Carotid intima media thickness measurements coupled with stroke severity strongly predict short-term outcome in patients with acute ischemic stroke: a machine learning study

Relationship between maximum carotid plaque area and prognosis of patients with acute ischaemic stroke

OBJECTIVE

In this study, the relationship between maximum carotid plaque area and stroke prognosis was analysed by carotid ultrasonography, and the relevant risk factors affecting the prognosis of acute ischaemic stroke (AIS) were investigated to provide novel insights into stroke prevention and management.

METHODS

A total of 205 AIS patients with carotid plaques were included in this study. Based on the mRS score at discharge, patients with AIS were classified into the good prognosis group (mRS ≤ 2) and poor prognosis group (mRS ≥ 3). SPSS 25.0 was used to analyse the data. Univariate and multivariate analyses were performed on the two groups with good and poor prognosis. Comparison between good and poor prognosis in patients with AIS in different circulatory systems was performed using the Kruskal-Wallis test. Differences were considered statistically significant at P < 0.05.

RESULTS

Comparison of baseline data revealed differences in carotid plaque diameter, carotid intima-media thickness, maximum carotid plaque area, history of previous stroke and plaque echogenicity between the good and poor prognosis groups (P < 0.05). Results of multifactorial analyses of logistic binary regression indicated that history of previous stroke and maximum carotid plaque area were predictors of poor prognosis, with odds ratio of 2.515 (95%CI [1.327-4.764]) and 1.019 (95%CI [1.006-1.032]), respectively.

CONCLUSION

The maximum carotid plaque area and history of previous stroke are important predictors for assessing prognosis in patients with AIS.

DNA methylation and stroke prognosis: an epigenome-wide association study

BACKGROUND AND AIMS

Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis.

METHODS AND RESULTS

To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10-5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10-5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-analysis = 6.39·10-9). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10-9 in all cases).

DISCUSSION

Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms.

Heterogeneity in the diagnosis and prognosis of ischemic stroke subtypes: 9-year follow-up of 22,000 cases in Chinese adults

BACKGROUND

Reliable classification of ischemic stroke (IS) etiological subtypes is required in research and clinical practice, but the predictive properties of these subtypes in population studies with incomplete investigations are poorly understood.

AIMS

To compare the prognosis of etiologically classified IS subtypes and use machine learning (ML) to classify incompletely investigated IS cases.

METHODS

In a 9-year follow-up of a prospective study of 512,726 Chinese adults, 22,216 incident IS cases, confirmed by clinical adjudication of medical records, were assigned subtypes using a modified Causative Classification System for Ischemic Stroke (CCS) (large artery atherosclerosis (LAA), small artery occlusion (SAO), cardioaortic embolism (CE), or undetermined etiology) and classified by CCS as "evident," "probable," or "possible" IS cases. For incompletely investigated IS cases where CCS yielded an undetermined etiology, an ML model was developed to predict IS subtypes from baseline risk factors and screening for cardioaortic sources of embolism. The 5-year risks of subsequent stroke and all-cause mortality (measured using cumulative incidence functions and 1 minus Kaplan-Meier estimates, respectively) for the ML-predicted IS subtypes were compared with etiologically classified IS subtypes.

RESULTS

Among 7443 IS subtypes with evident or probable etiology, 66% had SAO, 32% had LAA, and 2% had CE, but proportions of SAO-to-LAA cases varied by regions in China. CE had the highest rates of subsequent stroke and mortality (43.5% and 40.7%), followed by LAA (43.2% and 17.4%) and SAO (38.1% and 11.1%), respectively. ML provided classifications for cases with undetermined etiology and incomplete clinical data (24% of all IS cases; n = 5276), with area under the curves (AUC) of 0.99 (0.99-1.00) for CE, 0.67 (0.64-0.70) for LAA, and 0.70 (0.67-0.73) for SAO for unseen cases. ML-predicted IS subtypes yielded comparable subsequent stroke and all-cause mortality rates to the etiologically classified IS subtypes.

CONCLUSION

This study highlighted substantial heterogeneity in prognosis of IS subtypes and utility of ML approaches for classification of IS cases with incomplete clinical investigations.

