Changes in the combination of the triglyceride-glucose index and obesity indicators estimate the risk of cardiovascular disease.

BACKGROUND: Cardiovascular disease (CVD) is closely associated with the triglyceride glucose (TyG) index and its related indicators, particularly its combination with obesity indices. However, there is limited research on the relationship between changes in TyG-related indices and CVD, as most studies have focused on baseline TyG-related indices. METHODS: The data for this prospective cohort study were obtained from the China Health and Retirement Longitudinal Study. The exposures were changes in TyG-related indices and cumulative TyG-related indices from 2012 to 2015. The K-means algorithm was used to classify changes in each TyG-related index into four classes (Class 1 to Class 4). Multivariate logistic regressions were used to evaluate the associations between the changes in TyG-related indices and the incidence of CVD. RESULTS: In total, 3243 participants were included in this study, of whom 1761 (54.4%) were female, with a mean age of 57.62 years at baseline. Over a 5-year follow-up, 637 (19.6%) participants developed CVD. Fully adjusted logistic regression analyses revealed significant positive associations between changes in TyG-related indices, cumulative TyG-related indices and the incidence of CVD. Among these changes in TyG-related indices, changes in TyG-waist circumference (WC) showed the strongest association with incident CVD. Compared to the participants in Class 1 of changes in TyG-WC, the odds ratio (OR) for participants in Class 2 was 1.41 (95% confidence interval (CI) 1.08-1.84), the OR for participants in Class 3 was 1.54 (95% CI 1.15-2.07), and the OR for participants in Class 4 was 1.94 (95% CI 1.34-2.80). Moreover, cumulative TyG-WC exhibited the strongest association with incident CVD among cumulative TyG-related indices. Compared to the participants in Quartile 1 of cumulative TyG-WC, the OR for participants in Quartile 2 was 1.33 (95% CI 1.00-1.76), the OR for participants in Quartile 3 was 1.46 (95% CI 1.09-1.96), and the OR for participants in Quartile 4 was 1.79 (95% CI 1.30-2.47). CONCLUSIONS: Changes in TyG-related indices are independently associated with the risk of CVD. Changes in TyG-WC are expected to become more effective indicators for identifying individuals at a heightened risk of CVD.

Association between triglyceride glucose-body mass index and long-term adverse outcomes of heart failure patients with coronary heart disease.

BACKGROUND: The triglyceride glucose-body mass index (TyG-BMI) is recognized as a reliable surrogate for evaluating insulin resistance and an effective predictor of cardiovascular disease. However, the link between TyG-BMI index and adverse outcomes in heart failure (HF) patients remains unclear. This study examines the correlation of the TyG-BMI index with long-term adverse outcomes in HF patients with coronary heart disease (CHD). METHODS: This single-center, prospective cohort study included 823 HF patients with CHD. The TyG-BMI index was calculated as follows: ln [fasting triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2] × BMI. To explore the association between the TyG-BMI index and the occurrences of all-cause mortality and HF rehospitalization, we utilized multivariate Cox regression models and restricted cubic splines with threshold analysis. RESULTS: Over a follow-up period of 9.4 years, 425 patients died, and 484 were rehospitalized due to HF. Threshold analysis revealed a significant reverse "J"-shaped relationship between the TyG-BMI index and all-cause mortality, indicating a decreased risk of all-cause mortality with higher TyG-BMI index values below 240.0 (adjusted model: HR 0.90, 95% CI 0.86-0.93; Log-likelihood ratio p = 0.003). A distinct "U"-shaped nonlinear relationship was observed with HF rehospitalization, with the inflection point at 228.56 (adjusted model: below: HR 0.95, 95% CI 0.91-0.98; above: HR 1.08, 95% CI 1.03-1.13; Log-likelihood ratio p < 0.001). CONCLUSIONS: This study reveals a nonlinear association between the TyG-BMI index and both all-cause mortality and HF rehospitalization in HF patients with CHD, positioning the TyG-BMI index as a significant prognostic marker in this population.

Soluble ST2 for predicting heart failure, atrial fibrillation and death in patients with coronary heart disease with or without renal insufficiency.

