Risk factors and a prediction model for the prognosis of intracerebral hemorrhage using cerebral microhemorrhage and clinical factors

BackgroundThis study aimed to identify the risk factors and construct a prediction model for the prognosis of intracerebral hemorrhage (ICH) at discharge, 3 months, and 12 months.MethodsA total of 269 patients with ICH were retrospectively enrolled at our hospital between January 2014 and August 2016. The prognosis of ICH was assessed using the modified Rankin Scale (mRS); an mRS score > 2 was considered a poor outcome. The primary endpoint was the 3-month mRS, whereas the secondary endpoints included the mRS scores at discharge and 12 months, and mortality.ResultsThe Glasgow Coma Scale (GCS), National Institutes of Health (NIH) stroke scale, International Normalized Ratio (INR), blood urea nitrogen (BUN), epencephalon hemorrhage, and primary hematoma volume were significantly associated with a poor mRS score at 3 months. The predictive value of the prediction model based on these factors for a poor mRS score was 87.8%. Furthermore, a poor mRS score at discharge was affected by the GCS, NIH stroke scale, and primary hematoma volume; the constructed model based on these factors had a predictive value of 87.6%. In addition, the GCS, NIH stroke scale, and surgery were significantly related to a poor mRS score at 12 months; the predictive value of the constructed model based on the aforementioned factors for a poor mRS score was 86.5%. Finally, primary hematoma volume is significantly associated with the risk of 12 months mortality.ConclusionsThe study identified risk factors and constructed a prediction model for poor mRS scores and mortality at discharge, 3 and 12 months in patients with ICH. The prediction models for mRS scores showed a relatively high predictive performance

Seismic soil-structure interaction.

A time domain analysis procedure and computational models for seismic soil-structure interaction are presented in this work. The time domain analysis technique makes it possible to take the nonlinearity of the soil and the upper structure into account in the soil-structure interaction analysis. The boundary element method has been used to model the far-field soil which has been shown to be very effective for a surface foundation or an embedded foundation in a linearly elastic half space. A simplified vertical energy transmitting boundary has been developed for a large near-field in which nonlinear finite elements are used. This simplified vertical boundary requires much less computational effort than that required by the boundary element method because no numerical transformation is required. The bounding surface plasticity model has been implemented for the solid finite elements of the near-field soil and the beam elements of the upper structure. This model can also be used in the free field analysis. An approximate model for the far-field dynamic stiffness matrix has been proposed for the time domain analysis. By specifying the dynamic stiffness matrix of the far-field at the fundamental frequency of the soil-structure system, a nonlinear analysis of the near-field and the upper structure can be performed. Techniques to avoid the unstable solution of the approximate model are also given. Various partitioned analysis procedures are discussed and a numerical evaluation of the stabilities and their accuracies are presented. A primary investigation of the soil-structure interaction effects is performed for two sites, Period shift due to the presence of the flexible soil has a very strong influence on the structural responses and the large structural displacements relative to the free field caused by the soil- structure interaction were found to be responsible for the pounding of adjacent structures. The soil nonlinearity has been found to be an important factor for the foundation failure under seismic loading

FaFCNN: A General Disease Classification Framework Based on Feature Fusion Neural Networks

There are two fundamental problems in applying deep learning/machine learning methods to disease classification tasks, one is the insufficient number and poor quality of training samples; another one is how to effectively fuse multiple source features and thus train robust classification models. To address these problems, inspired by the process of human learning knowledge, we propose the Feature-aware Fusion Correlation Neural Network (FaFCNN), which introduces a feature-aware interaction module and a feature alignment module based on domain adversarial learning. This is a general framework for disease classification, and FaFCNN improves the way existing methods obtain sample correlation features. The experimental results show that training using augmented features obtained by pre-training gradient boosting decision tree yields more performance gains than random-forest based methods. On the low-quality dataset with a large amount of missing data in our setup, FaFCNN obtains a consistently optimal performance compared to competitive baselines. In addition, extensive experiments demonstrate the robustness of the proposed method and the effectiveness of each component of the model\footnote{Accepted in IEEE SMC2023}

