Cardiac Event
Conditions
Brief summary
The overall goal of this collaborative study is to advance the novel pulse contour analysis to the point at which it can be incorporated into a real-time device. The specific objective is to establish an auto-calibration algorithm that conveniently yields cardiac output (CO) in units of liters-per-minute. To achieve this objective, the waveforms for analysis and reference pulmonary artery catheter CO measurements will be recorded from critically ill patients and then analyzed off-line at Retia Medical. Successful completion of this study may ultimately help lead to improved outcomes of critically ill patients.
Interventions
DEVICERetia Non-Invasive Sensors
Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform.
Sponsors
Retia Medical
University of Michigan
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
OTHER
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* All adult patients admitted to the University of Michigan ICU following cardiac surgery with both a pulmonary and radial artery catheter.
Exclusion criteria
* Adult patients with mechanical cardiac support including intra-aortic balloon pumps, LVAD, or ECMO, and persistent ventricular arrhythmias.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output | 8 hours post cardiac surgery | The primary outcome of this work is to establish a dataset that would enable the calculation of a predicted cardiac output using waveform analysis from multiple sensors. The primary outcome of this work is the number of subjects that successfully contributed data. |
Countries
United States
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Retia Non-Invasive Sensors Sensors will be placed on the patient and connected to an amplifier that produces a waveform for 8 hours post cardiac surgery.
Retia Non-Invasive Sensors: Three adhesive sensor patches (similar to ECG patches) will be placed on the chest and a sensor similar to a pulse oximeter will be placed on the toe. The sensors will be connected to an electrical amplifier that produces a waveform. | 77 |
| Total | 77 |
Baseline characteristics
| Characteristic | Retia Non-Invasive Sensors |
|---|---|
| Age, Categorical <=18 years | 0 Participants |
| Age, Categorical >=65 years | 49 Participants |
| Age, Categorical Between 18 and 65 years | 28 Participants |
| Age, Continuous | 69 years |
| Region of Enrollment United States | 77 participants |
| Sex: Female, Male Female | 31 Participants |
| Sex: Female, Male Male | 46 Participants |
Adverse events
| Event type | EG000 affected / at risk |
|---|---|
| deaths Total, all-cause mortality | — / — |
| other Total, other adverse events | 0 / 77 |
| serious Total, serious adverse events | 0 / 77 |
Outcome results
Primary
Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output
The primary outcome of this work is to establish a dataset that would enable the calculation of a predicted cardiac output using waveform analysis from multiple sensors. The primary outcome of this work is the number of subjects that successfully contributed data.
Time frame: 8 hours post cardiac surgery
Population: patients had undergone routine cardiac surgery. some patients did not have PA catheters placed and subsequently data was not obtained on cardiac output.
| Arm | Measure | Category | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|---|
| Retia Non-Invasive Sensors | Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output | analyzable data obtained | 75 Participants |
| Retia Non-Invasive Sensors | Establishment of a Dataset to Create an Algorithm to Measure Cardiac Output | data flawed and unable to analyze | 2 Participants |