Long-term All-cause Mortality In Patients Research Articles

Prognostic value of initial electrocardiography in predicting long-term all-cause mortality in COVID-19

BackgroundThe electrocardiography (ECG) has short-term prognostic value in coronavirus disease 2019 (COVID-19), yet its ability to predict long-term mortality is unknown. This study aimed to elucidate the predictive role of initial ECG on long-term all-cause mortality in patients diagnosed with COVID-19. MethodsIn this prospective cohort study, adults with COVID-19 who underwent ECG testing within a 17-hospital health system in Northeast Ohio and Florida between 03/2020-06/2020 were identified. An expert ECG reader analyzed all studies blinded to patient status. The associations of ECG characteristics with long-term all-cause mortality and intensive care unit (ICU) admission were assessed using Cox proportional hazards regression model and multivariable logistic regression models, respectively. Status of long-term mortality was adjudicated on 01/07/2022. ResultsOf 837 patients (median age 65 years, 51% female, 44% Black), 683 (81.6%) were hospitalized, 281 (33.6%) required ICU admission, 67 (8.0%) died in-hospital, and 206 (24.6%) died at final follow-up after a median (IQR) of 21 (9-103) days after ECG. Overall, 179 (20.7%) patients presented with sinus tachycardia, 12 (1.4%) with atrial flutter, and 45 (5.4%) with atrial fibrillation (AF). After multivariable adjustment, sinus tachycardia (E-value for HR=3.09, lower CI=2.2) and AF (E-value for HR=3.13, lower CI=2.03) each independently predicted all-cause mortality. At final follow-up, patients with AF had 64.5% probability of death compared with 20.5% for those with normal sinus rhythm (P<.0001). ConclusionsSinus tachycardia and AF on initial ECG strongly predict long-term all-cause mortality in COVID-19. The ECG can serve as a powerful long-term prognostic tool in COVID-19.

LDL levels and long-term all-cause mortality in patients from nationwide LIPIDOGRAM 2004–2015 cohort studies

Abstract Background Data from multiple randomized clinical trials show that lowering LDL cholesterol with statins is associated with significant reduction of outcomes both in primary and secondary prevention. Despite this some epidemiological studies reported increased risk with lowest LDL levels. The reason for this apparent discrepancy is probably due to unbalanced confounding in epidemiological studies. Purpose To assess long term survival in propensity matched cohort from the LIPIDOGRAM study in patients on statin therapy. Methods Lipidogram studies were carried out in Poland in 2004, 2006 and 2015 in the population representative for patients in primary care setting. The median follow up was 5570 days. Patients were recruited in all 16 administrative regions in Poland and physicians (n&amp;gt;1100) were proportionally distributed to the number of inhabitants in a given administrative region. Each patient was asked to fill the questionnaire on chronic diseases, treatment and lifestyle. Questionnaire was supervised by physician. Patients who were taking statins at the time of enrollment were matched to patients who were not on statin therapy. Groups were matched with regard to age, sex, body mass index, LDL cholesterol, diabetes mellitus, hypertension, previous myocardial infarction, chronic kidney disease, previous ischemic stroke, and atrial fibrillation. Nearest neighbor matching method was employed. Results To 13676 patients (28.9% of the LIPIDOGRAM 2004–2015 cohort) that took statin at the time of enrollment and 13676 patients not on statin treatment were matched. There were no significant differences between two groups with regard to all variables used in matching procedure including LDL cholesterol level. After 15 years of follow up There were 2585 deaths (18.9%) in patients who were treated with statin at the time of enrollment as compared to 2824 (20.6%) in patients with no treatment for dyslipidemia (absolute risk reduction (ARR) of −1.7%, p=0.003) Hazard ratio for mortality in patients who were not treated with statin at the enrollment in this propensity matched cohort was 1.11 (95% CI; 1.05–1.17, p=0.0002). Conclusions Despite similar LDL levels patients treated with statin at the time of enrollment had lower mortality risk as compared to patients not taking statins in long-term follow-up. Lower LDL levels that are not due to statin therapy might imply other underlying conditions that influence prognosis. Therefore, data from epidemiological studies that contradict results of balanced randomized trials due to intrinsic limitations should be approached with skepticism. Funding Acknowledgement Type of funding sources: Private company. Main funding source(s): The present study was funded by an unrestricted educational grant from Valeant. As a supporter of the study, Valeant played no role in the study design, data analysis, data interpretation, or writing of the report. The present study was also supported by Silesian Analytical Laboratories (SLA, Katowice, Poland).

Eosinophil-to-Monocyte Ratio as a Candidate for a Novel Prognostic Marker in Acute Pulmonary Embolism: Is it a Consumptive Mechanism?

