hidden, and clinical symptoms generally do not appear until cardiovascular events occur. Therefore, an innovative method is needed to judge the risk of cardiovascular events and guide clinical decision conveniently and sensitively. The purpose of this study is to find out the risk factors related to MACE during hospitalization. In order to develop and verify the prediction model of energy metabolism substrates, and establish a nomogram to predict the incidence of MACE during hospitalization and evaluate their performance. The data were collected from the medical record data of Guang'anmen Hospital. This review study was collected the comprehensive clinical data of 5,935 adult patients hospitalized in the cardiovascular department from 2016 to 2021. The outcome index was the MACE during hospitalization. According to the occurrence of MACE during hospitalization, these data were divided into MACE group (n = 2,603) and non-MACE group (n = 425). Logistic regression was used to screen risk factors, and establish the nomogram to predict the risk of MACE during hospitalization. Calibration curve, C index and decision curve were used to evaluate the prediction model, and drawn ROC curve to find the best boundary value of risk factors. The logistic regression model was used to establish a risk model. Univariate logistic regression model was mainly used to screen the factors significantly related to MACE during hospitalization in the training set (each variable is put into the model in turn). According to the factors with statistical significance in univariate logistic regression, five cardiac energy metabolism risk factors, including age, albumin(ALB), free fatty acid(FFA), glucose(GLU) and apolipoprotein A1(ApoA1), were finally input into the multivariate logistic regression model as the risk model, and their nomogram were drawn. The sample size of the training set was 2,120, the sample size of the validation set was 908. The C index of the training set is 0.655 [0.621,0.689], and the C index of the validation set was 0.674 [0.623,0.724]. The calibration curve and clinical decision curve show that the model performs well. The ROC curve was used to establish the best boundary value of the five risk factors, which could quantitatively present the changes of cardiac energy metabolism substrate, and finally achieved prediction of MACE during hospitalization conveniently and sensitively. Age, albumin, free fatty acid, glucose and apolipoprotein A1 are independent factors of CHD in MACE during hospitalization. The nomogram based on the above factors of myocardial energy metabolism substrate provides prognosis prediction accurately.

Association Between Major Adverse Cardiovascular Events and the Gensini Score or Coronary Artery Calcification Score in Hypertensive Patients Who Have Undergone Coronary Computed Tomography Angiography

From the Fukuoka University Coronary Computed Tomography Angiography (FU-CCTA) registry, we present major adverse cardiovascular events (MACEs) in hypertensive patients who have undergone CCTA, and the association between MACEs and the Gensini score of coronary arteries or the coronary artery calcification (CAC) score. Of the patients who underwent CCTA for coronary artery disease (CAD) screening at Fukuoka University Hospital, 318 hypertensive patients who had at least one cardiovascular risk factor or suspected CAD were enrolled. The patients were divided into two groups: MACEs and non-MACEs groups. The severity of atherosclerosis of coronary arteries was assessed by the Gensini score. The CAC score was also defined by computed tomography (CT) images at the time of CCTA. A primary endpoint was MACEs (all-cause death, ischemic stroke, acute myocardial infarction, coronary revascularization). The patients were followed for up to 5 years. The patients were 68 ± 10 years, and 50% were males. The percentages of smoking, dyslipidemia, diabetes, and chronic kidney disease were 39%, 70%, 26% and 37%, respectively. The %males, %smoking, CAC score and Gensini score in the MACEs group were significantly higher than those in the non-MACEs group. On the other hand, the differences in age, dyslipidemia, diabetes, or chronic kidney disease between the groups were not seen. A multivariate analysis was performed regarding the presence or absence of MACE by logistic regression analysis of the CAC score or Gensini score in addition to conventional risk factors as independent variables. A Cox regression analysis revealed significant relationships for both the CAC score (P = 0.043) and the Gensini score (P = 0.008). The CAC score and the Gensini score could predict MACEs in hypertensive patients who have undergone CCTA.

The prognostic value of CZT SPECT myocardial blood flow (MBF) quantification in patients with ischemia and no obstructive coronary artery disease (INOCA): a pilot study

