Model Of Conventional Risk Factors Research Articles

Electrocardiography score based on the Minnesota code classification system predicts cardiovascular mortality in an asymptomatic low-risk population

Background The use of a single abnormal finding on electrocardiography (ECG) is not recommended for stratifying the risk of cardiovascular (CV) events in low-risk general populations because of its low discriminative power. However, the value of a scoring system containing multiple abnormal ECG findings for predicting CV death has not been sufficiently evaluated. Methods In a prospective community-based cohort study, 8417 participants without atherosclerotic CV diseases (ASCVDs) and any related symptoms were followed for 18 years. The standard 12-lead ECGs were recorded at baseline and the ECG findings were categorized using the Minnesota code classification. CV deaths were defined as death from myocardial infarction (MI), chronic ischemic heart disease, heart failure, fatal arrhythmia, cerebrovascular event, pulmonary thromboembolism, peripheral vascular disease and sudden cardiac arrest and identified using the Korean National Statistical Office (KOSTAT) database. Results In a multivariate Cox proportional hazard (CPH) model, major and minor ST-T wave abnormalities, atrial fibrillation (AF), Q waves in the anterior leads, the lack of Q waves in the posterior leads, high amplitudes of the left and right precordial leads, left axis deviation and sinus tachycardia were associated with higher risks of CV deaths. The ECG score consisted of these findings showed modest predictive values represented by C-statistics that ranged from 0.632 to 760 during the follow-up and performed better in the early follow-up period. The ECG score independently predicted CV death after adjustment for relevant covariates in a multivariate model, and improved the predictive performance of the 10-year ASCVD risk estimator and a model of conventional risk factors including age, diabetes and current smoking. The combined ECG score (Harrell’s C-index: 0.852, 95% confidence interval [CI], 0.828–0.876) composed of the ECG score and the conventional risk factors outperformed the 10-year ASCVD risk estimator (Harrell’s C-index: 0.806; 95% CI, 0.780–0.833) and the model of the conventional risk factors (Harrell’s C-index: 0.841, 95% CI, 0.817–0.865) and exhibited an excellent goodness of fit between the predicted and observed probabilities of CV death. Conclusions The ECG score could be useful to predict CV death independently and may add value to the conventional CV risk estimators regarding the risk stratification of CV death in asymptomatic low-risk general populations.

The Systemic Inflammation Index Predicts Poor Clinical Prognosis in Patients with Initially Diagnosed Acute Coronary Syndrome Undergoing Primary Coronary Angiography.

Systemic inflammation index (SII: neutrophil count * platelet count/lymphocyte count) is a new inflammatory marker that can reflect the degree of systemic inflammatory response after coronary artery disease (CAD). However, the predictive value of the SII for clinical prognosis in patients with initially diagnosed acute coronary syndrome (ACS) has yet to be thoroughly studied. Patients with initially diagnosed ACS who underwent primary coronary angiography in our hospital from January 2019 to April 2021 were included in this study. 757 patients with ACS who underwent primary coronary angiography were enrolled. According to the baseline SII level, the patients were divided into a high SII group and a low SII group. The primary endpoint was major cardiovascular events (MACEs), defined as cardiac death, non-fatal myocardial infarction (MI), and non-fatal stroke. At a median follow-up of 33.9 months, 140 (18.5%) MACEs were recorded. Receiver operating characteristic (ROC) curve analysis showed that SII's best cut-off value for predicting MACEs was 713.9*109/L. Kaplan-Meier survival curve analysis showed that the survival rate of the low SII group was higher than the high SII group (P<0.001). Compared with the low SII group, the risk of MACEs was significantly increased in the high SII group (89 cases (33.3%) vs.51 patients (10.4%), P<0.001). Univariate and multivariate Cox regression analysis manifested that high SII level was independently associated with the occurrence of MACEs in patients with ACS undergoing primary coronary angiography (adjusted hazard ratio [HR]: 2.915, 95% confidence interval (CI%): 1.830-4.641, P<0.001). Adding SII to the conventional risk factor model improved the predictive value of MACEs. This study showed that elevated SII was associated with adverse cardiovascular prognosis in patients with ACS undergoing primary coronary angiography, making SII a valuable predictor of poor prognosis in patients with ACS undergoing primary coronary angiography.

