Increase In C-statistic Research Articles

Prognostic value of stress perfusion cardiac magnetic resonance in patients with prediabetes and suspected coronary artery disease.

Stress perfusion cardiac magnetic resonance (CMR) is an accurate and comprehensive modality for evaluating patients with suspected coronary artery disease (CAD), but its prognostic value in prediabetic patients is uncertain. This retrospective study included 452 consecutive prediabetic patients without prior diagnoses of CAD who underwent adenosine stress perfusion CMR. The primary endpoint was major adverse cardiovascular events (MACE), defined as cardiovascular death, nonfatal myocardial infarction (MI), hospitalization for heart failure, ischemic stroke, and late coronary revascularization (>90 days post-CMR). The secondary endpoint was a composite of cardiovascular death, nonfatal MI, and hospitalization for heart failure. The mean age was 68±11 years (49% male). Over a median follow-up time of 8.1 (IQR 5.7, 10.4) years, 55 patients experienced MACE, and 24 met the secondary endpoint. Patients with inducible ischemia had significantly greater annualized event rates for MACE (5.7% vs. 0.7%, p<0.001) and for the secondary endpoint (2.0% vs. 0.3%, p<0.001) than those without ischemia. Multivariable analysis revealed inducible ischemia as a consistent predictor for MACE (HR 3.36, 95%CI 1.90-5.94, p<0.001) and for the secondary endpoint (HR 2.89, 95%CI 1.22-6.80, p = 0.01). Late gadolinium enhancement (LGE) was an independent predictor of the secondary endpoint (HR 3.56, 95%CI 1.25-10.13; p = 0.02). Incorporating inducible ischemia and LGE data significantly improved the model's ability to discriminate MACE risk (C-statistic increase from 0.77 to 0.83; net reclassification improvement 0.42; integrated discrimination improvement 0.05). Stress perfusion CMR offers substantial independent prognostic value and effectively aids in reclassifying cardiovascular risk among prediabetic patients with suspected CAD.

Obesity-Related Differences in Pathomechanism and Outcomes in Patients With HFpEF: A CMR Study

BackgroundClinical significance of an integrated evaluation of epicardial adipose tissue (EAT) and the right ventricle (RV) in heart failure with preserved ejection fraction (HFpEF) is unknown. ObjectivesThe authors investigated the potential of EAT and RV quantification for obesity-related pathophysiology and risk stratification in obese HFpEF patients using cardiovascular magnetic resonance (CMR). MethodsA total of 150 patients (obese, body mass index ≥30 kg/m2; n = 73, nonobese, body mass index <30 kg/m2; n = 77) with a clinical diagnosis of HFpEF undergoing CMR were retrospectively identified. EAT volume surrounding both ventricles were quantified with manual delineation on cine images. Total RV volume (TRVV) was calculated as the sum of RV cavity and mass at end-diastole. The endpoint was the composite of all-cause mortality and first HF hospitalization. ResultsDuring a median follow-up of 46 months, 39 nonobese patients (51%) and 32 obese patients (44%) experienced the endpoint. EAT was a prognostic biomarker regardless of obesity and was independently correlated with TRVV. In obese HFpEF, EAT correlated with RV longitudinal strain (r = 0.32, P = 0.006), and increased amount of EAT and TRVV was associated with greater left ventricular end-diastolic eccentric index (r = 0.36, P = 0.002). The integration of RV quantification into EAT provided improved risk stratification with a C-statistic increase from 0.70 to 0.79 in obese HFpEF. Obese patients with EAT<130 ml and TRVV<180 ml had low risk (annual event rate 3.2%), while those with increased EAT ≥130 ml and TRVV ≥180 ml had significantly higher risk (annual event rate 11.8%; P < 0.001). ConclusionsCMR quantification of EAT and RV structure provides additive risk stratification for adverse outcomes in obese HFpEF.

Pulse wave velocity has an additive prognostic value to SCORE2 in apparently healthy subjects at 6 years of follow up

Abstract Backround/Aim: Arterial stiffness is involved in the clinical course of atherogenesis. The purpose of this study was to investigate whether altered arterial wall properties of confers predictively and additively to estimation of cardiovascular risk. Methods Pulse wave velocity carotid-femoral (PWVc-f), the gold standard method to assess arterial stiffness, was measured non-invasively by Complior device. Increased PWV(c-f), especially above 10 m/s, indicates increased arterial stiffness. We measured baseline PWV(c-f) in 747 apparently healthy subjects (51.99±13.41 years old, 43.8% males), without established cardiovascular disease and calculated SCORE2 in each subject according to ESC guidelines.We prospectively monitored the occurrence of major cardiovascular events (MACEs-death, myocardial infarction, stroke) during a 6-year follow-up period using electronic records and clinic visits. Results Fifty-seven MACEs were documented during follow-up. In univariate analysis, subjects with increased PWV were found to exert greater risk for MACEs (hazard ratio (HR):1.12, 95%CI: 1.09-1.15, p&amp;lt;0.001). PWV remained a significant predictor for MACEs in a model including sex, age, hyperlipidemia, diabetes, hypertension, current smoking, family history of coronary artery disease and treatment with ACEi/ARBs or lipid lowering agents after using backward elimination (HR:1.13; 95% CI: 1.08-1.18, p&amp;lt;0.001). PWV was an independent and additive predictor of outcome when added in a model including solely SCORE2 (HR:1.10; 95% CI: 1.07-1.14,p&amp;lt;0.001; Chi-square change:20.08, p&amp;lt;0.001; C-statistic increase from 0.592 to 0.685) and also in a model encompassing risk factors not included in SCORE2, namely diabetes (HR:1.07; 95% CI: 1.04-1.11,p&amp;lt;0.001; Chi-square change: 43.12, p&amp;lt;0.001; C-statistic increase from 0.613 to 0.698). The HR of PWV for the prediction of MACE remained similar in subjects younger or older than the age of 50 years (p&amp;gt;0.05). Conclusion Arterial stiffness is an independent and additive predictor to conventional risk factors and SCORE2 for adverse outcome at 6 years follow-up.

