The U-Shape Relationship Between Glycated Hemoglobin Level and Long-Term All-Cause Mortality Among Patients With Coronary Artery Disease

Terminal trajectory of HbA1c for 10 years supports the HbA1c paradox: a longitudinal study using Health and Retirement Study data

Objectives

We aimed to assess the potential time-varying associations between HbA1c and mortality, as well as the terminal trajectory of HbA1c in the elderly to reveal the underlying mechanisms.

Design

The design is a longitudinal study using data from the Health and Retirement Study.

Setting and participants

Data were from the Health and Retirement Study. A total of 10,408 participants aged ≥50 years with available HbA1c measurements at baseline (2006/2008) were included.

Methods

Longitudinal HbA1c measured at 2010/2012 and 2014/2016 were collected. HbA1c values measured three times for their associations with all-cause mortality were assessed using Cox regression and restricted cubic splines. HbA1c terminal trajectories over 10 years before death were analyzed using linear mixed-effect models with a backward time scale.

Results

Women constitute 59.6% of the participants with a mean age of 69 years, with 3,070 decedents during the follow-up (8.9 years). The mortality rate during follow-up was 29.5%. Increased mortality risk became insignificant for the highest quartile of HbA1c compared to the third quartile (aHR 1.148, 1.302, and 1.069 for a follow-up of 8.9, 6.5, and 3.2 years, respectively) with a shorter follow-up, while it became higher for the lowest quartile of HbA1c (aHR 0.986, 1.068, and 1.439 for a follow-up of 8.9, 6.5, and 3.2 years, respectively). Accordingly, for both decedents with and without diabetes, an initial increase in HbA1c was followed by an accelerating terminal decline starting 5-6 years before death.

Conclusions and implications

The time-varying association between HbA1c and mortality mapped to the terminal trajectory in HbA1c. High and low HbA1c may have different clinical relationships with mortality. The HbA1c paradox may be partially explained by reverse causation, namely, early manifestation of death.

Some patients with type 2 diabetes may benefit from intensive glycaemic and blood pressure control: A post-hoc machine learning analysis of ACCORD trial data

AIM

The action to control cardiovascular risk in diabetes (ACCORD) trial showed a neutral average treatment effect of intensive blood glucose and blood pressure (BP) controls in preventing major adverse cardiovascular events (MACE) in individuals with type 2 diabetes. Yet, treatment effects across patient subgroups have not been well understood. We aimed to identify patient subgroups that might benefit from intensive glucose or BP controls for preventing MACE.

MATERIALS AND METHODS

As a post-hoc analysis of the ACCORD trial, we included 10 251 individuals with type 2 diabetes. We applied causal forest and causal tree models to identify participant characteristics that modify the efficacy of intensive glucose or BP controls from 68 candidate variables (demographics, comorbidities, medications and biomarkers) at the baseline. The exposure was (a) intensive versus standard glucose control [glycated haemoglobin (HbA1c) <6.0% vs. 7.0%-7.9%], and (b) intensive versus standard BP control (systolic BP <120 vs. <140 mmHg). The primary outcome was MACE.

RESULTS

Compared with standard glucose control, intensive one reduced MACE in those with baseline HbA1c <8.5% [relative risk (RR): 0.79, 95% confidence interval (CI): 0.67-0.93] and those with estimated glomerular filtration rate ≥106 ml/min/1.73 m2 (RR: 0.74, 95% CI: 0.55-0.99). Intensive BP control reduced MACE in those with normal high-density lipoprotein levels (women >55 mg/dl, men >45 mg/dl; RR: 0.51, 95% CI: 0.34-0.74). Risk reductions were not significant in other patient subgroups.

CONCLUSIONS

Our findings suggest heterogeneous treatment effects of intensive glucose and BP control and could provide biomarkers for future clinical trials to identify more precise HbA1c and BP treatment goals for individualized medicine.

