Predictor Of Major Adverse Cardiac Events Research Articles

Spherization indices measured by resting SPECT improve risk stratification in patients with ischemia with non-obstructive coronary artery disease (INOCA)

BackgroundThe prevalence of ischemia with non-obstructive coronary artery disease (INOCA) is substantial, but its risk stratification has been suboptimal. Resting SPECT myocardial perfusion imaging (MPI) could provide useful heart information including spherical indices. We aimed to evaluate the prognostic value of spherical indices in individuals with INOCA.ResultsDuring a median follow-up of 47.2 ± 20.8 months, 49 (17.2%) patients experienced major adverse cardiac events (MACE). Compared to those without MACE, those with MACE had a higher shape index (SI) (0.60 ± 0.07 vs. 0.58 ± 0.06; P = 0.028) and a lower E2 (eccentricity index calculated by the QPS) (0.81 ± 0.05 vs. 0.83 ± 0.04; P = 0.019). MACE event-free survival analysis revealed significant differences in the SI and E2 among all patients (all log-rank P < 0.01). Multivariate Cox analysis showed abnormal SI (HR: 2.73, 95% CI 1.44–5.18, P = 0.002) and E2 (HR: 1.94, 95% CI 1.08–3.48, P = 0.026) were both independent predictors for MACE when they were put into the same model, respectively. The incorporation of the SI into the baseline model demonstrated a significant improvement in the predictive accuracy for MACEs (P = 0.026), whereas E2 did not exhibit a similar improvement (P > 0.05).ConclusionFor patients with INOCA, spherical indices (especially the SI) were associated with long-term MACE, which could be a preferable indicator for risk stratification and prognostic prediction.

Long-term prognosis and prognostic factors after primary prophylactic implantable cardioverter-defibrillator therapy

BackgroundLittle is known regarding which patients with ischemic cardiomyopathy (ICM) should be considered for prophylactic therapies, such as an implantable cardioverter-defibrillator (ICD), in the primary percutaneous intervention era. The aim of this study was to investigate the influence of non-sustained ventricular tachycardia (NSVT) on major adverse cardiac events (MACE) in heart failure with reduced ejection fraction (HFrEF) patients. MethodsWe retrospectively analyzed patients of ICM and non-ICM who underwent ICD implantation at our institute from October 2006 to August 2020. MACE were defined as composite outcome of cardiovascular death, heart failure hospitalization, and appropriate ICD therapies. ResultsA total of 167 patients were enrolled [male, 138 (83 %); age, 62.1 ± 11.7 years; left ventricular ejection fraction, 23.5 ± 6.1 %; left ventricular diastolic diameter, 67.4 ± 9.0 mm; atrial fibrillation, 47 (28 %); NSVT, 124 (74 %); use of class III antiarrhythmic drugs, 55 (33 %); ischemic cardiomyopathy, 56 (34 %); cardiac resynchronization therapy, 73 (44 %)]. The median follow-up duration was 61 months. MACE occurred with 71 patients (43 %). When comparing baseline characteristics of the patients, left ventricular ejection fraction (p = 0.02) and atrial fibrillation (p = 0.04) were significantly associated with MACE. The multivariable Cox analysis for the target variable MACE identified atrial fibrillation (hazard ratio 2.00; 95 % confidence index 1.18–3.37; p = 0.01) as an independent predictor for MACE. ConclusionsPrior NSVT before ICD implantation was not an independent predictor of future MACE in patients with HFrEF with primary prophylactic ICD. In contrast, atrial fibrillation was associated with worse prognosis. To predict the prognosis of patients with primary prophylactic ICD, these factors should be assessed as comprehensive risk stratification factors for MACE.

Artificial intelligence of arterial Doppler waveforms to predict major adverse outcomes among patients with diabetes mellitus

ObjectivePatients with diabetes mellitus (DM) are at increased risk for peripheral artery disease (PAD) and its complications. Arterial calcification and non-compressibility may limit test interpretation in this population. Developing tools capable of identifying PAD and predicting major adverse cardiac event (MACE) and limb event (MALE) outcomes among patients with DM would be clinically useful. Deep neural network analysis of resting Doppler arterial waveforms was used to detect PAD among patients with DM and to identify those at greatest risk for major adverse outcome events. MethodsConsecutive patients with DM undergoing lower limb arterial testing (April 1, 2015-December 30, 2020) were randomly allocated to training, validation, and testing subsets (60%, 20%, and 20%). Deep neural networks were trained on resting posterior tibial arterial Doppler waveforms to predict all-cause mortality, MACE, and MALE at 5 years using quartiles based on the distribution of the prediction score. ResultsAmong 11,384 total patients, 4211 patients with DM met study criteria (mean age, 68.6 ± 11.9 years; 32.0% female). After allocating the training and validation subsets, the final test subset included 856 patients. During follow-up, there were 262 deaths, 319 MACE, and 99 MALE. Patients in the upper quartile of prediction based on deep neural network analysis of the posterior tibial artery waveform provided independent prediction of death (hazard ratio [HR], 3.58; 95% confidence interval [CI], 2.31-5.56), MACE (HR, 2.06; 95% CI, 1.49-2.91), and MALE (HR, 13.50; 95% CI, 5.83-31.27). ConclusionsAn artificial intelligence enabled analysis of a resting Doppler arterial waveform permits identification of major adverse outcomes including all-cause mortality, MACE, and MALE among patients with DM.

