Relationship between triglyceride levels and ischaemic stroke in elderly hypertensive patients

Association Between the Atherogenic Index of Plasma and 90-Day Clinical Prognosis in Patients with Acute Pontine Infarction: A Single Center Study

Background

The atherogenic index of plasma (AIP) is a biomarker for coronary heart disease, atherosclerosis, and metabolic syndrome. However, the mechanism of its action in the acute phase of acute pontine infarction remains unclear. This study investigated the association between the AIP and the short-term prognosis of acute pontine infarction.

Methods

Clinical and laboratory index data of patients admitted to the hospital for acute pontine infarction were continuously included, and these patients were followed up for 90 days after disease onset. The modified Rankin Scale (mRS) was used to evaluate the 90-day clinical outcomes of the patients, and an mRS score ≥3 was used to define adverse functional outcomes. Univariate analysis was used to detect differences in the indicators between the two groups. Patients were then divided into three groups according to the quantile of the AIP (T1: AIP ≤ 0.029; T2, 0.029 < AIP ≤ 0.248; T3, AIP > 0.248), and a binary logistic regression model was used to assess risk factors for prognosis shortly after acute pontine infarction.

Results

A total of 260 patients with acute pontine infarction (mean age=64.5±11.8 years) were included during the study period, and 68 (26.2%) patients had a poor 90-day prognosis. The AIP in the poor 90-day prognosis group was significantly greater (P <0.05) than that in the good 90-day prognosis group. The multivariate logistic regression analysis revealed that the AIP (OR=9.829; 95% CI: 2.837-34.051; p < 0.001), baseline NIHSS score (OR=1.663; 95% CI: 1.400-1.975; p < 0.001) and infarct volume (OR=1.762; 95% CI: 1.013-3.062; p=0.045) were significantly associated with poor 90-day prognosis in patients with acute pontine infarction.

Conclusion

In patients with acute pontine infarction, the AIP may serve as an important biological marker of poor clinical prognosis and is independently associated with poor 90-day prognosis.

Identifying gut microbiota with high specificity for ischemic stroke with large vessel occlusion

Gut microbiota can regulate the metabolic and immunological aspects of ischemic stroke and modulate the treatment effects. The present study aimed to identify specific changes in gut microbiota in patients with large vessel occlusion (LVO) ischemic stroke and assess the potential association between gut microbiota and clinical features of ischemic stroke. A total of 63 CSVD patients, 64 cerebral small vessel disease (CSVD) patients, and 36 matching normal controls (NCs) were included in this study. The fecal samples were collected for all participants and analyzed for gut microbiota using 16S rRNA gene sequencing technology. The abundances of five gut microbiota, including genera Bifidobacterium, Butyricimonas, Blautia, and Dorea and species Bifidobacterium_longum, showed significant changes with high specificity in the LVO patients as compared to the NCs and CSVD patients. In LVO patients, the genera Bifidobacterium and Blautia and species Bifidobacterium_longum were significantly correlated with the National Institutes of Health Stroke Scale (NIHSS) scores at the admission and discharge of the patients. Serum triglyceride levels could significantly affect the association of the abundance of genus Bifidobacterium and species Bifidobacterium_longum with the NIHSS scores at admission and modified Rankin Scale (mRS) at discharge in LVO patients. The identification of five gut microbiota with high specificity were identified in the early stage of LVO stroke, which contributed to performed an effective clinical management for LVO ischemic stroke.

Relationship between the cumulative exposure to atherogenic index of plasma and ischemic stroke: a retrospective cohort study

BACKGROUND

Atherogenic index of plasma (AIP) has been demonstrated as a surrogate marker for ischemic stroke, but there is limited evidence for the effect of long-term elevation of AIP on ischemic stroke. Therefore, we aimed to characterize the relationship between cumulative exposure to AIP and the risk of ischemic stroke.