Background:The role of eosinophils in thrombotic processes is well known, and the prognostic value of eosinophil to monocyte ratio had been determined in patients with ST elevated myocardial infarction and acute ischemic stroke in recent studies. We aimed to evaluate the impact of the eosinophil-to-monocyte ratio on short- and long-term all-cause mortality in patients with pulmonary embolism, which is another clinical condition closely related to the thrombotic pathway.Methods:In this study, a total of 212 retrospectively evaluated patients with intermediate-high risk and high-risk pulmonary embolism who underwent catheter-directed therapies with ultrasound-assisted thrombolysis or rheolytic thrombectomy (Angiojet©) and intravenous thrombolytic treatment were included.Results:The median Pulmonary Embolism Severity Index score was 105 (86-128; interquartile range: 25-75, min-max: 35-250). The intermediate-high status and high-risk status were noted in 83.5% and 16.5% of the patients, respectively. All of the reperfusion strategies resulted in significant improvements in the measures of pulmonary arterial pressure and right ventricular strain. Death was recorded in 42 (18.6%) patients during the follow-up period (median 1029 days, interquartile range: 651-1358). Multiple Cox regression analysis revealed that a higher pulmonary embolism severity index score (from 85 to 128; hazard ratio = 3.00; 95% CI: 2.11-4.29; P < .001) and a lower eosinophil-to-monocyte ratio (from 0.02 to 0.24; hazard ratio = 0.56; 95% CI: 0.34-0.98; P = .032) were 2 independent predictors for long-term all-cause mortality. The eosinophil-to-monocyte ratio at the admission of less than 0.03 was documented to be associated with higher mortality (P < .001).Conclusion:Our results revealed that a lower eosinophil-to-monocyte ratio and a higher pulmonary embolism severity index score independently predict the long-term mortality in patients with intermediate-high- and high-risk pulmonary embolism.

Association Between the Expression of MicroRNA-125b and Survival in Patients With Acute Coronary Syndrome and Coronary Multivessel Disease.

BackgroundMicroRNAs (miRNA, miR) have an undeniable physiological and pathophysiological significance and act as promising novel biomarkers. The aim of the study was to investigate blood-derived miRNAs and their association with long-term all-cause mortality in patients with multivessel disease (MVD) suffering from acute coronary syndrome (ACS).Materials and MethodsThis study was an observational prospective study, which included 90 patients with MVD and ACS. Expression of miR-125a, miR-125b, and miR-223 was analysed by polymerase chain reaction (PCR). Patients were followed-up for a median of 7.5 years. All-cause mortality was considered as the primary endpoint. Adjusted Cox-regression analysis was performed for prediction of events.ResultsElevated expression of miR-125b (>4.6) at the time-point of ACS was associated with increased long-term all-cause mortality (adjusted [adj.] hazard ratio [HR] = 11.26, 95% confidence interval [95% CI]: 1.15–110.38; p = 0.038). The receiver operating characteristic (ROC) analysis showed a satisfactory c-statistics for miR-125b for the prediction of long-term all-cause mortality (area under the curve [AUC] = 0.76, 95% CI: 0.61–0.91; p = 0.034; the negative predictive value of 98%). Kaplan–Meier time to event analysis confirmed an early separation of the survival curves between patients with high vs low expression of miR-125b (p = 0.003). An increased expression of miR-125a and miR-223 was found in patients with non-ST-segment elevation ACS (NSTE-ACS) as compared to those with ST-segment elevation myocardial infarction (STEMI) (p = 0.043 and p = 0.049, respectively) with no difference in the expression of miR-125b between the type of ACS.ConclusionIn this hypothesis generating study, lower values of miR-125b were related to improved long-term survival in patients with ACS and MVD. Larger studies are needed to investigate whether miR-125b can be used as a suitable predictor for long-term all-cause mortality.

The U-Shaped Relationship Between Serum Uric Acid and Long-Term All-Cause Mortality in Coronary Artery Disease Patients: A Cohort Study of 33,034 Patients.

