Arterial Waveform Analysis for Predicting Post-induction Hypotension

Status Active, not recruiting

Clinical Trial Summary

The goal of this observational study is to develop a computation model for accurately predicting post-induction hypotension in patients receiving laparoscopic surgery under general anesthesia. The main question[s] it aims to answer are: • whether the corresponding characteristics on pressure wave forms could be use to predict post-induction hypotension. Participants will be observed before and after induction of general anesthesia for non-invasive arterial pressure wave forms and blood pressure changes.

Clinical Trial Description

In this project, an equivalent circuit model will firstly be established to simulate patient's hemodynamics. This model will be applied into analyzing blood pressure wave forms in the MIMIC II database. It will facilitate deep understanding of the effects of induction drugs on pressure waveforms. As a result, the corresponding characteristics on pressure wave forms will be identified. The extracted characteristics from the MIMIC II database will then be applied for developing a computation model via machining learning approaches. The developed model will be validated with another available dataset of 100 patients. This project will then conduct a non-invasive and observational clinical study of 50 patients to prove the clinical value of this project. In this trial, a novel pressure sensor will be employed on patient's fingertip to continuously collect pressure waveform before and after anesthesia induction. Medical records and vital signs will also be collected for exploring the potential of the developed model for predicting other events. Endoscopic surgery patients will be recruited in this study. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT05756933
Study type	Observational
Source	Taipei Medical University
Contact
Status	Active, not recruiting
Phase
Start date	August 1, 2022
Completion date	April 30, 2024

View Details

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