Background: This study aimed to investigate the relationship between baseline soluble suppression of tumorigenesis-2 (sST2) concentration and the outcomes of heart failure (HF), atrial fibrillation (AF) or death in patients with coronary heart disease (CHD) with or without renal insufficiency (RI). Methods: Between March 2011 and December 2015, 3454 patients with CHD from the Chinese PLA General Hospital were enrolled in this cohort study. The patients were followed up until October 2021. AF, HF, and death events were recorded. Associations between baseline sST2 concentrations and clinical outcomes were assessed using Kaplan-Meier (K-M) curves, and Cox regression and generalised additive models. Subgroup analysis were carried out between RI and non-RI groups. Results: Among the patients with CHD (61.5 ± 11.8 years; 78.6 % men), 415 (12.02 %) had RI. During a median follow-up of 8.37 years, HF and AF were reported in 216 (6.25 %) and 174 (5.04 %) patients, respectively, and 297 (8.60 %) died. The K-M curves indicated that patients in the higher quartiles of sST2 concentrations were correlated with a poor survival rate of HF, AF, or death (all Ps < 0.001). Generalised additive model (GAM) demonstrated a nonlinear positive association between sST2 concentration and the risk of HF, AF, and death in CHD patients. The cut-off value of sST2 for predicting HF, AF and death were 32.1, 25.4 and 28.6 ng/mL, respectively. CHD patients with sST2 higher than the cut-off value had higher risks of HF (HR: 3.02, 95%CI: 2.24-4.05), AF (HR: 2.86; 95%CI: 2.10-3.90), and death (HR:2.11, 95%CI: 1.67-2.67). Furthermore, in patients with RI (12.02 %, n = 415), the prognostic value of sST2 over the cut-off value for HF and death remained unchanged (HR: 3.21 and 2.35; P < 0.05). In patients with CHD with or without RI, sST2 improved the area under the curve (AUC) of traditional risk models for predicting clinical endpoint events. Conclusions: The biomarker sST2 may be useful for predicting HF, AF, and death in patients with CHD. The predicted value was not affected by renal function.

Serum albumin and cardiovascular disease: a Mendelian randomization study.

BACKGROUND: An increasing body of evidence suggests that serum albumin levels play a role in cardiovascular diseases. However, the specific causal relationship between serum albumin levels and cardiovascular disease remains partially unknown. METHODS: Mendelian randomization (MR) was employed in this study to examine potential causal relationships between instrumental variables and cardiovascular diseases. Specifically, we utilized genetic variants of serum albumin levels within the reference range as our instrumental variables. To acquire data on genetic associations with cardiovascular diseases, we sourced information from renowned genome-wide association studies such as UK BioBank, EMBL-EBI, and FinnGen. Notably, our study leveraged summary statistics from large cohorts that have been previously described. RESULTS: We explored the association between serum albumin levels and various conditions, including heart failure (HF), venous thromboembolism (VTE), stroke, atrial fibrillation (AF), coronary artery disease (CAD), type 2 diabetes (T2DM), and pulmonary heart disease (PHD). Genetically predicted serum albumin levels were associated with PHD (odds ratio = 0.737, 95% CI = 0.622 - 0.874, P < 0.001), AF (odds ratio = 0.922, 95% CI = 0.870 - 0.977, P = 0.006), VTE (odds ratio = 0.993, 95% CI = 0.991 - 0.995, P < 0.001), and Stroke (odds ratio = 0.997, 95% CI = 0.995 - 0.999, P = 0.002). However, genetically predicted serum albumin level traits were not associated with HF, CAD and T2DM. CONCLUSION: Our study demonstrates a significant association between serum albumin levels and cardiovascular disease, underscoring the crucial role of low serum albumin as a predictive factor in patients with cardiovascular disease.

Prognostic value of growth differentiation factor-15 in heart failure among whole ejection fraction phenotypes.