BackgroundAssociations between high serum uric acid (SUA) and cardiovascular diseases have been reported. However, few studies have been conducted to explore the relationship between SUA and long-term all-cause mortality in coronary artery disease (CAD) patients. Our study aims to investigate the relationship between SUA and long-term all-cause mortality in patients with CAD.MethodsFrom January 2007 to December 2018, we divided 33,034 patients with CAD admitted in the Guangdong Provincial People's Hospital into five groups (quintile 1: SUA <5.05 mg/dl, quintile 2: 5.05 mg/dl ≤ SUA <5.59 mg/dl, quintile 3:5.59 mg/dl ≤ SUA <6.8 mg/dl, quintile 4, 6.8 mg/dl ≤ SUA <7.93 mg/dl, and quintile 5, SUA ≥7.93 mg/d;). This study used Kaplan–Meier survival analysis to evaluate patient outcomes with different ranges of SUA. Cox proportional hazards regression models and restricted cubic spline were applied to determine the association between serum uric and long-term all-cause mortality.ResultsA total of 33,034 participants were recruited, including 24,780 (75.01%) men and 8,254 (24.99) women in this cohort study. Median follow-up was 4.91 years. We found that SUA is an independent risk factor of long-term all-cause mortality according to the result of Cox proportional hazards models. This study also illustrated an approximate U-shape association between SUA and all-cause mortality when compared with 5.95 mg/lL ≤ SUA <6.8 mg/dl, SUA <5.0 5mg/dl (adjusted hazard ratio (aHR) =1.13, 95% CI: 1.01–1.26, p = 0.03), and SUA ≥8 mg/dL (aHR = 1.18, 95% CI: 1.06-1.32, p = 0.003).ConclusionOur study indicated a U-shaped relationship between SUA and long-term all-cause mortality in patients with CAD. No matter whether SUA is too high or too low, it increased the all-cause mortality in the CAD population, which deserves to be closely monitored.

Association of Rebleeding and Delayed Cerebral Ischemia with Long-term Mortality Among 1-year Survivors After Aneurysmal Subarachnoid Hemorrhage.

The potential impact of rebleeding and Delayed Cerebral Ischemia (DCI) on long-term survival in patients with aneurysmal subarachnoid hemorrhage (aSAH) remained unclear. This study aimed to investigate whether DCI and rebleeding increase the risk of long-term all-cause mortality in patients with aSAH who survived the follow-up period of one year. We retrospectively collected data on patients with atraumatic aSAH who were still alive 12 months after aSAH occurrence between December 2013 and June 2019 from the electronic health system. Patients were then classified by the occurrence of rebleeding or DCI during hospitalization. Death records were obtained from an administrative database, the Chinese Household Registration Administration System, until April 20, 2021. Multivariable Cox proportional hazards models were used to compare overall survival in different groups. Sensitivity analysis was performed with propensity-score matching (PSM). A total of 2,607 patients were alive one year after aSAH. The crude annual death rate from any cause among patients who had rebleeding (7.2 per 100 person-years) and patients who had DCI (3.7 per 100 person-years) during hospitalization was higher than that of patients with neither event (2.1 per 100 person-years). Multivariate analysis showed that rebleeding is an independent risk factor for long-term mortality (adjusted hazard ratio (aHR), 2.37; 95% confidence interval (CI), 1.47- 3.81). DCI was an independent prognostic factor of poorer overall survival (aHR, 2.09; 95% CI, 1.54-2.84). Amongst patients alive one year after aSAH, rebleeding and DCI during hospitalization were independently associated with higher rates of long-term mortality.

Fat-Free Mass and Body Fat in Patients with Myocardial Infarction Who Underwent Percutaneous Coronary Intervention

There are no data on the effects of fat-free mass (FFM) and body fat (BF) on prognosis in patients with myocardial infarction (MI). We investigated the effects of FFM and BF (which were estimated using formulas rather than direct measurements) on 30-day and long-term all-cause mortality in patients with MI who underwent percutaneous coronary intervention. We analyzed data from 6,453 patients with MI. The patients were divided into 2 categories (high/low) according to the fat-free mass index (FFMI) and 2 categories (low/high) according to the BF. The resultant 4 patient groups: HighFFMI-LowBF, HighFFMI-HighBF, LowFFMI-LowBF, and LowFFMI-HighBF, were compared. The lowest crude mortality after 30 days and in the long term was observed in the HighFFMI-LowBF group (3.0%,9.8%, respectively), followed by the HighFFMI-HighBF group (6.6%, 27.0%, respectively), the LowFFMI-LowBF group (10.4%, 36.0%, respectively), and the LowFFMI-HighBF group (14.7%, 56.8%, respectively). The difference was significant (p <0.0001), as was the difference between groups. After adjustment, the FFMI-BF groups independently predicted 30-day mortality (p = 0.003), but the risk was similar in all groups. Compared with the HighFFMI-LowBF group, the long-term mortality risk was similar in the HighFFMI-HighBF group (hazard ratio [HR] 1.11, 95% confidence interval [CI] 0.84 to 1.47, p = 0.47), but the LowFFMI-LowBF and LowFFMI-HighBF patients had a higher risk (HR 1.59, 95% CI 1.20 to 2.11, p = 0.001, HR 1.40, 95% CI 1.03 to 1.91, p = 0.033, respectively). Body composition predicted mortality better than body mass index in patients with MI. Mortality appeared to be inversely related to FFM, with patients with low FFM and low BF having a particularly high mortality risk. The body composition groups also confirmed the obesity paradox.