Fractal Analysis of Left Ventricular Trabeculae in Patients with End-Stage Renal Disease: A Random Survival Tree Analysis.

The complexity of left ventricular (LV) trabeculae is related to the prognosis of several cardiovascular diseases. To evaluate the prognostic value of LV trabecular complexity in patients with end-stage renal disease (ESRD). Prospective outcome study. 207 participants on maintenance dialysis, divided into development (160 patients from 2 centers) and external validation (47 patients from a third center) cohorts, and 72 healthy controls. 3.0T, steady-state free precession (SSFP) and modified Look-Locker imaging sequences. All participants had their trabecular complexity quantified by fractal analysis using cine SSFP images. Patients were followed up every 2 weeks until April 2023, or endpoint events happened. Random Forest (RF) and Cox regression models including age, diabetes, LV mass index, mean basal fractal dimension (FD), and left atrial volume index, were developed to predict major adverse cardiac events (MACE). Patients were divided into low- and high-risk groups based on scores derived from the RF model and survival compared. Receiver operating characteristic curve analysis; Kaplan-Meier survival analysis with log rank tests; Harrel's C-index to assess model performance. A P value <0.05 was considered statistically significant. Fifty-five patients (26.57%) experienced MACE during a median follow-up time of 21.83 months. An increased mean basal FD (≥1.324) was associated with a significantly higher risk of MACE. The RF model (C-index: 0.81) had significantly better discrimination than the Cox regression model (C-index: 0.74). Participants of the external validation dataset classified into the high-risk group had a hazard of experiencing MACE increased by 12.29 times compared to those in the low-risk group. LV basal FD was an independent predictor for MACE in patients with ESRD. Reliable risk stratification models could be generated based on LV basal FD and other MRI variables using RF analysis. 2 TECHNICAL EFFICACY: Stage 2.

Clinical characteristics and prognosis of patients with hypertrophic cardiomyopathy and heart failure with preserved ejection fraction.

Whether heart failure with preserved ejection fraction (HFpEF) is associated with an increased risk of developing systolic dysfunction and a poor prognosis in hypertrophic cardiomyopathy (HCM) patients is unknown. We aimed to assess risk factors for the development of end-stage (ES) heart failure (HF) (ejection fraction < 50%) and compare the prognosis of different HF phenotypes. This retrospective study was conducted on patients with HCM in China between January 2009 and February 2023. Patients were stratified into three different groups: HCM-non-HF, HCM-HFpEF and HCM-heart failure with reduced ejection fraction (HCM-HFrEF). The primary outcome was a composite of major adverse cardiac events (MACEs), including all-cause deaths, HF hospitalization, sudden cardiac death and ventricular tachycardia. Of 3,620 HCM patients enrolled, 1,553 (42.9%) had non-HF, 1,666 (46.0%) had HFpEF, and 579 patients (11.1%) had HFrEF at baseline. During the median follow-up period of 4.0 years (IQR 1.4-9.4 years), patients with HCM-HFpEF exhibited a higher incidence of ES-HF than those with HCM-non-HF (12.4% vs. 2.7%, P < 0.001). HFpEF was an independent risk factor for ES-HF development (HR 3.84, 2.54-5.80, P < 0.001). MACEs occurred in 26.9% with a higher incidence in HCM-HFpEF than HCM-non-HF (36.6% vs 12.2%, P < 0.001). HFpEF was an independent predictor of MACEs (HR 2.13, 1.75-2.59, P < 0.001). HFpEF is common in HCM. Compared to non-HF, it increases the risk of LVEF decline and poor prognosis. It may aid in risk stratification and need close echocardiography follow-up.

Optimized gated a SPECT-derived myocardial salvage index: its prognostic significance in predicting major adverse cardiac events following acute myocardial infarction percussion.

