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Summary: Background: The triglyceride-glucose (TyG) index has been recognized as a crucial risk factor for cardiovascular diseases. However, the association between the TyG index and mortality in the general population remains elusive. Methods: Participants were enrolled from the China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART), a nationwide prospective cohort study. The outcomes of interest were all-cause, cardiovascular, and cancer mortality. Restricted cubic splines and Cox regression models were used to assess the associations between the TyG index and outcomes. Findings: In total, 3,524,459 participants with a median follow-up of 4.6 (IQR, 3.1–5.8) years were included. The associations of the TyG index with all-cause and cardiovascular mortality were reverse L-shaped, with cut-off values of 9.75 for all-cause mortality and 9.85 for cardiovascular mortality. For each 1-unit increase in the TyG index, when below the cut-off values, the TyG index was not significantly associated with all-cause mortality (HR = 1.02, 95% CI: 1.00–1.03) and was only modestly associated with cardiovascular mortality (HR = 1.09, 95% CI: 1.06–1.11). Conversely, when the cut-off values were exceeded, the HRs (95% CI) were 2.10 (1.94–2.29) for all-cause mortality and 1.99 (1.72–2.30) for cardiovascular mortality. However, the association between the TyG index and cancer mortality was linearly negative (HR = 0.97, 95% CI: 0.94–0.99). Interpretation: The associations of the TyG index with all-cause and cardiovascular mortality displayed reverse L-shaped patterns, while an elevated TyG index showed a slight negative association with cancer mortality. We suggest that

Abstract Aims This study aimed to evaluate the cumulative high‐sensitivity cardiac troponin T (hs‐cTNT) from admission to 12 months after discharge and its association with mortality after 12 months among patients with acute heart failure (HF). Methods We used data from the China Patient‐Centered Evaluative Assessment of Cardiac Events Prospective Heart Failure Study (China PEACE 5p‐HF Study), which enrolled patients hospitalized primarily for HF from 52 hospitals between 2016 and 2018. We included patients who survived within 12 months and had hs‐cTNT data at admission (within 48 h of admission) and 1 and 12 months after discharge. To evaluate the long‐term cumulative hs‐cTNT, we calculated cumulative hs‐cTNT levels and cumulative times of high hs‐cTNT level. Patients were divided into groups according to the quartiles of cumulative hs‐cTNT levels (Quartiles 1–4) and cumulative times of high hs‐cTNT levels (0–3 times). Multivariable Cox models were constructed to examine the association of cumulative hs‐cTNT with mortality during the follow‐up period. Results We included 1137 patients with a median age of 64 [interquartile range (IQR), 54–73] years; 406 (35.7%) were female. The median cumulative hs‐cTNT level was 150 (IQR, 91–241) ng/L*month. Based on the cumulative times of high hs‐cTNT levels, 404 (35.5%) patients were with zero time, 203 (17.9%) with one time, 174 (15.3%) with two times, and 356 (31.3%) with three times. During a median follow‐up of 4.76 (IQR, 4.25–5.07) years, 303 (26.6%) all‐cause deaths occurred. The increasing cumulative hs‐cTNT level and cumulative times of high hs‐cTNT level were independently associated with excess all‐cause mortality. Compared with Quartile 1 group, Quartile 4 had the highest hazard ratio (HR) of all‐cause mortality [4.14; 95% confidence interval (CI): 2.51–6.85], followed by Quartile 3 (HR: 3.35; 95% CI: 2.05–5.48) and Quartile 2 (HR: 2.47; 95% CI: 1.49–4.08) groups. Similarly, taking the patients with zero time of high hs‐cTNT level as the reference, the HRs were 1.60 (95% CI: 1.05–2.45), 2.61 (95% CI: 1.76–3.87), and 2.86 (95% CI: 1.98–4.14) in patients who had one, two, and three times of high hs‐cTNT level, respectively. Conclusions Elevated cumulative hs‐cTNT from admission to 12 months after discharge was independently associated with mortality after 12 months among patients with acute HF. Repeated measurements of hs‐cTNT after discharge may help monitor the cardiac damage and identify patients with high risk of death.

