Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Will clinical outcome for patients be improved if triage in Acute wards and Emergency rooms is supplemented with a prognostic biomarker?
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.
Not provided
Not provided
Not provided
Not provided
| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Conventional | No Intervention | no suPAR measurement. Standard care. | |
| suPAR | Experimental | suPAR measurement and education of doctors working in the Emergency department in the meaning of low or elevated levels of suPAR. Since suPAR is measured on all patients regardless of disease the investigators cannot define a single intervention. A possible intervention depends on the clinical situation. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| suPAR measurement | Behavioral | 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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. | 10 months after the inclusions period ends mortality data will be assessed |
| Measure | Description | Time Frame |
|---|---|---|
| All Cause Mortality | Mortality within 30 days | 1 months after index admission mortality data will assessed |
| Number of Discharges From the Emergency Room Within 24 Hours | How many patients are discharged directly from the ED |
Not provided
Inclusion Criteria:
Exclusion Criteria:
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| Name | Affiliation | Role |
|---|---|---|
| Kasper K Iversen, MD, DMSci | Department of Cardiology, Herlev Hospital | Study Director |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Herlev Hospital, Department of Cardiology | Herlev | 2730 | Denmark |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 31236143 | Derived | Schultz M, Rasmussen LJH, Hoi-Hansen T, Kjoller E, Jensen BN, Lind MN, Ravn L, Kallemose T, Lange T, Kober L, Rasmussen LS, Eugen-Olsen J, Iversen KK. Early Discharge from the Emergency Department Based on Soluble Urokinase Plasminogen Activator Receptor (suPAR) Levels: A TRIAGE III Substudy. Dis Markers. 2019 May 19;2019:3403549. doi: 10.1155/2019/3403549. eCollection 2019. | |
| 30975178 |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
| ID | Title | Description |
|---|---|---|
| FG000 | Conventional | no suPAR measurement. Standard care. |
| FG001 | suPAR | suPAR measurement and education of doctors working in the Emergency department in the meaning of low or elevated levels of suPAR. |
| Title | Milestones | Reasons Not Completed | ||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Overall Study |
|
Not provided
Not provided
| ID | Title | Description |
|---|---|---|
| BG000 | Conventional | no suPAR measurement. Standard care. |
| BG001 | suPAR | suPAR measurement and education of doctors working in the Emergency department in the meaning of low or elevated levels of suPAR. |
| 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 | 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. | Posted | Count of Participants | Participants | 10 months after the inclusions period ends mortality data will be assessed |
|
1 year
Data on all outcomes were collected from national registries.
Not provided
| ID | Title | Description | Deaths (Affected) | Deaths (At Risk) | Serious Events (Affected) | Serious Events (At Risk) | Other Events (Affected) | Other Events (At Risk) |
|---|---|---|---|---|---|---|---|---|
| EG000 | Conventional | no suPAR measurement. Standard care. | 1,126 |
Not provided
| Term | Organ System | Source Vocabulary | Assessment Type | Notes | Statistical Information |
|---|---|---|---|---|---|
| New cancer diagnosis | Neoplasms benign, malignant and unspecified (incl cysts and polyps) | Systematic Assessment |
Not provided
| Title | Organization | Phone | Extension | |
|---|---|---|---|---|
| Dr. Martin Schultz | Herlev Hospital, Department of Cardiology | 004538683868 | martin.schultz@regionh.dk |
Not provided
| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot_SAP | Yes | Yes | No | Study Protocol and Statistical Analysis Plan | Jan 4, 2018 | Jul 30, 2020 | Prot_SAP_000.pdf |
Not provided
Not provided
Not provided
Not provided
Not provided
Not provided
|
| 24 hours |
| Number of Admissions to the Medical Ward | Number of Participants with Admissions to the Medical War | 30 days |
| Number of Patients With an Admission to the Intensive Care Unit | Number of Participants with transfer to the ICU | 30 days |
| Number of Patients With New Cancer Diagnosis in Control vs Intervention Groups | 10 months after inclusion period ends |
| Length of Stay During Admission. | Length of stay in days during the admission | 30 days |
| Number of Readmissions | Patients will be followed using central registers. All new admissions within 90 days of the same patient is defined as readmissions. | 90 days |
| Derived |
| Schultz M, Rasmussen LJH, Kallemose T, Kjoller E, Lind MN, Ravn L, Lange T, Kober L, Rasmussen LS, Eugen-Olsen J, Iversen K. Availability of suPAR in emergency departments may improve risk stratification: a secondary analysis of the TRIAGE III trial. Scand J Trauma Resusc Emerg Med. 2019 Apr 11;27(1):43. doi: 10.1186/s13049-019-0621-7. |
| 30153859 | Derived | Schultz M, Rasmussen LJH, Andersen MH, Stefansson JS, Falkentoft AC, Alstrup M, Sando A, Holle SLK, Meyer J, Tornkvist PBS, Hoi-Hansen T, Kjoller E, Jensen BN, Lind M, Ravn L, Kallemose T, Lange T, Kober L, Rasmussen LS, Eugen-Olsen J, Iversen KK. Use of the prognostic biomarker suPAR in the emergency department improves risk stratification but has no effect on mortality: a cluster-randomized clinical trial (TRIAGE III). Scand J Trauma Resusc Emerg Med. 2018 Aug 28;26(1):69. doi: 10.1186/s13049-018-0539-5. |
| 27491822 | Derived | Sando A, Schultz M, Eugen-Olsen J, Rasmussen LS, Kober L, Kjoller E, Jensen BN, Ravn L, Lange T, Iversen K. Introduction of a prognostic biomarker to strengthen risk stratification of acutely admitted patients: rationale and design of the TRIAGE III cluster randomized interventional trial. Scand J Trauma Resusc Emerg Med. 2016 Aug 5;24:100. doi: 10.1186/s13049-016-0290-8. |
| BG002 | Total | Total of all reporting groups |
| years |
|
| Sex: Female, Male | Count of Participants | Participants |
|
| Ethnicity (NIH/OMB) | Count of Participants | Participants |
|
| Region of Enrollment | Number | participants |
|
| Units | Counts |
|---|
| Participants |
|
|
| Secondary | All Cause Mortality | Mortality within 30 days | Posted | Count of Participants | Participants | 1 months after index admission mortality data will assessed |
|
|
|
| Secondary | Number of Discharges From the Emergency Room Within 24 Hours | How many patients are discharged directly from the ED | Posted | Count of Participants | Participants | 24 hours |
|
|
|
| Secondary | Number of Admissions to the Medical Ward | Number of Participants with Admissions to the Medical War | Posted | Count of Participants | Participants | 30 days |
|
|
|
| Secondary | Number of Patients With an Admission to the Intensive Care Unit | Number of Participants with transfer to the ICU | Posted | Count of Participants | Participants | 30 days |
|
|
|
| Secondary | Number of Patients With New Cancer Diagnosis in Control vs Intervention Groups | Posted | Count of Participants | Participants | 10 months after inclusion period ends |
|
|
|
| Secondary | Length of Stay During Admission. | Length of stay in days during the admission | Posted | Mean | Standard Error | Days | 30 days |
|
|
|
| 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. | Posted | Count of Participants | Participants | 90 days |
|
|
|
| 7,901 |
| 0 |
| 7,901 |
| 700 |
| 7,901 |
| EG001 | suPAR | suPAR measurement and education of doctors working in the Emergency department in the meaning of low or elevated levels of suPAR. | 1,241 | 8,900 | 0 | 8,900 | 777 | 8,900 |
Not provided
Not provided