Prognostic association supports indexing size measures in echocardiography by body surface area

Body surface area (BSA) is the most commonly used metric for body size indexation of echocardiographic measures, but its use in patients who are underweight or obese is questioned (body mass index (BMI) < 18.5 kg/m2 or ≥ 30 kg/m2, respectively). We aim to use survival analysis to identify an optimal body size indexation metric for echocardiographic measures that would be a better predictor of survival than BSA regardless of BMI. Adult patients with no prior valve replacement were selected from the National Echocardiography Database Australia. Survival analysis was performed for echocardiographic measures both unindexed and indexed to different body size metrics, with 5-year cardiovascular mortality as the primary endpoint. Indexation of echocardiographic measures (left ventricular end-diastolic diameter [n = 230,109] and mass [n = 224,244], left atrial volume [n = 150,540], aortic sinus diameter [n = 90,805], right atrial area [n = 59,516]) by BSA had better prognostic performance vs unindexed measures (underweight: C-statistic 0.655 vs 0.647; normal weight/overweight: average C-statistic 0.666 vs 0.625; obese: C-statistic 0.627 vs 0.613). Indexation by other body size metrics (lean body mass, height, and/or weight raised to different powers) did not improve prognostic performance versus BSA by a clinically relevant magnitude (average C-statistic increase ≤ 0.02), with smaller differences in other BMI subgroups. Indexing measures of cardiac and aortic size by BSA improves prognostic performance regardless of BMI, and no other body size metric has a clinically meaningful better performance.

Association between the systemic immune-inflammation index and outcomes among atrial fibrillation patients with diabetes undergoing radiofrequency catheter ablation.

To investigate the relationship between the incidence of atrial fibrillation (AF) recurrence and the levels of the systemic immune-inflammatory index (SII, platelet × neutrophil/lymphocyte ratio) in patients with AFand diabetes mellitus (DM) undergoing after radiofrequency catheter ablation (RFCA). Preoperative SII levels were determined in AF patients with DM undergoing RFCA. Restricted cubic splines were used to determine the correlation between SII and the risk of AF recurrence. Multivariate-adjusted logistic regression models were constructed to determine the relationship between SII levels and AF recurrence. The predictive value of the clinical model and combined with the SII index was estimated by the area under the receiver-operating characteristic curve, net reclassification improvement (NRI), and integrated discrimination improvement (IDI). A total of 204 patients with AF and DM who underwent RFCA in our hospital were included. Seventy-seven patients had AF recurred during a mean follow-up of 20 months. Restricted cubic spline analysis showed that when SII ≥ 444.77 × 109 /L, there was a positive correlation with the incidence of AF recurrence. In addition, adding the SII to the predictive model for AF recurrence after RFCA in patients with DM and AF could contribute to an increase in C-statistics (0.798 vs. 0.749, p = .034). After SII was incorporated into the clinical model, the comprehensive discrimination and net reclassification tended to improve (IDI and NRI > 0, p < .05). SII was independently and positively associated with recurrence after the first catheter ablation in patients with DMand AF.

Growth Differentiation Factor 15: A Prognostic Marker in Patients with Acute Chest Pain without Acute Myocardial Infarction.

Acute chest pain is associated with an increased risk of death and cardiovascular events even when acute myocardial infarction (AMI) has been excluded. Growth differentiation factor-15 (GDF-15) is a strong prognostic marker in patients with acute chest pain and AMI, but the prognostic value in patients without AMI is uncertain. This study sought to investigate the ability of GDF-15 to predict long-term prognosis in patients presenting with acute chest pain without AMI. In total, 1320 patients admitted with acute chest pain without AMI were followed for a median of 1523 days (range: 4 to 2208 days). The primary end point was all-cause mortality. Secondary end points included cardiovascular (CV) death, future AMI, heart failure hospitalization, and new-onset atrial fibrillation (AF). Higher concentrations of GDF-15 were associated with increased risk of death from all causes (median concentration in non-survivors vs survivors: 2124 pg/mL vs 852 pg/mL, P < 0.001), and all secondary end points. By multivariable Cox regression, GDF-15 concentration ≥4th quartile (compared to <4th quartile) remained an independent predictor of all-cause death (adjusted hazard ratio (HR): 2.75; 95% CI, 1.69-4.45, P < 0.001), CV death (adjusted HR: 3.74; 95% CI, 1.31-10.63, P = 0.013), and heart failure hospitalization (adjusted HR: 2.60; 95% CI, 1.11-6.06, P = 0.027). Adding GDF-15 to a model consisting of established risk factors and high-sensitivity cardiac troponin T (hs-cTnT) led to a significant increase in C-statistics for prediction of all-cause mortality. Higher concentrations of GDF-15 were associated with increased risk of mortality from all causes and risk of future CV events.