Background Elevated hsCRP (high‐sensitivity C‐reactive protein) level is associated with worse prognosis among patients hospitalized for heart failure. However, the prognostic value of the long‐term cumulative hsCRP remains unknown. Methods and Results We consecutively enrolled patients hospitalized for heart failure and collected their hsCRP data at admission and 1 and 12 months after discharge. Long‐term cumulative hsCRP was evaluated using 2 approaches, cumulative hsCRP level quartiles and cumulative times of high hsCRP levels. Patients were classified into 4 groups by cumulative hsCRP level quartiles and cumulative times of high hsCRP levels (0‐ to 3‐times: number of times that hsCRP levels were higher than cutoff values at admission or 1 or 12 months), respectively. Multivariable Cox models were used to assess the association of mortality with cumulative hsCRP. A total of 1281 patients were included; the median age was 64 (interquartile range, 54–73) years, and 35.4% were women. Over a 4.8‐year (interquartile range, 4.2–5.1) follow‐up, 374 (29.2%) patients died. Elevated long‐term cumulative hsCRP level was related to higher mortality. Specifically, taking the quartile 1 as the reference, the hazard ratios (HRs) were 1.29 (95% CI, 0.92–1.81) for quartile 2, 1.62 (95% CI, 1.16–2.25) for quartile 3, and 2.38 (95% CI, 1.75–3.23) for quartile 4. Similarly, compared with the patients with 0‐times (hsCRP level lower than the cutoff values in all 3 time points) of high hsCRP level, the HRs were 1.36 for 1‐time (hsCRP level higher than the cutoff value in one of the 3 time points) (95% CI, 0.92–2.01), 1.95 for 2‐times (hsCRP levels higher than the cutoff values in 2 of the 3 time points) (95% CI, 1.34–2.82), and 2.80 for 3‐times (hsCRP levels higher than the cutoff values in the 3 time points) (95% CI, 1.97–4.00). Conclusions Increasing long‐term cumulative hsCRP level was associated with worse outcomes in patients hospitalized for acute heart failure. Repeated hsCRP measurements could assist physicians in identifying patients with a high risk of death. Registration URL: https://www.clinicaltrials.gov; Unique identifier: NCT 02878811.

Background Improving health status is one of the major goals in the management of heart failure (HF). However, little is known about the long‐term individual trajectories of health status in patients with acute HF after discharge. Methods and Results We enrolled 2328 patients hospitalized for HF from 51 hospitals prospectively and measured their health status via the Kansas City Cardiomyopathy Questionnaire–12 at admission and 1, 6, and 12 months after discharge, respectively. The median age of the patients included was 66 years, and 63.3% were men. Six patterns of Kansas City Cardiomyopathy Questionnaire–12 trajectories were identified by a latent class trajectory model: persistently good (34.0%), rapidly improving (35.5%), slowly improving (10.4%), moderately regressing (7.4%), severely regressing (7.5%), and persistently poor (5.3%). Advanced age, decompensated chronic HF, HF with mildly reduced ejection fraction, HF with preserved ejection fraction, depression symptoms, cognitive impairment, and each additional HF rehospitalization within 1 year of discharge were associated with unfavorable health status (moderately regressing, severely regressing, and persistently poor) (P

Background The age‐related trends in the predictive ability of carotid intima‐media thickness (CIMT) for cardiovascular risk remain unclear. We aimed to identify the age‐related trends in the predictive value of CIMT for cardiovascular death. Methods and Results In a prospective cohort of adults aged 35 to 75 years without history of cardiovascular disease who were enrolled between 2014 and 2020, we measured CIMT at baseline and collected the vital status and cause of death. We divided the study population into 4 age groups (35–44, 45–54, 55–64, and 65–75 years). Competing risk models were fitted to estimate the associations between CIMT and cardiovascular death. The added values of CIMT in prediction were assessed by the differences of the Harrell's concordance index and the net reclassification improvement index. We included 369 478 adults and followed them for a median of 4.7 years. A total of 4723 (1.28%) cardiovascular deaths occurred. After adjusting for the traditional risk factors, the hazard ratios for CIMTmean per SD decreased with age, from 1.27 (95% CI, 1.17–1.37) in the 35 to 44 years age group to 1.14 (95% CI, 1.10–1.19) in the 65 to 75 years age group (P for interaction

