Category-free Net Reclassification Index Research Articles

Estimated pulse wave velocity and risk of new-onset heart failure.

As a potential surrogate of carotid-femoral pulse wave velocity, estimated pulse wave velocity (ePWV) has been confirmed to independently predict the cardiovascular events, but the association between ePWV and heart failure has not been well confirmed. Therefore, we performed this cohort study to evaluate the association between ePWV and risk of new-onset heart failure. A total of 98269 employees (mean age: 51.77±12.56years, male accounted for 79.9%) without prior heart failure who participated in the 2006-2007 health examination were selected as the observation cohort, with an average follow-up of 13.85±1.40years. Area under the receiver operator characteristic curve (AUC) of ePWV was calculated in prediction of heart failure. The adjusted Cox proportional hazard models were used to estimate hazard ratios and 95% confidence intervals. The category-free net reclassification index (NRI) was calculated to evaluate the reclassification performance of cardiovascular risk models after adding ePWV. The AUC of ePWV was 0.74 in prediction of heart failure. After adjusting for the traditional cardiovascular risk factors except for age and blood pressure, the risk of new-onset heart failure increased by 35% [hazard ratio (HR): 1.35, 95% confidence interval (CI): 1.33-1.37] for each 1m/s increase in ePWV. Subgroup analysis showed that ePWV was significantly associated with incident heart failure regardless of THE presence (HR: 1.33, 95% CI: 1.31-1.36, P<0.01) or absence (HR: 1.59, 95% CI: 1.46-1.73, P<0.01) of cardiovascular risk factors, male (HR: 1.33, 95% CI: 1.31-1.36, P<0.01) or female (HR: 1.44, 95% CI: 1.38-1.51, P<0.01), young and middle-aged (<52years) (HR: 1.50, 95% CI: 1.41-1.58, P<0.01), or middle-aged and elderly (≥52years) (HR: 1.23, 95% CI: 1.21-1.26, P<0.01). The addition of ePWV to the traditional cardiovascular risk model including age and mean arterial pressure could significantly improve the reclassification ability by 31.1% (category-free NRI=0.311, P<0.01). ePWV was an independent predictor for new-onset heart failure.

AI-enabled cardiac chambers volumetry in coronary artery calcium scans (AI-CACTM) predicts heart failure and outperforms NT-proBNP: The multi-ethnic study of Atherosclerosis

IntroductionCoronary artery calcium (CAC) scans contain useful information beyond the Agatston CAC score that is not currently reported. We recently reported that artificial intelligence (AI)-enabled cardiac chambers volumetry in CAC scans (AI-CAC™) predicted incident atrial fibrillation in the Multi-Ethnic Study of Atherosclerosis (MESA). In this study, we investigated the performance of AI-CAC cardiac chambers for prediction of incident heart failure (HF). MethodsWe applied AI-CAC to 5750 CAC scans of asymptomatic individuals (52% female, White 40%, Black 26%, Hispanic 22% Chinese 12%) free of known cardiovascular disease at the MESA baseline examination (2000–2002). We used the 15-year outcomes data and compared the time-dependent area under the curve (AUC) of AI-CAC volumetry versus NT-proBNP, Agatston score, and 9 known clinical risk factors (age, gender, diabetes, current smoking, hypertension medication, systolic and diastolic blood pressure, LDL, HDL for predicting incident HF over 15 years. ResultsOver 15 years of follow-up, 256 HF events accrued. The time-dependent AUC [95% CI] at 15 years for predicting HF with AI-CAC all chambers volumetry (0.86 [0.82,0.91]) was significantly higher than NT-proBNP (0.74 [0.69, 0.77]) and Agatston score (0.71 [0.68, 0.78]) (p ​< ​0.0001), and comparable to clinical risk factors (0.85, p ​= ​0.4141). Category-free Net Reclassification Index (NRI) [95% CI] adding AI-CAC LV significantly improved on clinical risk factors (0.32 [0.16,0.41]), NT-proBNP (0.46 [0.33,0.58]), and Agatston score (0.71 [0.57,0.81]) for HF prediction at 15 years (p ​< ​0.0001). ConclusionAI-CAC volumetry significantly outperformed NT-proBNP and the Agatston CAC score, and significantly improved the AUC and category-free NRI of clinical risk factors for incident HF prediction.

Association of plasma proteomics with incident coronary heart disease in individuals with and without type 2 diabetes: results from the population-based KORA study.