Personalised progression prediction in patients with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma (PANGEA): a retrospective, multicohort study

Patients with precursors to multiple myeloma are dichotomised as having monoclonal gammopathy of undetermined significance or smouldering multiple myeloma on the basis of monoclonal protein concentrations or bone marrow plasma cell percentage. Current risk stratifications use laboratory measurements at diagnosis and do not incorporate time-varying biomarkers. Our goal was to develop a monoclonal gammopathy of undetermined significance and smouldering multiple myeloma stratification algorithm that utilised accessible, time-varying biomarkers to model risk of progression to multiple myeloma. In this retrospective, multicohort study, we included patients who were 18 years or older with monoclonal gammopathy of undetermined significance or smouldering multiple myeloma. We evaluated several modelling approaches for predicting disease progression to multiple myeloma using a training cohort (with patients at Dana-Farber Cancer Institute, Boston, MA, USA; annotated from Nov, 13, 2019, to April, 13, 2022). We created the PANGEA models, which used data on biomarkers (monoclonal protein concentration, free light chain ratio, age, creatinine concentration, and bone marrow plasma cell percentage) and haemoglobin trajectories from medical records to predict progression from precursor disease to multiple myeloma. The models were validated in two independent validation cohorts from National and Kapodistrian University of Athens (Athens, Greece; from Jan 26, 2020, to Feb 7, 2022; validation cohort 1), University College London (London, UK; from June 9, 2020, to April 10, 2022; validation cohort 1), and Registry of Monoclonal Gammopathies (Czech Republic, Czech Republic; Jan 5, 2004, to March 10, 2022; validation cohort 2). We compared the PANGEA models (with bone marrow [BM] data and without bone marrow [no BM] data) to current criteria (International Myeloma Working Group [IMWG] monoclonal gammopathy of undetermined significance and 20/2/20 smouldering multiple myeloma risk criteria). We included 6441 patients, 4931 (77%) with monoclonal gammopathy of undetermined significance and 1510 (23%) with smouldering multiple myeloma. 3430 (53%) of 6441 participants were female. The PANGEA model (BM) improved prediction of progression from smouldering multiple myeloma to multiple myeloma compared with the 20/2/20 model, with a C-statistic increase from 0·533 (0·480-0·709) to 0·756 (0·629-0·785) at patient visit 1 to the clinic, 0·613 (0·504-0·704) to 0·720 (0·592-0·775) at visit 2, and 0·637 (0·386-0·841) to 0·756 (0·547-0·830) at visit three in validation cohort 1. The PANGEA model (no BM) improved prediction of smouldering multiple myeloma progression to multiple myeloma compared with the 20/2/20 model with a C-statistic increase from 0·534 (0·501-0·672) to 0·692 (0·614-0·736) at visit 1, 0·573 (0·518-0·647) to 0·693 (0·605-0·734) at visit 2, and 0·560 (0·497-0·645) to 0·692 (0·570-0·708) at visit 3 in validation cohort 1. The PANGEA models improved prediction of monoclonal gammopathy of undetermined significance progression to multiple myeloma compared with the IMWG rolling model at visit 1 in validation cohort 2, with C-statistics increases from 0·640 (0·518-0·718) to 0·729 (0·643-0·941) for the PANGEA model (BM) and 0·670 (0·523-0·729) to 0·879 (0·586-0·938) for the PANGEA model (no BM). Use of the PANGEA models in clinical practice will allow patients with precursor disease to receive more accurate measures of their risk of progression to multiple myeloma, thus prompting for more appropriate treatment strategies. SU2C Dream Team and Cancer Research UK.

The additive predictive value of arterial stiffness for outcome to endothelial glycocalyx and SCORE in middle age individuals: 6 years follow-up