Triglyceride-glucose index is associated with severe obstructive coronary artery disease and atherosclerotic target lesion failure among young adults

BackgroundEarly diagnosis and treatment effectiveness of early-onset coronary artery disease (EOCAD) are crucial, and non-invasive predictive biomarkers are needed for young adults. We aimed to evaluate the usefulness of the triglyceride-glucose (TyG) index, a novel marker of insulin resistance, in identifying young CAD patients and predicting their risk of developing target lesion failure (TLF).MethodsWe recruited EOCAD patients (luminal narrowing ≥ 70%) and controls free from CAD (luminal narrowing < 30%), both aged 45 years or younger, from 38 hospitals in China between 2017 and 2020. EOCAD patients who underwent successful percutaneous coronary intervention were followed for incident TLF. TyG index was defined as Ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2]. We used logistic regression and Cox proportional hazards modeling to evaluate the association of TyG index with prevalent EOCAD and incident TLF, respectively. The discriminatory ability of TyG index was assessed by the area under the receiver-operating characteristic curve (AUC).ResultsAmong the included 1513 EOCAD patients (39.6 ± 4.4 years, 95.4% male) and 1513 age-matched controls (39.0 ± 4.4 years, 46.4% male), TyG index was positively associated with the prevalence of EOCAD (adjusted odds ratio: 1.40, 95% confidence interval [CI] 1.23–1.60, per standard deviation [SD] increase in TyG index). The addition of TyG index to an empirical risk model provided an improvement in diagnostic ability for EOCAD, with a net reclassification improvement of 0.10 (95% CI 0.03–0.17, p = 0.005). During a medium of 33 month (IQR: 31–34 months) follow-up, 43 (3.3%) patients experienced TLF. Multivariate Cox regression model revealed that TyG index was an independent risk factor for TLF (adjusted hazard ratio [HR]: 2.410, 95% CI 1.07–5.42 comparing the top to bottom TyG index tertile groups; HR: 1.30, 95% CI 1.01–1.73, per SD increase in TyG index). Compared with a model of conventional risk factors alone, the addition of the TyG index modestly improved the AUC (0.722–0.734, p = 0.04) to predict TLF.ConclusionsTyG index is positively associated with prevalent EOCAD and incident TLF. TyG index appeared to be a valuable component of future efforts to improve CAD risk stratification and TLF outcome prediction among young adults.

Comparison of Genetic Susceptibility to Coronary Heart Disease in the Hungarian Populations: Risk Prediction Models for Coronary Heart Disease.

Background and Aim: It was evaluated whether the integration of genetic risk scores (GRS-unweighted, wGRS-weighted) into conventional risk factor (CRF) models for coronary heart disease or acute myocardial infarction (CHD/AMI) could improve the predictive ability of the models. Methods: Subjects and data collected in a previous survey were used to perform regression and ROC curve analyses as well as to examine the role of genetic components. Thirty SNPs were selected, and genotype and phenotype data were available for 558 participants (general: N = 279 and Roma: N = 279). Results: The mean GRS (27.27 ± 3.43 vs. 26.68 ± 3.51, p = 0.046) and wGRS (3.52 ± 0.68 vs. 3.33 ± 0.62, p = 0.001) were significantly higher in the general population. The addition of the wGRS to the CRF model yielded the strongest improvement in discrimination among Roma (from 0.8616 to 0.8674), while the addition of GRS to the CRF model yielded the strongest improvement in discrimination in the general population (from 0.8149 to 0.8160). In addition to that, the Roma individuals were likely to develop CHD/AMI at a younger age than subjects in the general population. Conclusions: The combination of the CRFs and genetic components improved the model's performance and predicted AMI/CHD better than CRFs alone.

Triglyceride-Glucose Index Independently Predicts New-Onset Atrial Fibrillation After Septal Myectomy for Hypertrophic Obstructive Cardiomyopathy Beyond the Traditional Risk Factors.

The triglyceride–glucose index is a valuable marker of insulin resistance. However, the predictive value of this index for postoperative atrial fibrillation in patients undergoing septal myectomy remains unclear. A total of 409 patients with hypertrophic obstructive cardiomyopathy who underwent septal myectomy were recruited in this study. The triglyceride–glucose index was calculated for all patients preoperatively. All patients underwent clinical data collection, blood sampling, and standard echocardiographic examinations during hospitalization. The prevalence of postoperative atrial fibrillation was approximately 15% in the present study. Multivariate logistic regression revealed that age (odds ratio [OR]: 1.053, 95% CI: 1.016–1.090, P = 0.004), hypertension (OR: 2.399, 95% CI: 1.228–4.686, P = 0.010), left atrial diameter (OR: 1.101, 95% CI: 1.050–1.155, P < 0.001), and triglyceride–glucose index (OR: 4.218, 95% CI: 2.381–7.473, P < 0.001) were independent risk factors for postoperative atrial fibrillation in patients undergoing septal myectomy. In receiver operating characteristic curve analysis, the triglyceride–glucose index could provide a moderate predictive value for postoperative atrial fibrillation after septal myectomy 0.723 (95% CI: 0.650–0.796, P < 0.001). Moreover, adding the triglyceride–glucose index to conventional risk factor model could numerically but not significantly increase our ability to predict postoperative atrial fibrillation (area under the receiver: 0.742 (0.671–0.814) vs. 0.793 (0.726–0.860), p = 0.065) after septal myectomy. In our retrospective cohort study, the triglyceride–glucose index was identified as an independent predictor of postoperative atrial fibrillation in patients undergoing septal myectomy.

