Can Non-Invasive Cardiac Hemodynamics and Fluid Content System (nicas) Parameters Predict Acute Heart Failure Outcomes in Caucasian and Asian Patients in the Emergency Department?

ADVANCES IN MEDICAL SCIENCES(2024)

引用 0|浏览0
暂无评分
摘要
PURPOSE:Acute heart failure (AHF) is a serious condition that requires prompt diagnosis and management. To optimize patient care, clinicians need a reliable, non-invasive method to assess hemodynamic parameters and total body congestion. Currently, no standardized technology is widely used for this purpose. However, NICaS technology, which measures hemodynamic parameters based on regional bioimpedance, has shown promise in monitoring AHF patients in a non-invasive and reliable manner. In this study, researchers aimed to evaluate the usefulness of NICaS technology in predicting patients' outcome in Caucasian and Asian AHF patients presenting to the emergency department (ED).PATIENTS AND METHODS:The study included 40 Caucasian patients from Italy (group A) and 71 Asian patients from Indonesia and Singapore (group B) with a diagnosis of AHF in the ED. The study compared data from NICaS parameters, clinical findings, laboratory, and radiological results with short-term events.RESULTS:In group A, NICaS data at ED arrival significantly predicted 30-day cardiovascular mortality and rehospitalization. At discharge, a value of cardiac output obtained using NICaS was a significant predictor for 30-day rehospitalization. In group B, NICaS variables, total peripheral resistance index on admission and during 48-72 ​h had prominent AUC compared to clinical congestion score and NT-proBNP in predicting mortality and rehospitalization.CONCLUSIONS:The results indicate that NICaS technology offers a simple, non-invasive, and reliable method of assessing cardiac hemodynamics and congestion in AHF patients. These measurements may enhance diagnosis, tailor management plans, stratify risk, and predict outcomes in both Caucasian and Asian patients.
更多
查看译文
关键词
Hemodynamic Monitoring,Cardiac Ultrasound
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要