19 research outputs found
Prognostic implications of surrogate markers of atherosclerosis in low to intermediate risk patients with type 2 diabetes.
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Clinical associations and prognostic value of MRI-visible perivascular spaces in patients with ischemic stroke or TIA: a pooled analysis
BACKGROUND AND OBJECTIVES: Visible perivascular spaces are an MRI marker of cerebral small vessel disease and might predict future stroke. However, results from existing studies vary. We aimed to clarify this through a large collaborative multicenter analysis. METHODS: We pooled individual patient data from a consortium of prospective cohort studies. Participants had recent ischemic stroke or transient ischemic attack (TIA), underwent baseline MRI, and were followed up for ischemic stroke and symptomatic intracranial hemorrhage (ICH). Perivascular spaces in the basal ganglia (BGPVS) and perivascular spaces in the centrum semiovale (CSOPVS) were rated locally using a validated visual scale. We investigated clinical and radiologic associations cross-sectionally using multinomial logistic regression and prospective associations with ischemic stroke and ICH using Cox regression. RESULTS: We included 7,778 participants (mean age 70.6 years; 42.7% female) from 16 studies, followed up for a median of 1.44 years. Eighty ICH and 424 ischemic strokes occurred. BGPVS were associated with increasing age, hypertension, previous ischemic stroke, previous ICH, lacunes, cerebral microbleeds, and white matter hyperintensities. CSOPVS showed consistently weaker associations. Prospectively, after adjusting for potential confounders including cerebral microbleeds, increasing BGPVS burden was independently associated with future ischemic stroke (versus 0-10 BGPVS, 11-20 BGPVS: HR 1.19, 95% CI 0.93-1.53; 21+ BGPVS: HR 1.50, 95% CI 1.10-2.06; = 0.040). Higher BGPVS burden was associated with increased ICH risk in univariable analysis, but not in adjusted analyses. CSOPVS were not significantly associated with either outcome. DISCUSSION: In patients with ischemic stroke or TIA, increasing BGPVS burden is associated with more severe cerebral small vessel disease and higher ischemic stroke risk. Neither BGPVS nor CSOPVS were independently associated with future ICH
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Breast lesion classification using ultrawideband early time breast lesion response
Breast lesion characterization for discriminating between localized malignant and benign lesions is important as the current breast screening techniques do not have the required specificity to be clinically acceptable. A method using ultrawideband (UWB) microwave imaging system for such classification is proposed in this paper. The early time portion of the backscatter breast response is processed for lesion discrimination. This method provides a high resolution since the early time lesion response has the largest signal strength. A correlator is used at the receiver to extract the early response and to quantify the degree of ruggedness of a lesion through several key parameters associated with the correlation operation. Subsequently, a large scale simulation study using a two-dimensional (2D) numerical breast model with an antenna array is used for the development of a lesion classification technique. It is shown that the lesion classification method is capable of discriminating between lesions with different morphologies
Additional file 1 of High-sensitivity C-reactive protein level in stable-state bronchiectasis predicts exacerbation risk
Supplementary Table S1 Baseline demographic and clinical characteristics; Supplementary Table S2 Risks of bronchiectasis exacerbation based on baseline hs-CRP level at stable-state, adjusted for gender, smoking status and individual components of E-FACED scor
An overview of radar based ultra wideband breast cancer detection algorithms
Breast cancer is the most common cancer in women in almost all countries around the world, and is one of the most common non-infective causes of death. Mammography, which uses ionising radiation, is the only early breast cancer screening technique proven to reduce breast cancer mortality in randomised controlled clinical trials. However, screening mammography is expensive, technically demanding and requires a high level of clinical expertise. It cannot be performed in general medical clinical settings readily. Ultra wideband (UWB) or microwave breast screening has the potential to be a safe, accurate and easy-to-use technique for breast disease detection that is more effective than routine clinical palpation or breast self-examination. Ultra wideband breast cancer detection algorithms have been researched by several groups for over a decade, with numerous algorithms reported. This paper serves to give an overview of existing algorithms for UWB breast cancer detection
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Cooperative communications in ultra-wideband wireless body area networks: Channel modeling and system diversity analysis
In this paper, we explore the application of cooperative communications in ultra-wideband (UWB) wireless body area networks (BANs), where a group of on-body devices may collaborate together to communicate with other groups of on-body equipment. Firstly, time-domain UWB channel measurements are presented to characterize the body-centric multipath channel and to facilitate the diversity analysis in a cooperative BAN (CoBAN). We focus on the system deployment scenario when the human subject is in the sitting posture. Important channel parameters such as the pathloss, power variation, power delay profile (PDP), and effective received power (ERP) crosscorrelation are investigated and statistically analyzed. Provided with the model preliminaries, a detailed analysis on the diversity level in a CoBAN is provided. Specifically, an intuitive measure is proposed to quantify the diversity gains in a single-hop cooperative network, which is defined as the number of independent multipaths that can be averaged over to detect symbols. As this measure provides the largest number of redundant copies of transmitted information through the body-centric channel, it can be used as a benchmark to access the performance bound of various diversity-based cooperative schemes in futuristic body sensor systems
Prognostic implications of surrogate markers of atherosclerosis in low to intermediate risk patients with Type 2 Diabetes
Abstract Background Type 2 diabetes mellitus (T2DM) patients are at increased risk of developing cardiovascular events. Unfortunately traditional risk assessment scores, including the Framingham Risk Score (FRS), have only modest accuracy in cardiovascular risk prediction in these patients. Methods We sought to determine the prognostic values of different non-invasive markers of atherosclerosis, including brachial artery endothelial function, carotid artery atheroma burden, ankle-brachial index, arterial stiffness and computed tomography coronary artery calcium score (CACS) in 151 T2DM Chinese patients that were identified low-intermediate risk from the FRS recalibrated for Chinese ( Results A total of 17 atherosclerotic events in 16 patients (11%) occurred during the follow-up period. The mean FRS of the study population was 5.0 ± 4.6% and area under curve (AUC) from receiver operating characteristic curve analysis for prediction of atherosclerotic events was 0.59 ± 0.07 (P = 0.21). Among different vascular assessments, CACS > 40 had the best prognostic value (AUC 0.81 ± 0.06, P ) and offered significantly better accuracy in prediction compared with FRS (P = 0.038 for AUC comparisons). Combination of FRS with CACS or other surrogate vascular markers did not further improve the prognostic values over CACS alone. Multivariate Cox regression analysis identified CACS > 40 as an independent predictor of atherosclerotic events in T2DM patients (Hazards Ratio 27.11, 95% Confidence Interval 3.36-218.81, P = 0.002). Conclusions In T2DM patients identified as low-intermediate risk by the FRS, a raised CACS > 40 was an independent predictor for atherosclerotic events.</p
Multi-variate Cox regression model of recurrent stroke in patients with and without cancer.
<p>Abbreviations: HR = hazards ratio; CI = confidence interval.</p
Kaplan-Meier estimate of percentage of cardiovascular mortality.
<p>Kaplan-Meier estimate of percentage of cardiovascular mortality.</p