Clinical Features of Trousseau's Syndrome with Multiple Acute Ischemic Strokes

2020 ◽  
Author(s):  
Yitong Ling ◽  
Yinye Li ◽  
Xiaoyu Zhang ◽  
Lihua Dong ◽  
Dongxiao Yao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Tumor Markers ◽  
Clinical Features ◽  
Clinical Data ◽  
Primary Tumor ◽  
Average Score ◽  
Imaging Features ◽  
Short Term ◽  
Trousseau’S Syndrome ◽  
D Dimer

Abstract Background:Trousseau’s syndrome can cause venous or arterial thrombosis, multiple acute ischemic strokes (MAIS) caused by Trousseau’s syndrome is rare. The aim of this study was to analyze the clinical features of Trousseau's syndrome with MAIS, and to improve the awareness and the knowledge of this disease.Methods:Clinical data from fifteen patients who were diagnosed as Trousseau's Syndrome with MAIS in Rizhao people's Hospital from January 2017 to April 2020 were collected and analyzed. The clinical data included the following: Patients’ basic information, laboratory results, imaging features, treatment regimens, and short-term prognoses were collected.Results:The mean age was 65.5 years, with thirteen males and two females. Most patients (11/15) had a history of smoking and (or) drinking. The average score of NIHSS was 2.13. 6 of the 15 patients first presented with ischemic stroke, and then found the primary tumor. Most common types of primary tumor was lung cancer (11/15), other types of primary tumor were gastric adenocarcinoma, renal cell carcinoma, esophageal adenosquamous carcinoma, and cholangiocarcinoma (one in each). All the 15 patients showed different levels of increase of D-dimer. The increase in CRP appears in 10 of the 15 patients. Various tumor markers were increased in the 15 patients, Especially for CYFRA-211, all the patients of which were higher than normal. All of the 15 patients had multiple vascular territories lesions in DWI, and most lesions were near the cortex areas. Only 4 of the 15 patients (26.7%) occurred with Peripheral venous thrombosis. 13 patients were given low molecular heparin for anticoagulant therapy, of which 9 patients were improved in short-term while 4 patients were not.Conclusion:Trousseau's syndrome with MAIS was associated with old-age male, smoking and (or) drinking history, low NIHSS score, increased D-dimer, CRP and tumor markers, lesions near the cortex areas with multiple vascular territories in DWI. Patients with these features should be alert of malignant tumor. Most common types of primary tumor were lung cancer. Treatment with Low molecular heparin may be effective in short-term.

scholarly journals Clinical features and biological markers of lung cancer-associated stroke

2016 ◽  
Vol 44 (6) ◽  
pp. 1483-1491 ◽  
Author(s):  
Xingrui Xie ◽  
Li Chen ◽  
Jinsheng Zeng ◽  
Chao Qin ◽  
Daobin Cheng ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Clinical Features ◽  
Biological Markers ◽  
Multivariate Logistic Regression Analysis ◽  
Blood Levels ◽  
Resonance Imaging ◽  
Multivariate Logistic Regression ◽  
Independent Risk Factors ◽  
And Biological Markers ◽  
D Dimer

Objective To identify the unique clinical features and biological markers of lung cancer-associated stroke. Methods We recruited 102 patients with lung cancer plus stroke, 102 with lung cancer, and 102 with stroke. Detailed information was analysed and compared among groups. Results The groups were age-matched. Patients with lung cancer plus stroke showed multiple lesions involving multiple cerebral artery territories on magnetic resonance imaging, compared with stroke-alone patients. These patients also had a poorer modified Rankin Scale score at 30 days, and high mortality (18.6%). Patients with lung cancer plus stroke had a higher incidence of metastasis, and higher blood levels of D-dimer, CA125 and CA199 compared with patients with lung cancer alone. Multivariate logistic regression analysis showed that levels of D-dimer, CA125 and CA199 were independently related to lung cancer-associated stroke. Conclusion Elevated plasma D-dimer, CA125 and CA199 may be independent risk factors for and biomarkers of lung cancer-associated stroke.

scholarly journals Different clinical features between patients with ROS1-positive and ALK-positive advanced non-small cell lung cancer

2021 ◽  
Vol 49 (2) ◽  
pp. 030006052199364
Author(s):  
Xianxiu Ji ◽  
Huikang Xie ◽  
Ren Zhu ◽  
Bin Chen ◽  
Sen Jiang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Small Cell Lung Cancer ◽  
Clinical Features ◽  
Cell Lung Cancer ◽  
Clinical Characteristics ◽  
Small Cell ◽  
Imaging Features ◽  
Small Cell Lung ◽  
Significant Difference ◽  
Alk Positive

