Trends in Hospitalization and In-Hospital Mortality From VTE, 2007 to 2016, in China

Zhu, Zhiming; Lei, Jieping; Shao, Xiang; Dong, Fen; Wang, Jing; Wang, Dingyi; Wu, Sinan; Xie, Wanmu; Wan, Jun; Chen, Hong; Ji, Yingqun; Yi, Qun; Xu, Xiaomao; Yang, Yuanhua; Zhai, Zhenguo; Wang, Chen; Jin, Zhangdong; Zhang, Peng; Mao, Yimin; Xiao-hong, Yang; Xia, Guoguang; Zheng, Rui; Gao, Yuan; Zhu, Guangfa; Zhu, Chenxi; Fu, Yingyun; Yu, Fangfei; Kuang, Jiulong; Li, Ziqiang; Cheng, Zhe; Wu, Rui; Cheng, Zhaozhong; Li, Tong; Yan-wen, Jiang; Sun, Jie; Xu, Qixia; Pan, Huiyun; Wang, Lihong; Zeng, Mian; Chen, Yanzhu; Yu, Chunxiao; Hua, Jing; Tang, Yongjun; An, Jun; Zhang, Yongxiang; Ding, Yawen; Zhang, Wei; Wu, Xiaomai; Chai, Weidong; Li, Jing; Wang, Haixia; Chen, Xiaoju; Zhang, Aizhen; Han, Jun; Ying, Kejing; Xu, Xianlin; Shi, Zhihong; Sun, Jiaolin; Zhao, Qihua; Liu, Guangjie; Zhuo, Jie; Shi, Guochao; Ding, Yongjie; He, Zhihong; Lang, Zhe; Hu, Xiaoyun; Fan, Fangfang; Liu, Hong; Sun, Guohua; Xing, Guoqiang; Zhang, Yingqi; Su, Guanli; Ni, Jixiang; Zhao, Tianming; Wang, Jun; Zhang, Nuofu; Qin, Simin; Huang, Songping; Xu, Qinghua; Li, Yunqiu; Liu, Qian; Wu, Qi; Li, Li; Chen, Xisheng; Niu, Zhiwei; Huang, Jianan; Zeng, Daxiong; Yuan, Yadong; Qian, Tian; Zhang, Jian; Han, Xinpeng; Yang, Jianhua; Bo, Baoying; Huang, Yurong; Luo, Qian; Pang, Gui-Fen; Hong-fei, Zheng; Zhang, Ping; Xu, Ruhong; Zhang, Yunfeng; Ni, Songshi; Li, Shengqing; Gong, Yi; Zhang, Jie; Zhu, Ling; Xia, Shuyue; Chang, Yule; Zhang, Hongyu; Xu, Xia; Zhang, Yiwen; Pan, Jingjing; Qin, Zhiqiang; Lao, Miaochan; Liu, Zhihong; Qin, Luo; Wang, Ning; Yang, Huiqin; Tang, Xiaoli; Bai, Xiangzhi; Chen, Yanwei; Han, Dong‐Dong; Shen, Shasha; Jin, Chen; Ye, Yanping; Suo, Lijun; Huang, Xiaoying; Wang, Jialie; Zhang, Xiangyan; Yang, Guoru; Yu, Guohua; Zhang, Shudong; Yang, Yinlou; Cheng, Jiangtao; Deng, Jiehui; Zhang, Hong; Wang, Ping; Li, Yueyue; Guo, Changcheng; Bian, Tao; Cai, S.W.; Cheng, Zhenshun; Wang, Ting; He, Yong; Huang, Wentong; Liu, Chengying; Zhao, Huijie; Tu, Fenglin; Zhu, Yanbing; Tian, Guizhen

doi:10.1016/j.chest.2018.10.040

Cited by 82 publications

(48 citation statements)

References 127 publications

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“…Acute pulmonary embolism (APE) is one of the leading causes of death in cardiovascular disease [1, 2]. Differentiating high-risk APE patients from others on the basis of hypotension [1] and treating this group of patients with reperfusion therapy to save their lives are crucial due to the greater than 50% mortality rate in this group of patients [3].…”

Section: Introductionmentioning

confidence: 99%

A decision tree built with parameters obtained by computed tomographic pulmonary angiography is useful for predicting adverse outcomes in non-high-risk acute pulmonary embolism patients

Dong

Zhang

et al. 2019

Respir Res

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Background Acute pulmonary embolism (APE) is one of the leading causes of death in cardiovascular disease. The 30-day mortality can still be 1.7–15% in non-high-risk APE patients. Some non-high-risk patients can progress into the high-risk group and even die, which is referred to as an adverse outcome. Promoting the diagnosis and predictive ability of adverse short-term prognosis was still a problem that needed to be solved. Computed tomography pulmonary angiography (CTPA) may be a way to promote the predictive ability. Our aim to develop predictive tools based on parameters obtained by computed tomographic pulmonary angiography (CTPA) in the form of a decision tree for use in non-high-risk acute pulmonary embolism (APE) patients. Methods Adverse outcome was defined within 30 days after admission to the hospital. A decision tree was built to predict adverse outcomes based on discriminating factors screened from cardiac volume and clot characteristics from recursive partitioning analysis and compared with simplified pulmonary embolism severity index (sPESI), Bova scores and risk stratification. The area under the receiver operating characteristic curve (ROC-AUC) was used to confirm the predictive ability. Results A total of 38 patients with and 303 patients without adverse outcomes were enrolled. Right ventricular/left ventricular (RV/LV) volume ratio, central pulmonary artery (CPA) embolism and right atria/left atria (RA/LA) volume ratio were used as splits in the decision tree to predict adverse outcomes in all patients. The ROC-AUC was 0.858. In CPA embolism patients, a recursive partitioning analysis was performed with cardiac volume and novel clot burden, but only the obstructing area (OA) ratio was included as a discriminating factor to build a second decision tree. The ROC-AUC for the second decision tree was 0.810. The decision trees were superior to those of sPESI, Bova scores and risk stratification, and there were no significant differences between the two decision trees. Conclusions A decision tree built by CTPA parameters can predict adverse outcomes in non-high-risk APE patients.