Background Although aldosterone antagonists improve outcomes in select individuals with heart failure and reduced ejection fraction, studies in the United States have raised concerns about underuse and overuse. Variations in the prescription of aldosterone antagonist in China are unknown. Methods and Results In the multicenter, hospital‐based, retrospective China PEACE (China Patient‐Centered Evaluative Assessment of Cardiac Events) study, we identified a nationally representative cohort of admissions for heart failure in a nationally representative sample of Chinese hospitals in 2015. Patients were classified into 1 of 3 groups according to their eligibility for spironolactone—“ideal” (left ventricular ejection fraction

BackgroundIndividual non-cardiac comorbidities are prevalent in HF; however, few studies reported how the aggregate burden of non-cardiac comorbidities affects long-term outcomes, and it is unknown whether this burden is associated with changes in health status.AimsTo assess the association of the overall burden of non-cardiac comorbidities with clinical outcomes and quality of life (QoL) in patients hospitalized for heart failure (HF).MethodsWe prospectively enrolled patients hospitalized for HF from 52 hospitals in China. Eight key non-cardiac comorbidities [diabetes, chronic renal disease, chronic obstructive pulmonary disease (COPD), anemia, stroke, cancer, peripheral arterial disease (PAD), and liver cirrhosis] were included, and patients were categorized into four groups: none, one, two, and three or more comorbidities. We fitted Cox proportional hazards models to assess the burden of comorbidities on 1-year death and rehospitalization.ResultsOf the 4,866 patients, 25.3% had no non-cardiac comorbidity, 32.2% had one, 22.9% had two, and 19.6% had three or more in China. Compared with those without non-cardiac comorbidities, patients with three or more comorbidities had higher risks of 1-year all-cause death [heart rate, HR 1.89; 95% confidence interval (CI) 1.48–2.39] and all-rehospitalization (HR 1.35; 95%CI 1.15–1.58) after adjustment. Although all patients with HF experienced a longitudinal improvement in QoL in the 180 days after discharge, those with three or more non-cardiac comorbidities had an unadjusted 11.4 (95%CI −13.4 to −9.4) lower Kansas City Cardiomyopathy Questionnaire (KCCQ) scores than patients without comorbidities. This difference decreased to −6.4 (95%CI −8.6 to −4.2) after adjustment for covariates.ConclusionAmong patients hospitalized with HF in this study, a higher burden of non-cardiac comorbidities was significantly associated with worse health-related QoL (HRQoL), increased risks of death, and rehospitalization post-discharge. The findings highlight the need to address the management of comorbidities effectively in standardized HF care.

ObjectiveTo quantitatively characterize the pattern of systemic impairment reflected by conventional biomarkers and assess how it relates to clinical outcomes and quality of life among patients hospitalized for heart failure (HF).MethodsPatients hospitalized for HF from 52 hospitals in China were enrolled between 2016 and 2018. They were divided into developing and validating cohorts; the developing cohort was used for calculating the weights of biomarkers and constructing the multi-biomarker panel, while the validating one was used for evaluating the relationship between multi-biomarker points and outcomes. In total, five conventional biomarkers reflecting various pathophysiological processes were included in the panel: N-terminal pro-B type natriuretic peptide, high-sensitivity troponin T, hemoglobin, albumin, and creatinine. The weights of the biomarkers were defined based on their relationship with cardiovascular death, and each patient had a multi-biomarker point ranging from 0 to 12. The primary clinical outcome was cardiovascular death, and the other clinical outcomes included rehospitalization for HF, all-cause death, and all-cause rehospitalization in 1-year. The quality of life was measured using Kansas City Cardiovascular Questionnaire. Multi-variable Cox proportional hazard models were used to assess the risks of clinical outcomes, and generalized linear models were used to evaluate the quality of life.ResultsIn total, 4,693 patients hospitalized for HF were included in this analysis; the median (interquartile range, IQR) age was 67 (57–75) years old and 1,763 (37.6%) were female. The median multi-biomarker point was 5 (IQR, 2–6). There were 18.0% of patients in the low point group (6). Compared with those in the low point group, the patients in the high point group had a significantly excess risk of cardiovascular death (adjusted hazard ratio: 5.69, 95% CI, 3.33–9.70). Furthermore, patients with higher points were also more prone to worse quality of life.ConclusionSystemic impairment reflected by abnormal conventional biomarker values was common amongst patients hospitalized for HF and had substantially cumulative adverse influence on clinical outcomes and quality of life.

