Multi-trajectories of lipid indices with incident cardiovascular disease, heart failure, and all-cause mortality: 23 years follow-up of two US cohort studies

Combined blood pressure and heart rate trajectories are associated with prognosis in critically ill patients with acute aortic dissection: A group-based multi-trajectory analysis

Background

Managing systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR) is pivotal in acute aortic dissection (AAD) care. However, no prior studies have jointly analyzed the trajectories of these parameters. This research aimed to characterize their joint longitudinal trajectories and investigate the influence on AAD prognosis.

Methods

We included AAD patients from the Medical Information Mart for Intensive Care (MIMIC)-IV database. Using group-based multi-trajectory modeling (GBMTM), we identified combined trajectories of SBP, DBP, and HR within the initial 24 h of intensive care unit (ICU) admission. Cox proportional hazard regression, log-binomial regression, and logistic regression were employed to assess the association between trajectory groups and mortality outcomes.

Results

Data from 337 patients were analyzed. GBMTM identified five combined trajectory groups. Group 1 featured rapidly declining SBP and DBP with high pulse pressure and low HR; Group 2 showed high to moderate SBP with slight rebound and persistently low HR; Group 3 displayed persistently moderate BP and HR; Group 4 was characterized by moderate blood pressure with persistently high HR; and Group 5 had high to moderate SBP with slight rebound, high but gradually declining DBP, and slightly high HR. Group 3 demonstrated a lower risk of mortality, with an adjusted hazard ratio of 0.32 (95 % CI, 0.14-0.74), and the adjusted relative risks for in-hospital, 30-day, and 1-year mortalities were 0.37 (95 % CI, 0.15-0.87), 0.25 (95 % CI, 0.10-0.62), and 0.41 (95 % CI, 0.22-0.79), respectively. The time-independent C-index curve demonstrated that the multi-trajectory groups had higher C-index values than any univariate trajectory groups or admission values of SBP, DBP, and HR.

Conclusions

Utilization of GBMTM can yield data-driven insights to identify distinct subphenotypes in AAD patients. The combined trajectories of SBP, DBP, and HR within 24 h of ICU admission significantly influenced the mortality rate.

Intraindividual difference in estimated GFR by creatinine and cystatin C, cognitive trajectories and motoric cognitive risk syndrome

BACKGROUND

Intraindividual differences between estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) and creatinine (eGFRcr) can convey important clinical information regarding health status. However, the clinical implications of these differences (eGFRdiff) for risk of cognitive decline and motoric cognitive risk (MCR) syndrome remains unclear. We aimed to investigate the longitudinal associations of eGFRdiff with cognitive trajectories and incident MCR.

METHODS

Based on the China Health and Retirement Longitudinal Study, we identified two study subcohorts: one for cognitive trajectory follow-up (6423 participants, 2011-2018) and another for incident MCR follow-up (2477 participants, 2011-2015). The eGFRdiff was defined as eGFRcys - eGFRcr. Adjusted ordinal and binary logistic regression models were separately used to assess the associations of eGFRdiff with cognitive trajectories and incident MCR. We also performed discordance analyses for eGFRdiff versus eGFRcys, eGFRcr or eGFR based on both creatinine and cystatin C (eGFRcys-cr).

RESULTS

In the first subcohort, four distinct 7-year cognitive trajectories were identified. Each 1 standard deviation (SD) higher eGFRdiff (value for eGFRcys - eGFRcr) was associated with a lower risk of poorer cognitive trajectories {odds ratio 0.909 [95% confidence interval (CI) 0.877-0.942]}. In the second subcohort, 121 participants developed incident MCR after a 4-year follow-up. Each 1-SD higher eGFRdiff (value for eGFRcys - eGFRcr) was linked with a 25.3% (95% CI 16.6-33.2) decreased risk for MCR. The above associations persisted in individuals with normal kidney function. Additionally, the risk for cognitive decline and incident MCR was more strongly associated with eGFRcys than eGFRcr and eGFRcys-cr. For the discordance analyses, the 'discordantly high eGFRdiff/low eGFR' group but not the 'discordantly low eGFRdiff/high eGFR' exhibited a significantly lower risk of poorer cognitive trajectories and MCR compared with the concordant group.

CONCLUSIONS

A large negative difference between eGFRcys and eGFRcr (eGFRcys < eGFRcr) was associated with a higher risk of cognitive decline and incident MCR. The eGFRdiff could capture additional valuable risk information beyond eGFRcys, eGFRcr and eGFRcys-cr.