Coronary heart disease (CHD) is a major global health concern, especially among individuals with type 2 diabetes (T2D). Given the crucial role of proteins in various biological processes, this study aimed to elucidate the aetiological role and predictive performance of protein biomarkers on incident CHD in individuals with and without T2D. The discovery cohort included 1492 participants from the Cooperative Health Research in the Region of Augsburg (KORA) S4 study with 147 incident CHD cases (45 vs. 102 cases in the group with T2D and without T2D, respectively) during 15.6 years of follow-up. The validation cohort included 888 participants from the KORA-Age1 study with 70 incident CHD cases (19 vs. 51 cases in the group with T2D and without T2D, respectively) during 6.9 years of follow-up. We measured 233 plasma proteins related to cardiovascular disease and inflammation using proximity extension assay technology. Associations of proteins with incident CHD were assessed using Cox regression and Mendelian randomization (MR) analysis. Predictive models were developed using priority-Lasso and were evaluated on top of Framingham risk score variables using the C-index, category-free net reclassification index (cfNRI), and relative integrated discrimination improvement (IDI). We identified two proteins associated with incident CHD in individuals with and 29 in those without baseline T2D, respectively. Six of these proteins are novel candidates for incident CHD. MR suggested a potential causal role for hepatocyte growth factor in CHD development. The developed four-protein-enriched model for individuals with baseline T2D (ΔC-index: 0.017; cfNRI: 0.253; IDI: 0.051) and the 12-protein-enriched model for individuals without baseline T2D (ΔC-index: 0.054; cfNRI: 0.462; IDI: 0.024) consistently improved CHD prediction in the discovery cohort, while in the validation cohort, significant improvements were only observed for selected performance measures (with T2D: cfNRI: 0.633; without T2D: ΔC-index: 0.038; cfNRI: 0.465). This study identified novel protein biomarkers associated with incident CHD in individuals with and without T2D and reaffirmed previously reported protein candidates. These findings enhance our understanding of CHD pathophysiology and provide potential targets for prevention and treatment.

Sex-specific association between monocyte to high-density lipoprotein cholesterol and extensive abdominal aortic calcification in humans.

Recent studies have identified monocyte-to-high-density lipoprotein cholesterol ratio (MHR) as a simple marker of atherosclerosis. Abdominal aortic calcification (AAC) is a direct result of vascular atherosclerosis. Our study aims to investigate the association between MHR and the prevalent extensive AAC and assess the value of MHR for identifying prevalent extensive AAC. 2857 subjects (28.07%) from the cross-sectional National Health and Nutrition Examination Survey 2013-2014 were included in our study. AAC was detected through dual-energy x-ray absorptiometry and quantified by Kauppila score. Extensive AAC was identified in 153 (10.44% of 1465) females and 146 (10.49% of 1392) males. With the full adjustment, each SD increase of MHR resulted in an 87.3% additional risk for extensive AAC in females. When dividing into quartiles, the top quartile had a 3.472 times risk of prevalent extensive AAC than the bottom quartile. However, no significant association was observed in males. Furthermore, smooth curve fitting implicated that the significant association was linear in the whole range of MHR among females. Additionally, ROC demonstrated an improvement in the identification of extensive AAC only among females when introducing MHR into established risk factors of atherosclerosis (0.808 vs. 0.864, p < 0.001). Finally, category-free net reclassification index and integrated discrimination index also supported the improvement by MHR in females. Our study revealed a linear association between MHR and prevalent extensive AAC in females. Moreover, our results implicated the potential value of MHR to refine the identification of prevalent extensive AAC in females.

Identification of ischemia-causing lesions using coronary plaque quantification and changes in fractional flow reserve derived from computed tomography across the lesion.

This study sought to evaluate the association between coronary plaque characteristics, changes in the fractional flow reserve (FFR) derived from computed tomography across the lesion (ΔFFRCT), and lesion-specific ischemia using the FFR in patients with suspected or known coronary artery disease. The study assessed coronary computed tomography (CT) angiography stenosis, plaque characteristics, ΔFFRCT, and FFR in 164 vessels of 144 patients. Obstructive stenosis was defined as stenosis ≥50%. An area under the receiver -operating characteristics curve (AUC) analysis was conducted to define the optimal thresholds for ΔFFRCT and the plaque variables. Ischemia was defined as a FFR of ≤0.80. The optimal cut-off value of ΔFFRCT was 0.14. Low-attenuation plaque (LAP) ≥76.23 mm3 and a percentage aggregate plaque volume (%APV) ≥28.91% can be used to predict ischemia independent of other plaque characteristics. The addition of LAP ≥76.23 mm3 and %APV ≥28.91% improved the discrimination (AUC, 0.742 vs. 0.649, P=0.001) and reclassification abilities [category-free net reclassification index (NRI), 0.339, P=0.027; relative integrated discrimination improvement (IDI) index, 0.093, P<0.001] of the assessments compared to the stenosis evaluation alone, and the addition of information about ΔFFRCT ≥0.14 further increased the discrimination (AUC, 0.828 vs. 0.742, P=0.004) and reclassification abilities (NRI, 1.029, P<0.001; relative IDI, 0.140, P<0.001) of the assessments. The addition of the plaque assessment and ΔFFRCT to the stenosis assessments improved the identification of ischemia compared to the stenosis assessment alone.