Estimate myocardial salvage index (MSI) using a single-gated Single-Photon Emission Computed Tomography (SPECT) myocardial perfusion imaging (GSMPI) early after percutaneous coronary intervention (PCI) in patients with acute myocardial infarction (AMI) and compare its predictive value with the traditional method especially for post-PCI left ventricular ejection fraction (LVEF) improvement and major adverse cardiac events (MACEs). GSMPI was performed in 62 patients with AMI early after PCI (3-10days). The MSI and the conventional parameters were obtained, including total perfusion deficit, LVEF, peak ejection rate (PER), and peak filling rate (PFR). The new calculation method (scoring evaluation method means the extent of abnormality is the percentage of the total scores of abnormal segments divided by the sum of the maximum scores of all myocardial segments using 4-point and 5-point scale semi-quantitative scoring method) and the reference method (number evaluation method means the extent of abnormality is the percentage of the number of abnormal segments divided by the total number of myocardial segments) were applied to acquire the MSI. We compared the predictive ability of the 2 methods based on the area under the receiver operating characteristic curve for LVEF improvement 6months after PCI using MSI. The Kaplan-Meier method was used for depicting survival curves for predicting MACEs by the 2 methods. Cox proportional-hazards regression was applied to confirm the independent predictors of MACEs. The MSI obtained by the new method indicated stronger prognostic significance in LVEF improvement [area under the curve (AUC): 0.793, 95% confidence interval (CI) 0.620-0.912, P < .001] compared with the reference method (AUC: 0.634, 95%CI 0.452-0.792, P = .187). Delong's test revealed a statistically significant difference in AUCs between the 2 methods (P < .05, 95%CI 0.003-0.316). The diagnostic value of the scoring evaluation method was higher than that of the number evaluation method. The Cox prevalence of MACEs was substantially higher in the < median MSI group than in the ≥ median MSI group (hazard ratio: 0.172; 95% CI 0.041-0.724; P < .05] using the new method, whereas no considerable differences were observed between the 2 groups using the reference method (P = .12). Further, the multivariate Cox regression analysis revealed that MSI was an independent indicator for predicting MACEs (P < .05). The MSI obtained from a simple GSMPI early after PCI, using the scoring evaluation method, was a reliable prognostic indicator for predicting LVEF improvement and MACEs in AMI. It remarkably improved the prognostic value compared with the previous reference methods.

Left Ventricular-Arterial Coupling as an Independent Predictor of Adverse Events in Young Patients with ST Elevation Myocardial Infarction-A 3D Echocardiographic Study.

Left ventricular-arterial coupling (VAC) is a key determinant of global cardiovascular performance, calculated as the ratio between arterial elastance (EA) and left ventricular end-systolic elastance (EES). Over the years, acute myocardial infarction (STEMI) has remained an important cause of morbidity and mortality worldwide. Although, until recently, it was considered a disease occurring mostly in older patients, its prevalence in the young population is continuously rising. In this study, we aimed to investigate the role of 3D VAC and its derived indices in predicting adverse outcomes in young patients with STEMI. We prospectively enrolled 84 young patients (18-51 years) with STEMI who underwent primary PCI and 28 healthy age and sex-matched controls. A 3D echocardiography was used for non-invasive measurements of end-systolic elastance (EES), arterial elastance (EA), and VAC (EA/EES). The occurrence of major adverse cardiac events (MACE) was assessed one year after the index STEMI. Out of 84 patients, 15.4% had adverse events at 12 months follow-up. Patients were divided into two groups according to the presence or absence of MACE. There were no significant differences in arterial elastance between the two groups. EA was higher in the MACE group but without statistical significance (2.65 vs. 2.33; p = 0.09). EES was significantly lower in the MACE group (1.25 ± 0.34 vs. 1.91 ± 0.56. p < 0.0001) and VAC was higher (2.2 ± 0.62 vs. 1.24 ± 0.29, p < 0.0001). ROC analysis showed that VAC has a better predictive value for MACE (AUC 0.927) compared with EA or EEA but also compared with a classical determinant of LV function (LVEF and LVGLS). A VAC value over 1.71 predicts unfavourable outcome with 83.3% sensitivity and 97.1% specificity. In both univariate and multivariate COX regression analysis, VAC remained an independent predictor for MACE and demonstrated incremental prognostic value over LVEF and LVGLS in the proposed statistical models. In conclusion, 3D VAC is an independent predictor of adverse events in young patients with STEMI at a 12 month follow-ups and could be used for a more accurate risk stratification in the acute phase.

Prediction of major adverse cardiac events in the emergency department using an artificial neural network with a systematic grid search

BackgroundThe aim of our research was to design and evaluate an Artificial Neural Network (ANN) model using a systemic grid search for the early prediction of major adverse cardiac events (MACE) among patients presenting to the triage of an emergency department.MethodsThis is a single-center, cross-sectional study using electronic health records from January 2017 to December 2020. The research population consists of adults coming to our emergency department triage at Aga Khan University Hospital. The MACE during hospitalization was the main outcome. To enhance the architecture of an ANN using triage data, we used a systematic grid search strategy. Four hidden ANN layers were used, followed by an output layer. Following each hidden layer was back normalization and a dropout layer. MACE was predicted using three binary classifiers: ANN, Random Forests (RF), and logistic regression (LR). The overall accuracy, sensitivity, specificity, precision, and recall of these models were examined. Each model was evaluated using the receiver operating characteristic curve (ROC) and an F1-score with a 95% confidence interval.ResultsA total of 97,333 emergency department visits were recorded during the study period, with 33% of patients having cardiovascular symptoms. The mean age was 54.08 (19.18) years old. The MACE was observed in 23,052 (23.7%) of the patients, in-hospital (up to 30 days) mortality in 10,888 (11.2%) patients, and cardiac arrest in 5483 (5.6%) patients. The data used for training and validation were 77,866 and 19,467 in an 80:20 ratio, respectively. The AUC score for MACE with ANN was 0.97, which was greater than RF (0.96) and LR (0.96). Similarly, the precision-recall curve for MACE utilizing ANN was greater (0.94 vs. 0.93 for RF and 0.93 for LR). The sensitivity for MACE prediction using ANN, RF, and LR classifiers was 99.3%, 99.4%, and 99.2%, respectively, with the specificities being 94.5%, 94.2%, and 94.2%, respectively.ConclusionWhen triage data is used to predict MACE, death, and cardiac arrest, ANN with systemic grid search gives precise and valid outcomes and will benefit in predicting MACE in emergency rooms with limited resources that have to deal with a substantial number of patients.