AIMS: The utility of growth differentiation factor-15 (GDF-15) in predicting long-term adverse outcomes in heart failure (HF) patients is not well established. This study explored the relationship between GDF-15 levels and adverse outcomes in HF patients across various ejection fraction (EF) phenotypes associated with coronary heart disease (CHD) and evaluated the added prognostic value of incorporating GDF-15 into the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score-based model. METHODS AND RESULTS: This single-centre cohort study included 823 HF patients, categorized into 230 (27.9%) reduced EF (HFrEF), 271 (32.9%) mid-range EF (HFmrEF), and 322 (39.1%) preserved EF (HFpEF) groups. The median age was 68.0 years (range: 56.0-77.0), and 245 (29.8%) were females. Compared with the HFrEF and HFmrEF groups, the HFpEF group had a higher GDF-15 concentration (P = 0.002) and a higher MAGGIC risk score (P < 0.001). We examined the associations between GDF-15 levels and the risks of all-cause mortality and HF rehospitalization using Cox regression models. The C-index, integrated discrimination improvement (IDI), and net reclassification improvement (NRI) metrics were employed to assess the incremental prognostic value. During the 9.4 year follow-up period, 425 patients died, and 484 were rehospitalized due to HF. Multivariate Cox regression analysis revealed that elevated GDF-15 levels were significantly associated with an increased risk of all-cause mortality [hazard ratio (HR) = 1.36, 95% confidence interval (CI): 1.20-1.54; P < 0.001] and HF rehospitalization (HR = 1.75, 95% CI: 1.57-1.95; P < 0.001) across all HF phenotypes. This association remained significant when GDF-15 was treated as a categorical variable (high GDF-15 group: all-cause death: HR = 1.73, 95% CI: 1.40-2.14; P < 0.001; HF rehospitalization: HR = 3.37, 95% CI: 2.73-4.15; P < 0.001). Inclusion of GDF-15 in the MAGGIC risk score-based model provided additional prognostic value for all HF patients (Δ C-index = 0.021, 95% CI: 0.002-0.041; IDI = 0.011, 95% CI: 0.001-0.025; continuous NRI = 0.489, 95% CI: 0.174-0.629) and HF rehospitalization (Δ C-index = 0.034, 95% CI: 0.005-0.063; IDI = 0.021, 95% CI: 0.007-0.032; continuous NRI = 0.307, 95% CI: 0.147-0.548), particularly in the HFpEF subgroup. CONCLUSIONS: GDF-15 is identified as an independent risk factor for adverse outcomes in HF patients across the entire EF spectrum in the context of CHD. Integrating GDF-15 into the MAGGIC risk score-based model enhances its prognostic capability for adverse outcomes in the general HF population. This incremental prognostic effect was observed specifically in the HFpEF subgroup and not in other subgroups.

The relationship between triglyceride-glucose index and prospective key clinical outcomes in patients hospitalised for coronary artery disease.

BACKGROUND: The triglyceride-glucose (TyG) index is regarded as a dependable alternative for assessing insulin resistance (IR), given its simplicity, cost-effectiveness, and strong correlation with IR. The relationship between the TyG index and adverse outcomes in patients with coronary heart disease (CHD) is not well established. This study examines the association of the TyG index with long-term adverse outcomes in hospitalized CHD patients. METHODS: In this single-center prospective cohort study, 3321 patients hospitalized with CHD were included. Multivariate Cox regression models were employed to assess the associations between the TyG index and the incidence of all-cause mortality and major adverse cardiovascular events (MACEs). To examine potential nonlinear associations, restricted cubic splines and threshold analysis were utilized. RESULTS: During a follow-up period of 9.4 years, 759 patients (22.9%) succumbed to mortality, while 1291 (38.9%) experienced MACEs. Threshold analysis demonstrated a significant "U"-shaped nonlinear relationship with MACEs, with different hazard ratios observed below and above a TyG index of 8.62 (below: HR 0.71, 95% CI 0.50-0.99; above: HR 1.28, 95% CI 1.10-1.48). Notably, an increased risk of all-cause mortality was observed only when the TyG index exceeded 8.77 (HR 1.53, 95% CI 1.19-1.96). CONCLUSIONS: This study reveals a nonlinear association between the TyG index and both all-cause mortality and MACEs in hospitalized CHD patients with CHD. Assessing the TyG index, particularly focusing on individuals with extremely low or high TyG index values, may enhance risk stratification for adverse outcomes in this patient population.

A comparison of three approaches to measuring frailty to determine adverse health outcomes in critically ill patients.

