PATIENT ASSESSMENT METHOD
20210109110 · 2021-04-15
Inventors
Cpc classification
G01N33/6872
PHYSICS
G16H50/30
PHYSICS
International classification
Abstract
A subject's level of soluble urokinase type plasminogen activator (suPAR) is checked as part of a risk stratification procedure in a hospital emergency department to help decide whether to admit the subject to the hospital, keep the subject in as a patient, or discharge a patient.
Claims
1. A method of applying risk stratification to a human subject who has been admitted to, or presents at, a hospital emergency department (ED), the method comprising measuring the soluble urokinase type plasminogen activator (suPAR) level in a sample obtained from the subject and comparing it with a reference suPAR value.
2. A method according to claim 1 comprising determining the morbidity of the subject.
3. A method according to claim 1 or 2 comprising determining the risk of in-hospital death or death within 28 days, 90 days, 6 months, 10 months or 2 months of the subject.
4. A method according to any of the preceding claims comprising determining the need to admit the subject into the hospital
5. A method according to any of the preceding claims comprising determining the ability to discharge the subject from the hospital or not to admit the subject into the hospital.
6. A method according to any of the preceding claims wherein the sample is blood, blood serum, blood plasma, cerebrospinal fluid or urine.
7. A method according to any of the preceding claims wherein the risk stratification additionally comprises measuring and/or processing one or more of: the subject's sex, age, medical history, haemoglobin level, C Reactive Protein level, creatinine level, leucocyte count, sodium level, potassium level, adrenomedullin level, albumin level, D-dimer level, troponin level (HEART Score); recording clinical symptoms and signs such as physiological parameters, such as pulse, cognition, blood pressure, temperature and respiratory rate; the output of a risk algorithm such as Early warning score and similar and locally adapted variables thereof (e.g. Decision-tree early warning score (DTEWS) or National Early Warning Score (NEWS), Acute Physiology and Chronic Health Evaluation (APACHE), Glasgow coma scale, electrocardiogram, age, risk factors, quick Sepsis Related Organ Failure Assessment (qSOFA), or the Model for Endstage Liver Disease (MELD), based on bilirubin, INR (international normalized ratio), and creatinine); the American Society of Anesthesiologists (ASA) classification; the Physiologic and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) score; or other risk scores for outcome prediction of acute hospitalized patients, such as the GRACE ACS Risk and Mortality Calculator, the Thrombolysis in Myocardial Infarction risk score (TIMI RS), Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using Integrilin Therapy risk score (PURSUIT RS), and Global Registry of Acute Cardiac Events risk score (GRACE RS) for in-hospital and 1 year mortality across the broad spectrum of non-ST-elevation acute coronary syndromes (ACS).
8. A method according to any of the preceding claims wherein the reference suPAR value is a plasma level of between 0 and 16 ng/ml.
9. A method according to claim 8 wherein a plasma suPAR level of higher than 4 ng/ml in the subject is a factor indicating that a subject should be admitted as a patient, or kept in as a patient, even if other components of the risk stratification procedure are factors indicating that the subject need not be admitted or can be discharged.
10. A method according to claim 8 or 9 wherein a plasma suPAR level of higher than 6 ng/ml, especially higher than 9 ng/ml, in the subject is a strong factor indicating that a subject should be admitted as a patient, or kept in as a patient, even if other components of the risk stratification procedure are factors indicating that the subject need not be admitted or can be discharged.
11. A method according to any of claims 8 to 10 wherein a plasma suPAR level of lower than 4 ng/ml, especially lower than 3 ng/ml, is a factor indicating that a subject need not be admitted as a patient, or can be discharged from the hospital.
12. A method according to any of the preceding claims wherein the subject's suPAR level is measured within 6 hours of the subject's arrival at the hospital emergency department.
13. Apparatus for applying risk stratification to a human subject who has been admitted to, or presents at, a hospital emergency department (ED), the apparatus comprising: means to accommodate a sample obtained from the subject, a detector configured to measure the level of soluble urokinase type plasminogen activator (suPAR) in the sample, a processing module to compare the level of suPAR with a reference suPAR value, and means to output a risk stratification.
14. Apparatus according to claim 13 wherein the means to output the risk stratification is a visual display or a printout.
15. Apparatus according to claim 13 or 14 wherein, in order to output the risk stratification, the apparatus additionally processes one or more of measuring and/or processing one or more of: the subject's sex, age, medical history, haemoglobin level, C Reactive Protein level, creatinine level, leucocyte count, sodium level, potassium level, adrenomedullin level, albumin level, D-dimer level, troponin level (HEART Score); recording clinical symptoms and signs such as physiological parameters, such as pulse, cognition, blood pressure, temperature and respiratory rate; the output of a risk algorithm such as Early warning score and similar and locally adapted variables thereof (e.g. Decision-tree early warning score (DTEWS) or National Early Warning Score (NEWS), Acute Physiology and Chronic Health Evaluation (APACHE), Glasgow coma scale, electrocardiogram, age, risk factors, quick Sepsis Related Organ Failure Assessment (qSOFA), or the Model for Endstage Liver Disease (MELD), based on bilirubin, INR (international normalized ratio), and creatinine); the American Society of Anesthesiologists (ASA) classification; the Physiologic and Operative Severity Score for the enUmeration of Mortality and Morbidity (POSSUM) score; or other risk scores for outcome prediction of acute hospitalized patients, such as the GRACE ACS Risk and Mortality Calculator, the Thrombolysis in Myocardial Infarction risk score (TIMI RS), Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using Integrilin Therapy risk score (PURSUIT RS), and Global Registry of Acute Cardiac Events risk score (GRACE RS) for in-hospital and 1 year mortality across the broad spectrum of non-ST-elevation acute coronary syndromes (ACS).
