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The purpose of this study is to develop new triage tool for trauma patients based on HRV. EKG will be prospectively measured in trauma patients in two locations: in the prehospital setting (the field and during transport by helicopter) and in the hospital setting. In each case HRV will be derived from the EKG signal, will be correlated with other non-invasive signals (e.g. near infrared spectroscopy (NIR), and bispectral EEG (BIS)), along with other routinely measured variables (blood pressure, respiratory rate, pulse oximetry, etc), will be correlated with injury severity and day of discharge. An algorithm will be constructed using multiple linear regression. The hypotheses are:
The eligible study population will be comprised of patients who meet level 1 trauma criteria and are transported by helicopter to Ryder Trauma Center or who are already admitted to the trauma center for presumptive traumatic brain injury. In addition to the EKG, trauma patients may also be connected to either an non-invasive NIR Monitor, which provides real-time information about perfusion status and/or a bispectral EEG monitor, which provides real-time information about brain metabolic activity.
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| Measure | Description | Time Frame |
|---|---|---|
| Base Deficit </= -6 | Indicator for volume deficit and resuscitation. Number of participants with Base Deficit \ | Upon arrival to the hospital |
| Serious Injury | A patient was classified as seriously injured when two of three blinded trauma surgeons classified the patient as similar after review of each patient chart and final diagnoses in retrospect. | Upon arrival to the hospital |
| Life Saving Intervention in the Operating Room. | A patient was classified as having a life saving intervention in the operating room when two of three blinded trauma surgeons classified the patient as similar after review of each patient chart and final diagnoses in retrospect. | Upon arrival to the hospital |
| SDNN: Standard Deviation of the Normal-to-normal R-R Interval | A determination of HRV derived from the time domain of a standard electrocardiogram, primarily determined by measuring the randomness of the exact occurrence of when one R wave follows a preceding R wave. | Upon arrival to the hospital |
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Inclusion Criteria:
Exclusion Criteria:
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All trauma patients
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| Name | Affiliation | Role |
|---|---|---|
| Kenneth G Proctor, PhD | University of Miami | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Ryder Trauma Center | Miami | Florida | 33136 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 17622866 | Background | Proctor KG, Atapattu SA, Duncan RC. Heart rate variability index in trauma patients. J Trauma. 2007 Jul;63(1):33-43. doi: 10.1097/01.ta.0000251593.32396.df. |
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| ID | Title | Description |
|---|---|---|
| FG000 | Trauma Patients | Patients transported to the trauma center by helicopter |
| Title | Milestones | Reasons Not Completed | ||||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
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75 patients with complete HRV and trauma registry data
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| ID | Title | Description |
|---|---|---|
| BG000 | Trauma Patients | Patients transported to the trauma center by helicopter |
| Units | Counts |
|---|---|
| Participants |
|
| Title | Description | Population Description | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Denominator Units Selected | Denominators | Classes |
|---|---|---|---|---|---|---|---|---|---|
| Age, Continuous | Mean |
| Type | Title | Description | Population Description | Reporting Status | Anticipated Posting Date | Parameter Type | Dispersion Type | Unit of Measure | Calculate Percentage | Time Frame | Units Analyzed | Denominator Units Selected | Arm/Group Information | Denominators | Classes | Analyses | |||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Primary | Base Deficit </= -6 | Indicator for volume deficit and resuscitation. Number of participants with Base Deficit \ | 75 patients with complete HRV and trauma registry data | Posted | Number | participants | Upon arrival to the hospital |
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Duration of transport from injury to hospital
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| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Trauma Patients | Patients transported to the trauma center by helicopter |
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| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Kenneth Proctor, PhD, Professor of Surgery | University of Miami | 305-355-4960 | kproctor@med.miami.edu |
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| ID | Term |
|---|---|
| D014947 | Wounds and Injuries |
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| years |
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| Sex: Female, Male | Count of Participants | Participants |
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| Counts |
|---|
| Participants |
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| Primary | Serious Injury | A patient was classified as seriously injured when two of three blinded trauma surgeons classified the patient as similar after review of each patient chart and final diagnoses in retrospect. | 75 patients with complete HRV and trauma registry data | Posted | Number | participants | Upon arrival to the hospital |
|
|
|
| Primary | Life Saving Intervention in the Operating Room. | A patient was classified as having a life saving intervention in the operating room when two of three blinded trauma surgeons classified the patient as similar after review of each patient chart and final diagnoses in retrospect. | 75 patients with complete HRV and trauma registry data | Posted | Number | participants | Upon arrival to the hospital |
|
|
|
| Primary | SDNN: Standard Deviation of the Normal-to-normal R-R Interval | A determination of HRV derived from the time domain of a standard electrocardiogram, primarily determined by measuring the randomness of the exact occurrence of when one R wave follows a preceding R wave. | Posted | Mean | Standard Deviation | milliseconds (ms) | Upon arrival to the hospital |
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| 0 |
| 75 |
| 0 |
| 75 |
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