Biomarkers to monitor the prognosis, disease severity, and treatment efficacy in coronary artery disease

INTRODUCTION

Coronary Artery Disease (CAD) is a prevalent condition characterized by the presence of atherosclerotic plaques in the coronary arteries of the heart. The global burden of CAD has increased significantly over the years, resulting in millions of deaths annually and making it the leading health-care expenditure and cause of mortality in developed countries. The lack of cost-effective strategies for monitoring the prognosis of CAD warrants a pressing need for accurate and efficient markers to assess disease severity and progression for both reducing health-care costs and improving patient outcomes.

AREA COVERED

To effectively monitor CAD, prognostic biomarkers and imaging techniques play a vital role in risk-stratified patients during acute treatment and over time. However, with over 1,000 potential markers of interest, it is crucial to identify the key markers with substantial utility in monitoring CAD progression and evaluating therapeutic interventions. This review focuses on identifying and highlighting the most relevant markers for monitoring CAD prognosis and disease severity. We searched for relevant literature using PubMed and Google Scholar.

EXPERT OPINION

By utilizing the markers discussed, health-care providers can improve patient care, optimize treatment plans, and ultimately reduce health-care costs associated with CAD management.

Intensified glycemic control by HbA1c for patients with coronary heart disease and Type 2 diabetes: a review of findings and conclusions

The occurrence and development of coronary heart disease (CHD) are closely linked to fluctuations in blood glucose levels. While the efficacy of intensified treatment guided by HbA1c levels remains uncertain for individuals with diabetes and CHD, this review summarizes the findings and conclusions regarding HbA1c in the context of CHD. Our review showed a curvilinear correlation between regulated level of HbA1c and therapeutic effectiveness of intensified glycemic control among patients with type 2 diabetes and coronary heart disease. It is necessary to optimize the dynamic monitoring indicators of HbA1c, combine genetic profiles, haptoglobin phenotypes for example and select more suitable hypoglycemic drugs to establish more appropriate glucose-controlling guideline for patients with CHD at different stage of diabetes.

Development and External Validation of Nomogram to Identify Risk Factors for CHD in T2DM in the Population of Northwestern China

Purpose

Cardiovascular disease is the leading cause of mortality in patients with type 2 diabetes mellitus (T2DM). This study aimed to develop and validate a nomogram for predicting the risk factors for coronary heart disease (CHD) in T2DM in the population of northwestern China.

Patients and Methods

The records of 2357 T2DM patients who were treated in the First Affiliated Hospital of Xinjiang Medical University from July 2021 to July 2022 were reviewed. After some data (n =239) were excluded, 2118 participants were included in the study and randomly divided into a training set (n =1483) and a validation set (n = 635) at a ratio of 3:1. Univariate and stepwise regression analysis was performed to screen risk factors and develop predictive models. The results of logistic regression are presented through a nomogram. The C-index, receiver operating characteristic (ROC) curve, calibration plot, and decision curve analysis (DCA) were employed to verify the distinction, calibration, and clinical practicality of the model.

Results

The stepwise logistic regression analysis suggested that independent factors in patients with T2DM combined with CHD were age, gender, hypertension (HTN), glycated hemoglobin (HbA1c), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), and Uygur, which were associated with the occurrence of CHD. The nomogram demonstrated good discrimination with a C-index of 0.771 (95% CI, 0.741, 0.800) in the training set and 0.785 (95% CI, 0.743, 0.828) in the validation set. The area under curve (AUC) of the ROC curves were 0.771 (95% CI, 0.741, 0.800) and 0.785 (95% CI, 0.743, 0.828) in the training and validation sets, respectively. The nomogram was well-calibrated. The DCA revealed that the nomogram was clinically valuable.

Conclusion

A nomogram based on 7 clinical characteristics was developed to predict CHD in patients with T2DM.

The association between prothrombin time-international normalized ratio and long-term mortality in patients with coronary artery disease: a large cohort retrospective study with 44,662 patients

BACKGROUND

The association between prothrombin time-international normalized ratio (PT-INR) and long-term prognosis among patients with coronary artery disease (CAD) without atrial fibrillation or anticoagulant therapy was still unclear. We analyzed the association of PT-INR levels and long-term mortality in a large cohort of CAD patients without atrial fibrillation or using of anticoagulant drugs.