Non-alcoholic fatty liver disease does not increase dementia risk although histology data might improve risk prediction

Background & AimsNon-alcoholic fatty liver disease (NAFLD) is common in the general population, but its association with dementia is unclear. We aimed to assess the risk of dementia related to NAFLD, and to determine whether histological parameters could improve the predictive capacity of a conventional risk model for dementia in patients with biopsy-proven NAFLD.MethodsA retrospective matched cohort study of 656 NAFLD patients underwent liver biopsy at 2 hospitals between 1971 and 2009. Up to 10 individuals (controls) from the general population (n = 6,436) were matched for age, sex, and municipality to each patient. Dementia was ascertained from National registers until 2014. Using Cox regression, we estimated hazard ratios for dementia with 95% confidence intervals. In the biopsy cohort, the discriminative power of adding histological markers to a conventional risk model was assessed by Harrell’s C-index and compared with a likelihood-ratio test.ResultsDuring a mean follow-up of 19.7 ± 8.7 years, 3.3% of the NAFLD patients and 4.9% of the controls developed dementia (p = 0.07). Overall, NAFLD was not significantly associated with incident dementia. In the biopsy cohort, the model of conventional risk factors (age, sex, hypertension, and cardiovascular diseases) had a C-index of 0.912 to predict incident dementia. Adding individual histological parameters significantly increased the prediction of dementia, with the most pronounced improvement for fibrosis stage (C-index = 0.938, p <0.05).ConclusionsAlthough NAFLD was not associated with the risk of dementia, we found that adding histological markers to a conventional risk model for dementia enhanced the predictive capacity, indicating a shared metabolic origin.Lay summaryBoth non-alcoholic fatty liver disease (NAFLD) and dementia are increasing in prevalence because of a more sedentary lifestyle, increased prevalence of obesity and population ageing. However, the link between these 2 diseases is not well studied. We investigated the association between NAFLD and the risk of dementia and found no association. However, liver histology parameters, especially fibrosis, could significantly improve the prediction of dementia risk.

High-Sensitive Cardiac Troponin T as a Reliable Biochemical Signature for Improvements of Mortality Prediction in Patients with Intracerebral Haemorrhage

Summary: BackgroundHigh-sensitive cardiac troponin T (hs-cTnT), as a preferred biomarker, has been used for auxiliary diagnosis and risk stratification of acute myocardial infarction. The prognostic value of hs-cTnT in intracerebral haemorrhage (ICH) remains unclear. Methods: To gauge if the hs-cTnT, either alone or combined with other risk factors, has the potential to predict in-hospital mortality among the ICH population in a diverse clinical scenario setting. We performed a multi-center, population-based, retrospective cohort study between November 2016 and December 2018. Admission hs-cTnT in serum was accessed, and additional information, including the demographics, baseline laboratory parameters. Clinical and imaging characteristic was collected as well. The primary outcome was in-hospital all-cause mortality. The associations between hs-cTnT and in-hospital death were assessed by multinomial logistic regression. We also use the Net Reclassification Index analysis strategy to address the incremental prognostic impact of hs-cTnT. Findings: Elevated high-sensitivity cardiac troponin (hs-cTnT) was observed in the entire population of 485 non-survival ICH patients, but show diversity by age, gender, and disease severity. After adjusting for confounding factors, a normalization of hs-cTnT concentrations was significantly associated with higher in-hospital death (odd's ratio 1.84, 95% CI: 1.31, 2.59, P=0.0005). Notably, patients with the highest quartile of hs-cTnT levels face a 6.98-fold higher risk of in-hospital death compared with those in the lowest quartile (OR 6.98, 95%CI 2.11-23.10; P=0.0015). More importantly, incorporating hs-cTnT into the conventional risk factor model significantly increased the C statistic in predicting in-hospital mortality (0.859 vs. 0.874; P= 0.0188). Further subgroup analyses suggested the additional prediction value of hs-cTnT was more sensitive to younger adults (P=0.0208), males (P=0.0189), and tend to those with severity ICH stage (P=0.0975). Interpretation: Elevated hs-cTnT is independently associated with an increased risk of in-hospital death. A combination of hs-cTnT and conventional risk factors promoted the prognostic value of ICH, in particular, sensitive to young adults, males, and severity stage of ICH, highlighting the value of heterogeneity and personalized care in the management of ICH. Funding Statement: This paper presents independent research funded by the significant application demonstration project of the Chengdu Science and Technology Bureau (2019-YF09-00211-SN). CY is supported by 1.3.5 project for disciplines of excellence, West China Hospital,Sichuan University (18HXFH010). Declaration of Interests: All authors declare no competing interests. Ethics Approval Statement: The Biomedical Research Ethics Committee of West China Hospital approved this study. The requirement for informed consent was waived for this retrospective analysis of anonymous data.

