Non-traditional lipid profiles and the risk of stroke: A systematic review and meta-analysis

Associations of nontraditional lipoprotein ratios with future cardiovascular events in patients with type 2 diabetes mellitus

BACKGROUND

Patients with type 2 diabetes mellitus (T2DM) face a heightened risk of future cardiovascular events. It is therefore important to stratify these patients according to their future cardiovascular event risk to allow early intervention and improve prognosis. Recent proposals have indicated that nontraditional lipoprotein ratios may be superior predictors of cardiovascular events compared to traditional lipid parameters. However, further evidence is required for widespread clinical application.

AIM

To elucidate the associations of nontraditional lipoprotein ratios with future cardiovascular events in patients with T2DM.

METHODS

This study performed post-hoc analysis of data obtained during a clinical trial involving 10182 participants. To ascertain the correlations between nontraditional lipoprotein ratios and future cardiovascular events, including major adverse cardiovascular events (MACEs) and congestive heart failure (CHF). We employed univariable and multivariable-adjusted Cox proportional hazards regression models. Potential dose-response relationships and threshold values were explored by conducting restricted cubic spline analyses and two-piecewise linear regression models. Possible relevant interactions influencing independent relationships were tested using subgroup and interaction analyses.

RESULTS

After adjustment for confounding factors, all nontraditional lipoprotein ratios studied were strongly associated with MACE risk in patients with T2DM. In comparison with patients in the lowest quartile, the hazard ratios (95% confidence intervals) of those in the highest quartile were 1.50 (1.29-1.73), 1.51 (1.30-1.74), 1.50 (1.29-1.73), and 1.30 (1.12-1.50) for total cholesterol/high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol/HDL-C, non-HDL-C/HDL-C, and remnant cholesterol/HDL-C, respectively. Similar findings were noted for CHF. Dose-response relationships between nontraditional lipoprotein ratios and MACE were observed, with threshold values of 7.29, 6.29, and 2.15 for total cholesterol/HDL-C, non-HDL-C/HDL-C, and remnant cholesterol/HDL-C, respectively. However, no notable dose-response relationships were detected between nontraditional lipoprotein ratios and CHF.

CONCLUSION

Elevated nontraditional lipoprotein ratios may independently predict the risk of MACE and CHF in patients with T2DM.

Association between the non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and cognitive impairment in patients with acute mild ischemic stroke

BACKGROUND

The non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) is a recently developed lipid parameter, but there are insufficient studies exploring its relationship with early cognitive impairment in patients with acute mild stroke. This study aims to determine the potential association between NHHR and early cognitive impairment in patients with acute mild stroke. By collecting data from patients with acute minor ischemic stroke in hospital, we will analyze the relationship between NHHR and cognitive function in these patients.

METHODS

This study enrolled 817 acute ischemic stroke (AIS) patients (NIHSS ≤ 5), Cognitive function was assessed using Mini-Mental State Examination (MMSE) within 2 weeks, with cognitive impairment defined by education-stratified thresholds. Statistical analysis of the baseline was performed. Multivariate logistic regression was performed to analyze the association between NHHR and cognitive impairment, and Receiver Operating Characteristic Curve (ROC) analysis were performed to evaluate the predictive value.

RESULTS

Patients were classified into cognitive impairment group (n = 473) and normal cognition group (n = 344). NHHR in the cognitive impairment group was significantly higher than that in the normal group (3.24 ± 1.63 vs. 3.02 ± 1.43, P = 0.046). There were significant differences in age and education level. There was a dose-response relationship between NHHR quartiles and the incidence of cognitive impairment (trend test P = 0.021). Multivariate regression analysis showed that for each unit increase in NHHR, the risk of cognitive impairment increases by 13.2% (OR = 1.13, 95% confidence interval 1.02-1.25, P = 0.018). The predictive model constructed by combining age and education level has an area under the ROC curve(AUC) of 0.71 (95% confidence interval 0.67-0.74).

CONCLUSIONS

NHHR is an independent risk factor for early cognitive impairment in mild AIS patients. The NHHR-based model demonstrates moderate predictive accuracy, supporting its potential clinical utility.