Abstract Background/Aim Arterial stiffness is involved in the clinical course of atherogenesis. We have previously shown that PBR, a marker of glycocalyx integrity is predictor of cardiovascular events in patients without established cardiovascular disease. The purpose of this study was to investigate whether altered arterial properties of the vessels confers predictively and additively to estimation of cardiovascular risk. Methods Pulse wave velocity carotid-femoral (PWVc-f), the gold standard method to assess arterial stiffness, was measured non-invasively by Complior device. Increased PWV(c-f), especially above 10 m/s, indicates increased arterial stiffness. We measured baseline PWV(c-f) in 600 apparently healthy subjects (47.61±13.84 years old, 50.1% males), without established cardiovascular disease. We prospectively monitored the occurrence of major cardiovascular events (MACE-death, myocardial infarction, stroke and heart failure hospitalization) during a 6-year follow-up period using electronic records and clinic visits. Results Fifty-seven MACEs were documented during follow-up. In univariate analysis, subjects with increased PWV were found to exert greater risk for MACEs (hazard ratio (HR): 1.09, 95% CI: 1.02–1.17, p=0.01). In all subjects, PWV predicted higher risk for MACEs in a model including PBR, sex, age, hyperlipidemia, diabetes, hypertension, current smoking, family history of coronary artery disease and treatment with ACEi/ARBs or lipid lowering agents (HR: 1.12; 95% CI: 1.04–1.17, p=0.029,net reclassification improvement (NRI): 23%; C-statistic: from 0.644 to 0.697). However, only in participants older than 50 years old, PWV was an independent and additive predictor of outcome when added in a model including PBR, SCORE, those risk factors not included in SCORE (diabetes, family history of CAD) and medication (HR: 1.09; 95% CI: 1.02–1.13, NRI: 23.8%, C-statistic increase from 0.703 to 0.762, p&amp;lt;0.01). Conclusion Arterial stiffness is an independent and additive predictor to endothelial glycocalyx and SCORE for adverse outcome at 6 years follow-up in individuals over 50 years old. Funding Acknowledgement Type of funding sources: None.

Abstract 2259: Predictive modeling of smoldering multiple myeloma progression to multiple myeloma by continuous variable analysis

Abstract Introduction: Multiple myeloma (MM) is consistently preceded by two precursor conditions, monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). The distinctions between MGUS, SMM, and MM rely on clinical values with inherent variation relating to tumor burden quantified from bone marrow biopsies, a measure subject to inconsistencies in location, timing, and pathologist interpretation. These challenges limit the potential of current standardized risk criteria and advocate for models that examine precursor disease kinetics. We thus developed a risk model that leverages dynamic changes in markers of precursor disease to improve clinical ability to predict time to disease progression. Methods: To model the evolution of progression risk, we built PANGEA, an international retrospective cohort of precursor patients with baseline and serial time points of clinical and biological variables. This cohort comprises 1095 SMM patients, 254 (23%) of which progressed to MM. Using this cohort, we modeled progression to MM with Cox regression using time-dependent and continuous clinical variables. The model was trained on a subset of data restricted to patients of the Dana-Farber Cancer Institute (DFCI) and validated its performance by computing the c-statistic in a sub-cohort independent from the DFCI training cohort. Results: The PANGEA cohort was first used to validate current models of SMM disease progression. We validated the 20/2/20 International Myeloma Working Group criteria for SMM patients using binary cutoffs of initial measurements (baseline model), and then extended this model, allowing for re-stratification by the 20/2/20 criteria over time (dynamic model). We then assessed whether rates of change in a set of myeloma-specific clinical variables unrestricted to those of the 20/2/20 criteria improved the predictive ability of the model. This improved our progression prediction as indicated by a c-statistic increase of more than 10% with respect to both 20/2/20 models (baseline and dynamic). Specifically, changes in disease indicators such as age and creatinine are highly predictive of imminent disease progression (p-value &amp;lt; 0.01). Finally, we clustered patients based on latent trajectories of these time-varying clinical variables and included the trajectory classes in the Cox regression. The resulting multivariable, dynamic algorithm is a dramatic improvement over current clinical standards in predicting progression from SMM to MM disease. Conclusion: The PANGEA multivariable algorithm’s use of continuous clinical variables enhances progression risk predictions in SMM. These findings demonstrate that disease progression from SMM to MM, which likely occurs by the acquisition of sequential changes to the plasma cell clone, can be tracked by trends in clinical values, thus improving prognostication for precursor patients. Citation Format: Annie Cowan, Habib El-Khoury, Federico Ferrari, Samuel S. Freeman, Robert Redd, Jacqueline Perry, Vidhi Patel, Priya Kaur, Hadley Barr, Katelyn Downey, David Argyelan, Anna V. Justis, David J. Lee, Elizabeth D. Lightbody, Foteini Theodorakakou, Despina Fotiou, Nikolaos Kanellias, Christine Liacos, Gad Getz, Lorenzo Trippa, Catherine Marinac, Efstathios Kastritis, Dimopoulos Meletios, Irene Ghobrial. Predictive modeling of smoldering multiple myeloma progression to multiple myeloma by continuous variable analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2259.

Impaired endothelial glycocalyx predicts adverse outcome in subjects without overt cardiovascular disease: a 6-year follow-up study