Lipid Levels During Adult Lifetime in Men and Women With and Without a Subsequent Incident Myocardial Infarction: A Longitudinal Analysis of Data From the Tromsø Study 1974 to 2016

Background The atherosclerotic effect of an adverse lipid profile is assumed to accumulate throughout life, leading to increased risk of myocardial infarction (MI). Still, little is known about age at onset and duration of unfavorable lipid levels before MI. Methods and Results Longitudinal data on serum lipid levels for 26 130 individuals (50.5% women, aged 20-89 years) were obtained from 7 population-based health surveys in Tromsø, Norway. Diagnoses of MI were obtained from national registers. A linear mixed model was applied to compare age- and sex-specific mean values of total cholesterol, high-density lipoprotein cholesterol (HDL-C), and triglyceride concentration by MI status (MI versus non-MI). Already from young adulthood, 20 to 35 years before the incident MI, individuals with a subsequent incident MI had on average more adverse lipid levels than individuals of the same age and sex without MI. Analogous to a dose-response relationship, there was a clear trend toward more severe adverse lipid levels the lower the age at incident MI (P<0.001, test for trend through ordered categories <55, 55-74, ≥75 years). This trend was particularly pronounced for high-density lipoprotein cholesterol in percentage of total cholesterol (both sexes) and for the relative relationship between triglyceride, high-density lipoprotein cholesterol, and total cholesterol level (women). The difference in mean lipid level by MI status was just as large in women as in men, but the age pattern differed (P≤0.05, tests of 3-way interaction). Conclusions Compared with general population mean levels, adverse lipid levels were seen 20 to 35 years before the incident MI in both men and women.

Effect of hypertriglyceridemia on left ventricular global longitudinal strain in patients with coronary heart disease in Jilin Province, China: a cross-sectional study

Aims

Using speckle tracking technology to investigate the effect of hypertriglyceridemia on the global longitudinal strain(GLS) of the left ventricle in patients with coronary heart disease in the early stage, and to explore the value of myocardial strain in early identification of cardiac dysfunction in patients with coronary heart disease in the pre-heart failure stage.

Methods

A cross-sectional study of 138 participants was conducted in Jilin Province, China. Basic clinical, biochemical, and echocardiographic data were obtained for all patients. Myocardial strain parameters were compared between the hypertriglyceridemia and normal triglyceride level groups and the effect of hypertriglyceridemia on early left ventricular global longitudinal strain impairment in coronary heart disease patients was evaluated.

Results

The overall longitudinal strain of the left ventricle was smaller in the hypertriglyceridemia group than in the normal triglyceride group. After the multivariate Logistic regression model adjusting for the influence of confounding factors, the results remained stable.

Conclusions

The risk of impairment of global longitudinal strain of the left ventricle in patients with coronary heart disease is positively correlated with triglyceride levels, and hypertriglyceridemia maybe an independent risk factor affecting early cardiac dysfunction in the pre-heart failure stage of patients with coronary heart disease.

Association of Multitrajectories of Lipid Indices With Premature Cardiovascular Disease: A Cohort Study

Background The multitrajectory model can identify joint longitudinal patterns of different lipids simultaneously, which might help better understand the heterogeneous risk of premature cardiovascular disease (CVD) and facilitate targeted prevention programs. This study aimed to investigate the associations between multitrajectories of lipids with premature CVD. Methods and Results The study enrolled 78 526 participants from the Kailuan study, a prospective cohort study in Tangshan, China. Five distinct multitrajectories of triglyceride, low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol over 6-year exposure were identified on the basis of Nagin's criteria, using group-based multitrajectory modeling. During a median follow-up of 6.75 years (507 645.94 person-years), 665 (0.85%) premature CVDs occurred. After adjustment for confounders, the highest risk of premature CVD was observed in group 4 (the highest and increasing triglyceride, optimal and decreasing LDL-C, low and decreasing high-density lipoprotein cholesterol) (hazard ratio [HR], 2.13 [95% CI, 1.36-3.32]), followed by group 5 (high and decreasing triglyceride, optimal and increasing LDL-C, low and decreasing high-density lipoprotein cholesterol) (HR, 2.07 [95% CI, 1.45-2.98]), and group 3 (optimal and increasing triglyceride, borderline high and increasing LDL-C, optimal and decreasing high-density lipoprotein cholesterol) (HR, 1.90 [95% CI, 1.32-2.73]). Conclusions Our results showed that the residual risk of premature CVD caused by increasing triglyceride levels remained high despite the fact that LDL-C levels were optimal or declining over time. These findings emphasized the importance of assessing the joint longitudinal patterns of lipids and undertaking potential interventions on triglyceride lowering to reduce the residual risk of premature CVD, even among individuals with optimal LDL-C levels.