Modifiable risk factors for stroke, dementia and late-life depression: a systematic review and DALY-weighted risk factors for a composite outcome

BACKGROUND

At least 60% of stroke, 40% of dementia and 35% of late-life depression (LLD) are attributable to modifiable risk factors, with great overlap due to shared pathophysiology. This study aims to systematically identify overlapping risk factors for these diseases and calculate their relative impact on a composite outcome.

METHODS

A systematic literature review was performed in PubMed, Embase and PsycInfo, between January 2000 and September 2023. We included meta-analyses reporting effect sizes of modifiable risk factors on the incidence of stroke, dementia and/or LLD. The most relevant meta-analyses were selected, and disability-adjusted life year (DALY) weighted beta (β)-coefficients were calculated for a composite outcome. The β-coefficients were normalised to assess relative impact.

RESULTS

Our search yielded 182 meta-analyses meeting the inclusion criteria, of which 59 were selected to calculate DALY-weighted risk factors for a composite outcome. Identified risk factors included alcohol (normalised β-coefficient highest category: -34), blood pressure (130), body mass index (70), fasting plasma glucose (94), total cholesterol (22), leisure time cognitive activity (-91), depressive symptoms (57), diet (51), hearing loss (60), kidney function (101), pain (42), physical activity (-56), purpose in life (-50), sleep (76), smoking (91), social engagement (53) and stress (55).

CONCLUSIONS

This study identified overlapping modifiable risk factors and calculated the relative impact of these factors on the risk of a composite outcome of stroke, dementia and LLD. These findings could guide preventative strategies and serve as an empirical foundation for future development of tools that can empower people to reduce their risk of these diseases.

PROSPERO REGISTRATION NUMBER

CRD42023476939.

Appraising non-HDL-C, systolic pressure, and a nomogram-based diagnostic model as auxiliary biomarkers in confirming acute ischemic stroke and transient ischemic attack

Acute ischemic stroke (AIS) is characterized by the abrupt onset of neurological dysfunction stemming from focal brain ischemia, confirmed through imaging evidence of infarction. In contrast, transient ischemic attack (TIA) manifests with neurological deficits in the absence of infarction, with imaging serving as the definitive diagnostic criterion. This study aims to assess the diagnostic value of combining non-high-density lipoprotein cholesterol (non-HDL-C) and blood pressure (BP) in differentiating AIS from TIA. We recruited 207 untreated AIS patients diagnosed within 72 h and 99 age- and gender-matched TIA patients. Upon admission, serum non-HDL-C levels, other lipid profiles, and BP measurements were obtained. Binary logistic regression was employed to identify risk factors, while receiver operator characteristic (ROC) curves were used to evaluate diagnostic performance. Furthermore, least absolute shrinkage and selection operator (LASSO) regression coupled with multivariate logistic regression was utilized to develop a nomogram model. The AIS group exhibited higher prevalence rates of hypertension, diabetes, family history of diabetes, and smoking (P < 0.05). Notably, non-HDL-C, systolic BP, diastolic BP, and other lipid markers were significantly elevated in the AIS group (P < 0.05). Multivariate analysis pinpointed non-HDL-C (OR [odds ratio] = 1.663, 95% CI [confidence interval]: 1.239-2.234, P < 0.01) and systolic BP (OR = 1.035, 95% CI: 1.012-1.057, P < 0.01) as independent risk factors. ROC analysis revealed that systolic BP alone achieved an AUC of 0.686 (sensitivity: 78.7%, specificity: 51.5%), whereas the combination of systolic BP and non-HDL-C enhanced diagnostic accuracy (AUC [area under the ROC curve] = 0.736, sensitivity: 75.4%, specificity: 64.6%). A nomogram incorporating low-density lipoprotein cholesterol (LDL-C), glucose (GLU), homocysteine, and smoking demonstrated high predictive accuracy, with training and validation AUCs of 0.769 and 0.704, respectively. Non-HDL-C and systolic BP emerge as independent risk factors for AIS, and their combined use augments diagnostic precision in differentiating AIS from TIA. A nomogram model presents a practical differentiation tool, particularly in settings with limited resources.

