Association between non-high-density lipoprotein cholesterol and haemorrhagic transformation in patients with acute ischaemic stroke

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.

Traditional and Non-Traditional Lipid Parameters in Relation to Parenchymal Hemorrhage Following Endovascular Treatment for Acute Ischemic Stroke in Anterior Circulation

Purpose

Lipid-lowering therapy is integral in acute ischemic stroke (AIS), yet the connection between lipid parameters and parenchymal hemorrhage (PH) after endovascular treatment (EVT) for AIS is not well-defined. This research aims to assess the association between various lipid parameters and the PH risk following EVT.

Patients and Methods

We examined a database of patients who underwent EVT for AIS between September 2021 and May 2023 retrospectively. Traditional and non-traditional lipid parameters were documented. PH was identified on dual energy computed tomography images within 48 h. We employed logistic regression analysis and restricted cubic splines to examine the association between various lipid parameters and the risk of PH. The predictive capacity of the lipid parameters for PH was evaluated by comparing the area under the curve.

Results

The study included 384 patients, 65 of whom (17.7%) developed PH. After adjusting for potential confounders, only triglyceride was associated with PH among the traditional lipid parameters, while all non-traditional lipid parameters were related to PH. Based on ROC curve, the ratio of remnant cholesterol to high-density lipoprotein cholesterol (RC/HDL-C) exhibited the highest predictive capability for PH. Furthermore, our analysis revealed a significant nonlinear correlation between triglyceride, non-high-density lipoprotein cholesterol, RC, RC/HDL-C and PH risk.

Conclusion

In assessing the risk of PH after EVT, non-traditional lipid parameters are often superior to traditional lipid parameters. It is recommended that routine evaluation of non-traditional lipid parameters could also be conducted in clinical practice as well.

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.

Impact of lipid profiles on parenchymal hemorrhage and early outcome after mechanical thrombectomy

OBJECTIVE

We aimed to investigate the association of lipid parameters with parenchymal hemorrhage (PH) and early neurological improvement (ENI) after mechanical thrombectomy (MT) in stroke patients.

METHODS

We retrospectively analyzed consecutive patients who underwent MT between January 2019 and February 2022 at a tertiary stroke center. PH was diagnosed and classified as PH-1 and PH-2 according to the European Cooperative Acute Stroke Study definition. ENI was defined as a decrease in the National Institutes of Health Stroke Scale (NIHSS) score by ≥8 or an NIHSS score of ≤1 at 24 h after MT.

RESULTS

Among 155 patients, PH occurred in 41 (26.5%) patients, and 34 (21.9%) patients achieved ENI. In multivariate analysis, lower triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C) value (OR = 0.51; 95% CI 0.30-0.89; p = 0.017) and higher HDL-C level (OR = 5.83; 95% CI 1.26-26.99; p = 0.024) were independently associated with PH. The combination of TG <0.77 mmol/L and HDL-C ≥ 0.85 mmol/L was the strongest predictor of PH (OR = 10.73; 95% CI 2.89-39.87; p < 0.001). A low HDL-C level was an independent predictor of ENI (OR 0.13; 95% CI 0.02-0.95; p = 0.045), and PH partially accounts for the failure of ENI in patients with higher HDL-C levels (estimate: -0.05; 95% CI: -0.11 to -0.01; p = 0.016).

INTERPRETATION

The combination of lower TG level and higher HDL-C level can predict PH after MT. Postprocedural PH partially accounts for the failure of ENI in patients with higher HDL-C levels. Further studies into the pathophysiological mechanisms underlying this observation are of interest.

Association of low-density lipoprotein-cholesterol with all-cause and cause-specific mortality

AIMS

To explore the association between low-density lipoprotein-cholesterol (LDL-C) and all-cause and cause-specific mortality based on a prospective cohort study.

METHODS

Among 10850 individuals enrolled from National Health and Nutrition Examination Survey (NHANES) 1999-2014, 1355 (12.5%) died after an average follow-up of 5.7 years. Cox proportional regression models were used to determine the association between LDL-C with the risk of mortality.