Abstract Aim Endothelial glycocalyx is involved in the clinical course of atherogenesis. The purpose of this study was to investigate whether disturbance of glycocalyx integrity is related with increased cardiovascular risk. Methods Perfused Boundary Region (PBR), a marker of glycocalyx integrity, was measured non-invasively in sublingual microvessels with a diameter ranging from 5–25 μm using a dedicated camera (Sideview, Darkfield Imaging). Increased PBR indicates reduced glycocalyx thickness. We measured baseline PBR in 400 apparently healthy subjects, without established cardiovascular disease. We prospectively monitored the occurrence of major cardiovascular events (MACE-death, myocardial infarction, stroke and heart failure hospitalization) during a 6-year follow-up period using electronic records and clinic visits. Results Forty-three MACE were documented during follow-up. Subjects with PBR at 5–9 μm microvessel diameter greater than 1.15 μm (mean value of the study cohort) had 2-fold higher risk for MACE than those with lower PBR in a model including sex, age, hyperlipidemia, diabetes, hypertension, current smoking, family history of coronary artery disease and treatment with ACEi/ARBs or lipid lowering agents (hazard ratio (HR): 2.49; 95% CI: 1.23–5.02, p=0.011, net reclassification improvement (NRI): 25%; C-statistic: 0.738). PBR5-9 ≥1.15 was an independent and additive predictor of outcome when added in a model including SCORE, risk factors not included in SCORE (diabetes, family history of CAD) and medication (HR: 2.48 NRI: 23.8%, C-statistic increase from 0.629 to 0.678, for all cardiac events and HR: 4.19, NRI: 33.1%, C-statistic increase from 0.654 to 0.734 for death myocardial infarction and stroke, p&amp;lt;0.01). Conclusion Endothelial glycocalyx integrity is an independent and additive predictor to atherosclerotic risk factors for adverse outcome at 6 years follow-up in individuals without diagnosed cardiovascular disease. Funding Acknowledgement Type of funding sources: None.

Triglyceride-glucose index is associated with in-stent restenosis in patients with acute coronary syndrome after percutaneous coronary intervention with drug-eluting stents

BackgroundThe triglyceride-glucose (TyG) index is an alternative marker of insulin resistance (IR) and is closely associated with the prevalence and prognosis of atherosclerotic cardiovascular disease (ASCVD). However, the association between the TyG index and in-stent restenosis (ISR) after drug-eluting stent (DES) implantation in patients with acute coronary syndrome (ACS) remains unknown.MethodsThe present study retrospectively recruited patients who were admitted for ACS and underwent coronary angiography at 6 to 24 months after successful DES-based percutaneous coronary intervention (PCI). In addition, we calculated the TyG index with the following formula: Ln(fasting triglyceride [mg/dL] × fasting blood glucose [mg/dL]/2) and divided patients into 3 groups according to the tertile of the TyG index. Most importantly, multivariate logistic regression analysis models were also constructed to assess the association between the TyG index and DES-ISR in patients with ACS.ResultsA total of 1574 patients with ACS (58.4 ± 9.4 years, 77.4% male) were included in this study. At the median follow-up time of 12 (9–14) months, the prevalence of DES-ISR increased stepwise with the increasing tertile of the TyG index (11.6% vs 17.3% vs 19.4%, p = 0.002), and the TyG index was also higher in the ISR group than in the non-ISR group (9.00 ± 0.58 vs 8.84 ± 0.61, p < 0.001). In addition, the positive association between the TyG index and the prevalence of DES-ISR was also determined in the fully adjusted model (TyG, per 1-unit increase: OR 1.424, 95% CI 1.116 to 1.818, p = 0.005; tertile of TyG, the OR (95% CI) values for tertile 2 and tertile 3 were 1.454 (1.013 to 2.087) and 1.634 (1.125 to 2.374), respectively, with tertile 1 as a reference). The association was also reflected in most subgroups. Moreover, adding the TyG index to the predictive model for DES-ISR in patients with ACS could contribute to an increase in C-statistics (0.675 vs 0.659, p = 0.010), categorical net reclassification improvement (0.090, p < 0.001), and integrated discrimination improvement (0.004, p = 0.040).ConclusionAn elevated TyG index was independently and positively associated with DES-ISR in patients with ACS who underwent PCI. However, the incremental predictive value of the TyG index for DES-ISR was slight. To further confirm our findings, future studies are needed.

Serum calcium and long-term outcome after ischemic stroke: Results from the China National stroke registry III

Background and aimsSerum calcium abnormality is associated with adverse cardiovascular outcomes, but the effects of serum calcium level on stroke outcomes remain unknown. We aimed to assess the relationship between serum calcium level and 1-year outcomes in patients with acute ischemic stroke and transient ischemic attack. MethodsWe included 9375 stroke patients from the China National Stroke Registry III for analysis. Participants were divided into 4 groups according to albumin corrected-calcium quartiles. Composite end point comprised recurrent stroke, myocardial infarction, other ischemic vascular events, and all-cause mortality. Multivariable Cox or logistic regression was used to evaluate the independent association of albumin corrected-calcium with all-cause mortality, recurrent stroke, composite end point, and poor functional outcome (modified Rankin Scale score ≥3). ResultsCompared with the lowest calcium quartile (<2.16 mmol/L), the adjusted hazard ratio (95% CI) of the top quartile (≥2.31 mmol/L) was 1.56 (1.11–2.18) for all-cause mortality, 1.06 (0.87–1.28) for recurrent stroke and 1.08 (0.90–1.01) for composite end point, and the adjusted odds ratio for poor functional outcome was 1.18 (0.96–1.44). The addition of serum calcium to conventional risk factors improved risk prediction of all-cause mortality, leading to a small but significant increase in C-statistics and reclassification with non-significant integrated discrimination improvement (C-statistics, p = 0.02; net reclassification index 11.8%, p = 0.038; integrated discrimination improvement 0.08%, p = 0.42). ConclusionsHigh serum calcium levels at baseline were associated with all-cause mortality at 1-year after ischemic stroke, suggesting that serum calcium may be a potential prognostic biomarker and therapeutic target for ischemic stroke.