Validation Of The BAN-ADHF Risk Score And Risk Of Long-term Mortality In Patients With Acute Decompensated Heart Failure

Introduction Heart failure (HF) remains one of the leading causes of mortality, especially after patients were admitted for acute decompensated HF (ADHF). However, risk scores for long-term risk prediction after developing ADHF using common clinical parameters have not been well studied. Recently, the BAN-ADHF risk score was developed using machine learning-based variable importance metrics in a cohort of patients with ADHF to predict diuretic resistance. However, its ability to predict long-term outcomes in real world cohort of patients with ADHF has not been established. Hypothesis We hypothesized that the BAN-ADHF risk score will accurately stratify risk of long-term all-cause mortality in patients with ADHF. Methods Electronic medical records of 965 patients admitted with ADHF at the Cleveland Clinic were reviewed. We excluded 70 patients with missing data for calculating the risk score for a final analysis cohort of 895 patients. The BAN-ADHF risk score were calculated using clinical variables and weighted scores, which included baseline BUN, Cr, NT-proBNP, diastolic blood pressure (DBP), age, history of diabetes, atrial fibrillation, and years of HF. Participants were categorized into quintile groups of BAN-ADHF scores (≤5, 6-7, 8, 9-11, and ≥12). Kaplan Meier and Cox proportional hazard models were used to evaluate the association between the BAN-ADHF score groups and mortality with differences determined using the log-rank test. Results Mean age was 69.8±15.6 years, 49.9% were men, 71.6% had AF, 58.4% had diabetes, and 85% had CKD. Median (IQR) was 71 (62-80) mmHg for DBP, 21 (15-10) mg/dL for BUN, 1.10 (0.87-1.50) mg/dL for Cr, and 2,856 (1,042.5-7,025.5) pg/mL for NT-proBNP. During median follow up of 1,467 days, 467 (52.2%) patients died. A step-wise increase in all-cause mortality was observed across increasing BAN-ADHF quintiles (Figure, log-rank p<0.001). Compared to Quintile 1, participants with BAN-ADHF scores in Quintile 5 had a 192% higher risk of all-cause mortality (HR 2.92, 95% CI 2.18-3.92, p<0.001). Conclusions Higher BAN-ADHF risk scores are significantly associated with an increased risk of long-term all-cause mortality in patients with ADHF. Heart failure (HF) remains one of the leading causes of mortality, especially after patients were admitted for acute decompensated HF (ADHF). However, risk scores for long-term risk prediction after developing ADHF using common clinical parameters have not been well studied. Recently, the BAN-ADHF risk score was developed using machine learning-based variable importance metrics in a cohort of patients with ADHF to predict diuretic resistance. However, its ability to predict long-term outcomes in real world cohort of patients with ADHF has not been established. We hypothesized that the BAN-ADHF risk score will accurately stratify risk of long-term all-cause mortality in patients with ADHF. Electronic medical records of 965 patients admitted with ADHF at the Cleveland Clinic were reviewed. We excluded 70 patients with missing data for calculating the risk score for a final analysis cohort of 895 patients. The BAN-ADHF risk score were calculated using clinical variables and weighted scores, which included baseline BUN, Cr, NT-proBNP, diastolic blood pressure (DBP), age, history of diabetes, atrial fibrillation, and years of HF. Participants were categorized into quintile groups of BAN-ADHF scores (≤5, 6-7, 8, 9-11, and ≥12). Kaplan Meier and Cox proportional hazard models were used to evaluate the association between the BAN-ADHF score groups and mortality with differences determined using the log-rank test. Mean age was 69.8±15.6 years, 49.9% were men, 71.6% had AF, 58.4% had diabetes, and 85% had CKD. Median (IQR) was 71 (62-80) mmHg for DBP, 21 (15-10) mg/dL for BUN, 1.10 (0.87-1.50) mg/dL for Cr, and 2,856 (1,042.5-7,025.5) pg/mL for NT-proBNP. During median follow up of 1,467 days, 467 (52.2%) patients died. A step-wise increase in all-cause mortality was observed across increasing BAN-ADHF quintiles (Figure, log-rank p<0.001). Compared to Quintile 1, participants with BAN-ADHF scores in Quintile 5 had a 192% higher risk of all-cause mortality (HR 2.92, 95% CI 2.18-3.92, p<0.001). Higher BAN-ADHF risk scores are significantly associated with an increased risk of long-term all-cause mortality in patients with ADHF.

