HEMODYNAMIC MONITORING AND PROGNOSTIC EVALUATING VALUE OF PiCCO IN PATIENTS WITH CARDIOPULMONARY RESUSCITATION WITH DIFFERENT PROGNOSIS
ACTA MEDICA MEDITERRANEA（2019）
Nanjing Univ
Abstract
Objective: PiCCO performs hemodynamic monitoring of patients with cardiopulmonary resuscitation with different prognosis. Method: This article reviews and analyzes the hemodynamic monitoring indicators of PiCCO in 35 patients with cardiopulmonary resuscitation (CPR) after spontaneous circulation recovery (ROSC) parallel target temperature management. According to whether 30 days after the onset of death, it was divided into group A (survival group) and B Group (death group), comparing differences in hemodynamic parameters, which are heart rate (HR), mean arterial pressure (MAP), and central venous pressure (CVP) at T1 (immediately after ROSC), T2 (12h after ROSC), T3 (24h after ROSC), and T4 (48h after ROSC). EXtravascular lung water ( EVLW), pulmonary vascular permeability index (PVPI), cardiac output index (CI), total end-diastolic volume (GEDV), intrathoracic blood volume (ITBV), peripheral vascular resistance index (SRVI), and so on. Results: There was no significant difference in age and sex between the two groups. The time points T3 and T4 in group B decreased compared with the time point T1. The time points T3 and T4 decreased compared with the time point 12. The MAP of group A and group B was significantly higher than that of T1 at 72, T3, and T4. The CVP of group A and group B was significantly higher than that of T1 at 12, T3, and T4. The EVLWI of group B was at T1. The time point 12 was significantly higher than that of the group A.The ITBVI of group A was higher than that of group B at T4. The SVRI time point T4 is lower than the time point T1 , the time points T3 and T4 are lower than the time point 12. Conclusions: HR, MAP, CVP, PVPI, CI, GEDV, ITBV, SRVI have no significant predictive value for the prognosis of patients after CPR.
MoreTranslated text
Key words
cardiopulmonary resuscitation,hemodynamics,PiCCO monitoring
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
Summary is being generated by the instructions you defined