Non Type-1 Brugada pattern, diagnostic yield of 5 ECG criteria in a young adult cohort

Abstract Introduction Distinguishing between non-Type 1 Brugada pattern (non-T1BrP) and an athlete's ECG remains challenging and may have important prognostic implications. We aimed to study prevalence and the diagnostic yield of experts and non-experts for the electrocardiographic non-T1BrP criteria in the young adults from the Sudden Cardiac Death-Screening Of risk factorS (SCD-SOS) cohort. Methods We performed a cross-sectional study in which we reviewed 14662 ECGs of SCD-SOS survey participants and selected 2494 that presented a rSr'-pattern in V1-V2. Among these, 98 were classified by experts in hereditary arrhythmic syndromes for the presence of non-T1BrP and by non-experts who performed manual measurements of the diagnostic criteria based on triangle formed by r'-wave. We estimated intra and interobserver concordance for each criterion, and used logistic regression and receiver operating characteristics (ROC) analysis and C-statistics for diagnostic accuracy and definition of the most appropriate cut-off values. Results We detected a rSr'-pattern in V1-V2 in 17% of the individuals and found that it was associated with higher PQ and QTc intervals, male gender and lower BMI. The manual measurements of non-T1BrP criteria were reproducible: we had high intraobserver concordance coefficients (CC) ranging from 0.90 to 0.94 (except for d(B) that had 0.66), but interobserver CC were lower (0.45–0.68). The measurements performed were highly correlated with non-T1BrP diagnosis and the criteria with higher discriminatory capacity were the distance d(B) (AUC 0.77; 95% CI0.69–0.84) and the degree of ST-ascent (AUC 0.79; 95% CI 0.72–0.86). The cut-offs defined by other authors had very low sensitivity (8–12%), despite high specificity (98%), so we defined new cut-offs: d(A) ≥2mm, d(B) ≥1.25mm, d(B)/h ≥0.38, β-angle ≥19° and ST-ascent ≥1mm. The addition of the degree of ST-ascent to a model with these 4 parameters presented an increase in C-statistics from 0.77 (95% CI: 0.68–0.86) to 0.83 (95% CI: 0.75–0.91) for the diagnosis of non-T1BrP by an expert in Sudden Arrhythmic Death and Channelopathies. Conclusion A rSr'-pattern in precordial leads V1-V2 is a frequent finding and the detection of non-T1BrP by using the aforementioned 5 measurements is reproducible and accurate. In this study, we describe new cut-off values that may help untrained clinicians to identify young individuals who should be referred for provocative drug testing for Brugada Syndrome. Accuracy of non-T1 BrP criteria Funding Acknowledgement Type of funding source: None

IgA Nephropathy Susceptibility Loci and Disease Progression.

At least 20 susceptibility loci of IgA nephropathy have been identified by genome-wide association studies to date. Whether these loci were associated with disease progression is unclear. We enrolled 613 adult patients with IgA nephropathy for a follow-up of ≥12 months. All 20 IgA nephropathy susceptibility loci were selected and their tag single nucleotide polymorphisms (SNPs) were genotyped. After strict quality control, 16 SNPs and 517 patients with IgA nephropathy were eligible for subsequent analysis. Progression was defined as ESKD or 50% decrease in eGFR. A stepwise Cox regression analysis of all SNPs on Akaike information criterion was performed to select the best model. A four-SNP model, rs11150612 (ITGAM-ITGAX), rs7634389 (ST6GAL1), rs2412971 (HORMAD2), and rs2856717 (HLA-DQ/DR), was selected as the best predictive model. The genetic risk score calculated on the basis of the four SNPs was independently associated with disease progression before (hazard ratio [HR], 1.65; 95% confidence interval [95% CI], 1.29 to 2.12) and after adjustment by a recently reported clinical model (HR, 1.29; 95% CI, 1.03 to 1.62) or clinical-pathologic model (HR, 1.35; 95% CI, 1.03 to 1.77). Compared with low genetic risk, patients with middle genetic risk had a 2.12-fold (95% CI, 1.33 to 3.40) increase of progression risk, whereas patients with high genetic risk had 3.61-fold (95% CI, 2.00 to 6.52) progression risk increase. In addition, incorporation of genetic risk score could potentially increase discrimination of the clinical model (c-statistic increase from 0.83 to 0.86) or the clinical-pathologic model (c-statistic increase from 0.82 to 0.85) in predicting 5-year progression risk. The four-SNP genetic risk score was independently associated with IgA nephropathy progression and could enhance the performance of clinical and clinical-pathologic risk models.