Predicting Long-Term Mortality in Patients With Acute Heart Failure by Using Machine Learning

High mortality rates in patients with acute heart failure (AHF) necessitate proper risk stratification. However, risk-assessment tools for long-term mortality are largely lacking. We aimed to develop a machine-learning (ML)-based risk-prediction model for long-term all-cause mortality in patients admitted for AHF. The ML model, based on boosted a Cox regression algorithm (CoxBoost), was trained with 2704 consecutive patients hospitalized for AHF (median age 73 years, 55% male, and median left ventricular ejection fraction 38%). We selected 27 input variables, including 19 clinical features and 8 echocardiographic parameters, for model development. The best-performing model, along with pre-existing risk scores (BIOSTAT-CHF and AHEAD scores), was validated in an independent test cohort of 1608 patients. During the median 32 months (interquartile range 12-54 months) of the follow-up period, 1050 (38.8%) and 690 (42.9%) deaths occurred in the training and test cohorts, respectively. The area under the receiver operating characteristic curve (AUROC) of the ML model for all-cause mortality at 3 years was 0.761 (95% CI: 0.754-0.767) in the training cohort and 0.760 (95% CI: 0.752-0.768) in the test cohort. The discrimination performance of the ML model significantly outperformed those of the pre-existing risk scores (AUROC 0.714, 95% CI 0.706-0.722 by BIOSTAT-CHF; and 0.681, 95% CI 0.672-0.689 by AHEAD). Risk stratification based on the ML model identified patients at high mortality risk regardless of heart failure phenotypes. The ML-based mortality-prediction model can predict long-term mortality accurately, leading to optimal risk stratification of patients with AHF.

Are There Any Differences in the Prognostic Value of Left Ventricular Ejection Fraction in Coronary Artery Disease Patients With or Without Moderate and Severe Mitral Regurgitation?

BackgroundLeft ventricular ejection fraction (LVEF) is a vital variable to describe left ventricle systolic function and contractility of left ventricle. However, the association between LVEF and the prognostic effect in patients with moderate or severe mitral regurgitation (MR) is still controversial.MethodsThis study comprised 30,775 coronary artery disease (CAD) patients who underwent coronary arteriography (CAG) in the Cardiorenal ImprovemeNt (CIN) registry from January 2007 to December 2018. Patients were divided into none or mild MR group and moderate or severe MR group, and 3 levels of LVEF ≥50, 40–50%, and <40% were further distinguished according to hospital baseline. Univariate and multivariate Cox proportional analyses were used to investigate the association between LVEF levels and long-term all-cause mortality in patients with different MR severities.ResultsOf 30,775 CAD patients (62.9 ± 10.6 years, females 23.8%), 26,474 (86.0%) patients had none or mild MR. Compared with none or mild MR patients, patients with moderate or severe MR were older and had worse cardio-renal function. In multivariable Cox proportional analysis, LVEF <40% was independently associated with higher mortality compared with LVEF ≥ 50% in all kinds of MR severity {none or mild MR [adjusted hazard ratio (HR): 1.79; 95% CI: 1.56–2.05, p < 0.001], moderate or severe MR [adjusted HR: 1.57; 95% CI: 1.29–1.91, p < 0.001]}.ConclusionsLVEF is a reliable prognostic index in CAD patients, even in those with moderate or severe MR. LVEF monitoring would still be clinically useful in CAD patients with moderate or severe MR. Clinical trials are needed to prospectively evaluate the optimal threshold for LVEF in patients with moderate or severe MR.

Prognostic value of serum albumin for long-term mortality in patients with dual-chamber permanent pacemakers.

Background: This investigation aims to examine the prognostic utility of albumin concentrations for long-term all-cause mortality in patients undergoing permanent pacemaker implantation. Methods: A total of 1798 patients who received permanent pacemaker implantation were divided into quartiles according to serum albumin concentrations. The significance of albumin in predicting long-term mortality was compared in these quartiles. Results: There was a higher rate of long-term mortality in the Q4 group compared with the Q1-3 groups (49.9 vs 15.8%). The risk of long-term mortality in the Q4 group was 3.6-times higher compared with the Q1-3 groups after adjustment for confounders. Conclusion: Serum albumin level at the time of device implantation has great value when assessing long-term mortality in patients with permanent pacemakers.

Long-term Prognosis Following Vascular Graft Infection: A 10-Year Cohort Study.

BackgroundVascular graft infection (VGI) remains a severe disease with high mortality and relapse rates. We performed a retrospective single-center cohort study to highlight factors associated with long-term all-cause mortality in patients with vascular graft infection.MethodsAll patients hospitalized in our facility over 10 years for VGI were included. VGI was defined by the presence of a vascular graft or an aortic stent graft (stent or fabric), associated with 2 criteria among clinical, biological, imaging, or microbiological elements in favor of VGI. The primary outcome was all-cause mortality. Empirical antibiotic therapy was considered as appropriate when all involved pathogens were susceptible in vitro to the antibiotics used. The surgical strategy was defined as nonoptimal when the graft was not removed in a late-onset surgery (>3 months) or no surgery was performed.ResultsOne hundred forty-six patients were included. Empirical antibiotic therapy was administered in 98 (67%) patients and considered appropriate in 55 (56%) patients. Surgery was performed in 136 patients (96%) and considered as optimal in 106 (73%) patients. In multivariable analysis, appropriate empirical antibiotic therapy was associated with a lower probability of mortality (hazard ratio, 0.47 [95% confidence interval, .30–.79]; P = .002). Long-term survival did not differ according to whether the surgical strategy was considered optimal or not (log-rank = 0.66).ConclusionsAppropriate empirical antibiotic therapy is a cornerstone of the management of VGI. Whenever possible, antibiotics must be associated with optimal surgical management. However, surgery could potentially be avoided in comorbid patients who are treated with appropriate antibiotics.