BACKGROUND: studies comparing different frailty measures in intensive care unit settings are lacking. We aimed to compare the frailty index based on physiological and laboratory tests (FI-Lab), modified frailty index (MFI) and hospital frailty risk score (HFRS) to predict short-term outcomes for critically ill patients. METHODS: we conducted a secondary analysis of data from the Medical Information Mart for Intensive Care IV database. Outcomes of interest included in-hospital mortality and discharge with need for nursing care. RESULTS: the primary analysis was conducted with 21,421 eligible critically ill patients. After adjusting for confounding variables, frailty as diagnosed by all three frailty measures was found to be significantly associated with increased in-hospital mortality. In addition, frail patients were more likely to receive further nursing care after being discharged. All three frailty scores could improve the discrimination ability of the initial model generated by baseline characteristics for adverse outcomes. The FI-Lab had the best predictive ability for in-hospital mortality, whereas the HFRS had the best predictive performance for discharge with need for nursing care amongst the three frailty measures. A combination of the FI-Lab with either the HFRS or MFI improved the identification of critically ill patients at increased risk of in-hospital mortality. CONCLUSIONS: frailty, as assessed by the HFRS, MFI and FI-Lab, was associated with short-term survival and discharge with need for nursing care amongst critically ill patients. The FI-Lab was a better predictor of in-hospital mortality than the HFRS and MFI. Future studies focusing on FI-Lab are warranted.

Association between allostatic load and adverse outcomes among older patients with heart failure with preserved ejection fraction.

BACKGROUND: The allostatic load (AL) refers to the cumulative weakening of multiple physiological systems caused by repeated adaptation of the body to stressors There are still no studies have focused on the association between AL and the prognosis of patients with heart failure with preserved ejection fraction (HFpEF). The present study aimed to investigate the association between AL and adverse outcomes, including mortality and HF admission, among elderly male patients with HFpEF. METHODS: We conducted a prospective cohort study of 1111 elderly male patients with HFpEF, diagnosed between 2015 and 2019 and followed up through 2021. We constructed an AL measure using a combination of 12 biomarkers. The diagnosis of HFpEF was made according to the 2021 European Society of Cardiology guidelines. A Cox proportional hazards model was used to determine the associations between AL and adverse outcomes. RESULTS: In multivariate analysis, AL was significantly associated with increased risk of all-cause mortality (medium AL: adjusted hazard ratio [HR] = 2.53; 95% confidence interval [CI] 1.37-4.68; high AL: HR = 4.21; 95% CI 2.27-7.83; per-score increase: HR = 1.31; 95% CI 1.18-1.46), cardiovascular mortality (medium AL: HR = 2.67; 95% CI 1.07-6.68; high AL: HR = 3.13; 95% CI 1.23-7.97; per-score increase: HR = 1.20; 95% CI 1.03-1.40), non-cardiovascular mortality (medium AL: HR = 2.45; 95% CI 1.06-5.63; high AL: HR = 5.81; 95% CI 2.55-10.28; per-score increase: HR = 1.46; 95% CI 1.26-1.69), and HF admission (medium AL: HR = 2.68; 95% CI 1.43-5.01; high AL: HR = 3.24; 95% CI 1.69-6.23; per-score increase: HR = 1.24; 95% CI 1.11-1.39). Consistent results were found in multiple subgroup analyses. CONCLUSIONS: A higher AL was associated with poor prognosis in elderly men with HFpEF. AL relies on information that is easily obtained in physical examinations and laboratory parameters and can be assessed in various care and clinical settings to help risk stratification of HFpEF patients.

Frailty index based on laboratory tests improves prediction of short-and long-term mortality in patients with critical acute myocardial infarction.