Objectives To develop a model of in-hospital mortality using medical record front page (MRFP) data and assess its validity in case-mix standardisation by comparison with a model developed using the complete medical record data.Design A nationally representative retrospective study.Setting Representative hospitals in China, covering 161 hospitals in modelling cohort and 156 hospitals in validation cohort.Participants Representative patients admitted for acute myocardial infarction. 8370 patients in modelling cohort and 9704 patients in validation cohort.Primary outcome measures In-hospital mortality, which was defined explicitly as death that occurred during hospitalisation, and the hospital-level risk standardised mortality rate (RSMR).Results A total of 14 variables were included in the model predicting in-hospital mortality based on MRFP data, with the area under receiver operating characteristic curve of 0.78 among modelling cohort and 0.79 among validation cohort. The median of absolute difference between the hospital RSMR predicted by hierarchical generalised linear models established based on MRFP data and complete medical record data, which was built as ‘reference model’, was 0.08% (10th and 90th percentiles: −1.8% and 1.6%). In the regression model comparing the RSMR between two models, the slope and intercept of the regression equation is 0.90 and 0.007 in modelling cohort, while 0.85 and 0.010 in validation cohort, which indicated that the evaluation capability from two models were very similar.Conclusions The models based on MRFP data showed good discrimination and calibration capability, as well as similar risk prediction effect in comparison with the model based on complete medical record data, which proved that MRFP data could be suitable for risk adjustment in hospital performance measurement.

This paper introduces a planar positioning sensing system based on orthogonal wheels and encoders for some surfaces that may float (such as ship decks). The positioning sensing system can obtain the desired position and angle information on any such ground that floats. In view of the current method of using the IMU gyroscope for positioning, the odometer data on these floating grounds are not consistent with the real-time data in the world coordinate system. The system takes advantage of the characteristic of the orthogonal wheel, using four vertical omnidirectional wheels and encoders to position on the floating ground. We design a new structure and obtain the position and angle information of a mobile robot by solving the encoder installed on four sets of omnidirectional wheels. Each orthogonal wheel is provided with a sliding mechanism. This is a good solution to the problem of irregular motion of the system facing the floating grounds. In the experiment, it is found that under the condition that the parameters of the four omnidirectional wheels are obtained by the encoder, the influence of the angle change of the robot in the world coordinate system caused by the flotation of the ground can be ignored, and the position and pose of the robot on the fluctuating ground can be well obtained. Regardless of straight or curved motion, the error can reach the centimeter level. In the mobile floating platform experiment, the maximum error of irregular movement process is 2.43 (±0.075) cm and the RMSE is 1.51 cm.

BackgroundThe aim of this study was to evaluate the value of copeptin in predicting mortality including both short-term and long-term mortality in patients with acute coronary syndrome (ACS).MethodsPotential studies were searched and selected through PubMed, Embase and Cochrane databases up to December 2019. The predictive performance was evaluated by the pooled sensitivity and specificity, and summary receiver operating characteristic curves. Cochran's Q test and I2 index were used to assess between-study heterogeneity, and Deek's test and funnel plots were used to assess publication bias.ResultsTotal six studies comprising 2269 patients were included in this meta-analysis. The area under the receiver operating characteristic curve of copeptin in predicting mortality in patients with ACS was 0.73 (95% CI: 0.69-0.77). The pooled sensitivity and specificity of copeptin were 0.77 (95% CI: 0.59-0.89) and 0.60 (95% CI: 0.47-0.71), respectively. Significant between-study heterogeneity was identified in both sensitivity (P = 0.01; I2 = 69.76%) and specificity (PConclusionsCopeptin has acceptable prognostic value for mortality in patients with ACS. Further studies based on multimarker strategy are needed to evaluate the prognostic value of copeptin for ACS in conjunction with other well-established biomarkers.