METHODS

A total of 54,123 participants in the Kailuan Study who attended consecutive health examinations in 2006, 2008, and 2010 and had no history of ischemic stroke or cancer were included. The time-weighted cumulative AIP (cumAIP) was calculated as a weighted sum of the mean AIP values for each time interval and then normalized to the total duration of exposure (2006-2010). Participants were divided into four groups according to quartile of cumAIP: the Q1 group, ≤-0.50; Q2 group, - 0.50 to - 0.12; Q3 group, - 0.12 to 0.28; and Q4 group, ≥ 0.28. Cox proportional hazard models were used to evaluate the relationship between cumAIP and ischemic stroke by calculating hazard ratios (HRs) and 95% confidence intervals (95% CIs).

RESULTS

After a median follow-up of 11.03 years, a total of 2,742 new ischemic stroke events occurred. The risk of ischemic stroke increased with increasing quartile of cumAIP. After adjustment for potential confounders, Cox regression models showed that participants in the Q2, Q3, and Q4 groups had significantly higher risks of ischemic stroke than those in the Q1 group. The HRs (95% CIs) for ischemic stroke in the Q2, Q3, and Q4 groups were 1.17 (1.03, 1.32), 1.33 (1.18, 1.50), and 1.45 (1.28, 1.64), respectively. The longer duration of high AIP exposure was significantly associated with increased ischemic stroke risk.

CONCLUSIONS

High cumulative AIP is associated with a higher risk of ischemic stroke, which implies that the long-term monitoring and maintenance of an appropriate AIP may help prevent such events.

Non-linear dose-response relationship between body mass index and stroke risk in middle-aged and elderly Chinese men: a nationwide Longitudinal Cohort Study from CHARLS

Objective

Body mass index (BMI) and stroke risk have been linked, but these findings are still debated. This study investigated the relationship between BMI and stroke risk in a middle-aged and elderly Chinese population.

Methods

This study used four waves of CHARLS data (2011, 2013, 2015, and 2018), including 12,161 participants. The CHARLS sample was obtained by multi-stage probability sampling and all participants were assessed by one-to-one interviews using a standardized questionnaire. We used a Cox proportional-hazards regression model to examine the relationship between BMI and stroke risk. We used Cox proportional hazards regression with cubic spline functions and smooth curve fitting to identify the non-linear relationship between them. A series of sensitivity analyses were also conducted.

Results

The multivariate Cox proportional hazards regression model identified a positive association between BMI and stroke risk (HR=1.025, 95% CI: 1.010-1.040). We also found a non-linear relationship between BMI and stroke incidence, with an inflection point at 26.63 kg/m2 for BMI. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 4.4% increase in stroke risk (HR=1.044, 95% CI: 1.019-1.069). We stratified individuals by gender to further investigate their association and found a particular non-linear relationship and saturation effect between BMI and stroke risk in men, with the inflection point at 25.94 kg/m2. Each 1 kg/m2 increase in BMI to the left of the inflection point was related to a 7.6% increase in stroke risk (HR=1.076, 95% CI 1.034-1.119). The association was linear in women, with each 1 kg/m2 increase in BMI associated with a 2.1% increase in stroke risk (HR=1.021, 95% CI 1.002, 1.040).

Conclusion

In men, there was a specific non-linear association and saturation effect of BMI with stroke (inflection point of 25.94 kg/m2), while in women, there was none. When males had a BMI below 25.94 kg/m2, the risk of stroke was significantly and positively associated with BMI. By controlling BMI below 25.94 kg/m2 in men, a further decrease in BMI may promote a significant reduction in stroke risk.

Interactive effect of increased high sensitive C-reactive protein and dyslipidemia on cardiovascular diseases: a 12-year prospective cohort study

BACKGROUND

Dyslipidemia and inflammation are significant factors for the onset of cardiovascular diseases (CVD); however, studies regarding their interactions on the risk of CVD are scarce. This study aimed to assess the interaction of dyslipidemia and high-sensitivity C-reactive protein (hs-CRP) on CVD.