RESULTS

The level of LDL-C was L-shaped associated with the risk of all-cause mortality, namely a low level was related to an increased mortality risk. The level of LDL-C associated with the lowest risk of all-cause mortality was 124 mg/dL (3.2 mmol/L) in the overall population, and 134 mg/dL (3.4 mmol/L) in individuals not receiving lipid lowering treatment. Compared with participants with LDL-C of 110-134 mg/dL (2.8-3.5 mmol/L), the multivariable adjusted hazard ratio was 1.18 (95% confidence interval 1.01 to 1.38) for individuals with the lowest quartile for all-cause mortality. In participants with coronary heart diseases, the conclusion was similar but the critical point was lower.

CONCLUSIONS

We found that low levels of LDL-C increased the risk of all-cause mortality, and the lowest risk of all-cause mortality for LDL-C concentration was 124 mg/dL (3.2 mmol/L). Our results provide a reasonable range of LDL-C when to initiate a statin therapy in clinical practice.

Impact of Traditional and Non-Traditional Lipid Parameters on Outcomes after Intravenous Thrombolysis in Acute Ischemic Stroke

Contradicting evidence exists regarding the role of lipids in outcomes following intravenous (IV) thrombolysis with tissue plasminogen activator (tPA). Restricted cubic spline curves and adjusted logistic regression were used to evaluate associations of low-density lipoprotein cholesterol (LDL-C), non-high-density lipoprotein cholesterol (non-HDL-C), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C) and LDL-C/HDL-C ratio with poor functional outcome, symptomatic intracranial hemorrhage (SICH) and 90-day mortality, among 1004 acute ischemic stroke (AIS) patients who received IV tPA in a comprehensive stroke center. Quartile (Q) 1, Q2 and Q3 of HDL-C were associated with increased odds of poor functional outcome (adjusted odds ratio (adjOR) 1.66, 95% CI 1.06-2.60, p = 0.028, adjOR 1.63, 95% CI 1.05-2.53, p = 0.027, adjOR 1.56, 95% CI 1.01-2.44, p = 0.048) compared to Q4. Q2 and Q4 of non-HDL-C were associated with increased odds of SICH (adjOR 4.28, 95% CI 1.36-18.90, p = 0.025, adjOR 5.17, 95% CI 1.64-22.81, p = 0.011) compared to Q3. Q1 and Q2 of LDL-C was associated with increased odds of mortality (adjOR 2.57, 95% CI 1.27-5.57, p = 0.011 and adjOR 2.28, 95% CI 1.10-5.02, p = 0.032) compared to Q3. In AIS patients who received IV tPA, low LDL-C was associated with increased odds of mortality while HDL-C may be protective against poor functional outcome.

Association of Dilated Perivascular Spaces With Lipid Indices in Ischemic Stroke Patients

Background

Dilated perivascular spaces (dPVS) in the basal ganglia are associated with aging, vascular risk factors, and other magnetic resonance imaging (MRI) markers of cerebral small vessel disease (cSVD). While high blood lipids are a well-demonstrated risk factor for large artery atherosclerosis, their role in cSVD remains largely elusive.

Methods

We evaluated lipid profiles, cardiovascular risk factors, and brain MRI findings in patients with ischemic stroke or transient ischemic attack. We analyzed the extent of dPVS, cerebral microbleed (CMB), and cerebral white matter hyperintensities (WMHs) as MRI indices of cSVD and investigated associations of dPVS with lipid parameters and other cSVD indices.

Results

Our study enrolled 173 patients with ischemic stroke or transient ischemic attack. The mean age was 68.38±14.31 (range 35-99) years, and 57.8% (n=100) of patients were male. dPVSwere detected in 97% (n=168) of the patients. Among the whole population, half of the patients (n=87) had moderate to severe dPVS. According to the univariate analysis, age, hypertension, previous antiaggregant and/or anticoagulant use, and the high-density lipoprotein to low-density lipoprotein (HDL/LDL) ratio but not other lipid profiles, cerebral microbleed load, and cerebral white matter hyperintensities severity were found to be positively associated with dPVS number in the basal ganglia. After multivariate logistic regression analysis, only age and WMH severity remained statistically significant.