Prognostic value of mid-term cardiovascular magnetic resonance follow-up in patients with non-ischemic dilated cardiomyopathy: a prospective cohort study

BackgroundThe prognostic value of follow-up cardiovascular magnetic resonance (CMR) in dilated cardiomyopathy (DCM) patients is unclear. We aimed to investigate the prognostic value of cardiac function, structure, and tissue characteristics at mid-term CMR follow-up. MethodsThe study population was a prospectively enrolled cohort of DCM patients who underwent guideline-directed medical therapy with baseline and follow-up CMR, which included measurement of biventricular volume and ejection fraction, late gadolinium enhancement, native T1, native T2, and extracellular volume. During follow-up, major adverse cardiac events (MACE) were defined as a composite endpoint of cardiovascular death, heart transplantation, and heart-failure readmission. ResultsAmong 235 DCM patients (median CMR interval: 15.3 months; interquartile range: 12.5–19.2 months), 54 (23.0%) experienced MACE during follow-up (median: 31.2 months; interquartile range: 20.8–50.0 months). In multivariable Cox regression, follow-up CMR models showed significantly superior predictive value than baseline CMR models. Stepwise multivariate Cox regression showed that follow-up left ventricular ejection fraction (LVEF; hazard ratio [HR], 0.93; 95% confidence interval [CI], 0.91–0.96; p < 0.001) and native T1 (HR, 1.01; 95% CI, 1.00–1.01; p = 0.030) were independent predictors of MACE. Follow-up LVEF ≥ 40% or stable LVEF < 40% with T1 ≤ 1273 ms indicated low risk (annual event rate < 4%), while stable LVEF < 40% and T1 > 1273 ms or LVEF < 40% with deterioration indicated high risk (annual event rate > 15%). ConclusionsFollow-up CMR provided better risk stratification than baseline CMR. Improvements in the LVEF and T1 mapping are associated with a lower risk of MACE.

Machine learning for major adverse cardiac events prediction in patients with acute coronary syndrome: Results from ADDICT-ICCU study

Machine learning for major adverse cardiac events prediction in patients with acute coronary syndrome: Results from ADDICT-ICCU study

A pilot study of S100A4, S100A8/A9, and S100A12 in dilated cardiomyopathy: novel biomarkers for diagnosis or prognosis?

Circulating biomarkers can provide important information for the diagnosis and prognosis of dilated cardiomyopathy (DCM). We explored novel biomarkers for the diagnosis and prognosis of DCM to improve clinical decision-making. A total of 238 DCM patients and 65 control were consecutively enrolled at Zhongshan Hospital between January 2017 and January 2019. In the screening set, four DCM patients and four controls underwent measurements of serum proteomic analysis. Seventy-six differentially expressed circulating proteins were screened by data-independent acquisition proteomics, and three of these proteins (S100A4, S100A8/A9, and S100A12) were validated by multiple-reaction monitoring-mass spectrometry. In the validation set, subsequently, a total of 234 DCM patients and 61 control subjects were evaluated by enzyme-linked immunosorbent assay. Circulating S100A4, S100A8/A9, and S100A12 were significantly increased in DCM patients (P<0.001). These three proteins were significant positively correlated with other parameters, such as Lg (NT-proBNP), IL-1β, TGF-β, CRP, left ventricular end-diastolic diameter, and left ventricular end-systolic diameter, whereas they were negatively correlated with left ventricular ejection fraction, respectively (P<0.05). The receiver operator characteristic curve showed the combination of S100A4, S100A8/A9, and S100A12 [area under curve (AUC) 0.88, 95% confidence interval (CI) 0.84-0.93] was better than single S100A4 (AUC 0.74, 95% CI 0.68-0.81), S100A8/A9 (AUC 0.82, 95% CI 0.77-0.88), or S100A12 (AUC 0.80, 95% CI 0.72-0.88) in the diagnosis of DCM (P<0.01). After a median follow-up period of 33.5months, 110 patients (47.01%) experienced major adverse cardiac events (MACEs), including 46 who had cardiac deaths and 64 who had heart failure rehospitalizations. Kaplan-Meier analysis indicated that the DCM patients with ≥75th percentile level of S100A4 had a significantly higher incidence of MACEs than those with <75th percentile level of S100A4 (61.40% vs. 42.37%, P<0.05). There were no significant differences of MACE rate among DCM patients with different concentrations of S100A8/A9 and S100A12 (P>0.05). Cox proportional hazards regression analysis revealed that S100A4 [≥75th percentile vs. <75th percentile: hazard ratio (HR) 1.65; 95% CI 1.11-2.45] remained significant independent predictors for MACEs (P<0.05); however, S100A8/A9 and S100A12 were not independent factors for predicting MACE (P≥0.05). S100A4, S100A8/A9, and S100A12 may be additional diagnostic tools for human DCM recognition, and the combination of these three indicators helped to improve the accuracy of a single index to diagnose DCM. Additionally, S100A4 was identified as a significant predictor of prognosis in patients with DCM.