Background: Previous studies have shown that the frailty index based on laboratory tests (FI-Lab) can identify older adults at increased risk of adverse health outcomes. This study aimed to determine whether the FI-Lab is associated with mortality risk and can provide incremental improvements in risk stratification of patients with critical acute myocardial infarction (AMI). Materials and methods: We conducted a secondary analysis of data from the Medical Information Mart for Intensive Care (MIMIC)-IV database. A 33-item FI-Lab was constructed. Outcomes of interest were in-hospital and 1-year mortality. Logistic regression models were used to investigate the association between the FI-Lab and outcomes. For the assessment of the incremental predictive value, the FI-Lab was added to several risk stratification scoring systems for critically ill patients, and the following indices were calculated: Δ C-statistic, integrated discrimination improvement (IDI), and net reclassification improvement (NRI). Results: Out of 2,159 patients, 477 died in hospital (22.1%), and 898 died during the 1-year follow-up period. After adjustment for confounders, the FI-Lab was associated with increased in-hospital mortality [odds ratio (OR) = 1.06, 95% confidence interval (CI): 1.05-1.07] and 1-year mortality (OR = 1.05, 95% CI: 1.04-1.06) when assessed as a continuous variable (per 0.01-score increase). When assessed as a categorical variable, the FI-Lab was associated with in-hospital mortality (2nd Quartile: OR = 1.89, 95% CI: 1.18-3.03; 3rd Quartile: OR = 3.46, 95% CI: 2.20-5.46; and 4th Quartile: OR = 5.79, 95% CI: 3.61-9.28 compared to 1st Quartile) as well as 1-year mortality (2nd Quartile: OR = 1.66, 95% CI: 1.23-2.24; 3rd Quartile: OR = 2.40, 95% CI: 1.76-3.26; and 4th Quartile: OR = 3.76, 95% CI: 2.66-5.30 compared to 1st Quartile) after adjustment for confounders. The addition of the FI-Lab to all disease severity scores improved discrimination and significantly reclassified in-hospital and 1-year mortality risk. Conclusion: The FI-Lab was a strong predictor of short- and long-term mortality in patients with critical AMI. The FI-Lab improved the ability to predict mortality in patients with critical AMI and therefore might be useful in the clinical decision-making process.

Characteristics of oral microbiota in plateau and plain youth-positive correlations between blood lipid level, metabolism and specific microflora in the plateau group.

Objectives: To analyze the characteristics of oral microbiota in plateau and plain youth and the possible function of the microbiome. Materials and methods: A total of 120 healthy young males (80 on the plateau, 40 on the plain) completed this cross-sectional study. Oral microflora samples were collected from all participants. The bacterial 16S rDNA was amplified using PCR and sequenced using Illumina MiSeq high-throughput sequencing. The data were analyzed to determine the microbial distribution and community structure of the oral microflora from the two groups. Metastats was used to test differences in relative species abundance between the groups. The correlation between the abundance of specific bacteria and blood indicators was also analyzed. Results: As demonstrated by alpha and beta diversity, the plateau group had lower microbial richness and a less even distribution of oral microbiota than the plain group. All predominant phyla and genera were qualitatively similar between the two groups, but their relative abundances differed. The relative abundance of bacteria in the phylum Firmicutes was significantly higher in the plateau group than in the plain group. At the genus level, Streptococcus spp. and Gemella spp. were also more abundant in the plateau group. The functional prediction indicated vigorous microbial metabolism in the oral bacterial community. We also found that the relative abundance of Streptococcus spp., the dominant genus, was positively correlated with triglyceride levels in the plateau group. Conclusions: With increasing altitude, the diversity of oral microbiota and the relative proportion of predominant bacteria were altered. The distribution and related function of Streptococcus spp. were prominent in plateau samples. This comprehensive study of the relationship between oral microecology and elevation provides a point of reference for studying the human body's adaptability or inadaptability to high altitude.

Correlation Between Plasma Proteomics and Adverse Outcomes Among Older Men With Chronic Coronary Syndrome.