Growth Differentiation Factor 15 and NT-proBNP as Blood-Based Markers of Vascular Brain Injury and Dementia.

BackgroundGDF15 (growth differentiation factor 15) and NT‐proBNP (N‐terminal pro‐B‐type natriuretic peptide) may offer promise as biomarkers for cognitive outcomes, including dementia. We determined the association of these biomarkers with cognitive outcomes in a community‐based cohort.Methods and ResultsPlasma GDF15 (n=1603) and NT‐proBNP levels (n=1590) (53% women; mean age, 68.7 years) were measured in dementia‐free Framingham Offspring cohort participants at examination 7 (1998–2001). Participants were followed up for incident dementia. Secondary outcomes included Alzheimer disease dementia, magnetic resonance imaging structural brain measures, and neurocognitive performance. During a median 11.8‐year follow‐up, 131 participants developed dementia. On multivariable Cox proportional‐hazards analysis, higher circulating GDF15 was associated with an increased risk of incident all‐cause and Alzheimer disease dementia (hazard ratio [HR] per SD increment in natural log‐transformed biomarker value, 1.54 [95% CI, 1.22–1.95] and 1.37 [95% CI, 1.03–1.81], respectively), whereas higher plasma NT‐proBNP was also associated with an increased risk of all‐cause dementia (HR, 1.32; 95% CI, 1.05–1.65). Elevated GDF15 was associated with lower total brain and hippocampal volumes, greater white matter hyperintensity volume, and poorer cognitive performance. Elevated NT‐proBNP was associated with greater white matter hyperintensity volume and poorer cognitive performance. Addition of both biomarkers to a conventional risk factor model improved dementia risk classification (net reclassification improvement index, 0.25; 95% CI, 0.05–0.45).ConclusionsElevated plasma GDF15 and NT‐proBNP were associated with vascular brain injury on magnetic resonance imaging, poorer neurocognitive performance, and increased risk of incident dementia in individuals aged >60 years. Both biomarkers improved dementia risk classification beyond that of traditional clinical risk factors, indicating their potential value in predicting incident dementia.

Prognostic significance of plasma IL-2 and sIL-2R\u03b1 in patients with first-ever ischaemic stroke

BackgroundAn imbalance between circulating neuroprotective and neurotoxic T cell subsets leads to poor prognosis in acute ischaemic stroke (AIS). Preclinical studies have indicated that the soluble form of the interleukin-2 receptor α (sIL-2Rα)-IL-2 complex regulates T cell differentiation. However, the association between sIL-2Rα levels and AIS remains unclear.MethodsA total of 201 first-ever AIS patients within 24 h after stroke onset and 76 control subjects were recruited. The National Institutes of Health Stroke Scale (NIHSS) score and 3-month functional outcome (modified Rankin Scale [mRS] score) at admission were assessed. Plasma sIL-2Rα and IL-2 levels at admission were measured. Prognostic significance was identified by using univariate and multivariate logistic regression analyses.ResultsPatients with poor functional outcomes at 3 months had significantly higher levels of sIL-2Rα and lower levels of IL-2 than patients with good outcomes. Moreover, sIL-2Rα levels showed a strong positive correlation with NIHSS and mRS scores (p < 0.0001), whereas IL-2 levels were negatively correlated with mRS scores (p < 0.01). Univariate analyses showed that higher sIL-2Rα and IL-2 levels were associated with an increased and reduced risk of unfavourable outcomes, respectively. After adjusting for confounding variables, the sIL-2Rα level remained independently associated with an increased risk of an unfavourable outcome, and adding sIL-2Rα levels to the conventional risk factor model significantly improved risk reclassification (net reclassification improvement 17.56%, p = 0.003; integrated discrimination improvement 5.78%, p = 0.0003).ConclusionssIL-2Rα levels represent a novel, independent prognostic marker that can improve the currently used risk stratification of AIS patients. Our findings also highlight that elevated plasma sIL-2Rα and IL-2 levels manifested opposite correlations with functional outcome, underlining the importance of IL-2/IL-2R autocrine loops in AIS.

A novel multi-locus genetic risk score identifies patients with higher risk of generalized aggressive periodontitis.