Risk prediction in post-infarction patients with moderately reduced left ventricular ejection fraction by combined assessment of the sympathetic and vagal cardiac autonomic nervous system

AimMost deaths after myocardial infarction (MI) occur in patients with normal or moderately reduced left ventricular ejection fraction (LVEF >35%). Periodic repolarization dynamics (PRD) and deceleration capacity (DC) are novel ECG-based markers related to sympathetic and vagal cardiac autonomic nervous system activity. Here, we test the combination of PRD and DC to predict risk in post-infarction patients with LVEF >35%. Methods and resultsWe included 823 survivors of acute MI with LVEF >35%, aged ≤80years and in sinus rhythm. PRD and DC were obtained from 30-min ECG-recordings within the second week after index infarction and dichotomized at established cut-off values of ≥5.75deg2 and ≤2.5ms, respectively. Patients were classified as having normal (CAF 0), partly abnormal (DC or PRD abnormal; CAF 1) or abnormal cardiac autonomic function (DC and PRD abnormal; CAF 2). Primary endpoint was 5-year all-cause mortality. Within the first 5years of follow-up, 51 patients died (6.2%). PRD and DC effectively stratified patients into low-risk (CAF 0; n=562), intermediate-risk (CAF 1; n=193) and high-risk patients (CAF 2; n=68) with cumulative 5-year mortality rates of 2.9%, 9.4% and 25.2%, respectively (p<0.001). On multivariable analyses, CAF was independent from established risk factors (GRACE-score, diabetes mellitus, mean heart rate, heart rate variability). Addition of CAF significantly improved the model (increase of C-statistics from 0.732 (0.651–0.812) to 0.777 (0.703–0.850), p=0.047; continuous NRI (0.400, 95% CI 0.230–0.560, p<0.001); IDI (0.056, 95% CI 0.022–0.122, p<0.001)). ConclusionCAF identifies new high-risk post-MI patients with LVEF >35% which might benefit from prophylactic strategies.

Bedside autonomic risk stratification after myocardial infarction by means of short-term deceleration capacity of heart rate.

Twenty-four-hour deceleration capacity (DC24h) of heart rate is a strong predictor of mortality after myocardial infarction (MI). Assessment of DC from short-term recordings (DCst) would be of practical use in everyday clinical practice but its predictive value is unknown. Here, we test the usefulness of DCst for autonomic bedside risk stratification after MI. We included 908 patients after acute MI enrolled in Munich and 478 patients with acute (n = 232) and chronic MI (n = 246) enrolled in Tuebingen, both in Germany. We assessed DCst from high-resolution resting electrocardiogram (ECG) recordings (<30 min) performed under standardized conditions in supine position. In the Munich cohort, we also assessed DC24h from 24-h Holter recordings. Deceleration capacity was dichotomized at the established cut-off value of ≤ 2.5 ms. Primary endpoint was 3-year mortality. Secondary endpoint was 3-year cardiovascular mortality. In addition to DC, multivariable analyses included the Global Registry of Acute Coronary Events score >140 and left ventricular ejection fraction ≤ 35%. During follow-up, 48 (5.3%) and 48 (10.0%) patients died in the Munich and Tuebingen cohorts, respectively. On multivariable analyses, DCst ≤ 2.5 ms was the strongest predictor of mortality, yielding hazard ratios of 5.04 (2.68-9.49; P < 0.001) and 3.19 (1.70-6.02; P < 0.001) in the Munich and Tuebingen cohorts, respectively. Deceleration capacity assessed from short-term recordings ≤ 2.5 ms was also an independent predictor of cardiovascular mortality in both cohorts. Implementation of DCst ≤ 2.5 ms into the multivariable models led to a significant increase of C-statistics and integrated discrimination improvement score. Deceleration capacity assessed from short-term recordings is a strong and independent predictor of mortality and cardiovascular mortality after MI, which is complementary to existing risk stratification strategies.

Noninvasive detection of increased carotid artery temperature in patients with coronary artery disease predicts major cardiovascular events at one year: Results from a prospective multicenter study

Background and aimsLimited prospective data have been reported regarding the impact of carotid inflammation on cardiovascular events in patients with coronary artery disease (CAD). Microwave radiometry (MWR) is a noninvasive, simple method that has been used for evaluation of carotid artery temperature which, when increased, predicts ‘inflamed’ plaques with vulnerable characteristics. We prospectively tested the hypothesis that increased carotid artery temperature predicts future cerebro- and cardiovascular events in patients with CAD. MethodsConsecutive patients from 3 centers, with documented CAD by coronary angiography, were studied. In both carotid arteries, common carotid intima-media thickness and plaque thickness were evaluated by ultrasound. Temperature difference (ΔT), measured by MWR, was considered as the maximal temperature along the carotid artery minus the minimum; ΔT ≥0.90 °C was assigned as high. Major cardiovascular events (MACE, death, stroke, myocardial infarction or revascularization) were recorded during the following year. ResultsIn total, 250 patients were studied; of them 40 patients (16%) had high ΔT values in both carotid arteries. MACEs occurred in 30% of patients having bilateral high ΔT versus 3.8% in the remaining patients (p<0.001). Bilateral high ΔT was independently associated with increased one-year MACE rate (HR = 6.32, 95% CI 2.42–16.53, p<0.001, by multivariate cox regression hazard model). The addition of ΔT information on a baseline model based on cardiovascular risk factors and extent of CAD significantly increased the prognostic value of the model (c-statistic increase 0.744 to 0.845, pdif = 0.05) ConclusionsCarotid inflammation, detected by MWR, has an incremental prognostic value in patients with documented CAD.

