Association Between Low-Density Lipoprotein Cholesterol (LDL-C) Level and Unfavorable Outcomes in Participants of Ischemic Stroke without Diabetes: A Multi-Center Retrospective Study

U-shaped association between low-density lipoprotein cholesterol levels and risk of futile reperfusion mediated by stroke-associated pneumonia in acute ischemic stroke after endovascular thrombectomy

OBJECTIVE

Futile reperfusion (FR) is becoming a major challenge in the treatment of patients with acute ischaemic stroke (AIS) undergoing endovascular thrombectomy. This study aims to determine the dose-response relationship between low-density lipoprotein cholesterol (LDL-C) levels and the risk of FR in patients with AIS undergoing endovascular thrombectomy and to investigate potential mediators.

METHODS

A total of 614 patients with AIS undergoing endovascular thrombectomy were enrolled and divided into five groups according to quintiles of LDL-C levels: Q1(≤2.27 mmol/l), Q2 (2.27-2.5 mmol/l), Q3 (2.5-2.59 mmol/l), Q4 (2.59-2.97 mmol/l) and Q5 (≥2.97 mmol/l). Associations between LDL-C levels and the risk of FR and stroke-associated pneumonia (SAP) were estimated using multivariate logistic regression models. Restricted cubic spline curves were used to describe the dose-response relationship between LDL-C levels and the risk of FR and SAP. Mediation effect analysis was performed in R software with 100 bootstrap samples.

RESULTS

After adjustment for confounders, both low and high LDL-C levels were significantly associated with a higher risk of FR compared with the reference group (Q3). We observed a U-shaped association between LDL-C levels and the risk of FR (P for nonlinear =0.012). Mediation analysis showed that the association between LDL-C levels and the risk of FR was 29.7 % (95 % CI: 2.96 %-75.0 %, P=0.02) mediated by SAP.

CONCLUSIONS

We found a U-shaped association between LDL-C levels and the risk of FR that was mediated by SAP. Clinicians should note that in AIS patients undergoing endovascular thrombectomy, lower LDL-C levels are not always better.

Association between low-density cholesterol change and outcomes in acute ischemic stroke patients who underwent reperfusion therapy

Background

Low-density lipoprotein cholesterol (LDL-C) can increase cardiovascular risk. However, the association between LDL-C change and functional outcomes in acute ischemic stroke (AIS) patients who underwent reperfusion therapy remains unclear.

Methods

Patients who received reperfusion therapy were consecutively enrolled. LDL-C measurement was conducted at the emergency department immediately after admission and during hospitalization. The change of LDL-C level (ΔLDL-C) was calculated by subtracting the lowest LDL-C among all measurements during hospitalization from the admission LDL-C. Poor functional outcome was defined as modified Rankin Scale (mRS) > 2 at 90 days.

Results

A total of 432 patients were enrolled (mean age 69.2 ± 13.5 years, 54.6 % males). The mean LDL-C level at admission was 2.55 ± 0.93 mmol/L. The median ΔLDL-C level was 0.43 mmol/L (IQR 0.08–0.94 mmol/L). A total of 263 (60.9 %) patients had poor functional outcomes at 90 days. There was no significant association between admission LDL-C level and functional outcome (OR 0.99, 95 % CI 0.77–1.27, p = 0.904). ΔLDL-C level was positively associated with poor functional outcome (OR 1.80, 95 % CI 1,12-2.91, p = 0.016). When patients were divided into tertiles according to ΔLDL-C, those in the upper tertile (T3, 0.80–3.98 mmol/L) were positively associated with poor functional outcomes compared to patients in the lower tertile (T1, -0.91-0.13 mmol/L) (OR 2.56, 95 % CI 1.22–5.36, p = 0.013). The risk of poor functional outcome increased significantly with ΔLDL-C tertile (P-trend = 0.010).

Conclusions

In AIS patients who underwent reperfusion therapy, the decrease in LDL-C level during hospitalization was significantly associated with poor functional outcomes at 90 days.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-021-02387-2.

Low LDL-C levels are associated with risk of mortality in a Chinese cohort study

BACKGROUND AND AIMS

Although low-density lipoprotein cholesterol (LDL-C) has been considered as a risk factor of atherosclerotic cardiovascular disease, limited studies can be available to evaluate the association of LDL-C with risk of mortality in the general population. This study aimed to examine the association of LDL-C level with risk of mortality using a propensity-score weighting method in a Chinese population, based on the health examination data.

METHODS

We performed a retrospective cohort study with 65,517 participants aged 40 years or older in Ningbo city, Zhejiang. LDL-C levels were categorized as five groups according to the Chinese dyslipidemia guidelines in adults. To minimize potential biases resulting from a complex array of covariates, we implemented a generalized boosted model to generate propensity-score weights on covariates. Then, we used Cox proportional hazard regression models with all-cause and cause-specific mortality as the dependent variables to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs).