Each genetic variant individually explains only a tiny proportion of the genetic variation with insignificant predictive power. The tool of multi-locus genetic risk score (GRS), which aggregates information from multiple genetic variants, has been widely used in many complex diseases but not yet applied to generalized aggressive periodontitis (GAgP). A total of 335 GAgP patients and 114 healthy controls were enrolled in the case-control study. The unweighted GRS (uGRS) and weighted GRS (wGRS) were calculated based on significant variants. Logistic regression models were conducted for the GRS-based association analyses on the risk of GAgP. Receiver operating characteristic analysis was performed to compare the discriminatory ability of predictors of GAgP risk. Four loci were found to be significantly associated with GAgP. They were matrix metalloproteinase 8 rs11225395 (odds ratio [OR]=1.40, 95% CI: 1.03 to 1.91), epidermal growth factor rs2237051 (OR=1.41, 95% CI: 1.03 to 1.93), PPAR-a rs4253623 (OR=1.53, 95% CI: 1.03 to 2.26), and apolipoprotein E rs429358 (OR=1.79, 95% CI: 1.08 to 2.97). Each additional point of the uGRS/wGRS was associated with a 50%/31% increased risk of developing GAgP (OR=1.50, 95% CI: 1.21 to 1.85 or OR=1.31, 95% CI: 1.14 to 1.51, respectively) after adjusting for age, sex, and body mass index (BMI). Participants in the high group of uGRS/wGRS (OR=2.87, 95% CI: 1.59 to 5.17 or OR=2.67, 95% CI: 1.46 to 4.88, respectively) and the middle group of uGRS/wGRS (OR=2.21, 95% CI: 1.29 to 3.78 or OR=1.88, 95% CI: 1.09 to 3.08, respectively) had an increased risk of GAgP compared with those in the low group of score after adjustment for age, sex, and BMI. The addition of GRS to a model of conventional risk factors improved discrimination by 4.5% (from 0.695 to 0.740, P=0.048). We demonstrated that the multi-locus GRS based on four significant single nucleotide polymorphisms might be useful to assess genetic predisposition to GAgP. The GRS in combination with conventional risk factors significantly improved the power of identifying subgroups of Chinese population with a particularly high risk for GAgP.

A Vascular Aging Index as Independent Predictor of Cardiovascular Events and Total Mortality in an Elderly Urban Population.

The morphology and function of the arteries can be directly measured using different established methods. This prospective cohort study aimed to translate 2 of these, aortic pulse wave velocity (aPWV) and carotid intima-media thickness (cIMT), into a combined Vascular Aging Index (VAI) and then evaluate the predictive power of aPWV, cIMT, and VAI. Patients (n = 2718) were included from the cardiovascular arm of the Malmö Diet and Cancer Study (median age 71.9 years, 62.2% females). Total follow-up time was 16 448 person-years and a composite cardiovascular disease (CVD) end point was used. Cox regressions yielded adjusted hazard ratios (95% confidence interval) per 1 standard deviation increment of loge aPWV, loge cIMT, and loge VAI of 1.25 (1.08-1.45, P = .003), 1.27 (1.13-1.44, P < .001), and 1.45 (1.26-1.68, P < .001), respectively. The C-statistics increased from 0.714 to 0.734 when adding aPWV and cIMT to a model of conventional risk factors. Net Reclassification Index also showed a significant (P < .001) improvement for the classification of event-free patients and no change for patients with events. A VAI based on aPWV and cIMT had a good predictive performance. Used together, aPWV and cIMT incrementally and significantly improve the prediction of CVD events by correctly down-adjusting the predicted risk for noncases.

A novel principled method for the measurement of vascular robustness uncovers hidden risk for premature CVD death.

The detection of high risk for premature death of cardiovascular disease (CVD) among individuals with low-to-moderate risk factor scores is a major challenge. Systems biology suggests that the vasculature's functional robustness against risk factor challenges may serve as a novel discriminator of mortality risk under similar risk factor loads. However, principled methods to measure vascular robustness are not available. To develop a score for the vasculature's functional robustness we used a recently presented method that applies computational physiological modeling to the quantitation of vascular function. We hypothesized that the expected inverse robustness-mortality association is verifiable as a significant robustness-calendar age trend in a cross-sectional investigation of a population cohort of risk factor-challenged individuals. Using only functional parameters of the cardiovascular system we applied multivariate linear regression to derive from our study population of 372 adults gender-specific multivariate robustness scoring algorithms. For any individual, the deviation of his/her robustness score from the value of the regression function characterizes the deviation of the individual's fatal CVD event probability from its age-appropriate fatal CVD event probability. Robustness correlated linearly with calendar age in our risk factor-challenged but not in our unchallenged cohorts. This observation supports the hypothesis of preferential elimination of less robust individuals along the aging trajectory under risk factor challenges. We conclude that physiologically principled scoring for vascular robustness may serve as a biomarker of vulnerability to CVD risk factor challenges, prognosticating otherwise undetectable elevated risk for premature CVD mortality. NEW & NOTEWORTHY We developed a principled method for the derivation of a vascular robustness score that we translated into a correction factor for calendar age. We demonstrated the score's potential to uncover risk for premature cardiovascular death in apparently healthy young adults whose risk elevation remains hidden in conventional risk factor models.