METHODS

This prospective cohort enrolled 4,128 adults at baseline in 2009 and followed them up until May 2022 for collecting CVD events. Cox-proportional hazard regression analysis estimated the hazard ratios (HRs) and 95% confidence intervals (CIs) of the associations of increased hs-CRP (≥ 1 mg/L) and dyslipidemia with CVD. The additive interactions were explored using the relative excess risk of interaction (RERI) and the multiplicative interactions were assessed with HRs (95% CI) while the multiplicative interactions were assessed by the HRs (95% CI) of interaction terms.

RESULTS

The HRs of the association between increased hs-CRP and CVD were 1.42 (95% CI: 1.14-1.79) and 1.17 (95% CI: 0.89-1.53) among subjects with normal lipid levels and subjects with dyslipidemia, respectively. Stratified analyses by hs-CRP levels showed that among participants with normal hs-CRP (< 1 mg/L), TC ≥ 240 mg/dL, LDL-C ≥ 160 mg/dL, non-HDL-C ≥ 190 mg/dL, ApoB < 0.7 g/L, and LDL/HDL-C ≥ 2.02 were associated with CVD [HRs (95%CIs): 1.75 (1.21-2.54), 2.16 (1.37-3.41), 1.95 (1.29-2.97), 1.37 (1.01-1.67), and 1.30 (1.00-1.69), all P < 0.05, respectively]. While in the population with increased hs-CRP, only ApoAI > 2.10 g/L had a significant association with CVD [HR (95% CI): 1.69 (1.14-2.51)]. Interaction analyses showed that increased hs-CRP had multiplicative and additive interactions with LDL-C ≥ 160 mg/dL and non-HDL-C ≥ 190 mg/dL on the risk of CVD [HRs (95%CIs): 0.309 (0.153-0.621), and 0.505 (0.295-0.866); RERIs (95%CIs): -1.704 (-3.430-0.021 and - 0.694 (-1.476-0.089), respectively, all P < 0.05].

CONCLUSION

Overall our findings indicate negative interactions between abnormal blood lipid levels and hs-CRP on the risk of CVD. Further large-scale cohort studies with trajectories measurement of lipids and hs-CRP might verify our results as well explore the biological mechanism behind that interaction.

Outcomes and predictors of periprocedural stroke after transcatheter aortic valve implantation

BACKGROUND

Risk factors for stroke after transcatheter aortic valve implantation (TAVI) are currently incompletely understood.

PURPOSE

To identify possible predictors of early post-TAVI stroke and explore its short-term outcomes.

METHODS

Retrospective analysis of consecutive patients (pts) submitted to TAVI between 2009 and 2020 in a tertiary center. Baseline characteristics, procedural information and stroke in first 30 days after TAVI were collected. In-hospital and 12 months outcomes were analyzed.

RESULTS

A total of 512pts (56,1% female, mean age of 82 ± 6years.) were included. In the first 30 days after TAVI 19pts (3,7%) had a stroke. In univariate analysis stroke was associated with higher body mass index (29 vs 27kg/m², p=0.035), higher triglyceridemia (> 117,5mg/dL, p=0,002), lower high-density lipoprotein (< 38,5mg/dL, p=0,009) and porcelain aorta (36,8% vs 15,5%, p=0,014) and more frequent use of post-dilatation (58,8% vs 32%, p=0,021). In multivariate analysis, triglycerides > 117,5mg/dL (p=0,032, OR = 3,751) and post-dilatation (p=0,019, OR = 3,694) were the independent predictors. Stroke after TAVI was associated with longer intensive care unit stay (12 vs 4 days, p<0,001) and post-TAVI hospital stay (25 vs 10 days, p<0,0001), higher intra-hospital mortality (21,1% vs 4,3%, p=0,003), cardiovascular 30-day mortality (15,8% vs 4,1%, p=0,026) and 1-year stroke (13,2% vs 1,1%, p=0,003).