RESULTS

During the 439,186.5 person years of follow-up, 2403 deaths occurred. Compared with the median LDL-C group (100-130 mg/dL), subjects with extremely low LDL-C levels (group 1) had a higher risk of deaths from all-cause (HR = 2.53, 95% CI:1.80-3.53), CVD (HR = 1.84, 95% CI: 1.28-2.61), ischemic stroke (HR = 2.29, 95% CI:1.32-3.94), hemorrhagic stroke (HR = 3.49, 95% CI: 1.57-7.85), and cancer (HR = 2.12, 95% CI: 1.04-4.31) while the corresponding HRs in LDL-C group 2 were relatively lower than that in group 1.

CONCLUSIONS

Low LDL-C levels were associated with an increased risk of all-cause, CVD, ischemic stroke, hemorrhagic stroke, and cancer mortality in the Chinese population.

The prognostic significance of the lipid profile after an ischemic stroke

BACKGROUND

The role that cholesterol levels play in stroke is still uncertain, especially in secondary prevention. The aim was to determine how a comprehensive analysis of the lipid profile can be associated with post-stroke outcomes.

Consecutive patients diagnosed with ischemic stroke were included in our cohort and followed up for 24months. Baseline clinical and demographic data were collected as well as a complete lipid profile 6-months after the index stroke. Lipid variables were analyzed quantitatively and qualitatively. Clinical outcomes included stroke recurrence, major cardiovascular events, and functional performance (assessed with the modified Rankin scale).

RESULTS

The study included 588 patients with an average age of 58.3 years. There were 148 (25.2%) patients with high total cholesterol, 260 (44.2%) with low HDL, 180 (30.6%) with high LDL, and 204 (34.7%) with high triglycerides. There were 164 (27.9%) patients with no abnormalities in the lipid profile. After the follow-up, 108 (18.3%) had another stroke, 32 (5.4%) had major cardiovascular events, and 360 (61.2%) presented good functional outcomes. A higher LDL-C/HDL-C ratio and a low HDL-C level were significantly associated with worse cardiovascular outcomes. The detection of LDL-C > 70 mg/dL was an independent predictor of a higher risk of stroke recurrence and worse functional performance. The greater the number of altered lipid variables, the greater the chance of developing an unfavorable composite outcome and presenting cardiovascular events after the stroke.

CONCLUSIONS

The complete analysis of the lipid panel allows the determination of the prognosis of patients who suffered a stroke.

Outcomes of Ischemic Stroke and Associated Factors Among Elderly Patients With Large-Artery Atherosclerosis: A Hospital-Based Follow-Up Study in China

Large-artery atherosclerotic (LAA) stroke is the most common subtype of ischemic stroke. However, risk factors for long-term outcomes of LAA stroke in the elderly Chinese population have not been well-described. Therefore, we aimed to assess outcomes and risk factors at 3, 12, and 36 months after LAA stroke onset among stroke patients aged 60 years and older. All consecutive LAA patients aged ≥ 60 years were prospectively recruited from Dongying People's Hospital between January 2016 and December 2018. The clinical features and outcome data at 3, 12, and 36 months after stroke were collected. Differences in outcomes and relationship between outcomes and risk factors were assessed. A total of 1,772 patients were included in our study (61.7% male, 38.3% female). The rates of mortality, recurrence, and dependency were 6.6, 12.6, and 12.6%, respectively, at 3 months after stroke onset. The corresponding rate rose rapidly at 36 months (23.2, 78.7, and 79.7%, respectively). We found the positive predictors associated outcomes at 3, 12, and 36 months after stroke onset. The relative risk (RR) with 95% confidential interval (CI) is 1.06 (1.02–1.10, P = 0.006) at 3 months, 1.06 (1.02–1.10, P = 0.003) at12 months, and 1.10 (1.05–1.15, P < 0.001) at 36 months after stroke onset for age; 1.09 (1.01–1.19, P = 0.029) at 12 months for fasting plasma glucose (FPG) level; 4.25 (2.14–8.43, P < 0.001) at 3 months, 4.95 (2.70–9.10, P < 0.001) at 12 months, and 4.82 (2.25–10.32, P < 0.001) at 36 months for moderate stroke; 7.56 (3.42–16.72, P < 0.001) at 3 months, 11.08 (5.26–23.34, P < 0.001) at 12 months, and 14.30 (4.85–42.11, P < 0.001) at 36 months for severe stroke, compared to mild stroke. Hypersensitive C-reactive protein (hs-CRP) level was an independent risk factor for mortality at different follow-up times, with the RR (95%) of 1.02 (1.01–1.02, P < 0.001) at 3 months, 1.01 (1.00–1.02, P = 0.002) at 12 months. White blood cell count (WBC) level was associated with both stroke recurrence (RR = 1.09, 95%CI: 1.01–1.18, P = 0.023) and dependency (RR = 1.10, 95%CI: 1.02–1.19, P = 0.018) at 3 months. In contrast, a higher level of low-density lipoprotein cholesterol (LDL-C) within the normal range was a protective factor for recurrence and dependency at shorter follow-up times, with the RR (95%) of 0.67 (0.51–0.89, P = 0.005) and 0.67 (0.50–0.88, P = 0.005), respectively. These findings suggest that it is necessary to control the risk factors of LAA to reduce the burden of LAA stroke. Especially, this study provides a new challenge to explore the possibility of lowering LDL-C level for improved stroke prognosis.