An age- and sex-specific gene expression score is associated with revascularization and coronary artery disease: Insights from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial

Identifying predictors of coronary artery disease (CAD)-related procedures and events remains a priority. We measured an age- and sex-specific gene expression score (ASGES) previously validated to detect obstructive CAD (oCAD) in symptomatic nondiabetic patients in the PROMISE trial. The outcomes were oCAD (≥70% stenosis in ≥1 vessel or ≥50% left main stenosis on CT angiography [CTA]) and a composite endpoint of death, myocardial infarction, revascularization, or unstable angina. The ASGES was determined in 2370 nondiabetic participants (47.5% male, median age 59.5 years, median follow-up 25 months), including 1137 with CTA data. An ASGES >15 was associated with oCAD (odds ratio 2.5 [95% CI 1.6-3.8], P<.001) and the composite endpoint (hazard ratio [HR] 2.6 [95% CI 1.8-3.9], P<.001) in unadjusted analyses. After adjustment for Framingham risk, an ASGES >15 remained associated with the composite endpoint (P=.02); the only component that was associated was revascularization (adjusted HR 2.69 [95% CI 1.52-4.79], P<.001). Compared to noninvasive testing, the ASGES improved prediction for the composite (increase in c-statistic=0.036; continuous net reclassification index=43.2%). Patients with an ASGES ≤15 had a composite endpoint rate no different from those with negative noninvasive test results (3.2% vs. 2.6%, P=.29). A blood-based genomic test for detecting oCAD significantly predicts near-term revascularization procedures, but not non-revascularization events. Larger studies will be needed to clarify the risk with non-revascularization events.

Improving prediction models with new markers: a comparison of updating strategies.

BackgroundNew markers hold the promise of improving risk prediction for individual patients. We aimed to compare the performance of different strategies to extend a previously developed prediction model with a new marker.MethodsOur motivating example was the extension of a risk calculator for prostate cancer with a new marker that was available in a relatively small dataset. Performance of the strategies was also investigated in simulations. Development, marker and test sets with different sample sizes originating from the same underlying population were generated. A prediction model was fitted using logistic regression in the development set, extended using the marker set and validated in the test set. Extension strategies considered were re-estimating individual regression coefficients, updating of predictions using conditional likelihood ratios (LR) and imputation of marker values in the development set and subsequently fitting a model in the combined development and marker sets. Sample sizes considered for the development and marker set were 500 and 100, 500 and 500, and 100 and 500 patients. Discriminative ability of the extended models was quantified using the concordance statistic (c-statistic) and calibration was quantified using the calibration slope.ResultsAll strategies led to extended models with increased discrimination (c-statistic increase from 0.75 to 0.80 in test sets). Strategies estimating a large number of parameters (re-estimation of all coefficients and updating using conditional LR) led to overfitting (calibration slope below 1). Parsimonious methods, limiting the number of coefficients to be re-estimated, or applying shrinkage after model revision, limited the amount of overfitting. Combining the development and marker set using imputation of missing marker values approach led to consistently good performing models in all scenarios. Similar results were observed in the motivating example.ConclusionWhen the sample with the new marker information is small, parsimonious methods are required to prevent overfitting of a new prediction model. Combining all data with imputation of missing marker values is an attractive option, even if a relatively large marker data set is available.Electronic supplementary materialThe online version of this article (doi:10.1186/s12874-016-0231-2) contains supplementary material, which is available to authorized users.

Usefulness of Psoas Muscle Area to Predict Mortality in Patients Undergoing Transcatheter Aortic Valve Replacement

Frailty has become high-priority theme in cardiovascular diseases because of aging and increasingly complex nature of patients. Low muscle mass is characteristic of frailty, in which invasive interventions are avoided if possible because of decreased physiological reserve. This study aimed to determine if the psoas muscle area (PMA) could predict mortality and to investigate its utility in patients who underwent transcatheter aortic valve replacement (TAVR). We retrospectively reviewed 232 consecutive patients who underwent TAVR. Cross-sectional areas of the psoas muscles at the level of fourth lumbar vertebra were measured by computed tomography and normalized to body surface area. Patients were divided into tertiles according to the normalized PMA for each gender (men: tertile 1, 1,708 to 1,178mm(2)/m(2); tertile 2, 1,176 to 1,011mm(2)/m(2); and tertile 3, 1,009 to 587mm(2)/m(2); women: tertile 1, 1,436 to 962mm(2)/m(2); tertile 2, 952 to 807mm(2)/m(2); and tertile 3, 806 to 527mm(2)/m(2)). Smaller normalized PMA was independently correlated with women and higher New York Heart Association classification. After adjustment for multiple confounding factors, the normalized PMA tertile was independently associated with mortality at 6months (adjusted hazard ratio 1.53, 95% confidence interval 1.06 to 2.21). Kaplan-Meier analysis showed that tertile 3 had higher mortality rates than tertile 1 at 6months (14% and 31%, respectively, p= 0.029). Receiver-operating characteristic analysis showed that normalized PMA provided the increase of C-statistics for predicting mortality for a clinical model and gait speed. In conclusion, PMA is an independent predictor of mortality after TAVR and can complement a clinical model and gait speed.