Clinical variables associated with major adverse cardiac events following radical cystectomy.

The objective of this study is to investigate the association between major adverse cardiac events (MACE) and clinical factors of patients undergoing radical cystectomy (RC) for bladder cancer. A retrospective analysis using the 2015-2020 National Surgical Quality Improvement Program database was performed on patients who underwent RC for bladder cancer. MACE was defined as any report of cerebrovascular accident, myocardial infarction, or thromboembolic events (pulmonary embolism or deep vein thrombosis). A multivariable-adjusted logistic regression was conducted to identify clinical predictors of postoperative MACE. A total of 10 308 (84.2%) patients underwent RC with incontinent urinary diversion (iUD), and 1938 (15.8%) underwent RC with continent urinary diversion (cUD). A total of 629 (5.1%) patients recorded a MACE, and on the multivariable-adjusted logistic regression, it was shown that MACE was significantly associated with increased age (OR = 1.035, 95% CI: 1.024-1.046, p < 0.001), obesity (OR = 1.583, 95% CI: 1.266-1.978, p < 0.001), current smokers (OR = 1.386, 95% CI: 1.130-1.700, p = 0.002), congestive heart failure before surgery (OR = 1.991, 95% CI: 1.016-3.900; p = 0.045), hypertension (OR = 1.209, 95% CI: 1.016-1.453, p = 0.043), and increase the surgical time (per 10min increase, OR = 1.010, 95% CI: 1.003-1.017, p = 0.009). We also report that increased age, obesity, and patients undergoing cUD (OR = 1.368, 95% CI: 1.040-1.798; p = 0.025) are associated with thromboembolic events. By considering the preoperative characteristics of patients, including age, obesity, smoking, congestive heart failure, and hypertension status, urologists may be able to decrease the incidence of MACE in patients undergoing RC. Urologists should aim for lower operative times as this was associated with a decreased risk of thromboembolic events.

Serum cystatin C predicts the risk of non-ST-elevation acute coronary syndrome

ObjectiveInflammation markers have been proposed as the predictors of adverse cardiac events in patients with non-ST-elevation acute coronary syndrome (NSTE-ACS). This study aimed to investigate prognostic value of serum cystatin C (Cys-C) for NSTE-ACS patients.MethodsCys-C, neutrophil to lymphocyte ratio (NLR) and high-sensitivity C-reactive protein (hsCRP) were examined in 212 NSTE-ACS patients and 60 controls. Global registry of acute coronary events (GRACE) score and major adverse cardiac events (MACE) in NSTE-ACS patients were recorded.ResultsCys-C level in the serum was significantly higher in NSTE-ACS patients than in control, and was positively correlated with hsCRP level and NLR as well as GRACE score at admission and 6 months after discharge in NSTE-ACS patients. Serum Cys-C level was identified as a new predictor of MACE.ConclusionSerum Cys-C level may be an inflammation biomarker in patients with NSTE-ACS, and could be used as an independent predictor of MACE.

Enhancing predictive accuracy of the cardiac risk score in open abdominal aortic surgery: the role of left ventricular wall motion abnormalities.

Open abdominal aortic surgery carries many potential complications, with cardiac adverse events being the most significant concern. The Vascular Study Group Cardiac Risk Index (VSG-CRI) is a commonly used tool for predicting severe cardiac complications and guiding clinical decision-making. However, despite the potential prognostic significance of left ventricular wall motion abnormalities (LVWMAs) and reduced LV ejection fraction (LVEF) for adverse outcomes, the VSG-CRI model has not accounted for them. Hence, the main objective of this study was to analyze the added value of LV wall motion on the discriminatory power of the modified VSG-CRI in predicting major postoperative cardiac complications. A prospective study was conducted involving 271 patients who underwent elective abdominal aortic surgery between 2019 and 2021. VSG-CRI scores were calculated, and preoperative transthoracic echocardiography was conducted for all patients. Subsequently, a modified version of the VSG-CRI, accounting for reduced LVEF and LVWMAs, was developed and incorporated into the dataset. The postoperative incidence of the composite endpoint of major adverse cardiac events (MACEs), including myocardial infarction, clinically relevant arrhythmias treated with medicaments or by cardioversion, or congestive heart failure, was assessed at discharge from the index hospitalization, with adjudicators blinded to events. The predictive accuracy of both the original and modified VSG-CRI was assessed using C-Statistics. In total, 61 patients (22.5%) experienced MACEs. Among these patients, a significantly higher proportion had preoperative LVWMAs compared to those without (62.3% vs. 32.9%, p < 0.001). Multivariable regression analysis revealed the VSG-CRI [odds ratio (OR) 1.46, 95% confidence interval (CI) 1.21-1.77; p < 0.001] and LVWMA (OR 2.76; 95% CI 1.46-5.23; p = 0.002) as independent predictors of MACEs. Additionally, the modified VSG-CRI model demonstrated superior predictability compared to the baseline VSG-CRI model, suggesting an improved predictive performance for anticipating MACEs following abdominal aortic surgery [area under the curve (AUC) 0.74; 95% CI 0.68-0.81 vs. AUC 0.70; 95% CI 0.63-0.77; respectively]. The findings of this study suggest that incorporating preoperative echocardiography can enhance the predictive accuracy of the VSG-CRI for predicting MACEs after open abdominal aortic surgery. Before its implementation in clinical settings, external validation is necessary to confirm the generalizability of this newly developed predictive model across different populations.

