Risk Stratification With Biomarker, Triage
Conditions
Keywords
Triage, Risk stratification, Acute care, suPAR
Brief summary
Will clinical outcome for patients be improved if triage in Acute wards and Emergency rooms is supplemented with a prognostic biomarker?
Detailed description
In a health care system where the general population is growing, more patients are living with chronic conditions and the hospitals are reducing beds and length of stay, it is crucial to perform safe and fast risk stratification of patients presenting in the Emergency departments. Risk stratification is currently performed with a combination of measurement of the vital signs and assessment of the primary complaint. The aim of the current study is to assess whether the supplement of biomarkers can improve the risk stratification in regard to mortality, readmissions and improve overall patient flow in the Emergency departments. Soluble urokinase plasminogen activating receptor (suPAR) is the soluble form of urokinase-type plasminogen activator receptor (uPAR). uPAR is present on various immunological active cells, as well as endothelia and smooth muscle cells. It is believed that suPAR mirrors the inflammatory response in patients. Previous studies have shown a strong association with mortality and severity of disease in a broad variety of conditions (infection, hepatic-, renal-, cardiac- and lung disease) as well as a possible marker of disease development in the general population. These abilities indicate that suPAR although unspecific would be ideal to identify patients at high- and at low-risk. The aim is to target interventions and limited clinical focus where it is most beneficial. In unselected patients suPAR is one of the strongest prognostic biomarker available to date. It is not known whether information on prognosis in the Emergency department can be used to prevent death, serious complications or reduce admissions and readmissions. The purpose of the current study is to examine if introduction of the biomarker suPAR and education of doctors in the meaning of suPAR levels and association to disease, can reduce mortality, admissions and readmission in patients referred to the emergency rooms.
Interventions
BEHAVIORALsuPAR measurement
The biomarker suPAR will be measured on all patients included in the study. Before the study period the doctors will receive information on suPAR. We want to study if the information provided by suPAR is useful in emergency medicine. Interventions depends on the clinical issue, as suPAR is an unspecific marker of disease. Usually a elevated suPAR level could result in more investigation e.g. diagnostic procedures or follow up, while a low suPAR could result in faster discharge.
Sponsors
Herlev Hospital
Study design
Allocation
RANDOMIZED
Intervention model
PARALLEL
Primary purpose
PREVENTION
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
16 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Patients presenting acutely to the Acute ward/Emergency department and have blood samples done which include both Hemoglobin, C reactive protein and Creatinine within 6 hours of registration within the study period. The study is carried out in 2 Hospitals in the Capital of Denmark.
Exclusion criteria
* Patients presenting in Pediatric, Gynecological or Obstetric units. Patients not being examined with blood samples.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| All Cause Mortality | 10 months after the inclusions period ends mortality data will be assessed | Time frame starts at the beginning of the index admission, defined as first admission in the study period. Patients will be followed using central registers. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Number of Discharges From the Emergency Room Within 24 Hours | 24 hours | How many patients are discharged directly from the ED |
| Number of Admissions to the Medical Ward | 30 days | Number of Participants with Admissions to the Medical War |
| Number of Patients With an Admission to the Intensive Care Unit | 30 days | Number of Participants with transfer to the ICU |
| All Cause Mortality | 1 months after index admission mortality data will assessed | Mortality within 30 days |
| Length of Stay During Admission. | 30 days | Length of stay in days during the admission |
| Number of Readmissions | 90 days | Patients will be followed using central registers. All new admissions within 90 days of the same patient is defined as readmissions. |