INVERSE PROBLEM ALGORITHM APPLICATION TO SEMI-QUANTITATIVE ANALYSIS OF 272 PATIENTS WITH ISCHEMIC STROKE SYMPTOMS: CAROTID STENOSIS RISK ASSESSMENT FOR FIVE RISK FACTORS

This study proposes the inverse problem algorithm (IPA) with five risk factors applied to the semi-quantitative analysis of carotid stenosis 272 patients with suspected ischemic stroke. The IPA is known to provide a substantiated machine learning-based prediction of the expected outcomes by solving an inverse matrix of variable coefficients. In case of carotid stenosis prediction, such risk factors as patient’s age, mean arterial pressure (MAP), glucose AC, low-density lipoprotein-cholesterol (LDL-C), and C-Reactive protein (CRP) were assessed for the main group of 217 patients. Their results were processed by the STATISTICA program with a customized loss function ([Formula: see text]), yielding the first-order nonlinear semi-empirical formula with 16 terms. The loss function was calculated via the total mismatch between the theoretical predictions and true carotid stenosis cases (%) for all 217 patients. Thus, the carotid stenosis (%) compromised solution array [[Formula: see text]] was optimized using [Formula: see text] individual data points via the proposed algorithm. The results showed a complete regression with loss function [Formula: see text]=2.3543, variance [Formula: see text]=87.46%, and correlation coefficient [Formula: see text]. The reference group of 55 more patients with the same preliminary diagnosis and symptoms was selected to validate the method predictive feasibility, which was found quite satisfactory. The decreasing order of three dominant risk factors was as follows: CRP, glucose AC, and MAP, whereas age and LDL-C weakly influenced the program computation results. The IPA showed a strong convergence by its default characteristic. The reduction of the number of variables in computation deteriorated the prediction accuracy, exhibiting the algorithm’s high sensitivity to the number of variables.

Clinical Utility of the Inflammatory Factors Combined With Lipid Markers in the Diagnostic and Prognostic Assessment of Ischemic Stroke: Based on Logistic Regression Models

BACKGROUND

In this study, we developed novel logistic regression models for the diagnostic and prognostic assessment of ischemic stroke.

METHODS

A total of 288 ischemic stroke patients and 300 controls admitted to The First Affiliated Hospital of Soochow University were included in the testing group. Two validation groups from The Affiliated Kunshan Hospital of Jiangsu University and The Second Affiliated Hospital of Soochow University were included to assess our novel assessment models.

RESULTS

Results from the testing group indicated that the diagnostic assessment model for ischemic stroke prediction was: Logit(P) = 437.116 - 87.329 (Hypertension) - 89.700 (Smoking history) - 87.427 (Family history of ischemic stroke) - .090 (high-density lipoprotein cholesterol [HDL-C]) - 1.984 (low-density lipoprotein cholesterol [LDL-C]) - 17.005 (Lp(a)) - 15.486 (Apo A/Apo B), and the final prognostic assessment model of ischemic stroke was: Logit(P) = 458.437-92.343 (Hypertension) - 89.763 (Smoking history) + .251 (NLR) - .088 (HDL-C) - 1.994 (LDL-C) - 2.883 (hs-CRP) - .058 (IL-6) - 6.356 (TNF-α) - 16.485 (Lp(a)) - 17.658 (Apo A/Apo B). In the validation groups, our novel diagnostic assessment model showed good identification (with 87.5% sensitivity and 84.2% specificity in The Affiliated Kunshan Hospital of Jiangsu University, with 85.5% sensitivity and 89.0% specificity in The Second Affiliated Hospital of Soochow University). Moreover, our novel prognostic assessment model has a high value in identifying poor prognosis patients in the validation groups from The Affiliated Kunshan Hospital of Jiangsu University (χ² = 8.461, P = .004), and The Second Affiliated Hospital of Soochow University (χ² = 7.844, P = .005).

CONCLUSIONS

The diagnostic and prognostic assessment models we have established are of great value in the diagnosis and prognostic evaluation of ischemic stroke.