Longitudinal association of remnant cholesterol with joint arteriosclerosis and atherosclerosis progression beyond LDL cholesterol

BACKGROUND

Arteriosclerosis and atherosclerosis are closely related with cardiovascular disease (CVD) risk. Remnant cholesterol (RC) could predict CVD. However, its effect on joint arteriosclerosis and atherosclerosis progression remains unclear. This study aims to evaluate the association of RC with joint arteriosclerosis and atherosclerosis progression trajectories in the general population.

METHODS

This study collected data across five biennial surveys of the Beijing Health Management Cohort from 2010 to 2019. Multi-trajectory model was used to determine the joint arteriosclerosis and atherosclerosis progression patterns by brachial-ankle pulse wave velocity (baPWV) and ankle brachial index (ABI). We also performed discordance analyses for RC vs. low density lipoprotein cholesterol (LDL-C) using ordinal logistics model.

RESULTS

A total of 3186 participants were included, with three clusters following distinct arteriosclerosis and atherosclerosis progression patterns identified using a multi-trajectory model. In the multivariable-adjusted ordinal logistics analyses, RC was significantly associated with baPWV and ABI progression (OR: 1.20; 95% CI: 1.13-1.28, per 10 mg/dL). For the discordance analyses, the discordant low RC group was associated with decreased risk compared to the concordant group (OR: 0.73; 95% CI: 0.60-0.89). People with a high RC level were at an increased risk of joint arteriosclerosis and atherosclerosis progression, even with optimal LDL-C.

CONCLUSIONS

RC is independently associated with joint arteriosclerosis and atherosclerosis progression beyond LDL-C. RC could be an earlier risk factor than LDL-C of arteriosclerosis and atherosclerosis in the general population.

Longitudinal effects of lipid indices on incident cardiovascular diseases adjusting for time-varying confounding using marginal structural models: 25 years follow-up of two US cohort studies

Background

This study assesses the effect of blood lipid indices and lipid ratios on cardiovascular diseases (CVDs) using inverse probability-of-exposure weighted estimation of marginal structural models (MSMs).

Methods

A pooled dataset of two US representative cohort studies, including 16736 participants aged 42-84 years with complete information at baseline, was used. The effect of each lipid index, including low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), triglyceride (TG), ratios of TC/HDL-C, LDL-C/HDL-C, and TG/HDL-C on coronary heart disease (CHD) and stroke were estimated using weighted Cox regression.

Results

There were 1638 cases of CHD and 1017 cases of stroke during a median follow-up of 17.1 years (interquartile range: 8.5 to 25.7). Compared to optimal levels, the risk of CVD outcomes increased substantially in high levels of TC, LDL-C, TC/HDL-C, and LDL-C/HDL-C. If everyone had always had high levels of TC (≥240 mg/dL), risk of CHD would have been 2.15 times higher, and risk of stroke 1.35 times higher than if they had always had optimal levels (<200 mg/dL). Moreover, if all participants had been kept at very high (≥190 mg/dL) levels of LDL-C, risk of CHD would have been 2.62 times higher and risk of stroke would have been 1.92 times higher than if all participants had been kept at optimal levels, respectively. Our results suggest that high levels of HDL-C may be protective for CHD, but not for stroke. There was also no evidence of an adverse effect of high triglyceride levels on stroke.

Conclusions

Using MSM, this study highlights the effect of TC and LDL-C on CVD, with a stronger effect on CHD than on stroke. There was no evidence for a protective effect of high levels of HDL-C on stroke. Besides, triglyceride was not found to affect stroke.

Trajectories of Lipid Profile and Risk of Carotid Atherosclerosis Progression: A Longitudinal Cohort Study