Baseline severity and soluble vascular cell adhesion molecule 1 (sVCAM-1) as biomarker predictors of short-term mortality in acute ischemic stroke

The aim was to investigate the association between plasma levels of cellular adhesion molecules (CAMs) and risk factors, subtypes, severity and short-term mortality of acute ischemic stroke (IS), and to identify a panel of biomarkers to predict short-term mortality after IS. The prospective study evaluated 132 IS patients within 24 h of their hospital admission. The baseline IS severity was assessed using the National Institutes Health Stroke Scale (NIHSS) and categorized as mild (NIHSS < 5), moderate (NIHSS 5-14) and severe (NIHSS ≥ 15). After three-month follow-up, the disability was assessed using the modified Rankin Scale (mRS); moreover, the patients were classified as survivors and non-survivors. Baseline inflammatory and anti-inflammatory cytokines and soluble CAMs were evaluated. Twenty-nine (21.9%) IS patients were non-survivors and showed higher NIHSS and soluble vascular cellular adhesion molecule 1 (sVCAM-1) than the survivors. The sVCAM-1 levels positively correlated with age, homocysteine, severity, and disability. The model #3 combining sVCAM-1 and NIHSS showed better results to predict short-term mortality with an area under the curve receiving operating characteristics (AUC/ROC) of 0.8841 [95% confidence interval (CI): 0.795-0.941] than the models with sVCAM-1 and NIHSS alone, with positive predictive value of 68.0%, negative predictive value of 91.3%, and accuracy of 86.5%. In conclusion, the combined model with baseline severity of IS and sVCAM-1 levels can early predict the prognosis of IS patients who may benefit with therapeutic measures of personalized therapy that taken into account these biomarkers. Moreover, this result suggests that VCAM-1 might be a potential target for the therapeutic strategies in IS.

In Mild and Moderate Acute Ischemic Stroke, Increased Lipid Peroxidation and Lowered Antioxidant Defenses Are Strongly Associated with Disabilities and Final Stroke Core Volume

In acute ischemic stroke (AIS), there are no data on whether oxidative stress biomarkers have effects above and beyond known risk factors and measurements of stroke volume. This study was conducted in 122 mild-moderate AIS patients and 40 controls and assessed the modified ranking scale (mRS) at baseline, and 3 and 6 months later. We measured lipid hydroperoxides (LOOH), malondialdehyde (MDA), advanced oxidation protein products, paraoxonase 1 (PON1) activities and PON1 Q192R genotypes, high density lipoprotein cholesterol (HDL), sulfhydryl (-SH) groups), and diffusion-weighted imaging (DWI) stroke volume and fluid-attenuated inversion recovery (FLAIR) signal intensity. We found that (a) AIS is characterized by lower chloromethyl acetate CMPAase PON1 activity, HDL and -SH groups and increased LOOH and neurotoxicity (a composite of LOOH, inflammatory markers and glycated hemoglobin); (b) oxidative and antioxidant biomarkers strongly and independently predict mRS scores 3 and 6 months later, DWI stroke volume and FLAIR signal intensity; and (c) the PON1 Q192R variant has multiple effects on stroke outcomes that are mediated by its effects on antioxidant defenses and lipid peroxidation. Lipid peroxidation and lowered -SH and PON1-HDL activity are drug targets to prevent AIS and consequent neurodegenerative processes and increased oxidative reperfusion mediators due to ischemia-reperfusion injury.

Effects of Low-Frequency (0.5 Hz) and High-Frequency (10 Hz) Repetitive Transcranial Magnetic Stimulation on Neurological Function, Motor Function, and Excitability of Cortex in Ischemic Stroke Patients

BACKGROUND

Repetitive transcranial magnetic stimulation (rTMS) is a noninvasive neuromodulation technique. The purpose of our study is to explore the effects of low-frequency (0.5 Hz) and high-frequency (10 Hz) rTMS on neurological function, motor function, and excitability of cortex in Chinese ischemic stroke patients.

MATERIALS AND METHODS

A total of 240 ischemic stroke patients were collected. The National Institutes of Health Stroke Scale (NIHSS), modified Rankin Scale (mRS), motor-evoked potential (MEP) cortical latency, central motor conduction time (CMCT), Fugel-Meyer assessment (FMA), Berg balance scale (BBS), and modified Barthel index (MBI) scores were recorded.

RESULTS

After treatment, the NIHSS, mRS, MEP cortical latency, CMCT, FMA, BBS, and MBI scores of the high-frequency group and low-frequency group were significantly improved than the sham stimulation group, and the changes in the low-frequency group were more significant (adjusted P <0.05). Compared with the sham stimulation group, high-frequency stimulation reduced the NIHSS score by 9.5%, mRS score by 12.6%, MEP latency by 2.5%, and CMCT by 5.8%, and increased the upper limb FMA scale by 16.4%, lower limb FMA scale by 8.8%, BBS by 26.3%, and MBI by 9.3%, while low-frequency stimulation reduced the NIHSS score by 23.8%, mRS score by 25.3%, MEP Latency by 11.7%, and CMCT by 9.1%, and increased the upper limb FMA scale by 24.1%, lower limb FMA scale by 18.4%, BBS by 27.4%, and MBI by 23.7% in our cohort.