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Section: Introductionmentioning

confidence: 99%

A decision tree built with parameters obtained by computed tomographic pulmonary angiography is useful for predicting adverse outcomes in non-high-risk acute pulmonary embolism patients

Dong

Zhang

et al. 2019

Respir Res

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“…According to the research of Chen Wang, in the 105,723 identified patients with VTE, hospitalization rate increased from 3.2 to 17.5 per 100,000 populations, in-hospital mortality decreased from 4.7% to 2.1%, and the mean length of stay declined from 14 to 11 days from 2007 to 2016. In addition, the hospitalization rate of VTE was higher in elderly male patients, same with the patients with PE and DVT 13 . Recently there is an increasing awareness of VTE diagnoses in physicians, along with an improvement in diagnostic techniques for the identification and more effective treatments.…”

Section: Discussionmentioning

confidence: 64%

Hospital-Acquired Conditions of a Grade A hospital in China

Jia

Zhao

Wang

et al. 2020

Preprint

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Background: This study aimed to investigate the Hospital-Acquired Conditions (HACs) and find deficits in our hospital, so as to improve the incidence of HACs in China from our retrospect. Methods: We conducted statistics on the incidence and the percentage of HACs, and managed the cost and length of stay of the 950 patients went through HACs in our hospital from 2016 to 2018. Results: The overall incidence was 0.571%. The two most common conditions with the most cost were deep vein thrombosis (DVT) and pulmonary embolisms (PE) (351), and surgical site infections (SSI) (143), which were followed closely by manifestations of poor glycemic control (53), vascular catheter-associated infections (VCAIs) (52), stage III and IV pressure ulcers (49), catheter-associated urinary tract infections (CAUTIs) (33), and falls and trauma (30). Iatrogenic pneumothorax with venous catheterization (7) only occupied small portions. Blood incompatibility and air embolism didn't happen in the three years. Conclusions: From the comparison of three years, the condition decreased in 2017, while met a higher increase in 2018. This may relative to the launch of medical reform in 2017. Chinese hospitals still need to investigate the HACs, give adaptable emphasis and concern to improve, and promote the overall level of medical management.

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“…Venous thromboembolism (VTE) is a complex and multi‐factorial thrombotic disorder that includes deep venous thrombosis (DVT), cerebral infarction and pulmonary embolism (PTE). The hospitalization rates of VTE increased from 3.2 to 17.5 per 100 000 population, and the mortality decreased from 4.7% to 2.1% in China . The acquired or inherited risk factors for VTE development include surgery, pregnancy, cancer.…”

Section: Introductionmentioning

confidence: 99%

Pathogenic variants of PROC gene caused type I activity deficiency in a familial Chinese venous thrombosis

Yue

Liu

Han

et al. 2019

J Cellular Molecular Medi

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Pathogenic mutation of protein C (PROC) gene results into the deficiency of PROC activity. This study aimed to identify the pathogenic genetic variants and to explore the functional consequence in Chinese familial venous thrombosis (VTE). Whole exome sequencing was performed to identify the pathogenic variants of anticoagulant factors. Serum coagulation and anti‐coagulation factors activity were assayed to evaluate the genetic association. Functional study of PROC antigen secretion deficiency was conducted in VTE subjects and in vitro cell lines. One rare pathogenic variant (p.Ala178Pro) was identified in the four VTE subjects but not in the normal subjects from the family. An inframeshift variant (rs199469469) was also identified in a paediatric subject of the pedigree. Further evaluation of serum PROC activity levels in p.Ala178Pro variants VTE carriers showed significantly lower PROC activity compared to non‐carriers. Furthermore, in vitro study showed that the p.Ala178Pro mutant cells had a consistent reduction in concentration of PROC antigen. In conclusions, our study demonstrated the pathogenic variant (p.Ala178Pro) contributed to PROC type I activity deficiency, which may be due to decreased secretion of PROC.

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Trends in Hospitalization and In-Hospital Mortality From VTE, 2007 to 2016, in China

Cited by 82 publications

References 127 publications

A decision tree built with parameters obtained by computed tomographic pulmonary angiography is useful for predicting adverse outcomes in non-high-risk acute pulmonary embolism patients

A decision tree built with parameters obtained by computed tomographic pulmonary angiography is useful for predicting adverse outcomes in non-high-risk acute pulmonary embolism patients

Hospital-Acquired Conditions of a Grade A hospital in China

Pathogenic variants of PROC gene caused type I activity deficiency in a familial Chinese venous thrombosis

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