CONCLUSION

Periprocedural and 30-day stroke is a relatively uncommon but potentially devastating complication after TAVI. In this cohort, 30-day stroke rate after TAVI was 3.7%. Hypertriglyceridemia and post-dilatation were found to be the only independent risk predictors. Outcomes after stroke, including 30-day mortality, were significantly worse.

Association between the atherogenic index of plasma and major adverse cardiovascular events among non-diabetic hypertensive older adults

Background

Literature on the association between the atherogenic index of plasma (AIP) and the risk of major adverse cardiovascular events (MACEs) among non-diabetic hypertensive older adults is quite limited.

Methods

A post-hoc analysis of data obtained from the Systolic Blood Pressure Intervention Trial was performed. The predictive value of AIP on the risk of MACEs among non-diabetic hypertensive older adults was assessed to evaluate whether the benefit of intensive blood pressure (BP) control in preventing MACEs is consistent in different AIP subgroups.

Results

In this study, 9323 participants with AIP were included, out of which 561 (6.02%) had composite cardiovascular outcomes during a median of 3.22 years of follow-up. Patients in the highest AIP quartile had a significantly increased risk of the primary outcome. In the fully adjusted Model 3, the adjusted hazard ratios (HRs) of the primary outcome for participants in Q2, Q3, and Q4 of AIP were 1.32 (1.02, 1.72), 1.38 (1.05, 1.81), and 1.56 (1.17, 2.08) respectively. Consistently, the trend test for the association between AIP quartiles and the primary outcome showed that a higher AIP quartile was associated with a significantly higher risk of the primary outcome (adjusted HR (95%CI) in model 3:1.14 (1.04, 1.25), P = 0,004). However, within each AIP quartile, absolute event rates were lower in the intensive treatment group. No evidence was found for the interaction between intensive BP control and AIP for the risk of the primary outcome (P for interaction = 0.932).

Conclusion

This study found that elevated AIP was independently and positively associated with the risk of MACEs among non-diabetic hypertensive older adults. The benefits of intensive BP control in managing cardiovascular events were consistent in different AIP subgroups.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01670-6.

The White Matter Functional Abnormalities in Patients with Transient Ischemic Attack: A Reinforcement Learning Approach

Background

Transient ischemic attack (TIA) is a known risk factor for stroke. Abnormal alterations in the low-frequency range of the gray matter (GM) of the brain have been studied in patients with TIA. However, whether there are abnormal neural activities in the low-frequency range of the white matter (WM) in patients with TIA remains unknown. The current study applied two resting-state metrics to explore functional abnormalities in the low-frequency range of WM in patients with TIA. Furthermore, a reinforcement learning method was used to investigate whether altered WM function could be a diagnostic indicator of TIA.

Methods

We enrolled 48 patients with TIA and 41 age- and sex-matched healthy controls (HCs). Resting-state functional magnetic resonance imaging (rs-fMRI) and clinical/physiological/biochemical data were collected from each participant. We compared the group differences between patients with TIA and HCs in the low-frequency range of WM using two resting-state metrics: amplitude of low-frequency fluctuation (ALFF) and fractional ALFF (fALFF). The altered ALFF and fALFF values were defined as features of the reinforcement learning method involving a Q-learning algorithm.

Results

Compared with HCs, patients with TIA showed decreased ALFF in the right cingulate gyrus/right superior longitudinal fasciculus/left superior corona radiata and decreased fALFF in the right cerebral peduncle/right cingulate gyrus/middle cerebellar peduncle. Based on these two rs-fMRI metrics, an optimal Q-learning model was obtained with an accuracy of 82.02%, sensitivity of 85.42%, specificity of 78.05%, precision of 82.00%, and area under the curve (AUC) of 0.87.