Serum N-terminal pro-B-type natriuretic peptide and cystatin C for acute kidney injury detection in critically ill adults in China: a prospective, observational study

ObjectiveSerum N-terminal pro-B-type natriuretic peptide (NT-proBNP) and cystatin C (sCysC) are available clinically and beneficial in diagnosing acute kidney injury (AKI). Our purpose is to identify the performance of their...

Incremental utility of circulating biomarkers for cardiovascular risk prediction beyond the updated SCORE2 model

Abstract Background Accurate risk prediction for future cardiovascular disease (CVD) is crucial for timely initiation of preventive measures in high-risk individuals. Most risk scores, such as the recently updated SCORE2 risk-prediction model supported by the European Society of Cardiology, consider only traditional cardiovascular risk factors. Whether the addition of circulating biomarkers to the existing SCORE2 model may improve risk prediction is unclear. Purpose We aimed to evaluate the incremental utility of four widely available circulating biomarkers to improve the prediction of 10-year CVD-risk beyond SCORE2. Methods Data from ten prospective population-based cohorts from seven countries across Europe were collected if information on SCORE2-variables and at least one of the following four investigational biomarkers was available: high-sensitivity cardiac troponin I (hs-cTnI), NT-pro-B-type natriuretic peptide (NT-proBNP), high-sensitivity C-reactive protein (hs-CRP) and creatinine-based estimated glomerular filtration rate (eGFR). Primary outcome was incidence of CVD at 10 years, defined as the composite of cardiovascular mortality, non-fatal myocardial infarction and non-fatal stroke. We used Fine and Gray models adjusted for competing-risk and SCORE2-variables as well as penalized cubic splines to assess and visualize the association of individual biomarkers with incident CVD. In a multimarker approach, we performed backward selection to identify biomarkers providing independent predictive value beyond SCORE2-components. C-indices and category-free net reclassification index (cfNRI) were used to compare the performance of the original SCORE2 model to the biomarker-extended model. Results In 78'507 individuals, median age was 50 years and 50.3% were females. NT-proBNP, hs-CRP and hs-cTnI but not eGFR showed strong associations with 10-year CVD-risk when adjusted for SCORE2 and provided incremental predictive value when individually added to SCORE2 (Figure 1). In a multimarker approach, all three biomarkers remained independently associated with CVD beyond SCORE2 with strongest association of NT-proBNP, followed by hs-CRP and hs-cTnI (Table 1). The simultaneous addition of these three biomarkers to the SCORE2 model significantly increased discrimination (C-index; 0.782 [95% CI, 0.757, 0.806] versus 0.793 [95% CI, 0.768, 0.817], Delta 0.011 [95% CI, 0.005, 0.016]) and risk reclassification, driven by an improvement in non-events (cfNRIoverall 0.17 [95% CI, 0.12, 0.22], cfNRIevents 0.06 [95% CI, 0.02, 0.11], cfNRInon-events 0.11 [95% CI, 0.10, 0.11]). Conclusion NT-proBNP, hs-CRP and hs-cTnI but not eGFR provide incremental predictive value when added to the SCORE2 risk-prediction model and may help to further improve personalized CVD-risk prediction. Funding Acknowledgement Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Community's Seventh Framework Programme (FP7/2007-2013)

Value of estimated glucose disposal rate to detect prevalent left ventricular hypertrophy: implications from a general population

ABSTRACT Background Insulin resistance plays a pivotal role in developing left ventricular hypertrophy (LVH). Researchers have identified the estimated glucose disposal rate (eGDR) as a simple and cost-effective surrogate of insulin resistance. Our work aims to investigate the association between eGDR and the prevalent LVH and explore the incremental value of eGDR to detect prevalent LVH. Methods The present work enrolled 3839 subjects from a cross-sectional survey conducted between October 2019 to April 2020 in the rural areas of southeastern China. eGDR was calculated based on waist-to-hip circumference ratio, hypertension, and glycated hemoglobin. Results The prevalence of LVH was 17.30%. After adjusting demographic, anthropometric, laboratory, and medical history co-variates, each standard deviation increase of eGDR decreased a 29.6% risk of prevalent LVH. When dividing eGDR into quartiles, the top quartile had a 38.4% risk compared to the bottom quartile. Moreover, smooth curve fitting revealed that the association between eGDR and prevalent LVH was linear in the whole range of eGDR. Additionally, subgroup analysis demonstrated that our main finding was robust to age, sex, BMI, hypertension, and diabetes subgroups. Finally, ROC analysis exhibited a significant improvement by adding eGDR into LVH risk factors (0.780 vs. 0.803, P < 0.001), and category-free net reclassification index (0.702, P < 0.001) and integrated discrimination index (0.027, P < 0.001) also confirmed the improvement from eGDR to detect prevalent LVH. Conclusion Our analysis revealed a linear, robust association between eGDR and prevalent LVH and demonstrated the incremental value of eGDR to optimize the detection of prevalent LVH.