Pre-Procedural Right Ventricular Longitudinal Strain and Post-Procedural Tricuspid Regurgitation Predict Mortality in Patients Undergoing Transcatheter Aortic Valve Implantation (TAVI).

Background: Right ventricular (RV) dysfunction has been linked to worse outcomes in patients undergoing TAVI. Assessment of RV function is challenging due to its complex morphology. RV longitudinal strain (LS) assessed by speckle-tracking echocardiography (STE) is a novel measure that may overcome most of the limitations of conventional echocardiographic parameters of RV function. The aim of current study was to assess the prognostic value of RV LS in patients undergoing TAVI and to assess echocardiographic predictors of long-term mortality. Methods and results: A retrospective analysis of all consecutive patients who underwent TAVI at our hospital between 1 January 2015 and 1 June 2016. Indication for TAVI was approved by a local heart-team. Echocardiographic data at baseline and after TAVI were re-analyzed and RV LS was measured in all patients with adequate image quality. A total of 229 patients were included in our study (mean age 83.8 ± 5 years, 62% women, mean EuroSCORE II 5.7 ± 5%). All-cause mortality occurred in 17.3% over a mean follow-up of 929 ± 373 days. In multivariate analysis, only baseline average RV free-wall LS (HR 1.05, 95% CI (1.01 to 1.10), p = 0.049) and more than mild tricuspid valve regurgitation (TR) after TAVI (HR 4.39, 95% CI (2.22 to 8.70), p < 0.001) independently increased the risk of all-cause mortality at long- term follow-up (2.5 years), while conventional echocardiographic parameters of RV function did not predict mortality. Conclusion: Pre-procedural RV LS and post-procedural tricuspid regurgitation significantly predicted long-term all-cause mortality in patients undergoing TAVI while conventional echocardiographic parameters of RV function failed in predicting long-term outcome. RV longitudinal strain by STE should be considered in the routine echocardiographic assessments of patients with severe AS.

Epicardial adipose tissue radiodensity is associated with all-cause mortality in patients undergoing hemodialysis

The radiodensity and volume of epicardial adipose tissue (EAT) on computed tomography angiography (CTA) may provide information regarding cardiovascular risk and long-term outcomes. EAT volume is associated with mortality in patients undergoing incident hemodialysis. However, the relationship between EAT radiodensity/volume and all-cause mortality in patients with end-stage renal disease (ESRD) undergoing maintenance hemodialysis remains elusive. In this retrospective study, EAT radiodensity (in Hounsfield units) and volume (in cm3) on coronary CTA were quantified for patients with ESRD using automatic, quantitative measurement software between January 2012 and December 2018. All-cause mortality data (up to December 2019) were obtained from the Korean National Statistical Office. The prognostic values of EAT radiodensity and volume for predicting long-term mortality were assessed using multivariable Cox regression models, which were adjusted for potential confounders. A total of 221 patients (mean age: 64.88 ± 11.09 years; 114 women and 107 men) with ESRD were included. The median follow-up duration (interquartile range) after coronary CTA was 29.63 (range 16.67–44.7) months. During follow-up, 82 (37.1%) deaths occurred. In the multivariable analysis, EAT radiodensity (hazard ratio [HR] 1.055; 95% confidence interval [CI] 1.015–1.095; p = 0.006) was an independent predictor of all-cause mortality in patients with ESRD. However, EAT volume was not associated with mortality. Higher EAT radiodensity on CTA is associated with higher long-term all-cause mortality in patients undergoing prevalent hemodialysis, highlighting its potential as a prognostic imaging biomarker in patients undergoing hemodialysis.