The cardiovascular robustness hypothesis: Unmasking young adults' hidden risk for premature cardiovascular death

An undetected high risk for premature death of cardiovascular disease (CVD) among individuals with low-to-moderate risk factor levels is an acknowledged obstacle to CVD prevention.In this paper, we present the hypothesis that the vasculature's robustness against risk factor load will complement conventional risk factor models as a novel stratifier of risk. Figuratively speaking, mortality risk prediction without robustness scoring is akin to predicting the breaking risk of a lake's ice sheet considering load only while disregarding the sheet's bearing strength.Taking the cue from systems biology, which defines robustness as the ability to maintain function against internal and external challenges, we develop a robustness score from the physical parameters that comprehensively quantitate cardiovascular function. We derive the functional parameters using a recently introduced novel system, VascAssist 2 (iSYMED GmbH, Butzbach, Germany). VascAssist 2 (VA) applies the electronic-hydraulic analogy to a digital model of the arterial tree, replicating non-invasively acquired pule pressure waves by modulating the electronic equivalents of the physical parameters that describe in vivo arterial hemodynamics.As the latter is also subject to aging-associated degeneration which (a) progresses at inter-individually different rates, and which (b) affects the biomarker-mortality association, we express the robustness score as a correction factor to calendar age (CA), the dominant risk factor in all CVD risk factor models. We then propose a method for the validation of the score against known time-to-event data in reference populations.Our conceptualization of robustness implies that risk factor-challenged individuals with low robustness scores will face preferential elimination from the population resulting in a significant robustness-CA correlation in this strata absent in the unchallenged stratum. Hence, we also present an outline of a cross-sectional study design suitable to test this hypothesis. We finally discuss the objections that may validly be raised against our robustness hypothesis, and how available evidence encourages us to refute these objections.

High Level of Fasting Plasma Proenkephalin-A Predicts Deterioration of Kidney Function and Incidence of CKD.

High levels of proenkephalin-A (pro-ENK) have been associated with decreased eGFR in an acute setting. Here, we examined whether pro-ENK levels predict CKD and decline of renal function in a prospective cohort of 2568 participants without CKD (eGFR>60 ml/min per 1.73 m2) at baseline. During a mean follow-up of 16.6 years, 31.7% of participants developed CKD. Participants with baseline pro-ENK levels in the highest tertile had significantly greater yearly mean decline of eGFR (Ptrend<0.001) and rise of cystatin C (Ptrend=0.01) and creatinine (Ptrend<0.001) levels. Furthermore, compared with participants in the lowest tertile, participants in the highest tertile of baseline pro-ENK concentration had increased CKD incidence (odds ratio, 1.51; 95% confidence interval, 1.18 to 1.94) when adjusted for multiple factors. Adding pro-ENK to a model of conventional risk factors in net reclassification improvement analysis resulted in reclassification of 14.14% of participants. Genome-wide association analysis in 4150 participants of the same cohort revealed the strongest association of pro-ENK levels with rs1012178 near the PENK gene, where the minor T-allele associated with a 0.057 pmol/L higher pro-ENK level per allele (P=4.67x10-21). Furthermore, the T-allele associated with a 19% increased risk of CKD per allele (P=0.03) and a significant decrease in the instrumental variable estimator for eGFR (P<0.01) in a Mendelian randomization analysis. In conclusion, circulating plasma pro-ENK level predicts incident CKD and may aid in identifying subjects in need of primary preventive regimens. Additionally, the Mendelian randomization analysis suggests a causal relationship between pro-ENK level and deterioration of kidney function over time.

