Publications by authors named "Minghai Xian"

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Nomogram to predict survival outcome of patients with veno-arterial extracorporeal membrane oxygenation after refractory cardiogenic shock.

Postgrad Med 2021 May 20:1-10. Epub 2021 May 20.

Department of Critical Care Medicine, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, The Second School of Clinical Medicine, Southern Medical University, Gaozhou, Guangdong, China.

: This study aims to develop a nomogram model to predict the survival of refractory cardiogenic shock (RCS) patients that received veno-arterial extracorporeal membrane oxygenation (VA-ECMO).: A total of 235 and 209 RCS patients were supported with VA-ECMO from January 2018 to December 2019 in Guangdong Provincial People's Hospital, and from January 2020 to December 2020 in four third-grade and class-A hospitals were a development cohort (DC) and validation cohort (VC), respectively. Finally, 137 and 98 patients were included in the DC and VC. Multivariate logistic regression analysis was used to identify variables, and only these independent risk factors were used to establish the nomogram model. The receiver operating characteristic curve (ROC), calibration plot, decision curve, and clinical impact curves were used to evaluate the nomogram's discriminative ability, predictive accuracy, and clinical application value.: Pre-ECMO cardiogenic arrest (pre-ECA), lactate (Lac), inotropic score (IS), and modified nutrition risk in the critically ill score (mNUTRIC score) were incorporated into the nomogram. This showed good discrimination in the DC, with an area under ROC (AUROC) and a 95% confidence interval (CI) of 0.959 (0.911-0.986). The AUROC (95% CI) of the VC was 0.928 (0.858-0.971). The calibration plots of the DC and VC presented good calibration results. The decision curve and clinical impact curve of the nomogram provided improved benefits for RCS patients.: This study established a prediction nomogram composed of pre-ECA, Lac, IS, and mNUTRIC scores that could help clinicians to predict the survival probability at hospital discharge precisely and rapidly for RCS patients that received VA-ECMO.
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http://dx.doi.org/10.1080/00325481.2021.1925562DOI Listing
May 2021