CONCLUSIONS

Low-frequency rTMS is better than high-frequency rTMS stimulation in improving neurological function, motor function, and excitability of cortex in ischemic stroke.

Influence of Carotid Intima-Media Thickness Levels at Bifurcation on Short-Term Functional Outcomes Among Non-Cardiogenic Ischemic Stroke Patients with and without Type 2 Diabetes Mellitus

PURPOSE

The intima-media thickness (IMT) is broadly reported to have relationships with non-cardiogenic ischemic stroke and with diabetes. But how does IMT affect the short-term prognosis of stroke seems unknown yet. We investigated the influence of the intima-media thickness at carotid bifurcation (IMTbif) on short-term functional outcomes among non-cardiogenic ischemic stroke patients with and without type 2 diabetes mellitus (T2DM).

PATIENTS AND METHODS

A total of 314 patients with non-cardiogenic ischemic stroke (122 with T2DM and 192 without diabetes) were included in this retrospective study. Poor functional outcome was defined as a modified Rankin Scale (mRS) > 2 at 3 months after stroke onset. Group comparisons were done in favorable and poor outcome groups. Linear regression analysis was utilized to verify the associations between IMTbif and mRS in subgroups with and without diabetes, respectively.

RESULTS

The median IMTbif of total patients was 1.40mm. Patients with poor outcomes were significantly older, had higher National Institutes of Health Stroke Scale (NIHSS) scores, lower haemoglobin, higher fasting glucose and higher systolic blood pressure values. Their IMTbif levels were also markedly higher. Among 122 included stroke patients with T2DM, IMTbif levels and NIHSS were independently associated with functional outcomes at 3 months, whereas there was no significant association between IMTbif levels and short-term functional outcomes among patients without diabetes.

CONCLUSION

The IMTbif levels were significantly associated with 3-month functional outcomes in non-cardiogenic ischemic stroke patients with T2DM. The ultrasound detection of the IMTbif therefore suggests a prognostic value among patients with stroke and T2DM.

New Drug Targets to Prevent Death Due to Stroke: A Review Based on Results of Protein-Protein Interaction Network, Enrichment, and Annotation Analyses

This study used established biomarkers of death from ischemic stroke (IS) versus stroke survival to perform network, enrichment, and annotation analyses. Protein-protein interaction (PPI) network analysis revealed that the backbone of the highly connective network of IS death consisted of IL6, ALB, TNF, SERPINE1, VWF, VCAM1, TGFB1, and SELE. Cluster analysis revealed immune and hemostasis subnetworks, which were strongly interconnected through the major switches ALB and VWF. Enrichment analysis revealed that the PPI immune subnetwork of death due to IS was highly associated with TLR2/4, TNF, JAK-STAT, NOD, IL10, IL13, IL4, and TGF-β1/SMAD pathways. The top biological and molecular functions and pathways enriched in the hemostasis network of death due to IS were platelet degranulation and activation, the intrinsic pathway of fibrin clot formation, the urokinase-type plasminogen activator pathway, post-translational protein phosphorylation, integrin cell-surface interactions, and the proteoglycan-integrin extracellular matrix complex (ECM). Regulation Explorer analysis of transcriptional factors shows: (a) that NFKB1, RELA and SP1 were the major regulating actors of the PPI network; and (b) hsa-mir-26-5p and hsa-16-5p were the major regulating microRNA actors. In conclusion, prevention of death due to IS should consider that current IS treatments may be improved by targeting VWF, the proteoglycan-integrin-ECM complex, TGF-β1/SMAD, NF-κB/RELA and SP1.

Brain tumor detection and classification using machine learning: a comprehensive survey

Brain tumor occurs owing to uncontrolled and rapid growth of cells. If not treated at an initial phase, it may lead to death. Despite many significant efforts and promising outcomes in this domain, accurate segmentation and classification remain a challenging task. A major challenge for brain tumor detection arises from the variations in tumor location, shape, and size. The objective of this survey is to deliver a comprehensive literature on brain tumor detection through magnetic resonance imaging to help the researchers. This survey covered the anatomy of brain tumors, publicly available datasets, enhancement techniques, segmentation, feature extraction, classification, and deep learning, transfer learning and quantum machine learning for brain tumors analysis. Finally, this survey provides all important literature for the detection of brain tumors with their advantages, limitations, developments, and future trends.