A novel interpretative tool for early prediction of low cardiac output syndrome after valve surgery: online machine learning models-Reference-Cited by-同舟云学术

A novel interpretative tool for early prediction of low cardiac output syndrome after valve surgery: online machine learning models

Published:2023-12-12 Issue:2 Volume:55 Page:
ISSN:0785-3890
Container-title:Annals of Medicine
language:en
Short-container-title:Annals of Medicine

Author:

Hong Liang¹,Feng Tianling²³,Qiu Runze³⁴,Lin Shiteng²³,Xue Yinying¹,Huang Kaizong³⁴,Chen Chen³⁴,Wang Jiawen³⁵,Xie Rongrong¹,Song Sanbing¹,Zhang Cui¹,Zou Jianjun³⁴

Affiliation:

1. Cardiovascular Intensive Care Unit, Department of Critical Care Medicine, Nanjing First Hospital, Nanjing Medical University, Nanjing, China

2. School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, China

3. Department of Clinical Pharmacology, Nanjing First Hospital, Nanjing Medical University, Nanjing, China

4. Department of Pharmacy, Nanjing First Hospital, China Pharmaceutical University, Nanjing, China

5. School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China

Funder

Nanjing Key Medical Science and Technology Development Foundation

National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

General Medicine

Link

https://www.tandfonline.com/doi/pdf/10.1080/07853890.2023.2293244

Reference37 articles.

1. Commentary: Low cardiac output syndrome: A definition or a diagnosis code?

2. Improving risk assessment for post-surgical low cardiac output syndrome in patients without severely reduced ejection fraction undergoing open aortic valve replacement. The role of global longitudinal strain and right ventricular free wall strain

3. Outcome of cardiac surgery in patients with low preoperative ejection fraction

4. Systemic Vascular Load in Calcific Degenerative Aortic Valve Stenosis

5. Possible role of juxtaglomerular apparatus in low cardiac output syndrome and multiple organ failure: modulation by high sodium load

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