METHODS

We obtained data from 44,662 patients who were diagnosed with CAD and had follow-up information from January 2008 to December 2018. The patients were divided into 4 groups (Quartile 1: PT-INR ≤ 0.96; Quartile2: 0.96 < PT-INR ≤ 1.01; Quartile3: 1.01 < PT-INR ≤ 1.06; Quartile4: PT-INR > 1.06). The main endpoint was long-term all-cause death. Kaplan-Meier curve analysis and Cox proportional hazards models were used to investigate the association between quartiles of PT-INR levels and long-term all-cause mortality.

RESULTS

During a median follow-up of 5.25 years, 5613 (12.57%) patients died. We observed a non-linear shaped association between PT-INR levels and long-term all-cause mortality. Patients in high PT-INR level (Quartile4: PT-INR > 1.06) showed a significantly higher long-term mortality than other groups (Quartile2 or 3 or 4), (Compared with Quartile 1, Quartile 2 [0.96 < PT-INR ≤ 1.01], aHR = 1.00, 95% CI 0.91-1.00, P = 0.99; Quartile 3 [1.01 < PT-INR ≤ 1.06], aHR = 1.10, 95% CI 1.01-1.20, P = 0.03; Quartile 4 [PT-INR > 1.06], aHR = 1.33, 95% CI 1.22-1.45, P < 0.05).

CONCLUSIONS

Our study demonstrates high levels of PT-INR were associated with an increased risk of all-cause mortality.

Association of glycated hemoglobin A1c levels with cardiovascular outcomes in the general population: results from the BiomarCaRE (Biomarker for Cardiovascular Risk Assessment in Europe) consortium

BACKGROUND

Biomarkers may contribute to improved cardiovascular risk estimation. Glycated hemoglobin A1c (HbA1c) is used to monitor the quality of diabetes treatment. Its strength of association with cardiovascular outcomes in the general population remains uncertain. This study aims to assess the association of HbA1c with cardiovascular outcomes in the general population.

METHODS

Data from six prospective population-based cohort studies across Europe comprising 36,180 participants were analyzed. HbA1c was evaluated in conjunction with classical cardiovascular risk factors (CVRFs) for association with cardiovascular mortality, cardiovascular disease (CVD) incidence, and overall mortality in subjects without diabetes (N = 32,496) and with diabetes (N = 3684).

RESULTS

Kaplan-Meier curves showed higher event rates with increasing HbA1c levels (log-rank-test: p < 0.001). Cox regression analysis revealed significant associations between HbA1c (in mmol/mol) in the total study population and the examined outcomes. Thus, a hazard ratio (HR) of 1.16 (95% confidence interval (CI) 1.02-1.31, p = 0.02) for cardiovascular mortality, 1.13 (95% CI 1.03-1.24, p = 0.01) for CVD incidence, and 1.09 (95% CI 1.02-1.17, p = 0.01) for overall mortality was observed per 10 mmol/mol increase in HbA1c. The association with CVD incidence and overall mortality was also observed in study participants without diabetes with increased HbA1c levels (HR 1.12; 95% CI 1.01-1.25, p = 0.04) and HR 1.10; 95% CI 1.01-1.20, p = 0.02) respectively. HbA1c cut-off values of 39.9 mmol/mol (5.8%), 36.6 mmol/mol (5.5%), and 38.8 mmol/mol (5.7%) for cardiovascular mortality, CVD incidence, and overall mortality, showed also an increased risk.

CONCLUSIONS

HbA1c is independently associated with cardiovascular mortality, overall mortality and cardiovascular disease in the general European population. A mostly monotonically increasing relationship was observed between HbA1c levels and outcomes. Elevated HbA1c levels were associated with cardiovascular disease incidence and overall mortality in participants without diabetes underlining the importance of HbA1c levels in the overall population.