Background: Chronic coronary syndrome (CCS) is a newly proposed concept and is hallmarked by more long-term major adverse cardiovascular events (MACEs), calling for accurate prognostic biomarkers for initial risk stratification. Methods: Data-independent acquisition liquid chromatography tandem mass spectrometry (DIA LC-MS/MS) quantitative proteomics was performed on 38 patients with CCS; 19 in the CCS events group and 19 in the non-events group as the controls. We also developed a machine-learning-based pipeline to identify proteins as potential biomarkers and validated the target proteins by enzyme-linked immunosorbent assay in an independent prospective cohort. Results: Fifty-seven differentially expressed proteins were identified by quantitative proteomics and three final biomarkers were preliminarily selected from the machine-learning-based pipeline. Further validation with the prospective cohort showed that endothelial protein C receptor (EPCR) and cholesteryl ester transfer protein (CETP) levels at admission were significantly higher in the CCS events group than they were in the non-events group, whereas the carboxypeptidase B2 (CPB2) level was similar in the two groups. In the Cox survival analysis, EPCR and CETP were independent risk factors for MACEs. We constructed a new prognostic model by combining the Framingham coronary heart disease (CHD) risk model with EPCR and CETP levels. This new model significantly improved the C-statistics for MACE prediction compared with that of the Framingham CHD risk model alone. Conclusion: Plasma proteomics was used to find biomarkers of predicting MACEs in patients with CCS. EPCR and CETP were identified as promising prognostic biomarkers for CCS.

Impact of the CYP2D6 Genotype on Metoprolol Tolerance and Adverse Events in Elderly Chinese Patients With Cardiovascular Diseases.

The latest consensus has changed CYP2D6 genotyping among Chinese population, while its impact on metoprolol tolerance and adverse events in elderly Chinese patients with cardiovascular diseases remains unclear. In this study, we prospectively included elderly patients who started metoprolol treatment for cardiovascular indications. According to the latest consensus on CYP2D6 genotype-to-phenotype translation, the patients were categorized as normal, intermediate, or poor metabolizers (NMs, IMs, or PMs, respectively) by detecting the presence of the CYP2D6*1, *2, *5, *10, and *14. Logistic regression model was used to analyze the correlation between the CYP2D6 phenotype and incidence of adverse events, which were assessed over a 12-week period. In this study, there were 651 (62.7%) NMs, 385 (37.1%) IMs, and 3 (0.3%) PMs. After 12 weeks of follow-up, compared with NMs, IMs had the lower maintenance dose [50.0 (25.0-50.0) mg/day vs. 25.0 (25.0-50.0) mg/day, p < 0.001] and lower weight-adjusted maintenance doses (0.52 ± 0.25 mg/day/kg vs. 0.42 ± 0.22 mg/day/kg, p < 0.001), and had higher incidence of postural hypotension (6.0% vs. 10.9%, p = 0.006), bradycardia (21.5% vs. 28.6%, p = 0.011), asystole (0.8% vs. 3.1%, p = 0.009) and syncope (2.0% vs. 6.2%, p = 0.001). In logistic regression model, the overall incidence of adverse events was 1.37-fold larger in IMs than in NMs (odds ratio = 1.37, 95% confidence interval = 1.05-1.79, p = 0.021). We conclude that IMs have lower tolerance and higher incidence of metoprolol-related adverse events than NMs in elderly Chinese patients with cardiovascular diseases. CYP2D6 genotyping is justifiable in elderly patients to minimize the risk of adverse events and ensure the benefits of metoprolol.

Association between frailty and short- and long-term mortality in patients with critical acute myocardial infarction: Results from MIMIC-IV.

Background: Frailty has been recognized as an important prognostic indicator in patients with acute myocardial infarction (AMI). However, no study has focused on critical AMI patients. We aimed to determine the impact of frailty on short- and long-term mortality risk in critical AMI patients. Methods: Data from the Medical Information Mart for Intensive Care (MIMIC)-IV database was used. Frailty was assessed using the Hospital Frailty Risk Score (HFRS). Outcomes were in-hospital mortality and 1-year mortality. Logistic regression and Cox proportional-hazards models were used to investigate the association between frailty and outcomes. Results: Among 5,003 critical AMI patients, 2,176 were non-frail (43.5%), 2,355 were pre-frail (47.1%), and 472 were frail (9.4%). The in-hospital mortality rate was 13.8%, and the 1-year mortality rate was 29.5%. In our multivariable model, frailty was significantly associated with in-hospital mortality [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.20-1.41] and 1-year mortality [hazard ratio (HR) = 1.29, 95% CI: 1.24-1.35] as a continuous variable (per five-score increase). When assessed as categorical variables, pre-frailty and frailty were both associated with in-hospital mortality (OR = 2.80, 95% CI: 2.19-3.59 and OR = 2.69, 95% CI: 1.93-3.73, respectively) and 1-year mortality (HR = 2.32, 95% CI: 2.00-2.69 and HR = 2.81, 95% CI: 2.33-3.39, respectively) after adjustment for confounders. Subgroup analysis showed that frailty was only associated with in-hospital mortality in critically ill patients with non-ST-segment elevation myocardial infarction (STEMI) but not STEMI (p for interaction = 0.012). In addition, frailty was associated with 1-year mortality in both STEMI and non-STEMI patients (p for interaction = 0.447). The addition of frailty produced the incremental value over the initial model generated by baseline characteristics for both in-hospital and 1-year mortality. Conclusion: Frailty, as assessed by the HFRS, was associated with both in-hospital and 1-year mortality in critical AMI patients. Frailty improves the prediction of short- and long-term mortality in critical AMI patients and may have potential clinical applications.