Machine learning-based long-term outcome prediction in patients undergoing percutaneous coronary intervention

Traditional prognostic risk assessment in patients with coronary artery disease undergoing percutaneous coronary intervention (PCI) is based on a limited selection of clinical and imaging findings. Machine learning (ML) can consider a higher number and complexity of variables and may be useful for characterising cardiovascular risk, predicting outcomes, and identifying biomarkers in large population studies. We prospectively enrolled 9,680 consecutive patients with coronary artery disease who underwent PCI at our institution between January 2013 and December 2013. Clinical features were selected and used to train 6 different ML models (support vector machine, decision tree, random forest, gradient boosting decision tree, neural network, and logistic regression) to predict cardiovascular outcomes, 10-fold cross-validation to evaluate the performance of models. During the 5-year follow-up, 467 (4.82%) patients died. Eighty-seven risk baseline measurements were used to train ML models. Compared with the other models, the random forest model (RF-PCI) exhibited the best performance on predicting all-cause mortality (area under the receiver operating characteristic curve: 0.71±0.04). Calibration plots demonstrated a slight overprediction for patients using the RF-PCI model (Hosmer-Lemeshow test: P>0.05). The top 15 features related to PCI candidates' long-term prognosis, among which 11 were laboratory measures. ML models improved the prediction of long-term all-cause mortality in patients with coronary artery disease before PCI. The performance of the RF model was better than that of the other models, providing a meaningful stratification.

MiR-126 Is an Independent Predictor of Long-Term All-Cause Mortality in Patients with Type 2 Diabetes Mellitus.

MicroRNAs are endogenous non-coding RNAs that are involved in numerous biological processes through regulation of gene expression. The aim of our study was to determine the ability of several miRNAs to predict mortality and response to antiplatelet treatment among T2DM patients. Two hundred fifty-two patients with diabetes were enrolled in the study. Among the patients included, 26 (10.3%) patients died within a median observation time of 5.9 years. The patients were receiving either acetylsalicylic acid (ASA) 75 mg (65%), ASA 150 mg (15%) or clopidogrel (19%). Plasma miR-126, miR-223, miR-125a-3p and Let-7e expressions were assessed by quantitative real time PCR and compared between the patients who survived and those who died. Adjusted Cox-regression analysis was used for prediction of mortality. Differential miRNA expression due to different antiplatelet treatment was analyzed. After including all miRNAs into one multivariate Cox regression model, only miR-126 was predictive of future occurrence of long-term all-cause death (HR = 5.82, 95% CI: 1.3–24.9; p = 0.024). Furthermore, miR-126, Let-7e and miR-223 expressions in the clopidogrel group were significantly higher than in the ASA group (p = 0.014; p = 0.013; p = 0.028, respectively). To conclude, miR-126 expression is a strong and independent predictor of long-term all-cause mortality among patients with T2DM. Moreover, miR-223, miR-126 and Let-7e present significant interactions with antiplatelet treatment regimens and clinical outcomes.

Utility of plasma galectin-3 in predicting long-term mortality in patients with acute heart failure

Background: Several studies have investigated Galectin-3 as a promising biomarker for predicting the short-term and long-term mortality of patients with acute heart failure. This study aimed to examine the usefulness of plasma galectin-3 at the time of admission in predicting long-term mortality in Vietnamese patients with acute heart failure (AHF).&#x0D; Methods: We carried out a cohort study including 117 patients consecutively diagnosed with acute heart failure in a single cardiology department. Plasma galectin-3 and other biomarkers were measured at the time of admission. The patient’s clinical and analytical characteristics were recorded. The main endpoint was one-year all-cause mortality.&#x0D; Results: There were six patients (5%) lost to follow-up and 59 patients (53.2%) reaching primary outcome within one year after ‎hospital admission.‎ The median plasma galectin-3 level (ng/mL) in patients with acute heart failure was 34.6 (26.7 – 44.1). Plasma galectin-3 in the alive group was significantly higher than that in the deceased group at one-year follow-up. In predicting one-year all-cause mortality, galectin-3 had an area under the curve (AUC) of 0.71 (95% confidence interval (CI), 0.62 – 0.81) representing a good prognostic factor while brain natriuretic peptide (BNP) and troponin I were inferior to galectin-3 with an AUC of 0.69 (95% CI, 0.59 – 0.79) and 0.63 (95% CI, 0.53 – 0.74), respectively. The optimal cut-off value for galectin-3 was 40.75 ng/mL with a sensitivity of 50.1% and a specificity of 88.5%. In a multivariate model, patients with galectin-3 levels &gt; 40.75 ng/mL had a hazard ratio (HR) of 2.8 (95% CI, 1.5 – 5; p = 0.001). The best prediction model was the combined model of galectin-3 and BNP, yielding an AUC of 0.78 (95% CI, 0.70 – 0.86; p &lt; 0.001).&#x0D; Conclusions: Our study suggested that galectin-3 levels could predict long-term all-cause mortality in patients with acute heart failure with a good prognostic capacity. Combining galectin-3 and BNP could bring up a better risk-stratification.