OPR-Miner: Order-preserving rule mining for time series

Discovering frequent trends in time series is a critical task in data mining. Recently, order-preserving matching was proposed to find all occurrences of a pattern in a time series, where the pattern is a relative order (regarded as a trend) and an occurrence is a sub-time series whose relative order coincides with the pattern. Inspired by the order-preserving matching, the existing order-preserving pattern (OPP) mining algorithm employs order-preserving matching to calculate the support, which leads to low efficiency. To address this deficiency, this paper proposes an algorithm called efficient frequent OPP miner (EFO-Miner) to find all frequent OPPs. EFO-Miner is composed of four parts: a pattern fusion strategy to generate candidate patterns, a matching process for the results of sub-patterns to calculate the support of super-patterns, a screening strategy to dynamically reduce the size of prefix and suffix arrays, and a pruning strategy to further dynamically prune candidate patterns. Moreover, this paper explores the order-preserving rule (OPR) mining and proposes an algorithm called OPR-Miner to discover strong rules from all frequent OPPs using EFO-Miner. Experimental results verify that OPR-Miner gives better performance than other competitive algorithms. More importantly, clustering and classification experiments further validate that OPR-Miner achieves good performance

Is there a correlation between socioeconomic disparity and functional outcome after acute ischemic stroke?

Background To investigate the impact of low socioeconomic status (SES), indicated by low level of education, occupation and income, on 3 months functional outcome after ischemic stroke. Methods We analyzed data from the China National Stroke Registry (CNSR), a multicenter and prospective registry of consecutive patients with acute cerebrovascular events occurred between September 2007 and August 2008. 11226 patients with ischemic stroke had SES and clinical characteristics data collected at baseline and mRS measured as indicator of functional outcome in 3 months follow up. Multinomial and ordinal logistic regression models were performed to examine associations between SES and the functional outcome. Results At 3 months after stroke, 5.3% of total patients had mRS scored at 5, 11.3% at score 4, 11.1% at score 3, 14.4% at score 2, 34.2% at score 1 and 23.7% at score 0. Compared to patients with educational level of ≥ 6 years and non-manual laboring, those < 6 years and manual laboring tended to have higher mRS score (P<0.001). Multinomial adjusted odds ratios (ORs) of outcome in manual workers were significantly increased (ORs from1.38 to 1.87), but OR in patients with less income was not significant. There were similar patterns of association The impact may be stronger in patients aged <65 years (P = 0.003, P<0.001 respectively) and being male (P = 0.001, P<0.001 respectively). Conclusions Our study provides evidence that people who are relatively more deprived in socioeconomic status suffer poorer outcome after ischemic stroke. The influence of low educational level and manual laboring can be more intensive than low income level on 3-month outcome. Health policy and service should target the deprived populations to reduce the public health burden in the society.This study is supported by grants from the Ministry of Science and Technology of the People’s Republic of China (2006BAI01A11, 2011BAI08B01, 2011BAI08B02, 2012ZX09303-005-001, and 2013BAI09B03), a grant from the Beijing Biobank of Cerebral Vascular Disease (D131100005313003) and a grant from Beijing Institute for Brain Disorders (BIBD-PXM2013_014226_07_000084

Homocysteine and Carotid Plaque Stability: A Cross-Sectional Study in Chinese Adults