Conclusions

dPVS are closely associated with other cSVD subtypes and aging. The studied lipid indices were not independently associated with moderate to severe dPVS in basal ganglia in ischemic stroke patients. The association of each lipid and HDL/LDL ratio needs to be further studied with a larger number of participants.

Development and Validation of a Predictive Model for Spontaneous Hemorrhagic Transformation After Ischemic Stroke

Background: Hemorrhagic transformation (HT) after reperfusion therapy for acute ischemic stroke (AIS) has been well studied; however, there is scarce research focusing on spontaneous HT (sHT). Spontaneous HT is no less important with a relatively high incidence and could be associated with neurological worsening. We aimed to develop and validate a simple and practical model to predict sHT after AIS (SHAIS) and compared the predictive value of the SHAIS score against the models of post-Reperfusion HT for sHT.

Methods: Patients with AIS admitted within 24 h of onset were prospectively screened to develop and validate the SHAIS score. The primary outcome was sHT during hospitalization (within 30 days after onset), and the secondary outcomes were symptomatic sHT and parenchymal hematoma (PH). Clinical information, laboratory, and neuroimaging data were screened to construct the SHAIS score. We selected six commonly used scales for predicting HT after reperfusion therapy and compared their predictive ability for sHT with the SHAIS score using Delong's test.

Results: The derivation cohort included 539 patients (mean age, 68.1 years; men, 61.4%), of whom 91 (16.9%) patients developed sHT with 25.3% (23/91) being symptomatic sHT and 62.6% (57/91) being PH. Five variables (atrial fibrillation, NIHSS score ≥ 10, hypodensity > 1/3 of middle cerebral artery territory, hyperdense artery sign, and anterior circulation infarction) composed the SHAIS score, which ranged from 0 to 11 points. The area under the receiver-operating characteristic curve (AUC) was 0.86 (95% CI 0.82–0.91, p < 0.001) for the overall sHT, 0.85 (95% CI 0.76–0.92, p < 0.001) for symptomatic sHT, and 0.89 (95% CI 0.85–0.94, p < 0.001) for PH. No evidence of miscalibration of the SHAIS score was found to predict the overall sHT (p = 0.19), symptomatic sHT (p = 0.44), and PH (p = 0.22). The internal (n = 245) and external validation cohorts (n = 200) depicted similar predictive performance compared to the derivation cohort. The SHAIS score had a higher AUC to predict sHT than any of the six pre-Existing models (p < 0.05).

Conclusions: The SHAIS score provides an easy-to-use model to predict sHT, which could help providers with decision-making about treatments with high bleeding risk, and to counsel patients and families on the baseline risk of HT, aligning expectations with probable outcomes.

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.

Predictors and Prognosis of Symptomatic Intracranial Hemorrhage in Acute Ischemic Stroke Patients Without Thrombolysis: Analysis of Data From the Chinese Acute Ischemic Stroke Treatment Outcome Registry

Background and Purpose: There is limited information on symptomatic intracranial hemorrhage (sICH) in stroke patients without thrombolysis. This study aimed to evaluate the risk factors of sICH and the association between sICH and the prognosis at 3 and 12 months in acute ischemic stroke patients without thrombolysis.

Methods: Data originated from the Chinese Acute Ischemic Stroke Treatment Outcome Registry. Univariate analysis and multivariate logistic regression were used to screen the risk factors of sICH. Multivariable logistic regression models were used to assess the association of sICH with poor outcome and all-cause mortality.