Predictive value of type D personality for cardiac events in Chinese patients with acute myocardial infarction

BackgroundOur study aimed to investigate the association between type D personality and adverse cardiac events in chinese patients after acute myocardial infarction (AMI).MethodsPatients with AMI admitted to cardiac care unit (CCU) of China-Japan Friendship Hospital, Beijing, China between January 2016 and December 2017 were enrolled. 257 patients completed psychological questionnaires at enrollment. Type D personality was assessed with 14-item Type D Scale-14 (DS14). Anxiety and depression were quantified using Hospital Anxiety and Depression Scale (HADS). Multivariable logistic regression analysis was used to determine the independent predictors of in-hospital major adverse cardiac events (MACEs), while cox regression analysis was used to evaluate post-discharge endpoints.Results54 patients (21%) were classified as Type D personality defined by the combination of a negative affectivity (NA) score ≥ 10 and a social inhibition (SI) score ≥ 10 on the DS14. Patients with Type D personality displayed significantly higher scores of anxiety (7.4 ± 3.1 vs. 4.2 ± 3.1, p < .001) and depression (7.2 ± 3.8 vs. 4.0 ± 3.4, p < .001). AMI patients with Type D personality had higher prevalence rates of anxiety (χ2 = 30.095, P < .001) and depression (χ2 = 27.082, P < .001). Type D group also displayed a significantly higher level of blood lipoprotein(a) (177.2 ± 200.7 vs. 118.1 ± 255.7 mg/L, P = .048). The incidence of in-hospital MACEs was higher in type D than in non-Type D patients (24.1% vs. 11.3%, χ2 = 5.751, P = .026). Multivariable logistic regression showed three significant independent predictors of in-hospital MACEs: age [odds ratio(OR) = 1.055; 95%CI 1.016–1.095, p = .004], type-D personality(OR 3.332; 95% CI 1.149–9.661, p = .014) and killip classification(OR 2.275, 95% CI 1.506–3.437, p < .001). The average follow-up time was 31 (23-37.5) months. Type D patients had higher incidences of post-discharge events(23.1% vs. 11.5%, p = .032). In the analysis of post-discharge events by Cox regression, χ2 of the Cox regression equation was 16.795 (P = .032). Smoking (HR 2.602; 95% CI1.266–5.347, p = .009) and type-D personality (HR 2.265; 95%CI 1.028–4.988, p = .042) were independent predictors of long-term cardiac events. Kaplan–Meier curves showed significant difference in event-free survival between type D and non-type D group (p = .043).ConclusionsType D personality is an independent predictor of in-hospital and post-discharge cardiac events after AMI in Chinese patients.

Retrospective Multicenter Analysis of Intravascular Lithotripsy Use During Calcified Left Main Coronary Artery Percutaneous Coronary Interventions

BackgroundIntravascular lithotripsy (IVL) safely and effectively modifies calcified coronary lesions during percutaneous coronary interventions (PCI). Data regarding its utility in modifying calcified left main coronary artery (LMCA) disease are limited. This study aimed to evaluate short-term outcomes of IVL-assisted LMCA PCI. MethodsThis retrospective multicenter all-comers study analyzed patients who underwent intravascular imaging-guided, IVL-assisted PCI for calcified LMCA disease. Clinical and procedural characteristics were obtained, including intravascular imaging measurements. Technical success was defined as successful stent deployment with <30% residual diameter stenosis. Major adverse cardiac events (MACE) was a composite of all-cause death, myocardial infarction, and target vessel revascularization evaluated immediately postprocedure and at 30-day follow-up. ResultsAmong 184 patients treated at 7 centers from 2019-2023, IVL-assisted LMCA PCI achieved 99.4% technical success. Calcium fracture was identified in 136/165 cases (82.4%) on post-IVL imaging. Pretreatment minimal luminal area increased significantly compared to post-PCI minimal stent area (MSA) (4.1 ± 1.3 to 9.3 ± 2.5 mm2, respectively; P < .001). There was a direct correlation between IVL balloon size and the final MSA (P = .002). In-hospital MACE was 4.4% and 30-day MACE was 8.8%. In multivariate logistic regression, presentation with troponin-positive myocardial infarction was the sole predictor of 30-day MACE. ConclusionsIVL-assisted PCI for calcified LMCA lesions was safe and resulted in high technical success rates, confirming its utility as an effective treatment in this challenging lesion subset.