Impact of estimated glucose disposal rate for identifying prevalent ischemic heart disease: findings from a cross-sectional study

BackgroundInsulin resistance is one of the major mechanisms for cardiovascular events. Estimated glucose disposal rate(eGDR) has been demonstrated as a simple, accurate, and cost-effective estimator of insulin resistance. Our study aims to evaluate the correlation between eGDR and the prevalent IHD and assess the incremental value of eGDR for identifying prevalent IHD in the rural general population.MethodsOur study enrolled 10,895 participants from a cross-sectional survey of a metabolic management program. The survey was conducted in the rural areas of southeastern China between October 2019 and April 2020. eGDR = 21.158 − (0.09 * waist circumference) − (3.407 * hypertension) − (0.551 * HbA1c).ResultsThe prevalence of IHD was 4.20%. After adjusting for demographic, anthropometric, laboratory, and medical history covariates, each SD increase of eGDR brought a 25.9% risk reduction for prevalent IHD. After dividing eGDR into groups, the top group had a 58.9% risk reduction than the bottom group. Furthermore, smooth curve fitting demonstrated that the correlation between eGDR and prevalent IHD was linear in the whole range of eGDR. Additionally, AUC suggested that eGDR could significantly improve the identification of prevalent IHD by adding it to cardiovascular risk factors (0.703 vs. 0.711, P for comparison = 0.041). Finally, the category-free net reclassification index and integrated discrimination index also implicated the improvement from eGDR to identify prevalent IHD.ConclusionOur data demonstrated a significant, negative, and linear correlation between eGDR and prevalent IHD. Our findings could suggest the potential usefulness of eGDR to improve the identification of prevalent IHD in the rural general population.

The Perivascular Fat Attenuation Index Improves the Diagnostic Performance for Functional Coronary Stenosis.

Background: Coronary computed tomography angiography (CCTA) is an established first-line test in the investigation of patients with suspected coronary artery disease (CAD), while the perivascular fat attenuation index (FAI) derived from CT seems to be a feasible and efficient tool for the identification of ischemia. The association between the FAI and lesion-specific ischemia as assessed by fractional flow reserve (FFR) remains unclear. Methods: In a total of 261 patients, 294 vessels were assessed for CCTA stenosis, vessel-specific FAI, lesion-specific FAI, and plaque characteristics. The diagnostic accuracies of each parameter and the combined approach were analyzed via the receiver operating characteristic curve (ROC) with FFR as the reference standard. The determinants of FAI were statistically analyzed. Results: The cutoff values of vessel-specific FAI and lesion-specific FAI scores calculated according to the Youden index were −70.97 and −73.95 HU, respectively. No significant differences were noted between them; however, they exhibited a strong correlation. No significant differences were noted between the area under the curve (AUC) scores of vessel-specific FAI (0.677), lesion-specific FAI (0.665), and CCTA (0.607) (p > 0.05 for all) results. The addition of two FAI measures to the CCTA showed improvements in the discrimination (AUC) and reclassification ability (relative integrated discrimination improvement (IDI) and category-free net reclassification index (NRI)), vessel-specific FAI (AUC, 0.696; NRI, 49.6%; IDI, 5.9%), and lesion-specific FAI scores (AUC, 0.676; NRI, 43.3%; IDI, 5.4%); (p < 0.01 for all). Multivariate analysis revealed that low-attenuation plaque (LAP) volume was an independent predictor of two FAI measures. Conclusion: The combined approach of adding vessel-specific FAI or lesion-specific FAI scores could improve the identification of ischemia compared with CCTA alone. The LAP volume was the independent risk factor for both tools.