Background: Early assessment of carotid atherosclerotic plaque characteristics is essential for atherosclerotic cardiovascular disease (ASCVD) risk stratification and prediction. We aimed to identify different trajectories of lipid profiles and investigate the association of lipid trajectories with carotid atherosclerosis (CAS) progression in a large, longitudinal cohort of the Chinese population. Methods: 10,412 participants aged ≥18 years with ≥2 times general health checkups were included in this longitudinally prospective cohort study at Peking University Third Hospital. We used latent class trajectory models to identify trajectories of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) over follow-up time (757 days, IQR: 388–844 days). Results: Participants with carotid plaque were more likely to be older, male, have higher body mass index, have a higher prevalence of hypertension and diabetes, and have a higher level of blood pressure, TG, TC, and LDL-C, compared with carotid intima-media thickness (cIMT) and normal group. Subjects were trichotomized according to different trajectory patterns into stable, moderate-stable, and elevated-increasing classes. TC ≥ 5.18 mmol/L and moderate-stable class (hazard ratio (HR): 1.416, 95% confidence interval (CI): 1.285–1.559, p: 0.000), TG ≥ 1.70 mmol/L and moderate-stable class (HR: 1.492, 95% CI: 1.163–1.913, p: 0.002), TG ≥ 1.70 mmol/L and elevated-increasing class (HR: 1.218, 95% CI: 1.094–1.357, p: 0.000), LDL-C ≥ 3.36 mmol/L and stable class (HR: 1.500, 95% CI: 1.361–1.653, p: 0.000) were statistically significant associated with CAS progression compared with the reference group. Conclusions: Borderline elevated baseline lipid (TC, TG, and LDL-C) with stable and elevated-increasing trajectories were associated with CAS progression. Long-term strategies for low-level lipid are beneficial for ASCVD management.

Distinct patterns of fasting plasma glucose and lipid profile levels over time in adults tested positive for HIV on HAART in Shanghai, China, revealed using growth mixture models

Objectives

This study sought to identify potential change patterns and predictors of fasting plasma glucose (FPG) and lipid levels after initiating highly active antiretroviral therapy (HAART).

Methods

A retrospective cohort study was conducted on 1,572 patients tested positive for HIV who initiated HAART between January 2010 and October 2020 in Shanghai, China. The growth mixture models (GMM) were used for capturing subgroups of FPG trajectories as well as triglyceride (TG) and total cholesterol (TC) dual-trajectories. Multinomial logistic regression models identified correlates of given trajectories.

Results

The median follow-up time was 2.0 years (IQR 1.0-4.7). Three FPG trajectory subgroups were identified as FPG low-stable (62.3%), medium-stable (30.5%), and high-increasing (7.2%). Furthermore, three subgroups of TG and TC dual-trajectories were identified as TG and TC high-slight increasing (13.7%), low-rapid increasing (27.6%), and a subgroup of medium-stable TC and slight-decreasing TG (58.7%). Older age, high TG, FPG, BMI, CD4 count of <200 at baseline, and initial use of zidovudine (AZT) and protease inhibitors (PIs) helped to identify the class with increasing glucose or lipid metabolism trajectories.

Conclusion

The change patterns of plasma glucose and lipid in patients tested positive for HIV were heterogeneous and tailored interventions should be considered in specific subgroups.

Disease evolution and risk-based disease trajectories in congestive heart failure patients

Congestive Heart Failure (CHF) is among the most prevalent chronic diseases worldwide, and is commonly associated with comorbidities and complex health conditions. Consequently, CHF patients are typically hospitalized frequently, and are at a high risk of premature death. Early detection of an envisaged patient disease trajectory is crucial for precision medicine. However, despite the abundance of patient-level data, cardiologists currently struggle to identify disease trajectories and track the evolution patterns of the disease over time, especially in small groups of patients with specific disease subtypes. The present study proposed a five-step method that allows clustering CHF patients, detecting cluster similarity, and identifying disease trajectories, and promises to overcome the existing difficulties. This work is based on a rich dataset of patients' records spanning ten years of hospital visits. The dataset contains all the health information documented in the hospital during each visit, including diagnoses, lab results, clinical data, and demographics. It utilizes an innovative Cluster Evolution Analysis (CEA) method to analyze the complex CHF population where each subject is potentially associated with numerous variables. We have defined sub-groups for mortality risk levels, which we used to characterize patients' disease evolution by refined data clustering in three points in time over ten years, and generating patients' migration patterns across periods. The results elicited 18, 23, and 25 clusters respective to the first, second, and third visits, uncovering clinically interesting small sub-groups of patients. In the following post-processing stage, we identified meaningful patterns. The analysis yielded fine-grained patient clusters divided into several finite risk levels, including several small-sized groups of high-risk patients. Significantly, the analysis also yielded longitudinal patterns where patients' risk levels changed over time. Four types of disease trajectories were identified: decline, preserved state, improvement, and mixed-progress. This stage is a unique contribution of the work. The resulting fine partitioning and longitudinal insights promise to significantly assist cardiologists in tailoring personalized interventions to improve care quality. Cardiologists could utilize these results to glean previously undetected relationships between symptoms and disease evolution that would allow a more informed clinical decision-making and effective interventions.