Resource Type

Journal Article 4

Year

2023 1

2022 1

2020 1

2013 1

Keywords

Academy 2

Engineering 2

THE AUTHORS.Published 2

behalf 2

COVID-19 1

China 1

Company 1

Education Press 1

Education Press Limited Company. 1

HD-marker approach” 1

September 1

carbon changes 1

city areas 1

coronary artery bypass grafting 1

decades: Implications 1

genotyping 1

in-hospital mortality 1

online 1

organ function support 1

repertoire 1

open ︾

Search scope:

排序： Display mode:

Organ function support in patients with coronavirus disease 2019: Tongji experience

Jia Wei, Zeyang Ding, Luyun Wang, Peng Chen, Shuiming Guo, Binhao Zhang, Xiaoning Wan, Wei Zhu, on behalf

Frontiers of Medicine 2020, Volume 14, Issue 2,   Pages 232-248 doi: 10.1007/s11684-020-0774-9

Abstract: Coronavirus disease 2019 (COVID-19) is a highly contagious disease and a serious threat to human health. COVID-19 can cause multiple organ dysfunction, such as respiratory and circulatory failure, liver and kidney injury, gastrointestinal dysfunction, disseminated intravascular coagulation, and thromboembolism, and even death. The World Health Organization reports that the mortality rate of severe-type COVID-19 is over 50%. Currently, the number of severe cases worldwide has increased rapidly, but the experience in the treatment of infected patients is still limited. Given the lack of specific antiviral drugs, multi-organ function support treatment is important for patients with COVID-19. To improve the cure rate and reduce the mortality of patients with severe- and critical-type COVID-19, this paper summarizes the experience of organ function support in patients with severe- and critical-type COVID-19 in Optical Valley Branch of Tongji Hospital, Wuhan, China. This paper systematically summarizes the procedures of functional support therapies for multiple organs and systems, including respiratory, circulatory, renal, gastrointestinal, hepatic, and hematological systems, among patients with severe- and critical-type COVID-19. This paper provides a clinical reference and a new strategy for the optimal treatment of COVID-19 worldwide.

Keywords： COVID-19     severe and critical type     organ function support    

HTML PDF Collect

SinoSCORE: a logistically derived additive prediction model for post-coronary artery bypass grafting in-hospital mortality in a Chinese population

Zhe Zheng, Lu Zhang, Xi Li, Shengshou Hu, on behalf of the Chinese CABG Registry Study

Frontiers of Medicine 2013, Volume 7, Issue 4,   Pages 477-485 doi: 10.1007/s11684-013-0284-0

Abstract:

This study aims to construct a logistically derived additive score for predicting in-hospital mortality risk in Chinese patients undergoing coronary artery bypass surgery (CABG). Data from 9839 consecutive CABG patients in 43 Chinese centers were collected between 2007 and 2008 from the Chinese Coronary Artery Bypass Grafting Registry. This database was randomly divided into developmental and validation subsets (9:1). The data in the developmental dataset were used to develop the model using logistic regression. Calibration and discrimination characteristics were assessed using the validation dataset. Thresholds were defined for each model to distinguish different risk groups. After excluding 275 patients with incomplete information, the overall mortality rate of the remaining 9564 patients was 2.5%. The SinoSCORE model was constructed based on 11 variables: age, preoperative NYHA stage III or IV, chronic renal failure, extracardiac arteriopathy, chronic obstructive pulmonary disease, preoperative atrial fibrillation or flutter (within 2βweeks), left ventricular ejection fraction, other elective surgery, combined valve procedures, preoperative critical state, and BMI. In the developmental dataset, calibration using a Hosmer-Lemeshow (HL) test was at =β0.44 and discrimination based on the area under the receiver operating characteristic curve (ROC) was 0.80. In the validation dataset, the HL test was at =β0.34 and the area under the ROC (AUC) was 0.78. A logistically derived additive model for predicting in-hospital mortality among Chinese patients undergoing CABG was developed based on the most up-to-date multi-center data from China.

Keywords： coronary artery bypass grafting     risk stratification     in-hospital mortality    

HTML PDF Collect

Soil Organic Carbon Changes in City Areas of China Over the Past Three Decades: Implications for Achieving Carbon Neutrality

Zhenrui Zhang, Xinghui Xia, Zhifeng Yang

Engineering 2023, Volume 28, Issue 9,   Pages 11-15 doi: 10.1016/j.eng.2022.04.014

Keywords： China     city areas     THE AUTHORS.Published     behalf     Company     Engineering     Education Press     Academy     carbon changes    

HTML PDF Collect

Erratum to “Targeted Genotyping of a Whole-Gene Repertoire by an Ultrahigh-Multiplex and Flexible HD-Marker Approach” [Engineering 13 (2022) 186–196] Erratum

Pingping Liu,Jia Lv,Cen Ma,Tianqi Zhang,Xiaowen Huang,Zhihui Yang,Lingling Zhang,Jingjie Hu,Shi Wang,Zhenmin Bao,

Engineering 2022, Volume 18, Issue 11,   Pages 259-259 doi: 10.1016/j.eng.2022.09.002

Keywords： online     THE AUTHORS.Published     repertoire     behalf     Engineering     September     genotyping     Academy     HD-marker approach    

HTML PDF Collect

Title Author Date Type Operation

Organ function support in patients with coronavirus disease 2019: Tongji experience

Jia Wei, Zeyang Ding, Luyun Wang, Peng Chen, Shuiming Guo, Binhao Zhang, Xiaoning Wan, Wei Zhu, on behalf

Journal Article

SinoSCORE: a logistically derived additive prediction model for post-coronary artery bypass grafting in-hospital mortality in a Chinese population

Zhe Zheng, Lu Zhang, Xi Li, Shengshou Hu, on behalf of the Chinese CABG Registry Study

Journal Article

Soil Organic Carbon Changes in City Areas of China Over the Past Three Decades: Implications for Achieving Carbon Neutrality

Zhenrui Zhang, Xinghui Xia, Zhifeng Yang

Journal Article

Erratum to “Targeted Genotyping of a Whole-Gene Repertoire by an Ultrahigh-Multiplex and Flexible HD-Marker Approach” [Engineering 13 (2022) 186–196]

Pingping Liu,Jia Lv,Cen Ma,Tianqi Zhang,Xiaowen Huang,Zhihui Yang,Lingling Zhang,Jingjie Hu,Shi Wang,Zhenmin Bao,

Journal Article