Impact of non-traditional lipid profiles on 1-year vascular outcomes in ischemic stroke patients with prior statin therapy and LDL-C < 100 mg/dL

This study aimed to investigate the association between non-traditional lipid profiles and the risk of 1-year vascular events in patients who were already using statins before stroke and had admission LDL-C < 100 mg/dL. This study was an analysis of a prospective, multicenter, nationwide registry of consecutive patients with acute ischemic stroke patients who treated with statin before index stroke and LDL-C < 100 mg/dL on admission. Non-traditional lipid profiles including non-HDL, TC/HDL ratio, LDL/HDL ratio, and TG/HDL ratio were analyzed as a continuous or categorical variable. The primary vascular outcome within one year was a composite of recurrent stroke (either hemorrhagic or ischemic), myocardial infarction (MI) and all-cause mortality. Hazard ratios (95% Cis) for 1-year vascular outcomes were analyzed using the Cox PH model for each non-traditional lipid profiles groups. A total of 7028 patients (age 70.3 ± 10.8years, male 59.8%) were finally analyzed for the study. In unadjusted analysis, no significant associations were observed in the quartiles of LDL/HDL ratio and 1-year primary outcome. However, after adjustment of relevant variables, compared with Q1 of the LDL/HDL ratio, Q4 was significantly associated with increasing the risk of 1-year primary outcome (HR 1.48 [1.19-1.83]). For the LDL/HDL ratio, a linear relationship was observed (P for linearity < 0.001). Higher quartiles of the LDL/HDL ratio were significantly and linearly associated with increasing the risk of 1-year primary vascular outcomes. These findings suggest that even during statin therapy with LDL-C < 100 mg/dl on admission, there should be consideration for residual risk based on the LDL/HDL ratio, following stroke.

Relationship between changes in the triglyceride glucose-body mass index and frail development trajectory and incidence in middle-aged and elderly individuals: a national cohort study

BACKGROUND

Insulin resistance is linked to an increased risk of frailty, yet the comprehensive relationship between the triglyceride glucose-body mass index (TyG-BMI), which reflects weight, and frailty, remains unclear. This relationship is investigated in this study.

METHODS

Data from 9135 participants in the China Health and Retirement Longitudinal Study (2011-2020) were analysed. Baseline TyG-BMI, changes in the TyG-BMI and cumulative TyG-BMI between baseline and 2015, along with the frailty index (FI) over nine years, were calculated. Participants were grouped into different categories based on TyG-BMI changes using K-means clustering. FI trajectories were assessed using a group-based trajectory model. Logistic and Cox regression models were used to analyse the associations between the TyG-BMI and FI trajectory and frail incidence. Nonlinear relationships were explored using restricted cubic splines, and a linear mixed-effects model was used to evaluate FI development speed. Weighted quantile regression was used to identify the primary contributing factors.

RESULTS

Four classes of changes in the TyG-BMI and two FI trajectories were identified. Individuals in the third (OR = 1.25, 95% CI: 1.10-1.42) and fourth (OR = 1.83, 95% CI: 1.61-2.09) quartiles of baseline TyG-BMI, those with consistently second to highest (OR = 1.49, 95% CI: 1.32-1.70) and the highest (OR = 2.17, 95% CI: 1.84-2.56) TyG-BMI changes, and those in the third (OR = 1.20, 95% CI: 1.05-1.36) and fourth (OR = 1.94, 95% CI: 1.70-2.22) quartiles of the cumulative TyG-BMI had greater odds of experiencing a rapid FI trajectory. Higher frail risk was noted in those in the fourth quartile of baseline TyG-BMI (HR = 1.42, 95% CI: 1.28-1.58), with consistently second to highest (HR = 1.23, 95% CI: 1.12-1.34) and the highest TyG-BMI changes (HR = 1.58, 95% CI: 1.42-1.77), and those in the third (HR = 1.10, 95% CI: 1.00-1.21) and fourth quartile of cumulative TyG-BMI (HR = 1.46, 95% CI: 1.33-1.60). Participants with persistently second-lowest to the highest TyG-BMI changes (β = 0.15, 0.38 and 0.76 respectively) and those experiencing the third to fourth cumulative TyG-BMI (β = 0.25 and 0.56, respectively) demonstrated accelerated FI progression. A U-shaped association was observed between TyG-BMI levels and both rapid FI trajectory and higher frail risk, with BMI being the primary factor.

CONCLUSION

A higher TyG-BMI is associated with the rapid development of FI trajectory and a greater frail risk. However, excessively low TyG-BMI levels also appear to contribute to frail development. Maintaining a healthy TyG-BMI, especially a healthy BMI, may help prevent or delay the frail onset.