Associations of falls and severe falls with blood pressure and frailty among Chinese community-dwelling oldest olds: The Chinese Longitudinal Health and Longevity Study.

INTRODUCTION: Falls are a leading cause of death among Chinese oldest olds. However, studies on Chinese community-dwelling older adults are lacking. We aimed to identify the associations of falls and severe falls with blood pressure and frailty among Chinese community-dwelling oldest olds. METHODS: Cross-sectional analyses were conducted with 6,595 community-dwelling oldest olds (aged ≥80 years) from 22 Chinese provinces from the Chinese Longitudinal Health and Longevity Study (CLHLS). Systolic BP (SBP) and diastolic BP (DBP) were measured twice at participants' homes, and a 38-item frailty index was used to assess the frailty status of participants. Falls and severe falls were confirmed through face-to-face interviews. Multivariate logistic regression was used to investigate the associations of BP and frailty with falls and severe falls. RESULTS: The mean participant age was 91.0 years, and 56.1% were female. In total, 24.2% participants had a history of fall and 8.3% had a history of severe falls. The multivariate-adjusted odds ratio (OR) for falls among the oldest old with SBP ≥140 mm Hg compared to those with an SBP of 120-129 mm Hg was 1.20 (95% confidence interval [CI], 1.01-1.44). The adjusted OR for falls among frail participants compared to robust participants was 1.39 (95% CI, 1.02-1.89). DBP and pre-frailty were not associated with falls after multivariate adjustment. SBP, DBP, and frailty status were not associated with severe falls after multivariate adjustment. CONCLUSIONS: SBP and frailty but not DBP and pre-frailty are associated with increased odds of falls among Chinese community-dwelling oldest olds.

Waist to height ratio is associated with an increased risk of mortality in Chinese patients with heart failure with preserved ejection fraction.

BACKGROUND: Abdominal obesity as a predominant comorbidity has played a key role in the incidence and worsening of heart failure with preserved ejection fraction (HFpEF), and waist-to-height ratio (WHtR) behaves better than waist circumference or body mass index in evaluating abdominal obesity. While the association between WHtR and all-cause death in Chinese patients with HFpEF remains unclear. METHODS: Patients with stable HFpEF (N = 2041) who presented to our hospital from January 2008 to July 2019 were divided into low-WHtR (< 0.5, N = 378) and high-WHtR (≥ 0.5, N = 1663). Multivariable Cox proportional-hazard models were used to examine the association of WHtR with all-cause death. RESULTS: The average age was 76.63 ± 11.44 years, and the mean follow-up was 4.53 years. During follow-up, 185 patients (9.06%) reached the primary outcome of all-cause death. As for the secondary outcome, 79 patients (3.87%) experienced cardiovascular death, 106 (5.19%) had non-cardiovascular death, and 94 (4.61%) had heart failure rehospitalization. After multivariable adjustment, a higher WHtR was significantly associated with the increased risks of all-cause death [adjusted hazard ratios (HR) 1.91, 95% confidence interval (CI) 1.06-3.45, p = 0.032], cardiovascular death (adjusted HR 2.58; 95% CI 1.01-6.67, p = 0.048), and HF rehospitalization (adjusted HR 3.04; 95% CI 1.26-7.31, p = 0.013). CONCLUSIONS: Higher WHtR is an independent risk factor for all-cause death in Chinese patients with HFpEF.