Long-term mortality predictors in pulmonary embolism

Abstract Funding Acknowledgements Type of funding sources: None. Introduction Acute Pulmonary embolism(PE)is a common and potentially fatal medical condition.In contemporary adult population,PE is associated with increased long-term mortality. Purpose Identify predictors of long-term all-cause mortality in patients(pts)admitted due to pulmonary embolism. Methods Retrospective single-center study of hospitalized pts with acute PE between 2015 and 2018.We evaluated comorbidities, admission(AD)presentation such as vitals(with hypotension defined as systolic blood pressure(SBP)&amp;lt;90mmHg,and tachycardia as &amp;gt;100ppm),lab analyses during in-hospital period,imaging features. Mortality(long-term &amp;gt;3months)was also assessed using national registry of citizens.We performed uni and multivariate analysis to compare clinical characteristics of pts who died and who survived,using Cox regression and Kaplan-Meier methods.For the predictor age we assessed discrimination power and defined the best cut-off using area under the ROC curve(AUC)method. Results From 2015 to 2018,182 pts were admitted with diagnosis of pulmonary embolism,60% female with a mean age of 74 ± 13years old.Seventy-one(39%)pts died after a median follow-up of 26[10-41]months.Pts who died were older(80 ± 8 vs71 ± 14,p &amp;lt; 0.001).The best cut-off value of age to predict mortality with 70%sensitivity and 61%specificity was 77years old(AUC 0.703;CI95% 0.63-0.78).Pts who died had more frequently history of neoplasia (21%vs 9%,p = 0.009).The remaining comorbidities were similar in both groups.Pts who did not survive were more frequently hypotensive(28% vs 13%, p = 0.008),had higher creatinine(1.1[0.8-1.4] vs 1.0[0.8-1.2], p = 0.002), lactate(2.3[1.8-2.8]vs 1.8[1.5-2.0],p = 0.007)and NT-proBNP(4694[1498-12300]vs2070[492-6660], p &amp;lt; 0.001)at AD.Maximum troponin I (0.176[0.037-0.727]vs0.126[0.050-0.365]ng/mL,p = 0.012) was also higher than in pts who survived. After adjusting for history of neoplasia,ADcreatinine and maximum troponin I,we found that age (HR1.057;95%CI 1.01-1.11,p = 0.021),AD SBP &amp;lt; 90(HR 2.215;95%CI 1.03-4.76,p = 0.041),lactate(HR 1.17;95%CI 1.01-1.36,p = 0.035)and NT-proBNP(HR 1.510;95%CI 1.250-1.780,p &amp;lt; 0.001)were independent predictors of all-cause mortality. Conclusion In our cohort,the long-term all-cause mortality was 39%over a median follow-up of 26[10-41]months.In patients with pulmonary embolism,aside from already identified age(especially when ≥70 years old)and NT-proBNP,lactate should also be considered when evaluating long-term prognosis. Furthermore,hypotension at admission increases by 2fold long-term mortality in patients who suffered acute PE.

Body mass index linked to short-term and long-term all-cause mortality in patients with acute myocardial infarction

Purposes of studyThis study aimed to elucidate the relationship between obesity and short-term and long-term mortality in patients with acute myocardial infarction (AMI) by analysing the body mass index (BMI).Study...

Predictors of long-term mortality in acute ST-elevation myocardial infarction patients undergoing emergent coronary artery bypass graft surgery

Coronary artery bypass graft (CABG) surgery as a primary treatment for acute ST-elevation myocardial infarction (STEMI) is still debated. This study aimed to evaluate the predictors of long-term mortality in STEMI patients undergoing emergent CABG. To the best of our knowledge, this is the first study to evaluate the long-term mortality predictors in patients with STEMI revascularized by primary CABG.This retrospective study included 88 consecutive patients with STEMI, who did not qualify for primary percutaneous intervention and required emergent CABG between 2010 and 2017. The study population was divided into the following 2 groups: survivors and nonsurvivors. The 2 groups were compared in terms of demographics, preoperative, intraoperative, and postoperative characteristics.23 of the 88 patients, died during the median 92.8 (69.0-105.1) months of follow-up. Data were evaluated with univariate and multivariate analyses. Killip class (p<0.001) was found to be an independent predictor of long-term all-cause mortality in patients with STEMI revascularized by CABG, and mortality rates increased significantly as Killip class increased (log-rank test, p<0.001). Moreover, age (p=0.044) was found to be an independent predictor of long-term mortality. Left ventricular ejection fraction, glomerular filtration rate, glucose levels, and left anterior descending artery to the left internal mammary artery graft usage (p=0.001, p=0.009, p<0.001, and p=0.039, respectively) were significantly associated with long-term all-cause mortality for our study population.Killip class was found to be an independent predictor of long-term all-cause mortality in patients with STEMI who underwent emergent CABG. The patients' admission status may give valuable information about long-term mortality.