Pericoronary fat attenuation index and coronary plaque quantified from coronary computed tomography angiography identify ischemia-causing lesions

BackgroundThe association between pericoronary fat attenuation index (FAI), plaque characteristics, and lesion-specific ischemia identified by fractional flow reserve (FFR) remains unclear. MethodsCoronary computed tomography angiography (CCTA) stenosis, FAI, plaque characteristics, FFR derived from computed tomography (FFRCT) and FFR were assessed in 280 vessels of 247 patients. Stenosis ≥50% was considered obstructive. Optimal thresholds of FAI and plaque variables were defined by the area under the receiver-operating characteristics curve (AUC) analysis. Ischemia was defined by FFR ≤ 0.80. ResultsFAI ≥ −71.9 HU, low-attenuation plaque (LAP) ≥ 49.62 mm3 and aggregate plaque volume (APV) ≥ 28.91% predicted ischemia independent of other plaque characteristics. The addition of FAI ≥ −71.9 HU improved discrimination (AUC, 0.720 vs. 0.674, P = 0.035) and reclassification abilities (category-free net reclassification index [NRI], 0.470, P < 0.001; relative integrated discrimination improvement [IDI], 0.047, P < 0.001) of ischemia compared with stenosis evaluation alone, with further discrimination (AUC, 0.772 vs. 0.720, P = 0.028) and reclassification abilities (NRI, 0.385, P = 0.001; relative IDI, 0.077, P < 0.001) of ischemia by adding information regarding LAP ≥49.62 mm3 + APV ≥ 28.91%. And the diagnostic performance of combination approach was comparable to that of FFRCT alone (AUC, 0.772 vs. 0.762, P = 0.771). ConclusionsStenosis severity, FAI, plaque characteristics predicted lesion-specific ischemia. The combination of FAI and plaque assessment improved the discrimination of ischemia compared with stenosis assessment alone.

Incremental Prognostic Value of Pericoronary Adipose Tissue Thickness Measured Using Cardiac Magnetic Resonance Imaging After Revascularization in Patients With ST-Elevation Myocardial Infarction.

Background and AimPericoronary adipose tissue (PCAT) reflects pericoronary inflammation and is associated with coronary artery disease. We aimed to identify the association between local PCTA thickness using cardiac magnetic resonance (CMR) and prognosis of patients with ST-elevation myocardial infarction (STEMI), and to investigate the incremental prognostic value of PCAT thickness in STEMI after reperfusion.MethodsA total of 245 patients with STEMI (mean age, 55.61 ± 10.52 years) who underwent CMR imaging within 1 week of percutaneous coronary intervention therapy and 35 matched controls (mean age, 53.89 ± 9.45 years) were enrolled. PCAT thickness indexed to body surface area at five locations, ventricular volume and function, infarct-related parameters, and global strain indices were evaluated using CMR. Associations between PCAT thickness index and 1-year major adverse cardiovascular events (MACE) after STEMI were calculated. The prognostic value of the standard model based on features of clinical and CMR and updated model including PACT thickness index were further assessed.ResultsPatients with MACE had a more significant increase in PCAT thickness index at superior interventricular groove (SIVGi) than patients without MACE. The SIVGi was significantly associated with left ventricular ejection fraction (LVEF), infarct size, and global deformation. SIVGi > 4.98 mm/m2 was an independent predictor of MACE (hazard ratio, 3.2; 95% CI: 1.6–6.38; p < 0.001). The updated model significantly improved the power of prediction and had better discrimination ability than that of the standard model for predicting 1-year MACE (areas under the ROC curve [AUC] = 0.8 [95% CI: 0.74–0.87] vs. AUC = 0.76 [95% CI: 0.68–0.83], p < 0.05; category-free net reclassification index [cfNRI] = 0.38 [95% CI: 0.1–0.53, p = 0.01]; integrated discrimination improvement [IDI] = 0.09 [95% CI: 0.01–0.18, p = 0.02]).ConclusionsThis study demonstrated SIVGi as an independent predictor conferred incremental value over standard model based on clinical and CMR factors in 1-year MACE predictions for STEMI.

Sex-specific prediction value of common carotid artery diameter for stroke risk in a hypertensive population: a cross-sectional study.

The importance of sex as a risk factor for stroke has been established. This study aimed to assess sex-related disparities in carotid artery diameter and stroke in a hypertensive population. The cross-sectional survey was conducted in rural areas of northeast China. A multistage cluster sampling method was employed to select a representative population. The study comprised 3,245 individuals with hypertension. The common carotid artery (CCA) interadventitial diameter was measured by ultrasound. A linear model of restricted cubic spline function was used to characterize the concentration-response (C-R) relationship between CCA diameter and stroke. The overall prevalence of stroke was 8.9% among hypertensive individuals, with a higher rate in men than in women (10.8% vs. 7.6%). When the women's CCA diameters were divided into quartiles, the top quartile (>8.10 mm) had a 2.49 (95% CI: 1.36-4.56) times greater risk of stroke compared to the bottom quartile (≤6.80 mm) after adjustment was made for other variables. The C-R relationship further confirmed a positive association between CCA diameter and stroke prevalence in women. Moreover, a category-free net reclassification index (0.325; 95% CI: 0.173-0.476; P<0.001) and an integrated discrimination index (0.008; 95% CI: 0.004-0.012, P<0.001) showed improvement in predicting the probability of stroke from CCA diameter. However, no significant relationship between CCA diameter and prevalence of stroke was found in men. The risk of stroke increased proportionally with the enlargement of the CCA diameter in women, supporting the sex-specific value of CCA diameter in optimizing the risk stratification of stroke.