Validation of the 2014 European Society of Cardiology Guidelines Risk Prediction Model for the Primary Prevention of Sudden Cardiac Death in Hypertrophic Cardiomyopathy

The recently released 2014 European Society of Cardiology guidelines of hypertrophic cardiomyopathy (HCM) use a new clinical risk prediction model for sudden cardiac death (SCD), based on the HCM Risk-SCD study. Our study is the first external and independent validation of this new risk prediction model. The study population consisted of a consecutive cohort of 706 patients with HCM without prior SCD event, from 2 tertiary referral centers. The primary end point was a composite of SCD and appropriate implantable cardioverter-defibrillator therapy, identical to the HCM Risk-SCD end point. The 5-year SCD risk was calculated using the HCM Risk-SCD formula. Receiver operating characteristic curves and C-statistics were calculated for the 2014 European Society of Cardiology guidelines, and risk stratification methods of the 2003 American College of Cardiology/European Society of Cardiology guidelines and 2011 American College of Cardiology Foundation/American Heart Association guidelines. During follow-up of 7.7±5.3 years, SCD occurred in 42 (5.9%) of 706 patients (ages 49±16 years; 34% women). The C-statistic of the new model was 0.69 (95% CI, 0.57-0.82; P=0.008), which performed significantly better than the conventional risk factor models based on the 2003 guidelines (C-statistic of 0.55: 95% CI, 0.47-0.63; P=0.3), and 2011 guidelines (C-statistic of 0.60: 95% CI, 0.50-0.70; P=0.07). The HCM Risk-SCD model improves the risk stratification of patients with HCM for primary prevention of SCD, and calculating an individual risk estimate contributes to the clinical decision-making process. Improved risk stratification is important for the decision making before implantable cardioverter-defibrillator implantation for the primary prevention of SCD.

Left Ventricular Mass and the Risk of Sudden Cardiac Death: A Population‐Based Study

BackgroundLeft ventricular (LV) mass ascertained using echocardiography may enhance risk stratification for sudden cardiac death. The objective of this study was to assess the association between left ventricular mass and the risk of sudden cardiac death in a population‐based cohort and determine its incremental value beyond conventional risk predictors.Methods and ResultsAssessment of LV mass was based on echocardiography in a sample of 905 middle‐aged men representative of the general population (aged 42 to 61 years). During the follow‐up period of 20 years, there were a total of 63 sudden cardiac deaths. In a comparison of the top versus the bottom quartile of LV mass adjusted by body surface area (>120 versus <89 g/m2), the multivariable adjusted hazard ratio was 2.57 (95% CI 1.24 to 5.31, P=0.010). Further adjustment for LV function only modestly attenuated the risk of sudden cardiac death among men with LV mass of >120 g/m2 (hazard ratio 2.29, 95% CI 1.10 to 4.74, P=0.026). Addition of LV mass adjusted by body surface area to a conventional risk factor model for sudden cardiac death improved the integrated discrimination index by 0.033 (95% CI 0.009 to 0.057, P=0.007) and the category‐free net reclassification index by 0.501 (95% CI 0.092 to 0.911, P=0.016).ConclusionsIndexed LV mass by body surface area is an independent predictor of sudden cardiac death and may help improve the risk prediction of sudden cardiac death beyond conventional cardiovascular risk factors.

Interaction Between Geriatric Nutritional Risk Index and Decoy Receptor 3 Predicts Mortality in Chronic Hemodialysis Patients

Background: Protein-energy wasting (PEW) is common and associated with poor outcome in hemodialysis patients. In hemodialysis patients, geriatric nutritional risk index (GNRI) and decoy receptor 3 (DcR3) have been shown as the nutritional and inflammatory markers, respectively. The present study aimed to assess the predictive ability of GNRI and DcR3 for PEW status and long-term outcomes in chronic hemodialysis patients. Methods: A prospective cohort of 318 hemodialysis patients was conducted with a median follow-up of 54 months. Malnutrition-inflammation score (MIS) was used as the reference standard for the presence of PEW. Endpoints were cardiovascular and all-cause mortality. Results: Baseline GNRI had a strong negative correlation with DcR3 and MIS score. For patients with age < or ≥60, high DcR3 and low GNRI were independent predictors for the presence of PEW at baseline. At the end of the study, 81 patients died (27 cardiovascular deaths). The adjusted hazard ratios (95% confidence intervals) of low GNRI and high DcR3 were 1.93 (1.1-4.8) and 2.53 (1.2-5.5) for cardiovascular mortality and 1.85 (1.1-3.2) and 2.37 (1.5-3.7) for all-cause mortality, respectively. While integrated into a model of conventional risk factors, GNRI together with DcR3 further significantly improved the predictability for overall mortality (c statistic, 0.823). Conclusions: Low GNRI and high DcR3 were the alternatives for identifying hemodialysis patients at risk of PEW and overall mortality. Further studies are needed to verify whether timely recognition of hemodialysis patients with a high malnutrition-inflammation risk could reduce their mortality by appropriate interventional strategies.