Prognostic value of soluble suppression of tumorigenesis-2 (sST2) for cardiovascular events in coronary artery disease patients with and without diabetes mellitus.

BACKGROUND: Soluble suppression of tumorigenesis-2 (sST2) is implicated in myocardial overload and has long been recognized as an inflammatory marker related to heart failure and acute coronary syndrome, but data on the prognostic value of sST2 in patients with coronary artery disease (CAD) remain limited. This study sought to investigate the prognostic value of sST2 in patients with established CAD and its predictive value in CAD patients with and without type 2 diabetes mellitus (T2DM). METHODS: A total of 3641 consecutive patients were included in this prospective cohort study. The primary end point was major adverse cardiovascular events (MACEs). The secondary end point was all-cause death. The association between sST2 and outcomes was investigated using multivariable Cox regression. RESULTS: During a median follow-up of 6.4 years, MACEs occurred in 775 patients, and 275 patients died. Multiple Cox regression models showed that a higher level of sST2 was an independent predictor of MACEs development (HR = 1.36, 95% CI 1.17-1.56, p < 0.001) and all-cause death (HR = 2.01, 95% CI 1.56-2.59, p < 0.001). The addition of sST2 to established risk factors significantly improved risk prediction of the composite outcome of MACEs and all-cause death (C-index, net reclassification index, and integrated discrimination improvement, all p < 0.05). In subgroup analysis depending on diabetes status, the diabetes group had a significantly higher level of sST2, which remained a significant predictor of MACEs and all-cause death in patients with and without T2DM in multivariable models. The area under the curve (AUC) of CAD patients with diabetes mellitus was significantly higher than that of those without T2DM. For MACEs, the AUC was 0.737 (patients with T2DM) vs 0.620 (patients without T2DM). For all-cause death, the AUC was 0.923 (patients with T2DM) vs 0.789 (patients without T2DM). CONCLUSIONS: A higher level of sST2 is significantly associated with long-term MACEs and all-cause death in CAD patients with and without T2DM. sST2 has strong predictive value for cardiovascular adverse events in CAD patients with T2DM, and these results provide new evidence for the role of sST2.

Growth differentiation factor-15 is associated with cardiovascular outcomes in patients with coronary artery disease.

BACKGROUND: Growth differentiation factor-15 (GDF-15) is a marker of inflammation, oxidative stress and it is associated with adverse prognosis in cardiovascular disease. The aim of the present cohort study is to investigate the prognostic value of GDF-15 in patients with coronary artery disease (CAD) during long-term follow up. METHODS: A total of 3641 consecutive patients with CAD were prospectively enrolled into the study and followed up for major adverse cardiovascular events (MACEs) and all-cause death up to 5.3-7.6 years. Plasma GDF-15 was measured and clinical data and long-term events were registered. The patients were subsequently divided into three groups by the levels of GDF-15 and the prognostic value of GDF-15 level with MACEs and all-cause death was evaluated. RESULTS: After a median follow-up at 6.4 years later, 775 patients (event rate of 21%) had developed MACEs and 275 patients died (event rate of 7.55%). Kaplan-Meier analysis indicated that the patients with GDF-15 > 1800 ng/L were significantly associated with an increased risk of MACEs and all-cause death. Cox regression analysis indicated that GDF-15 > 1800 ng/L were independently associated with the composite of MACEs (HR 1.74; 95% CI 1.44-2.02; P < 0.001) and all-cause death (HR 2.04; 95% CI 1.57-2.61; P < 0.001). For MACEs, GDF-15 significantly improved the C-statistic (area under the curve, 0.583 [95% CI 0.559-0.606] to 0.628 [0.605-0.651]; P < 0.001), net reclassification index (0.578; P = 0.031), and integrated discrimination index (0.021; P = 0.027). For all-cause death, GDF-15 significantly improved the C-statistic (0.728 [95% CI 0.694-0.761] to 0.817 [0.781-0.846]; P < 0.001), net reclassification index (0.629; P = 0.001), and integrated discrimination index (0.035; P = 0.002). CONCLUSIONS: In the setting of CAD, GDF-15 is associated with long-term MACEs and all-cause death, and provides incremental prognostic value beyond traditional risks factors.