Prospective association of serum adipocyte fatty acid-binding protein with heart failure hospitalization in diabetes.

AimsAdipocyte fatty acid‐binding protein (AFABP) is associated with cardiovascular diseases in type 2 diabetes. Whether circulating AFABP levels are associated with the risk of heart failure (HF) in type 2 diabetes remains undefined. We investigated the prospective association of circulating AFABP levels with incident HF hospitalization in type 2 diabetes, and its relationship to the use of sodium glucose co‐transporter 2 inhibitors (SGLT2i) which reduce HF risk.Methods and resultsBaseline serum AFABP level was measured in 3322 Chinese participants without known history of cardiovascular diseases or hospitalization for HF, recruited from the Hong Kong West Diabetes Registry. Its association with incident HF hospitalization was evaluated using multivariable Cox regression analysis. Use of SGLT2i was included as a time‐dependent covariate. Among these 3322 participants (52.9% men; mean age 60.0 ± 12.6), 176 (5.3%) developed HF hospitalization over a median follow‐up of 8 years. Seven hundred and thirty‐one (22%) were started on SGLT2i during the study period (empagliflozin 55.1%, dapagliflozin 44.2%, canagliflozin 0.4%, and ertugliflozin 0.3%). Serum AFABP levels were significantly higher in participants who developed HF hospitalization than those who did not (men: 14.8 vs. 8.3 ng/mL; women: 21.5 vs. 14.6 ng/mL; all: 18.6 vs. 10.9 ng/mL, P < 0.001). In multivariable Cox regression analysis, baseline serum AFABP level was significantly associated with incident HF hospitalization [hazard ratio (HR) 1.38, 95% confidence interval (CI) 1.06–1.80, P = 0.019] independent of the use of SGLT2i, in a model also consisting of age; sex; body mass index; smoking status; duration of diabetes; hypertension, dyslipidaemia; atrial fibrillation; presence of chronic kidney disease and albuminuria; glycated haemoglobin and high‐sensitivity C‐reactive protein levels; and use of metformin, insulin, aspirin, furosemide, and beta‐blockers at baseline. High cumulative defined daily dose (cDDD) of SGLT2i was protective of incident HF hospitalization (HR 0.10, 95% CI 0.01–0.68, P = 0.019). The addition of circulating AFABP level to a clinical model of conventional HF risk factors provided significant improvement in the category‐free net reclassification index (11.5%, 95% CI 1.6–22.1, P = 0.02) and integrated discrimination improvement (0.3%, 95% CI 0.1–1.7, P = 0.04). A dose‐dependent reduction in cumulative incidence of HF hospitalization in response to SGLT2i, based on cDDD, was more clearly observed in participants with a higher baseline AFABP level above the sex‐specific median (P for trend <0.01).ConclusionsCirculating AFABP level is independently associated with incident HF hospitalization in type 2 diabetes and is potentially helpful in risk stratification for the prevention of HF hospitalization.

Comparison of genetic risk prediction models to improve prediction of coronary heart disease in two large cohorts of the MONICA/KORA study.

It is still unclear how genetic information, provided as single-nucleotide polymorphisms (SNPs), can be most effectively integrated into risk prediction models for coronary heart disease (CHD)to add significant predictive value beyond clinical risk models. For the present study, a population-based case-cohort was used as a trainingset (451 incident cases, 1488 noncases) and an independent cohort as testset (160 incident cases, 2749 noncases). The following strategies to quantify genetic information were compared: A weighted genetic risk score including Metabochip SNPs associated with CHD in the literature (GRSMetabo ); selection of the most predictive SNPs among these literature-confirmed variants using priority-Lasso (PLMetabo ); validation of two comprehensive polygenic risk scores: GRSGola based on Metabochip data, and GRSKhera (available in the testset only) based on cross-validated genome-wide genotyping data. We used Cox regression to assess associations with incident CHD. C-index, category-free net reclassification index (cfNRI) and relative integrated discrimination improvement (IDIrel ) were used to quantify the predictive performance of genetic information beyond Framingham risk score variables. In contrast to GRSMetabo and PLMetabo , GRSGola significantly improved the prediction (delta C-index [95% confidence interval]: 0.0087 [0.0044, 0.0130]; IDIrel : 0.0509 [0.0131, 0.0894]; cfNRI improved only in cases: 0.1761 [0.0253, 0.3219]). GRSKhera yielded slightly worse prediction results than GRSGola .