Objective To compare the baseline clinical characteristics between patients with ROS1-positive and ALK-positive advanced non-small cell lung cancer (NSCLC), and the correlations of these subtypes with the distribution of metastases. Methods We compared the clinical characteristics and imaging features of patients with ROS1-positive and ALK-positive NSCLC using statistical methods. Results Data for 232 patients were analyzed. Compared with ALK-positive NSCLC, ROS1-positive NSCLC was more likely to occur in women (71% vs 53%), and primary lesions ≤3 cm were more common in patients with ROS1-positive compared with ALK-positive NSCLC (58% vs 37%). There was no significant difference in the distribution of metastases between the two groups. Subgroup analysis within the ROS1-positive group showed that, compared with primary lesions >3 cm, primary lesions ≤3 cm were more likely to present as peripheral tumors (72% vs 43%) and more likely to exhibit non-solid density (44% vs 4%). Conclusions Although ROS1-positive and ALK-positive NSCLCs show similar clinical features, the differences may help clinicians to identify patients requiring further genotyping at initial diagnosis.

scholarly journals Application of Artificial Neural Networks for Prognostic Modeling in Lung Cancer after Combining Radiomic and Clinical Features

2019 ◽  
Vol 05 (02) ◽  
pp. 050-055
Author(s):  
Kundan S. Chufal ◽  
Irfan Ahmad ◽  
Anjali K. Pahuja ◽  
Alexis A. Miller ◽  
Rajpal Singh ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Neural Networks ◽  
Artificial Neural Networks ◽  
Clinical Features ◽  
Clinical Data ◽  
Hybrid Modeling ◽  
Model Accuracy ◽  
Ann Modeling ◽  
Prognostic Modeling ◽  
Artificial Neural

Abstract Objective This study was aimed to investigate machine learning (ML) and artificial neural networks (ANNs) in the prognostic modeling of lung cancer, utilizing high-dimensional data. Materials and Methods A computed tomography (CT) dataset of inoperable nonsmall cell lung carcinoma (NSCLC) patients with embedded tumor segmentation and survival status, comprising 422 patients, was selected. Radiomic data extraction was performed on Computation Environment for Radiation Research (CERR). The survival probability was first determined based on clinical features only and then unsupervised ML methods. Supervised ANN modeling was performed by direct and hybrid modeling which were subsequently compared. Statistical significance was set at <0.05. Results Survival analyses based on clinical features alone were not significant, except for gender. ML clustering performed on unselected radiomic and clinical data demonstrated a significant difference in survival (two-step cluster, median overall survival [ mOS]: 30.3 vs. 17.2 m; p = 0.03; K-means cluster, mOS: 21.1 vs. 7.3 m; p < 0.001). Direct ANN modeling yielded a better overall model accuracy utilizing multilayer perceptron (MLP) than radial basis function (RBF; 79.2 vs. 61.4%, respectively). Hybrid modeling with MLP (after feature selection with ML) resulted in an overall model accuracy of 80%. There was no difference in model accuracy after direct and hybrid modeling (p = 0.164). Conclusion Our preliminary study supports the application of ANN in predicting outcomes based on radiomic and clinical data.

10-year patient journey of stage III non-small cell lung cancer patients: A single-center, observational, retrospective study in Korea real-time automatically updated data warehouse in health care (UNIVERSE - ROOT study).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 8536-8536
Author(s):  
Keunchil Park ◽  
Hyun Ae Jung ◽  
Jong-Mu Sun ◽  
Se-Hoon Lee ◽  
Jin Seok Ahn ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Big Data ◽  
Data Warehouse ◽  
Clinical Features ◽  
Clinical Data ◽  
Treatment Strategy ◽  
Locally Advanced ◽  
Stage Iii ◽  
Curative Surgery ◽  
Stage Iii Nsclc

8536 Background: The current standard of care (SoC) for locally advanced stage III NSCLC is concurrent chemoradiotherapy (CCRT) but the outcomes are poor and unsatisfactory. The purpose of this study is to analyze the clinical features of patients with locally advanced lung cancer for 10 years in order to help develop future treatment strategy. Methods: This study through big data analysis retrospectively collected de-identified patient data from clinical data warehouse (CDW) using an unique algorithm with Standard Query Language (SQL). This new algorithm was developed by the close interactive collaboration between senior data scientists and medical oncologists. These algorithms include clinical natural language processing (NLP) systems that generate structured information from unstructured free text and structured data capture (SDC). We performed pre-processing work and data quality management (DQM) operation using over 700 clinical variables from 23,735 patients with NSCLC. Through data extraction, transformation, cleansing, and organization, we have developed a systematic and optimized program for lung cancer cohorts, including clinical features and molecular study and outcomes. It is also automatically updated every 24 hours in real time. Results: In the past 10 years, 23,735 patients were diagnosed with NSCLC and complete clinical data were available in 22,718 patients (95.7%). Out of total 22,718 patients 4,138 (18.2%) were diagnosed with stage III NSCLC. Among them, 2,676 patients (64.7%) received any type(s) of anti-cancer treatments or regular follow up at our institute. Of these 2,676 patients, 1,275 (47.6%) received curative surgery (+/- neo- and/or adjuvant CCRT); 685 (25.6%) patients definitive CCRT ; 220 (8.2%) patients palliative thoracic RT; 76 (2.8%) patients best supportive care. Median OS was 48.0 months for neoadjuvant CCRT followed by curative surgery, 51.8 months for curative surgery +/- adjuvant treatment, 29.4 months for unresected definitive CCRT (PFS 10.0 months (range: 9.1-10.9). Molecular profiles as well as updated clinical data will be presented. Conclusions: This unique in-house algorithm enables us to do a rapid and comprehensive analysis of the big data through CDW, which can be also automatically updated daily. This should provide clinically relevant information about real-world treatment outcomes and help implement or develop new treatment strategy in a timely manner.