| Number of Patients With New Cancer Diagnosis in Control vs Intervention Groups | 10 months after inclusion period ends | — |
Countries
Denmark
Participant flow
Participants by arm
| Arm | Count |
|---|---|
| Conventional no suPAR measurement. Standard care. | 7,901 |
| suPAR suPAR measurement and education of doctors working in the Emergency department in the meaning of low or elevated levels of suPAR. | 8,900 |
| Total | 16,801 |
Baseline characteristics
| Characteristic | Conventional | suPAR | Total |
|---|---|---|---|
| Age, Continuous | 60.9 years STANDARD_DEVIATION 20.7 | 60.4 years STANDARD_DEVIATION 20.8 | 60.6 years STANDARD_DEVIATION 20.7 |
| Ethnicity (NIH/OMB) Hispanic or Latino | 0 Participants | 0 Participants | 0 Participants |
| Ethnicity (NIH/OMB) Not Hispanic or Latino | 0 Participants | 0 Participants | 0 Participants |
| Ethnicity (NIH/OMB) Unknown or Not Reported | 7901 Participants | 8900 Participants | 16801 Participants |
| Region of Enrollment Denmark | 7901 participants | 8900 participants | 16801 participants |
| Sex: Female, Male Female | 4175 Participants | 4689 Participants | 8864 Participants |
| Sex: Female, Male Male | 3726 Participants | 4211 Participants | 7937 Participants |
Adverse events
| Event type | EG000 affected / at risk | EG001 affected / at risk |
|---|---|---|
| deaths Total, all-cause mortality | 1,126 / 7,901 | 1,241 / 8,900 |
| other Total, other adverse events | 700 / 7,901 | 777 / 8,900 |
| serious Total, serious adverse events | 0 / 7,901 | 0 / 8,900 |
Outcome results
Primary
All Cause Mortality
Time frame starts at the beginning of the index admission, defined as first admission in the study period. Patients will be followed using central registers.
Time frame: 10 months after the inclusions period ends mortality data will be assessed
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | All Cause Mortality | 1126 Participants |
| suPAR | All Cause Mortality | 1241 Participants |
Secondary
All Cause Mortality
Mortality within 30 days
Time frame: 1 months after index admission mortality data will assessed
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | All Cause Mortality | 319 Participants |
| suPAR | All Cause Mortality | 359 Participants |
Secondary
Length of Stay During Admission.
Length of stay in days during the admission
Time frame: 30 days
| Arm | Measure | Value (MEAN) | Dispersion |
|---|---|---|---|
| Conventional | Length of Stay During Admission. | 4.53 Days | Standard Error 8.7 |
| suPAR | Length of Stay During Admission. | 4.39 Days | Standard Error 8.27 |
Secondary
Number of Admissions to the Medical Ward
Number of Participants with Admissions to the Medical War
Time frame: 30 days
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | Number of Admissions to the Medical Ward | 3500 Participants |
| suPAR | Number of Admissions to the Medical Ward | 3738 Participants |
Secondary
Number of Discharges From the Emergency Room Within 24 Hours
How many patients are discharged directly from the ED
Time frame: 24 hours
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | Number of Discharges From the Emergency Room Within 24 Hours | 3934 Participants |
| suPAR | Number of Discharges From the Emergency Room Within 24 Hours | 4352 Participants |
Secondary
Number of Patients With an Admission to the Intensive Care Unit
Number of Participants with transfer to the ICU
Time frame: 30 days
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | Number of Patients With an Admission to the Intensive Care Unit | 1027 Participants |
| suPAR | Number of Patients With an Admission to the Intensive Care Unit | 1157 Participants |
Secondary
Number of Patients With New Cancer Diagnosis in Control vs Intervention Groups
Time frame: 10 months after inclusion period ends
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | Number of Patients With New Cancer Diagnosis in Control vs Intervention Groups | 687 Participants |
| suPAR | Number of Patients With New Cancer Diagnosis in Control vs Intervention Groups | 917 Participants |
Secondary
Number of Readmissions
Patients will be followed using central registers. All new admissions within 90 days of the same patient is defined as readmissions.
Time frame: 90 days
| Arm | Measure | Value (COUNT_OF_PARTICIPANTS) |
|---|---|---|
| Conventional | Number of Readmissions | 687 Participants |
| suPAR | Number of Readmissions | 917 Participants |