BackgroundDespite the demonstrated adverse outcome, it is difficult to early identify the risks for patients with ischemia and no obstructive coronary artery disease (INOCA). We aimed to explore the prognostic potential of CZT SPECT in INOCA patients.MethodsThe study population consisted of a retrospective cohort of 118 INOCA patients, all of whom underwent CZT SPECT imaging and invasive coronary angiography (ICA). Dynamic data were reconstructed, and MBF was quantified using net retention model. Major adverse cardiovascular events (MACEs) were defined as cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, heart failure, late coronary revascularization, or hospitalization for unstable angina.ResultsDuring a median follow-up of 15 months (interquartile range (IQR) 11–20), 19 (16.1%) MACEs occurred; both stress myocardial blood flow (sMBF) (p<0.001) and coronary flow reserve (CFR) (p<0.001) were significantly lower in the MACE group. Optimal thresholds of sMBF<3.16 and CFR<2.52 were extracted from the ROC curves, and both impaired sMBF (HR: 15.08; 95% CI 2.95–77.07; p=0.001) and CFR (HR: 6.51; 95% CI 1.43–29.65; p=0.01) were identified as prognostic factors for MACEs. Only sMBF<3.16 (HR: 11.20; 95% CI 2.04–61.41; p=0.005) remained a robust predictor when sMBF and CFR were integrated considered. Compared with CFR, sMBF provides better prognostic model discrimination and reclassification ability (C-index improvement = 0.06, p=0.02; net reclassification improvement (NRI) = 0.19; integrated discrimination improvement (IDI) = 0.10).ConclusionThe preliminary results demonstrated that quantitative analysis on CZT SPECT provides prognostic value for INOCA patients, which may allow the stratification for early prevention and intervention.

Advanced Lung Cancer Inflammation Index for Predicting Prognostic Risk for Patients with Acute Coronary Syndrome Undergoing Percutaneous Coronary Intervention.

The decreased advanced lung cancer inflammation index (ALI), defined as body mass index (BMI) * albumin (Alb)/neutrophil-to-lymphocyte ratio (NLR), is an independent prognostic risk factor for overall survival in gastric, lung, and colorectal cancers. This study aimed to investigate the value of ALI in predicting the risk of major adverse cardiovascular events (MACEs) in patients with acute coronary syndrome (ACS). A total of 1624 patients with ACS undergoing percutaneous coronary intervention (PCI) were consecutively enrolled between January 2016 and December 2018. Follow-up data were collected at 1, 3, 6, and 12 months and annually thereafter. The primary endpoints were MACEs. All endpoints were defined as all-cause mortality, recurrent angina pectoris, restenosis/intra stent thrombosis, stroke, heart failure, and all-cause bleeding. The MACEs group and non-MACEs group showed significant differences in patients with age >65 years (28 [50.0%] vs 319 [23.7%]), history of heart failure (16 [28.6%] vs 127 [9.4%]), history of ischemic stroke (14 [25.0%] vs 186 [13.8%]), history of cardiogenic shock (6 [10.71%] vs 16 [1.19%]), left ventricular ejection fraction <40% (8 [14.29%] vs 33 [2.46%]), and ALI <343.96 (44 [78.65%] vs 680 [50.60%]) (all p<0.001). The optimal cut-off value for ALI was 334.96. The area under the curve (AUC) of the 1-, 2-, 3-, and 5-year was 0.560, 0.577, 0.665, and 0.749, respectively. The survival rate was significantly lower in the low ALI group than in the high ALI group (log-rank p<0.001). Low ALI was an independent risk factor for the long-term prognosis of patients with ACS after PCI, univariate HR: 3.671, 95% CI: 1.938-6.953, p<0.001; multivariate HR: 3.009, 95% CI: 1.57-5.769, p=0.001. ALI score less than 334.96 is an independent prognostic risk factor for patients with ACS undergoing PCI and may be a novel marker for clinical practice.

Association of GNRI, NLR, and FT3 with the Clinical Prognosis of Older Patients with Heart Failure.

We investigated the relationship between heart failure and malnutrition, inflammation, and thyroid function and evaluated the predictive potential of these markers for major adverse cardiovascular events (MACEs).This study included 454 patients aged over 65 years with heart failure as the main diagnosis for 18 months follow-up. The nutritional and inflammatory status were assessed using the geriatric nutritional risk index (GNRI) and neutrophil-to-lymphocyte ratio (NLR), respectively. Free triiodothyronine (FT3) in thyroid hormone was divided into low, medium, and high FT3. Older patients were divided into two groups according to whether they had endpoint events. Differences in nutrition, inflammation, and thyroid hormone were compared between the two groups. The prognostic value of the combination of GNRI, NLR, and FT3 was analyzed.Older patients in the MACEs (+) group had lower levels of GNRI and FT3 and higher NLR than those in the MACEs (-) group. Low GNRI and FT3 and high NLR were associated with MACEs (P < 0.05). Multivariate Cox regression analysis revealed that low FT3 was an independent predictor of MACEs (P < 0.05). Regardless of how the LVEF changed, when patients had low GNRI and FT3 and high NLR risk factors, the risk of developing MACEs significantly increased. The addition of GNRI, NLR, and FT3 to the basic model significantly increased the predictability of MACEs in patients.Low GNRI and FT3 and high NLR were associated with MACEs. The combination of GNRI, NLR, and FT3 increased the predictive value of MACEs in older patients with heart failure.