Conclusion

The present study revealed abnormal WM functional alterations in the low-frequency range in patients with TIA. These results support the role of WM functional neural activity as a potential neuromarker in classifying patients with TIA and offer novel insights into the underlying mechanisms in patients with TIA from the perspective of WM function.

The triglyceride glucose index is associated with the cerebral small vessel disease in a memory clinic population

BACKGROUND AND OBJECTIVES

Insulin resistance (IR) has been associated with the cerebral small vessel disease (cSVD). However, as the surrogate marker of IR, there is little known about the relationship between the triglyceride glucose (TyG) index and cSVD. In this cross-sectional study, we aimed to evaluate the relationship between the TyG index and cSVD in a memory clinic population and explore the value of TyG index to improve the risk stratification of cSVD.

METHODS

We included participants who attended our memory clinic from January 2016 to December 2020. TyG index was determined as ln [fasting triglyceride (mg/dL) × fasting plasma glucose (mg/dL)/2]. We assessed lacunes, microbleeds, white matter hyperintensity (WMH) and enlarged perivascular spaces (EPVS) on MRI and calculated the total cSVD burden.

RESULTS

A total of 297 subjects were included (median age: 65 years, male sex: 64.98%). In the adjusted model, when dividing TyG index into quartiles, subjects with TyG index in the top quartile, compared with those in the bottom quartile, were more likely to have lacunes (P = 0.035), moderate-severe WMH (P = 0.001), a higher grade of deep WMH (P = 0.004), a higher grade of PVWMH (P = 0.032), a higher grade of EPVS (P = 0.002), and a higher cSVD score (P < 0.001). When introducing TyG index into traditional risk factors to predict moderate to severe cSVD, both area under the curve (0.745 vs 0.802, P = 0.003) and integrated discrimination index (0.080, 95% CI 0.050-0.110, P < 0.001) displayed an improvement from TyG index.

CONCLUSIONS

The TyG index is correlated with cSVD and may have the potential to be a surrogate marker of insulin resistance and optimize the risk stratification.

Hyperlipidemia and hypertension have synergistic interaction on ischemic stroke: insights from a general population survey in China

Background

Hyperlipidemia (HLP) and hypertension (HTN) are both independent risk factors for ischemic stroke. This study aimed to assess whether HTN and HLP have a synergistic effect on the risk of ischemic stroke.

Methods

Between January and August 2013, 11,695 subjects in rural areas of northeastern China were enrolled. The additive and multiplicative scales were used to evaluate the interaction.

Results

The prevalence of ischemic stroke was 5.7%. Using the healthy group (without HTN or HLP) as the reference group, subjects with both HTN and HLP had a higher risk of ischemic stroke (odds ratio [OR]: 3.369, 95% confidence interval [CI]: 2.579–4.402), and this OR was greater than that of subjects with only HTN (OR: 1.995, 95% CI 1.526–2.610) or HLP (OR: 1.321, 95% CI 0.937–1.862) (adjusting for age, sex, race, education level, family income, current smoking and drinking status, physical activity, body mass index, diabetes, family history of stroke, and atrial fibrillation). Regarding the additive scale, the relative excess risk due to interaction (OR: 1.053, 95% CI 0.458–1.648) was positive after adjusting for confounders. Moreover, the attributable proportion was 31.3%, which means that 31.3% of the total risk of ischemic stroke was due to the synergistic interaction between HTN and HLP. Furthermore, the synergistic index (S) of ischemic stroke was 1.8 (95% CI 1.157–2.801), which also indicates a synergistic interaction between HTN and HLP. Regarding the multiplicative scale, the interaction effect was also significant after adjusting for confounders (OR: 2.163, 95% CI 1.817–2.575).

Conclusion

The results suggest that the synergistic effect of HTN and HLP on ischemic stroke is significantly higher than the sum of their independent effects. The quantification of the combined effect should help to promote healthy blood pressure and blood lipid levels among the general population.

Hypertriglyceridemia: A Neglected Risk Factor for Ischemic Stroke?