Predicted Heart Mass in Obese Heart Transplant Donors and Recipients: An Analysis of the ISHLT Registry

<h3>Purpose</h3> Predicted heart mass (PHM) was neither derived nor validated in an obese population. Our objectives were to determine survival according to size mismatch defined by actual PHM and recalculated PHM using ideal body weight (IBW) in obese recipients or recipients of obese donors, and to evaluate whether size mismatch using IBW-adjusted PHM improves risk assessment. <h3>Methods</h3> We included HT recipients (≥18 y) with BMI ≥30 kg/m² or recipients of donors with BMI ≥30 kg/m² from the ISHLT registry between 2008-2017. IBW was calculated using Devine's formula. Donor-recipient PHM was evaluated as a continuous variable and according to established groups: <-30%, -30 to -20%, -20 to 20%, 20 to 30% and >30%. We used Kaplan-Meier survival and multivariable Cox PH analyses to evaluate post-HT mortality by actual/IBW-adjusted PHM groups. We compared the 2 models using net reclassification index (NRI). <h3>Results</h3> We included 10,817 HT recipients, age 55 (IQR 46-62) yrs, 23% female, BMI 31 kg/m² (28-33) with follow up of 3.1 (1.2-6.0) yrs. Included donors were 34 (24-44) yrs, 31% female, and BMI 31 kg/m² (26-34). 692 (6%) and 335 (3%) recipient-donor pairs were reclassified as undersized by 20-30% and >30% respectively using IBW-adjusted PHM. 462 (4%) and 431 (4%) recipient-donor pairs were reclassified as oversized by 20-30% and >30% respectively when using IBW-adjusted PHM. Actual PHM was associated with lower 1-year survival (<i>p</i><0.001); however, differences in 1-year survival between IBW-adjusted PHM groups were not discernible (<i>p</i>=0.25). Undersizing using actual PHM was associated with higher 1-year mortality (<i>p</i><0.001), not seen with IBW-adjusted PHM (p=0.15 Fig). Models based on IBW-adjusted PHM had worse risk quantification for post-HT mortality than using actual PHM (category-free NRI -0.078, 95% CI -0.158, 0.006). <h3>Conclusion</h3> Calculation of PHM using IBW was not associated with post-HT survival. Actual PHM can be used for size matching when assessing mortality risk in recipients of obese donors or obese recipients.

Plasma soluble suppression of tumorigenicity 2 and depression after acute ischemic stroke.

Soluble suppression of tumorigenicity 2 (sST2) might be related to stroke and depression, but the association of sST2 with poststroke depression (PSD) is unclear. The study aimed to prospectively assess the association between plasma sST2 levels and PSD. A total of 635 acute ischemic stroke patients with sST2 measurements from the China Antihypertensive Trial in Acute Ischemic Stroke were included in this analysis. We used the 24-item Hamilton Rating Scale for Depression to assess depression at 3months, and PSD was defined as a score of ≥8. Logistic regression analysis was performed to estimate the risk of PSD associated with sST2, and net reclassification index (NRI) and integrated discrimination improvement (IDI) were calculated to assess the predictive value of sST2. Two hundred fifty (39.4%) patients developed depression at 3months after ischemic stroke. Patients with PSD had higher sST2 levels than patients without PSD (172.7 vs. 153.8pg/ml; p=0.003). After adjustment for age, sex, education, National Institutes of Health Stroke Scale score, and other covariates, the odds ratio for the highest quartile of sST2 compared with the lowest quartile was 1.84 (95% confidence interval, 1.10-3.08) for PSD. Adding sST2 to a conventional model notably improved risk prediction for PSD (category-free NRI=19.34%, 95% confidence interval=4.39%-34.28%, p=0.017; IDI=1.20%, 95% confidence interval=0.25%-2.15%, p=0.014). Increased plasma sST2 levels in the acute phase of ischemic stroke were significantly associated with the increased risk of PSD, independently of conventional risk factors.

A Panel of 6 Biomarkers Significantly Improves the Prediction of Type 2 Diabetes in the MONICA/KORA Study Population.