High mannose correlates with surrogate indexes of insulin resistance and predicts cardiovascular events independently of glycaemic status and traditional risk factors

Abstract Background Plasma mannose, an emerging marker of insulin resistance (IR), is independently associated with coronary artery disease and cardiovascular (CV) events, not only in patients with altered glycaemic status, but also among those with normal glucose tolerance (NGT) [1, 2]. Whether mannose is a predictor of future CV events is not known. Purpose To investigate the association of mannose with surrogate indexes of IR as well as with long-term prognosis in patients with and without dysglycaemia. Methods Fasting plasma mannose was measured by high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS-MS) in 696 cases with a first myocardial infarction (MI) and 707 controls matched for age, gender and living area from the PAROKRANK study [3]. Subjects free of known diabetes were further categorized as having either NGT (n=1045) or newly detected dysglycaemia (i.e., impaired glucose tolerance or type 2 diabetes; n=358) according to the results of an oral glucose tolerance test (OGTT). Surrogate indexes of IR and insulin secretion were calculated using glucose, insulin and C-peptide levels measured at 0, 30 and 120 minutes during the OGTT. The relationship between plasma mannose and different indexes was explored by fitting univariate and multivariate linear regression models. Kaplan-Meier functions were used to estimate crude survival across mannose quartiles. Unadjusted and adjusted Cox proportional hazards models were used to investigate the prognostic capacity of mannose, categorized as high (top quartile) vs low (lowest three quartiles), in relation to major adverse cardiac events (MACE) defined as CV death, MI and stroke during 10 years of follow-up. Secondary outcomes were single components of MACE and all-cause mortality. Results Mannose levels were associated with indexes of IR independently of BMI and other covariates in both the NGT and dysglycaemia subgroups. There was no difference in crude MACE-free survival between subjects with high and low mannose (log-rank p=0.10; Figure 1). However, high mannose remained as the only predictor of MACE in the overall population (Hazard ratio (HR): 1.58 (1.10-2.27); p=0.014) after multiple adjustments (Figure 2). This association was independent of the presence of dysglycaemia (interaction p between mannose category and dysglycaemia group=0.94) and IR expressed as HOMA-IR. High mannose also predicted MI, independently of the presence of a first MI (HR: 1.62 (1.00-2.62); p=0.050), while there was no significant association with the other secondary outcomes. Conclusions In a case-control setting of first MI, high mannose was the only significant predictor of future CV events, independently of traditional CV risk factors including a previous MI, glycaemic state and IR. Our findings expand the knowledge indicating that mannose might be used as a clinical tool for CV risk stratification.

STANLEy score: a new predictive model of 3-year major adverse cardiac events following "Full Metal Jacket" using new-generation drug-eluting stents

Abstract Introduction Percutaneous Coronary Intervention (PCI) using a "Full Metal Jacket" (FMJ) procedure (≥60 mm of continuous stent length) is often required to treat very long lesions, but its clinical efficacy and safety using contemporary drug-eluting stents (DES) remains to be determined. Objectives To identify predictors of major adverse cardiac events (MACE) associated with FMJ using new-generation DES. We sought to develop a simple model capable of accurately predict 3-year MACE following FMJ PCI. Methods A retrospective single-centre analysis of consecutive FMJ PCI performed between January 2015 and December 2018. Exclusion criteria were use of non-third generation DES, unsuccessful procedure and loss to follow-up. The primary endpoint was a composite of all-cause death, myocardial infarction, and target vessel revascularization. Demographic, clinical, angiographic, and procedural variables were evaluated. Logistic regression analysis was performed to determine independent predictors of outcome. Based on the results, a weighted scoring system was developed. Results The derivation cohort included 162 patients, mean age 65.9 ± 11.1 years, 83% male. The mean stent length was 73.8 ± 12.3 mm (range 60 to 116 mm), and the average number of stents was 2.74 ± 0.74 (range 2 to 5). 30-day, 1-year and 3-year MACE were 5.5%, 12.9% and 29.0%, respectively. Multivariate analysis identified diabEtes mellitus (hazard ratio (HR) 5.92; 95% confidence interval (CI) 1.57-11.54; p=0.011), Smoking habits (HR 8.37; 95%CI 3.05-15.55; p=0.001), Acute coronary syndrome (HR 3.51; 95%CI 1.030-8.98; p=0.045), Non-right coronary artery (HR 4.38; 95%CI 1.09-7.68; p=0.038), osTial lesion (HR 10.01; 95%CI 2.91-19.14; p=0.006) and severe caLcification (HR 8.59; 95%CI 2.65-15.72; p=0.001) as independent predictors of 3-year MACE. A composite score based on these 6 variables (STANLEy score) was created, ranging from 0 to 10 (Fig.1). High acuity was verified by ROC curve analysis (AUC 0.941, p &amp;lt;0.001). A score ≤ 3 was associated with a reduced probability (&amp;lt;15%) and a score ≥ 7 with high probability (&amp;gt;90%) of 3-year MACE. Conclusion The STANLEy score is a good predictive model which relies on 6 simple clinical and angiographic characteristics. This score may assist physicians in selecting high-risk patients for closer monitoring or aggressive antithrombotic strategy.Figure 1