Background and Purpose This study aimed to explore the possible association of plasma total homocysteine with carotid plaque stability. Methods: A cross-sectional study was conducted from 2010 to 2011. A stratified random sample of 2,919 Chinese participants aged 40 years or older was enrolled. Plasma total homocysteine levels were measured and carotid plaques were evaluated by ultrasonography. Logistic regression model was used to analyze the association of homocysteine levels to the progression of carotid plaque development, while adjusting for demographics and vascular risk factors. Results: The mean level of plasma homocysteine in the subjects was 14.9 µmol/l. Along with increase in homocysteine level, the risk of advanced carotid plaque elevated (odds ratio = 1.28; 95% confidence interval = 1.09–1.51) after adjusting for age, sex, and other potential confounders. Stratified by sex, higher homocysteine level was strongly associated with advanced carotid plaque in men (OR = 1.41; 95% confidence interval = 1.17–1.70), but not in women. Conclusion: The findings suggest that plasma level of homocysteine may be associated with advanced carotid plaque, which constitutes high risks of stroke, in male Chinese adults

Elevated Plasma Total Cholesterol Level Is Associated with the Risk of Asymptomatic Intracranial Arterial Stenosis

Background: Intracranial arterial stenosis (ICAS) is one of the most common causes of stroke, and dyslipidemia was one of the most common risk factors related to ICAS. However, the correlation between the plasma total cholesterol level (PTC) and ICAS, especially asymptomatic ICAS (AICAS) is not clear. Materials and Methods 5,300 participants were enrolled in this study. The diagnosis of AICAS was made by transcranial Doppler ultrasonography. The participants were then divided into 5 essentially equal-sized groups based on their PTC levels. The multivariate logistic regression was used to analyze the correlation between the PTC level and the prevalence of AICAS. Results: 13.0% of the participants were diagnosed with AICAS. The prevalence of AICAS gradually increased with the increasing PTC level. After adjusted by the possible confounding factors, the Odds Ratios (OR) of the AICAS prevalence between the 1st quintile group and the other 4 groups were 1.13, 1.23, 1.63 and 1.75 with 95% confident intervals (CI) of 0.84–1.52, 0.91–1.66, 1.20–2.22 and 1.23–2.47, respectively. The further subgroup analysis revealed that the PTC level was stronger for males (OR 1.42 95%CI 1.23–1.64), regarding the prevalence of AICAS. Conclusions: In this large community-based study, the prevalence of AICAS is 13.0%, subjects with higher PTC levels showed a mild increase in the prevalence of AICAS. The PTC level is an independent risk factor of AICAS. Males seem to be significantly more vulnerable to the risk of AICAS

Socioeconomic Status and the Quality of Acute Stroke Care

Background and Purpose—The association of socioeconomic status (SES) with quality of stroke care is not well understood, and few studies have examined the association with different indicators of SES simultaneously. We assessed the impacts of low levels of education, occupation, and income on the quality of stroke care. Methods—We examined data from the China National Stroke Registry recording consecutive stroke patients between September 2007 and August 2008. Baseline low SES was measured using educational level <6 years, occupation as manual workers or no job, and average family income per capita at ≤¥1000 per month. Compliance with 11 performances was summarized in a composite score defined as the proportion of all needed care given. Poor quality of care was defined as having a composite score of 0.71 or less. Results—Among 12 270 patients with ischemic stroke, 38.6% had <6 educational years, 37.6% had manual workers/no job, and 34.7% had income ≤¥1000 per month. There was an increased chance of receiving poor quality of care in patients with low education (adjusted odds ratio 1.15, 95% confidence interval 1.03–1.28), low occupation (adjusted odds ratio 1.16, 95% confidence interval 1.01–1.32), and low income (adjusted odds ratio 1.18, 95% confidence interval 1.06–1.30), respectively. People with low SES had poor performances on some aspects of care quality. Combined effects existed among these SES indicators; those with low SES from all 3 indicators had the poorest quality of care. Conclusions—There was a social gradient in the quality of stroke care. Continuous efforts of socioeconomic improvement will increase the quality of acute stroke care.The Ministry of Science and Technology of the People’s Republic of China (2006BAI01A11, 2011BAI08B01, 2011BAI08B02, 2012ZX09303-005-001, and 2013BAI09B03), The Beijing Biobank of Cerebral Vascular Disease (D131100005313003), Beijing Institute for Brain Disorders (BIBD-PXM2013_014226_07_000084

