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Catheter ablation is currently the only curative treatment for scar-related ventricular tachycardias (VTs). However, not only are ablation procedures long, with relatively high risk, but success rates are punitively low, with frequent VT recurrence. Personalized in-silico approaches have the opportunity to address these limitations. However, state-of-the-art reaction diffusion (R-D) simulations of VT induction and subsequent circuits used for in-silico ablation target identification require long execution times, along with vast computational resources, which are incompatible with the clinical workflow. Here, we present the Virtual Induction and Treatment of Arrhythmias (VITA), a novel, rapid and fully automated computational approach that uses reaction-Eikonal methodology to induce VT and identify subsequent ablation targets. The rationale for VITA is based on finding isosurfaces associated with an activation wavefront that splits in the ventricles due to the presence of an isolated isthmus of conduction within the scar; once identified, each isthmus may be assessed for their vulnerability to sustain a reentrant circuit, and the corresponding exit site automatically identified for potential ablation targeting. VITA was tested on a virtual cohort of 7 post-infarcted porcine hearts and the results compared to R-D simulations. Using only a standard desktop machine, VITA could detect all scar-related VTs, simulating activation time maps and ECGs (for clinical comparison) as well as computing ablation targets in 48 minutes. The comparable VTs probed by the R-D simulations took 68.5 hours on 256 cores of high-performance computing infrastructure. The set of lesions computed by VITA was shown to render the ventricular model VT-free. VITA could be used in near real-time as a complementary modality aiding in clinical decision-making in the treatment of post-infarction VTs.  相似文献   
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目的探讨扩张型心肌病患者药物治疗后发生心脏结构和功能逆转的预测因素。方法回顾性分析2016年8月至2017年4月在徐州市中心医院住院的156例扩张型心肌病患者资料,根据患者治疗后的临床效果和超声心动图结果的不同反应性,将156例扩张型心肌病患者分为左心室逆重构(LVRR)组(27例)和非LVRR组(129例)。记录所有患者的年龄、性别、体质量指数、病程、收缩压、纽约心脏病学会分级、高血压、糖尿病、心房颤动、血管紧张素转化酶抑制剂/血管紧张素Ⅱ受体阻滞剂、β受体阻滞剂、螺内酯、完全性左束支传导阻滞、QRS波时限、N末端脑钠肽前体、左心室射血分数、左心室舒张末期内径、左室收缩末期容积指数、6 min步行试验、服药依从性、6个月再住院率及6个月病死率等资料。采用多因素Logistic回归分析扩张型心肌病患者发生LVRR的相关因素;采用受试者工作特征(ROC)曲线分析QRS波时限、服药依从性对扩张型心肌病患者发生LVRR的预测价值。结果LVRR组患者年龄[(54±16)岁vs.(60±12)岁,t=5.899,P=0.021]和QRS波时限[(104±21)ms vs.(122±29)ms,t=10.464,P=0.003]均较非LVRR组显著降低,服药依从性[(6.0±1.0)分vs.(5.3±1.5)分,t=8.962,P=0.002]较非LVRR组显著升高。多因素Logistic回归分析结果显示,QRS波时限[比值比(OR)=0.969,95%置信区间(CI)(0.946,0.993),P=0.011]、服药依从性[OR=1.541,95%CI(1.064,2.230),P=0.022]是心功能恢复正常的独立影响因素。ROC曲线分析结果显示,QRS波时限[曲线下面积(AUC)=0.721,95%CI(0.619,0.824),P<0.001]、服药依从性[AUC=0.661,95%CI(0.559,0.762),P=0.009]均对扩张型心肌病患者发生LVRR具有预测价值。结论QRS波时限及服药依从性是扩张型心肌病患者发生LVRR的重要预测因素。  相似文献   
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目的 评价影响胸部放化疗后完全缓解的ⅡB-ⅢB期小细胞肺癌患者发生脑转移的临床因素。方法 回顾性分析191例于2009年1月至2016年4月在浙江省肿瘤医院接受胸部放化疗达到完全缓解的ⅡB-ⅢB期小细胞肺癌患者。对脑转移预后相关的因素,如性别、年龄、胸部放疗剂量、放化疗模式、治疗前血清神经元特异性烯醇化酶(NSE)和乳酸脱氢酶(LDH)、是否行预防性全脑照射(PCI)、TMN分期、体力状态评分(PS)等进行分析。使用log-rank法进行单因素分析,使用COX回归法进行多因素分析,使用Kaplan-Meier法绘制生存曲线。结果 单因素分析提示治疗前LDH≥240 IU、治疗前NSE≥17 ng/ml、未行PCI和脑转移风险正相关(P<0.05)。多因素分析提示脑转移风险只和治疗前LDH≥240 IU(HR=1.90,95%CI为1.07~3.37,P=0.029)、未行PCI(HR=2.08,95%CI为1.17~3.72),P=0.013)正相关。结论 治疗前血清LDH水平可为预测胸部放化疗后达到完全缓解的ⅡB-ⅢB期小细胞肺癌患者的脑转移风险提供重要价值。  相似文献   
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Background and aimsThis study aims to develop a predictive model of cardiovascular events in dysglycemia among the Indonesian adult population.MethodsThis is a retrospective cohort study conducted on subjects over 25 years in the “The Bogor Cohort Study of Noncommunicable Diseases Risk Factors” from 2011 to 2018. Data associated with age, gender, blood pressure, body mass index, waist circumference, blood glucose, cholesterol, smoking habits, family history of cardiovascular disease, and physical activity were obtained. Cardiovascular events in six years were observed; this included coronary heart disease, stroke, or all-cause cardiovascular mortality. Cox proportional hazards regression models were used to determine independent predictors of cardiovascular events.ResultsA total of 1085 subjects with prediabetes and diabetes mellitus were included in this study, with 73.5% female. The cumulative incidence of cardiovascular events in six years was 9.7%. Predictors of cardiovascular events were age ≥45 years (HR = 2.737; 95% CI 1.565–4.787) and hypertension (HR = 2.580; 95% CI 1.619–4.112).ConclusionsAge ≥45 years and hypertension were predictors of cardiovascular events in six years among the adult Indonesian population with prediabetes and diabetes, necessitating targeted intervention among these subjects.  相似文献   