Use of Tumor Markers in Lung Cancer

1994 ◽  
Vol 8 (3) ◽  
pp. 507-532 ◽  
Author(s):  
Gary M. Strauss ◽  
Arthur T. Skarin
Keyword(s):  
Lung Cancer ◽  
Tumor Markers

ASSOCIATION OF PATENT DUCTUS ARTERIOSUS SIZE WITH CLINICAL FEATURES AND SHORT-TERM OUTCOMES IN PRETERM INFANTS LESS THAN 34 WEEKS

2020 ◽  
Vol 07 (03) ◽  
pp. 105-108
Author(s):  
Chandrakala Bada Shekharappa ◽  
Edison Albert Balakrishnan Elizabeth ◽  
Bharathi Balachander
Keyword(s):  
Patent Ductus Arteriosus ◽  
Preterm Infants ◽  
Clinical Features ◽  
Ductus Arteriosus ◽  
Short Term ◽  
Patent Ductus

scholarly journals Robot-assisted thoracic surgery versus video-assisted thoracic surgery for lung lobectomy or segmentectomy in patients with non-small cell lung cancer: a meta-analysis

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Jianglei Ma ◽  
Xiaoyao Li ◽  
Shifu Zhao ◽  
Jiawei Wang ◽  
Wujia Zhang ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Sensitivity Analysis ◽  
Thoracic Surgery ◽  
Conversion Rate ◽  
Meta Analysis ◽  
Small Cell ◽  
Small Cell Lung ◽  
Robot Assisted ◽  
Short Term

Abstract Background It remains no clear conclusion about which is better between robot-assisted thoracic surgery (RATS) and video-assisted thoracic surgery (VATS) for the treatment of patients with non-small cell lung cancer (NSCLC). Therefore, this meta-analysis aimed to compare the short-term and long-term efficacy between RATS and VATS for NSCLC. Methods Pubmed, Cochrane Library, Embase, China National Knowledge Infrastructure (CNKI), Medline, and Web of Science databases were comprehensively searched for studies published before December 2020. The quality of the articles was evaluated using the Newcastle-Ottawa Scale (NOS) and the data analyzed using the Review Manager 5.3 software. Fixed or random effect models were applied according to heterogeneity. Subgroup analysis and sensitivity analysis were conducted. Results A total of 18 studies including 11,247 patients were included in the meta-analyses, of which 5114 patients were in the RATS group and 6133 in the VATS group. Compared with VATS, RATS was associated with less blood loss (WMD = − 50.40, 95% CI -90.32 ~ − 10.48, P = 0.010), lower conversion rate (OR = 0.50, 95% CI 0.43 ~ 0.60, P < 0.001), more harvested lymph nodes (WMD = 1.72, 95% CI 0.63 ~ 2.81, P = 0.002) and stations (WMD = 0.51, 95% CI 0.15 ~ 0.86, P = 0.005), shorter duration of postoperative chest tube drainage (WMD = − 0.61, 95% CI -0.78 ~ − 0.44, P < 0.001) and hospital stay (WMD = − 1.12, 95% CI -1.58 ~ − 0.66, P < 0.001), lower overall complication rate (OR = 0.90, 95% CI 0.83 ~ 0.99, P = 0.020), lower recurrence rate (OR = 0.51, 95% CI 0.36 ~ 0.72, P < 0.001), and higher cost (WMD = 3909.87 USD, 95% CI 3706.90 ~ 4112.84, P < 0.001). There was no significant difference between RATS and VATS in operative time, mortality, overall survival (OS), and disease-free survival (DFS). Sensitivity analysis showed that no significant differences were found between the two techniques in conversion rate, number of harvested lymph nodes and stations, and overall complication. Conclusions The results revealed that RATS is a feasible and safe technique compared with VATS in terms of short-term and long-term outcomes. Moreover, more randomized controlled trials comparing the two techniques with rigorous study designs are still essential to evaluate the value of robotic surgery for NSCLC.

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