Association of admission blood glucose to albumin ratio and clinical outcomes in patients with ST-elevation myocardial infarction undergoing percutaneous coronary intervention

Abstract Background It is unclear whether admission blood glucose to albumin ratio (AAR) predicts clinical adverse outcomes in patients with ST-segment elevation myocardial infarction (STEMI) treated with percutaneous coronary intervention (PCI). Purpose Here, we explored the predictive value of AAR. Methods Patients diagnosed with STEMI undergoing PCI between January 2010 and February 2020 were enrolled. The patients were classified into three groups according to AAR quantiles. In-hospital all-cause mortality was regarded as the primary outcome. Logistic regression, Kaplan-Meier analysis and Cox proportional hazard regression were mainly used to estimate outcomes. Results Among the 3,224 enrolled patients, 130 (3.9%) of them suffered in-hospital all-cause mortality and 181 (5.4%) experienced major adverse cardiac events (MACEs). After the adjustment, multivariate analysis demonstrated that an increase in AAR was associated with the increased risk of in-hospital all-cause mortality (adjusted OR: 2.72, 95% CI: 1.47–5.03, p = 0.001) and MACEs (adjusted OR: 1.91, 95% CI: 1.18–3.10, p = 0.009), as well as for long-term all-cause mortality (adjusted HR: 1.64, 95% CI: 1.19–2.28, p = 0.003) and MACEs (adjusted HR: 1.58, 95% CI: 1.16–2.14, p= 0.003). ROC analysis indicated that AAR could accurately predict in-hospital all-cause mortality (AUC = 0.718, 95% CI: 0.675–0.761) and MACEs (AUC = 0.672, 95% CI: 0.631–0.712). Conclusions AAR is a novel and convenient independent predictor of all-cause mortality and MACEs both at the in-hospital and long-term levels in STEMI patients receiving PCI.ROC curve of AARKaplan–Meier survival curves

Very long-term prognostic value of clinical SYNTAX score in patients undergoing percutaneous coronary intervention for left main coronary artery disease

Abstract Background Recently, long-term prognostic value of SYNTAX score (SS) has been validated in patients with left main coronary artery disease (LMCA). However, the ability of clinical SYNTAX score (CSS) to predict very long-term outcomes in patients undergoing percutaneous coronary intervention (PCI) for LMCA has not been fully investigated yet. Purpose We aimed to validate the impact of CSS on very long-term outcomes in patients undergoing PCI for LMCA. Methods Between June 2006 and December 2012, 279 patients underwent unprotected LMCA PCI were analyzed. The SS for each patient was calculated by scoring all coronary lesions using SS algorithm. CSS was calculated by multiplying the SS to an ACEF score (age/left ventricular ejection fraction + 1 if serum creatinine&amp;gt;2mg/dL). Major adverse cardiac events (MACEs) were defined as death, non-fatal myocardial infarction, and revascularizations. Mean follow-up duration was 2,529±1664 days. Results The CSS (26.8±11.9 versus 39.9±26.1, p&amp;lt;0.001) as well as SS (23.2±6.9 versus 25.8±7.9, p=0.003) was significantly higher in patients with MACEs. Area under the curve for MACEs (0.672 versus 0.599, p=0.0023) and mortality (0.744 versus 0.626, p&amp;lt;0.0001) of CSS was significantly higher compared with those of SS (Figure 1). The CSS significantly improved the reclassification and the integrated discrimination of patients compared to SS. Log CSS was an independent predictor for MACEs (hazard ratio [HR] 5.37, 95% confidence interval [CI] 1.98 – 14.61; p = 0.006) and mortality (HR 11.69, 95% CI 3.30 – 41.31; p &amp;lt; 0.001). When patients were categorized into 3 groups according to tertiles of CSS (Low CSS ≤ 22, 22 &amp;lt; Mid CSS ≤ 34, High CSS &amp;gt; 34), patients in the highest CSS tertile had significantly higher rates of MACEs (log-rank p&amp;lt;0.001) and mortality (log-rank p&amp;lt;0.001) compared with those in the lower 2 tertiles (Figure 2). The highest CSS tertile was an independent predictor for MACEs (HR 2.33, 95% CI 1.42 – 3.82; p = 0.001) and mortality (HR 5.66, 95% CI 2.20 – 14.57; p &amp;lt; 0.001). Conclusions The CSS is useful to predict very long-term clinical outcome in patients underwent unprotected LMCA PCI.