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This study identifies potential predictors of participation changes in various areas for preschool children with cerebral palsy (CP). Eighty children with CP (2–6 years) were enrolled. Seven potential predictors were identified: age; sex; socioeconomic status, CP subtype; cognitive function, Function Independence Measure for Children (WeeFIM), and motor composite variable from 5 motor factors (gross motor function classification system (GMFCS) level; bimanual fine motor function level; selective motor control score; Modified Ashworth Scale score; and Spinal Alignment and Range of Motion Measure). Outcome was assessed at baseline and at 6-month follow-up using the Assessment of Preschool Children's Participation (APCP) including diversity and intensity scores in the areas of play (PA), skill development (SD), active physical recreation, social activities (SA), and total areas. Dependent variables were change scores of APCP scores at baseline and 6-month follow-up. Regression analyses shows age and sex together predicted for APCP-total, APCP-SD diversity and APCP-total intensity changes (r2 = 0.13–0.25, p < 0.001); cognitive function and WeeFIM were negative predictors for APCP-SA and APCP-PA diversity changes, respectively. CP subtype, motor composite variable, and socioeconomic status predicted for APCP changes in some areas. Findings suggest that young boys with poor cognitive function and daily activity predicted most on participation changes.  相似文献   
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BackgroundThe objective of this study was to identify the predictors of the conservative management outcomes in patients with lumbar herniated nucleus pulposus (HNP).MethodsA prospective study was conducted between June 2010 and April 2012 in Banda Aceh, Indonesia. Clinical and baseline neurologic examinations such as passive straight leg raising test (SLRT), cross SLRT, and patellar and Achilles reflexes were assessed prior to the conservative management. The patients were evaluated at 2nd, 4th, 8th, 12th and 24th week following commencement of the conservative management.ResultsWe recruited and followed 171 HNP patients of which 35.7% of them had good outcome. At univariate analysis, patients with more than 12 months duration of complaint, those with dominant radicular pain, severe pain intensity (visual analogue scale 7–10), positive SLRT, positive cross SLRT, and reduced motor power of knee extensors (muscle strength grade 1–4), were associated with poor outcome. Multivariate analysis suggested that patients with dominant radicular type of pain were likely to had poor outcome compared to those with dominant back pain (odd ratio (OR) 10.57 with 95% confidence interval (CI) 1.15–96.93). Patients with reduced motor power of knee extensors also had a higher chance to have poor outcome compared to those who were normal (OR: 10.57; 95% CI: 1.15–96.93).ConclusionType of pain and the strength of lower extremities could be able to predict the failure of conservative management in patients with lumbar disc herniation. However, further studies with the bigger sample size are warrant to validate our results.  相似文献   
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Most adults with Major Depressive Disorder (MDD) will not experience a remission with the first antidepressant trial. No practical biomarkers presently exist to predict responsiveness to antidepressants. Herein we report pilot data for a rest-activity biomarker of antidepressant response.Fifty-eight medication-free adults with MDD underwent a week-long collection of actigraphic data before beginning a 9 week open label trial of fluoxetine, coupled with blinded randomized assignment to eszopiclone/placebo. Depression severity was repeatedly measured with the Hamilton Rating Scale for Depression (HRSD). Baseline actigraphic data was analyzed with functional data analysis to create smoothed 24-h curves of activity. The time of the lowest point of activity (the bathyphase) was calculated for each patient, as well the mean difference between bedtime and the bathyphase (BBD). At the end of treatment, patients were characterized as treatment responders (50% reduction in HRSD) or non-responders, and receiver operating curves were calculated to find the optimal cut point of the BBD for prediction of treatment response.The best cut point for BBD was at 260.2 min, resulting in an effect size of 1.45, and with a positive predictive value of 0.75 and a negative predictive value of 0.88.We conclude that actigraphically-determined measures of rest-activity patterns show promise as potential biomarker predictors of antidepressant response. However, this conclusion is based upon a small number of patients who received only one choice of antidepressant, for a single trial. Replication with a larger sample is needed.  相似文献   
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