A nonlinear relationship between the triglycerides to high-density lipoprotein cholesterol ratio and stroke risk: an analysis based on data from the China Health and Retirement Longitudinal Study

OBJECTIVE

The connection between triglycerides to high-density lipoprotein cholesterol (TG/HDL-C) ratio and stroke risk is controversial. Our goal was to explore this relationship in individuals aged 45 and older enrolled in the China Health and Retirement Longitudinal Study (CHARLS).

METHODS

Our analysis encompassed 10,164 participants from the CHARLS cohorts. We applied the Cox proportional-hazards regression model to evaluate the potential correlation between the TG/HDL-C ratio and stroke incidence. Using a cubic spline function and smooth curve fitting within the Cox model allowed us to unearth a possible non-linear pattern in this relationship. We also conducted thorough sensitivity and subgroup analyses to deepen our understanding of the TG/HDL-C ratio's impact on stroke risk.

RESULTS

Adjusting for various risk factors, we observed a significant link between the TG/HDL-C ratio and increased stroke risk in individuals aged 45 and above (HR: 1.03, 95% CI 1.00-1.05, P = 0.0426). The relationship appeared non-linear, with an inflection at a TG/HDL-C ratio of 1.85. Ratios below this threshold indicated a heightened stroke risk (HR: 1.28, 95% CI 1.06-1.54, P = 0.0089), while ratios above it did not show a significant risk increase (HR: 1.01, 95% CI 0.98-1.04, P = 0.6738). Sensitivity analysis confirmed the robustness of these findings. Notably, non-smokers exhibited a stronger correlation between the TG/HDL-C ratio and stroke risk compared to past and current smokers.

CONCLUSION

Our investigation revealed a significant, yet non-linear, association between the TG/HDL-C ratio and the incidence of stroke among individuals aged 45 and above. Specifically, we found that stroke risk increased in correlation with TG/HDL-C ratio below the threshold of 1.85. These insights may guide healthcare providers in advising and developing more effective strategies for stroke prevention in this demographic.

A non-linear connection between the total cholesterol to high-density lipoprotein cholesterol ratio and stroke risk: a retrospective cohort study from the China Health and Retirement Longitudinal Study

OBJECTIVE

The connection between total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) ratio and stroke risk is controversial. This study aims to examine the connection between the TC/HDL-C ratio and stroke in middle-aged and older individuals who are part of the China Health and Retirement Longitudinal Study (CHARLS).

METHODS

This study conducted a retrospective cohort analysis, enrolling a total of 10,184 participants who met the designated criteria from CHARLS between 2011 and 2012. We then used the Cox proportional-hazards regression model to analyze the relationship between the TC/HDL-C ratio and stroke risk. Using a Cox proportional hazards regression model with cubic spline functions and smooth curve fitting, we were able to identify the non-linear relationship between the TC/HDL-C ratio and stroke occurrence. The sensitivity and subgroup analyses were also performed to investigate the connection between TC/HDL-C ratio and stroke.

RESULTS

This study revealed a statistically significant association between the TC/HDL-C ratio and stroke risk in subjects aged 45 years or older after adjusting for risk factors (HR: 1.05, 95%CI 1.00-1.10, P = 0.0410). Furthermore, a non-linear connection between the TC/HDL-C ratio and stroke risk was detected, with a TC/HDL-C ratio inflection point of 3.71. We identified a significant positive connection between the TC/HDL-C ratio and stroke risk, when the TC/HDL-C ratio was less than 3.71 (HR: 1.25, 95%CI 1.07-1.45, P = 0.0039). However, their connection was not significant when the TC/HDL-C ratio exceeded 3.71 (HR: 1.00, 95%CI 0.94-1.06, P = 0.9232). The sensitivity analysis and subgroup analyses revealed that our findings were well-robust.

CONCLUSION

Our study demonstrated a positive, non-linear connection between the TC/HDL-C ratio and stroke risk in middle-aged and older individuals. There was a significant positive connection between the TC/HDL-C ratio and stroke risk, when the TC/HDL-C ratio was less than 3.71. The current research can be used as a guideline to support clinician consultation and optimize stroke prevention measures for middle-aged and older adults.