Results: Totally, 9,484 patients were included, of which 69 (0.73%) had sICH. Atrial fibrillation (odds ratio [OR], 3.682; 95% confidence interval [CI], 1.945–6.971; p < 0.001), history of tumors (OR, 2.956; 95% CI, 1.115–7.593; p = 0.024), and the National Institutes of Health Stroke Scale (NIHSS) score on admission ([6–15: OR, 2.344; 95% CI, 1.365–4.024; p = 0.002] [>15: OR, 4.731; 95% CI, 1.648–13.583; p = 0.004]) were independently associated with sICH. After adjustment of the confounders, patients with sICH had a higher risk of poor outcome (OR, 1.983; 95% CI, 1.117–3.521; p = 0.018) at 3 months and that of all-cause mortality at 3 (OR, 6.135; 95% CI, 2.328–16.169; p < 0.001) and 12 months (OR, 3.720; 95% CI, 1.513–9.148; p = 0.004).

Conclusion: sICH occurred in 0.73% of acute ischemic stroke patients without thrombolysis and was associated with a worse prognosis at 3 and 12 months. Atrial fibrillation, history of tumors, and NIHSS score at admission were independent risk factors of sICH.

SWATH-MS for prospective identification of protein blood biomarkers of rtPA-associated intracranial hemorrhage in acute ischemic stroke: a pilot study

Intravenous recombinant tissue plasminogen activator (rtPA) is, besides mechanical thrombectomy, the highest class evidence based reperfusion treatment of acute ischemic stroke (AIS). The biggest concern of the therapy is symptomatic intracranial hemorrhage (sICH), which occurs in 3-7% of all treated patients, and is associated with worse functional outcome. Finding a method of the powerful identification of patients at highest risk of sICH, in order to increase the percentage of stroke patients safely treated with rtPA, is one of the most important challenges in stroke research. To address this problem, we designed a complex project to identify blood, neuroimaging, and clinical biomarkers combined for prospective assessment of the risk of rtPA-associated ICH. In this paper we present results of blood proteomic and peptide analysis of pilot 41 AIS patients before rtPA administration (the test ICH group, n = 9 or the controls, without ICH, n = 32). We demonstrated that pre-treatment blood profiles of 15 proteins differ depending on whether the patients develop rtPA-associated ICH or not. SWATH-MS quantification of serum or plasma proteins might allow for robust selection of blood biomarkers to increase the prospective assessment of rtPA-associated ICH over that based solely on clinical and neuroimaging characteristics.

Prediction of Hemorrhagic Transformation After Ischemic Stroke: Development and Validation Study of a Novel Multi-biomarker Model

Objectives: We aimed to develop and validate a novel multi-biomarker model for predicting hemorrhagic transformation (HT) risk after acute ischemic stroke (AIS).

Methods: We prospectively included patients with AIS admitted within 24 h of stroke from January 1st 2016 to January 31st 2019. A panel of 17 circulating biomarkers was measured and analyzed in this cohort. We assessed the ability of individual circulating biomarkers and the combination of multiple biomarkers to predict any HT, symptomatic HT (sHT) and parenchymal hematoma (PH) after AIS. The strategy of multiple biomarkers in combination was then externally validated in an independent cohort of 288 Chinese patients.

Results: A total of 1207 patients with AIS (727 males; mean age, 67.2 ± 13.9 years) were included as a derivation cohort, of whom 179 patients (14.8%) developed HT. The final multi-biomarker model included three biomarkers [platelets, neutrophil-to-lymphocyte ratios (NLR), and high-density lipoprotein (HDL)] from different pathways, showing a good performance for predicting HT in both the derivation cohort (c statistic = 0·64, 95% CI 0·60–0·69), and validation cohort (c statistic = 0·70, 95% CI 0·58–0·82). Adding these three biomarkers simultaneously to the basic model with conventional risk factors improved the ability of HT reclassification [net reclassification improvement (NRI) 65.6%, P < 0.001], PH (NRI 64.7%, P < 0.001), and sHT (NRI 71.3%, P < 0.001).

Conclusion: This easily applied multi-biomarker model had a good performance for predicting HT in both the derivation and external validation cohorts. Incorporation of biomarkers into clinical decision making may help to identify patients at high risk of HT after AIS and warrants further consideration.