Chronic Kidney Disease Clinical Trial
Official title:
Using Contact Free Sensor to Analyse Cardio-respiratory Patterns in Order to Early Detect the Clinical Complications in the Hemodialysis Patients.
The incidence and prevalence of dialysis in Taiwan remains higher as compared to past
several years. The number of dialysis reported about 6-7 million people each year and the
2014 full-year cost estimation was about 330 million NTDs. According to age-standardized
population statistics in 1995, the number of dialysis per million population in 2006 year
were 372.2 people, 381.9 people in 2012 year and the annual growth rate of 0.43 percent
recorded.
EarlySense system is certified by TFDA, FDA and many other countries, which consists of
mainly two parts. One for the sensing element, which placed under the mattress and the other
one is AC-powered display panel bed. This system has the ability to monitor the patients
physiological functions just be in contact via bed. When the patient laid on bed, the sensor
which is placed under the bed would detects heart rate, breathing rate and activity level as
well as other physiological signals. The system is also able to distinguish between patients
in bed and out of bed during the operation to save the patient's records and information
(including heart rate, respiratory rate and level of activity, and may render trends). The
system is also have capability for real-time data transmission information which includes a
warning to the nurses' station or other monitoring center of the screen by providing
real-time information to nurse.
In this research project, we will use EarlySense equipment for continuous monitoring the
dialysis patient's physiological data along with clinical data such as A. acute
complications such as rapid changes in blood pressure, respiratory rate, movements of
patients and Nausea or vomiting, etc phenomenon's) B. Lab examination data C. Status of
patient whether patients hospitalized or not and patient death occurred or not. The study is
expected to have a pilot study for more than three months' duration. Through this EarlySense
continuous monitoring and gather the data, we will analyse to develop a prediction model and
confirmed with indicators. Evidences from these analytics would help to propose ways to
improve it and implement Positive predictive validity models.
n/a
Observational Model: Case-Only, Time Perspective: Prospective
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