Hypertriglyceridemia is caused by defects in triglyceride metabolism and generally manifests as abnormally high plasma triglyceride levels. Although the role of hypertriglyceridemia may not draw as much attention as that of plasma cholesterol in stroke, plasma triglycerides, especially nonfasting triglycerides, are thought to be correlated with the risk of ischemic stroke. Hypertriglyceridemia may increase the risk of ischemic stroke by promoting atherosclerosis and thrombosis and increasing blood viscosity. Moreover, hypertriglyceridemia may have some protective effects in patients who have already suffered a stroke via unclear mechanisms. Therefore, further studies are needed to elucidate the role of hypertriglyceridemia in the development and prognosis of ischemic stroke.

Atherogenic Index of Plasma Predicts Outcomes in Acute Ischemic Stroke

Aim: The atherogenic index of plasma (AIP) was significantly related to adverse outcomes in patients with cardiovascular disease. Our aim was to investigate the association between AIP and adverse outcomes in acute ischemic stroke.

Methods: Patients with acute ischemic stroke (AIS) admitted between 2015 and 2018 were prospectively enrolled in this study. Functional outcomes were evaluated by the modified Rankin Scale (mRS). Poor outcomes were defined as mRS 3–6. The relationship of AIP with the risk of outcomes was analyzed by multivariate logistic regression models.

Results: A total of 1,463 patients with AIS within 24 h of symptom onset were enrolled. The poor outcome group had a significantly higher level of AIP [0.09 (−0.10 to 0.27) vs. 0.04 (−0.09 to 0.18), p < 0.001] compared with the good outcome group. Multivariable logistic regression analysis showed that higher AIP was associated with poor outcomes in all the stroke patients (OR 1.84, 95% CI, 1.23–2.53, p = 0.007), which was more evident in patients with large-artery atherosclerosis subtype (OR 1.90, 95% CI, 1.53–2.62, p = 0.002), but not in the other subtypes. Receiver operating curve (ROC) analysis revealed that the best predictive cutoff value of AIP was 0.112, with a sensitivity of 70.8% and a specificity of 59.2%, and the area under the ROC curves for AIP was 0.685.

Conclusion: AIP may be an important and independent predictor of the outcome of dysfunction in patients with AIS, especially the stroke subtype of large-artery atherosclerosis.

The association of blood lipid parameters variability with ischemic stroke in hypertensive patients

BACKGROUND AND AIMS

The relationship between lipid variability and stroke among patients with hypertension were inconclusive. We aimed to investigate the association of lipid variability with ischemic stroke in hypertensive patients.

METHODS AND RESULTS

This retrospective cohort study included 4995 individuals with hypertension between 2013 and 2015, and recorded their status of ischemic stroke until the end of 2018. The variability in total cholesterol (TC), triglyceride (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C) were measured using the standard deviation (SD), coefficient of variation (CV), variability independent of the mean (VIM) and average absolute difference between successive values (ASV). Multivariate Cox proportional hazards models with hazard ratios (HRs) and 95% confidence interval (CI) were performed. There were 110 cases of ischemic stroke during a median follow up of 4.2 years. The multivariable adjusted HRs and 95% CIs comparing the highest versus the lowest quartiles of SD of TC, LDL-C, HDL-C and TG were 4.429 (95% CI: 2.292, 8.560), 2.140 (95% CI: 1.264, 3.621), 1.368 (95% CI: 0.793, 2.359) and 1.421 (95% CI: 0.800, 2.525), respectively. High variability in TC and LDL-C were associated with a higher risk for ischemic stroke. Similarly, the results were consistent when calculating variability of TC and LDL-C using CV, ASV and VIM, and in various subgroup analyses.

CONCLUSION

Higher variability of TC and LDL-C associated with the risk of ischemic stroke among hypertensive patients. These findings suggest reducing variability of lipid parameters may decrease adverse outcomes.