ContextImproved strategies to identify persons at high risk of type 2 diabetes are important to target costly preventive efforts to those who will benefit most.ObjectiveThis work aimed to assess whether novel biomarkers improve the prediction of type 2 diabetes beyond noninvasive standard clinical risk factors alone or in combination with glycated hemoglobin A1c (HbA1c).MethodsWe used a population-based case-cohort study for discovery (689 incident cases and 1850 noncases) and an independent cohort study (262 incident cases, 2549 noncases) for validation. An L1-penalized (lasso) Cox model was used to select the most predictive set among 47 serum biomarkers from multiple etiological pathways. All variables available from the noninvasive German Diabetes Risk Score (GDRSadapted) were forced into the models. The C index and the category-free net reclassification index (cfNRI) were used to evaluate the predictive performance of the selected biomarkers beyond the GDRSadapted model (plus HbA1c).ResultsInterleukin-1 receptor antagonist, insulin-like growth factor binding protein 2, soluble E-selectin, decorin, adiponectin, and high-density lipoprotein cholesterol were selected as the most relevant biomarkers. The simultaneous addition of these 6 biomarkers significantly improved the predictive performance both in the discovery (C index [95% CI], 0.053 [0.039-0.066]; cfNRI [95% CI], 67.4% [57.3%-79.5%]) and the validation study (0.034 [0.019-0.053]; 48.4% [35.6%-60.8%]). Significant improvements by these biomarkers were also seen on top of the GDRSadapted model plus HbA1c in both studies.ConclusionThe addition of 6 biomarkers significantly improved the prediction of type 2 diabetes when added to a noninvasive clinical model or to a clinical model plus HbA1c.

Usefulness of atherogenic index of plasma for estimating reduced eGFR risk: insights from the national health and nutrition examination survey

ABSTRACT Aims Previous studies have identified Atherogenic index of plasma (AIP) as a simple measure of atherosclerosis. Because atherosclerosis plays a role in the development of renal damage, our study aims to evaluate the effect of AIP on the risk of reduced eGFR and assess its usefulness to refine the risk stratification of reduced estimated glomerular filtration rate (eGFR). Methods Our study included 15,836 participants from the National Health and Nutritional Survey (NHANES) 2009–2016. Association was investigated by logistic regression. AIP was calculated as log (triglycerides/high-density lipoprotein cholesterol). Reduced eGFR was determined as eGFR < 60 ml/min per 1.73 m*2. Results The prevalence of reduced eGFR was 8.01%. In the full model, each SD increase of AIP leaded to 27.4% additional risk for reduced eGFR. After dividing AIP into quartiles, the fourth quartile had a 1.649 times risk than the first quartile. Moreover, smooth curve fitting suggested that the risk of reduced eGFR elevated linearly with the increase of AIP. Subgroup analysis demonstrated that the association between AIP and reduced eGFR was robust in sex, body mass index, hypertension, and diabetes subpopulation, but the association was significantly stronger in black race and people aged less than 50 years old. Additionally, AUC displayed an advancement when introducing AIP into established risk factors (0.875 cs. 0.897, P < 0.001), category-free net reclassification index (0.249, 95% CI: 0.192–0.306, P < 0.001) and integrated discrimination index (0.007, 95% CI: 0.004–0.009, P < 0.001) also suggested the improvement from AIP. Conclusion The present work suggested a linear association between AIP and reduced eGFR. Furthermore, the results showed that the association was stronger in black race and people aged less than 50 years old. Most importantly, our work implicated the usefulness of AIP to refine the risk stratification of reduced eGFR.

Evaluation of the usefulness of red blood cell distribution width in critically ill pediatric patients.

Red blood cell distribution width (RDW) is a component of routine complete blood count, which reflects variability in the size of circulating erythrocytes. Recently, there have been many reports about RDW as a strong prognostic marker in various disease conditions in the adult population. However, only a few studies have been performed in children. This study aimed to investigate the association between RDW and pediatric intensive care unit (PICU) mortality in critically ill children. This study includes 960 patients admitted to the PICU from November 2012 to May 2018. We evaluated the associations between RDW and clinical parameters including PICU mortality outcomes. The median age of the study population was 15.5 (interquartile range, 4.8–54.5) months. The mean RDW was 15.6% ± 3.3%. The overall PICU mortality was 8.8%. As we categorized patients into 3 groups with respect to RDW values (Group 1: ≤14.5%; Group 2: 14.5%–16.5%; and Group 3: >16.5%) and compared clinical parameters, the higher RDW groups (Groups 2 and 3) showed more use of vasoactive-inotropic drugs, mechanical ventilator support, higher severity scores, including pediatric risk of mortality III, pediatric sequential organ failure assessment, pediatric logistic organ dysfunction-2 (PELOD-2), and pediatric multiple organ dysfunction syndrome scores, and higher PICU mortality than the lower RDW group (Group 1) (P < .05). Based on multivariate logistic regression analysis adjusted for age and sex, higher RDW value (≥14.5%) was an independent risk factor of PICU mortality. Moreover, adding RDW improved the performance of the PELOD-2 score in predicting PICU mortality (category-free net reclassification index 0.357, 95% confidence interval 0.153–0.562, P = .001). In conclusion, higher RDW value was significantly associated with worse clinical parameters including PICU mortality. RDW was an independent risk factor of PICU mortality and the addition of RDW significantly improved the performance of PELOD-2 score in predicting PICU mortality. Thus, RDW could be a promising prognostic factor with advantages of simple and easy measurement in critically ill pediatric patients.