Association between Non-High-Density-Lipoprotein-Cholesterol Levels and the Prevalence of Asymptomatic Intracranial Arterial Stenosis

Objective: The aim of this study was to assess the association between non-high-density-lipoprotein-cholesterol (non-HDL-C) and the prevalence of asymptomatic intracranial arterial stenosis (ICAS). Methods and Results: The Asymptomatic Polyvascular Abnormalities Community (APAC) study is a prospective cohort study based on the Kailuan district (China) population. A total of 5351 eligible subjects, aged ≥40, and without history of stroke or myocardial infarction, were enrolled in this study. Transcranial Doppler Ultrasonography (TCD) was performed on all enrolled subjects for the evaluation of ICAS presence. Out of 5351 patients, 698 subjects showed evidence of ICAS (prevalence of 13.04%). Multivariate analysis showed that non-HDL-C is an independent indicator for the presence of ICAS (OR = 1.15, 95%CI: 1.08 – 1.23), but with a gender difference (P for interaction<0.01): in men, non-HDL-C is an independent indicator for ICAS (multivariate-adjusted OR = 1.28, 95%CI: 1.18–1.39), but not in women (multivariate-adjusted OR = 1.03, 95%CI: 0.93–1.14). Subjects were divided into five subgroups based non-HDL-C levels and these levels correlated linearly with the prevalence of ICAS (P for trend <0.01). Compared with the first quintile, multivariate-adjusted OR (95%CI) of the second, third, fourth and fifth quintiles were: 1.05 (0.71–1.56), 1.33 (0.91–1.95), 1.83 (1.27–2.63), 2.48 (1.72–3.57), respectively. Conclusion: Non-HDL-C is an independent predictor of ICAS prevalence in men but not in women, suggesting that non-HDL-C levels could be used as a surveillance factor in the primary prevention of ischemic stroke, especially in men

Relationship between C - Reactive Protein and Stroke: A Large Prospective Community Based Study

Objective: Previous studies have suggested that C-reactive protein (CRP) was associated with risk of stroke. There were few studies in Asian population, or on stroke subtypes other than ischemic stroke. We thus investigated the relationship between CRP and the risks of all stroke and its subtypes in a Chinese adult population. Methods: In the current study, we included 90,517 Chinese adults free of stroke and myocardial infarction at baseline (June 2006 to October 2007) in analyses. Strokes were classified as ischemic stroke (IS), intracranial heamorrhage (ICH) and subarachnoid heamorrhage (SAH). High-sensitivity CRP (hs-CRP) were categorized into three groups: 3 mg/L. Cox proportional hazards regression was used to calculate the association between hs-CRP concentrations and all stroke, as well as its subtypes. Results: During a median follow-up time of 49 months, we documented 1,472 incident stroke cases. Of which 1,049 (71.3%) were IS, 383 (26.0%) were ICH, and 40 (2.7%) were SAH. After multivariate adjustment, hs-CRP concentrations ≥1 mg/L were associated with increased risks of all stroke (hs-CRP 1–3 mg/L: hazard ratio (HR) 1.17, 95% confidential interval (CI) 1.03–1.33; hs-CRP>3 mg/L: HR 1.25, 95% CI 1.07–1.46) and IS (hs-CRP 1–3 mg/L: HR 1.17, 95% CI 1.01–1.36; hs-CRP>3 mg/L: HR 1.33, 95% CI 1.11–1.60), but not with ICH and SAH. Subgroup analyses showed that higher hs-CRP concentration was more prone to be a risk factor for all stroke and IS in non-fatal stroke, male and hypertensive participants. Conclusion: We found that higher hs-CRP concentrations were associated with a higher risk of IS, particularly for non-fatal stroke, male and hypertensive subjects. In contrast, we did not observe significant associations between hs-CRP and ICH/SAH