Progression of Kidney Disease in Non-Diabetic Patients with Coronary Artery Disease: Predictive Role of Circulating Matrix Metalloproteinase-2, -3, and -9

BackgroundCirculating matrix metalloproteinase (MMP)-2, -3 and -9 are well recognized in predicting cardiovascular outcome in coronary artery disease (CAD), but their risks for chronic kidney disease (CKD) are lacking. Therefore, the present study aimed to investigate whether circulating MMP levels could independently predict future kidney disease progression in non-diabetic CAD patients.MethodsThe prospective study enrolled 251 non-diabetic subjects referred for coronary angiography, containing normal coronary artery (n = 30) and CAD with insignificant (n = 95) and significant (n = 126) stenosis. Estimated glomerular filtration rate (eGFR) was calculated using the CKD-EPI formula. eGFR decline rate was calculated and the primary endpoint was a decline in eGFR over 25% from baseline.ResultsThe eGFR decline rate (ml/min/1.73 m2 per year) in patients with CAD (1.22 [−1.27, 1.05]) was greater than that in those with normal coronary artery (0.21 [−2.63, 0.47], P<0.01). The circulating MMP-2, -3 and -9 were independently associated with faster eGFR decline among CAD patients. The mean follow-up period was 8.5±2.4 years, and 39 patients reached the primary endpoint. In multivariate Cox regression model, the adjusted hazard ratios of MMP-2 ≥861 ng/mL, MMP-3 ≥227 ng/mL and MMP-9 ≥49 ng/mL for predicting CKD progression were 2.47 (95% CI, 1.21 to 5.07), 2.15 (1.12 to 4.18), and 4.71 (2.14 to 10.4), respectively. While added to a model of conventional risk factors and baseline eGFR, MMP-2, -3 and -9 further significantly improved the model predictability for CKD progression (c statistic, 0.817). In the sensitivity analyses, the results were similar no matter if we changed the endpoints of a decline of >20% in eGFR from baseline or final eGFR < 60 mL/min/1.73 m2.ConclusionCirculating MMP-2, -3 and -9 are independently associated with kidney disease progression in non-diabetic CAD patients and add incremental predictive power to conventional risk factors.

Urinary excretion of kynurenine and tryptophan, cardiovascular events, and mortality after elective coronary angiography

Kynurenine is a potent endothelium-derived vasodilator. Its synthesis from tryptophan is stimulated by interferon γ and may represent an important compensatory pathway for the regulation of vascular function in inflammatory conditions. We assessed associations of urine kynurenine to tryptophan ratio (KTR) levels to incident major coronary events (MCEs), acute myocardial infarction (AMI), and ischaemic stroke and mortality in patients with suspected stable coronary artery disease (CAD). A total of 3224 patients (mean age 62 years, 69% men) underwent urine and blood sampling prior to elective coronary angiography and were subsequently followed up for median 55 months. A total of 8.4% experienced an MCE, 7.8% suffered an AMI, and 7.6% died. In age- and gender-adjusted analyses, the hazard ratios [HRs; 95% confidence intervals (CI)] of MCE, AMI, and all-cause mortality were 1.43 (1.29-1.59), 1.44 (1.29-1.59), and 1.38 (1.23-1.54) per standard deviation increment of the (log-transformed) urinary KTR, respectively. These estimates were only minimally attenuated after adjustment for potential confounders. The addition of the urine KTR to a model of conventional risk factors significantly improved goodness of fit, discrimination, and risk classification for these clinical endpoints. No association was seen between the urine KTR and the risk of incident ischaemic stroke. A novel urinary inflammation marker, KTR, is strongly associated with adverse prognosis in patients with suspected stable CAD. Underlying pathomechanisms should be further elucidated.

Serum uric acid associates with the incidence of type 2 diabetes in a prospective cohort of middle-aged and elderly Chinese

This study is to prospectively investigate the association between serum uric acid and the incidence of type 2 diabetes in middle-aged and elderly Chinese. This study consisted of 924 non-diabetic adults aged 40 years or older at baseline. Subjects who received antidiabetic therapies and those who responded positively to the 75-g oral glucose tolerance test according to the 1999 World Health Organization criteria were diagnosed as having type 2 diabetes. Ninety-eight subjects developed type 2 diabetes during the 3.5-year follow-up. The hazard ratio (HR) for incident diabetes was 1.50 [95% confidence interval (CI) 1.18-1.92] for the highest sex-specific quartile of serum uric acid compared with the lowest after controlling for confounders. Participants with hyperuricemia had an HR of 1.95 (95% CI 1.11-3.44) for incident diabetes compared with those without hyperuricemia. Compared with the lowest quartile, the highest quartile had an HR for incident diabetes of 2.45 (95% CI 1.39-4.33) in men and 1.39 (95% CI 1.04-1.84) in women after fully adjustment. Adding serum uric acid to a model of conventional risk factors for diabetes improved the area under the curve for prediction of type 2 diabetes by 5%. Serum uric acid was an independent predictor of incident type 2 diabetes in middle-aged and elderly Chinese.