Description
FIGURES
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EXAMPLE 1—MEASUREMENT OF SUPAR LEVEL
[0049] suPAR levels may be measured in body fluids by the methods taught in WO 2008/077958, which is incorporated herein for that purpose.
[0050] More specifically, suPAR levels may be determined by ELISA assay as follows: Nunc Maxisorp ELISA-plates (Nunc, Roskilde, Denmark) are coated overnight at 4° C. with a monoclonal rat anti-suPAR antibody (VG-1, ViroGates NS, Copenhagen, Denmark, 3 μg/ml, 100 μl/well). Plates are blocked with PBS buffer+1% BSA and 0.1% Tween 20, 1 hour at room temperature, and washed 3 times with PBS buffer containing 0.1% Tween 20. 85 μl dilution buffer (100 mm phosphate, 97.5 mm NaCl, 10 g L.sup.−1 bovine serum albumin (BSA, Fraction V, Roche Diagnostics GmbH Penzberg, Germany), 50 U mL.sup.−1 heparin sodium salt (Sigma Chemical Co., St. Louis, Mo.), 0.1% (v/v) Tween 20, pH 7.4) containing 1.5 μg/ml HRP labeled mouse anti-suPAR antibody (VG-2-HRP, ViroGates) and 15 μl plasma (or serum or urine) sample is added in duplicates to the ELISA plate. After 1 hour of incubation at 37° C., plates are washed 10 times with PBS buffer+0.1% Tween 20 and 100 μl/well HRP substrate added (Substrate Reagent Pack, R&D Systems Minneapolis, Minn.). The colour reaction is stopped after 30 min using 50 μl per well 1M H.sub.2S0.sub.4 and measured at 450 nm.
[0051] Furthermore, suPAR can be measured in bodily fluids using commercially available CE/IVD approved assays such as the suPARnostic product line according to the manufacturer's instructions. In the TRIAGE III trials, suPAR was quantified using the suPARnostic Quick Triage lateral flow assay.
EXAMPLE 2—CORRELATION OF PLASMA AND URINE LEVELS OF SUPAR
[0052] WO 2008/077958 shows that plasma levels of suPAR in HIV-infected patients on stable HAART correlate with urine suPAR, as has been demonstrated previously in HIV negative individuals, and that diurnal changes in urine suPAR are small (Sier et al., 1999, Lab Invest 79:717-722). A sub-sample of 24 of 36 patients had provided overnight-fasting urine. The effect of differences in dilution of the urine on suPAR levels was corrected with the amount of creatinine, as described previously (Sier et al, 1999, Lab Invest. 79:717-722). Urine creatinine was measured as described (Mustjoki et al, 2000, Cancer Res. 60:7126-7132).
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EXAMPLE 3—CLINICAL TRIAL STRUCTURE
[0054] A randomized intervention study was carried out at two large hospitals in the capital region of Denmark (ClinicalTrials.gov number, NCT02643459). The hypothesis of the study was that the introduction, fast measurement and immediate reporting (knowledge) of the suPAR level to attending physicians or other hospital professionals in the EDs will be associated with a reduction in all-cause mortality at least 10 months after admission.
[0055] The primary aim of the study was to evaluate whether the determination of the subject's suPAR level can be used as a part of risk stratification of unselected acutely admitted subjects in order to reduce all-cause mortality.
[0056] The secondary aims included: [0057] All cause mortality after index admission, after 30 days. [0058] Number of discharges from the emergency room within 24 hours. [0059] Length of stay during admission. [Time Frame: In-hospital stay]. [0060] Number of readmissions [Time Frame: 30 and 90 days]. All new admissions within 91 days of the same patient are defined as readmissions. [0061] Economical expenses [Time Frame: in-hospital stay, 30 days and 10 months after inclusion period ends].
[0062] The main hypothesis was to assess if all-cause mortality at 10 months after admission is lower when the suPAR biomarker is measured on acutely admitted patients. Using a 5% level of significance and a power of 80%, a sample of 7340 subjects was needed in each randomization group to detect an absolute risk reduction in mortality at least 10 months after admission of 1.5%.
TABLE-US-00001 TABLE 1 Trial structure Cycle 1 2 3 4 5 6 Hospital 1 +suPAR Control +suPAR Control +suPAR Control Hospital 2 Control +suPAR Control +suPAR Control +suPAR
[0063] Each cycle consisted of three weeks with (+suPAR) or without (Control) suPAR measurements in the ED.
Quantification of suPAR
[0064] Blood samples (6 mL EDTA plasma tubes) for measurement of plasma suPAR were drawn along with the routine blood work. For quantification of suPAR, blood collection tubes were spun for 60 s at 6000 RPM. 10 μL of plasma was added to a prefabricated tube containing 100 μL of running buffer. Using a 60 μL pipette, the plasma and buffer were mixed by pipetting the solution up and down 5 times. From this mixture, 60 μL was added to the suPARnostic® Quick Triage stick, a lateral flow device (also called suPARnostic® Quick Test). After 20 min, the lateral flow device was visually inspected for test and control line, and the suPAR test line quantified using a suPARnostic Quick test device reader (Qiagen, Germany) [20]. According to the test manufacturer (ViroGates NS, Birkeroed, Denmark), the limit of Detection (LOD) for the suPARnostic quick test was 0.3 ng/ml. The limit of quantification (LOQ) was 2 ng/mL defined at the lowest concentration with a CV % that does not exceed 25%. The intra- and interserial measured CV % on 5 samples×4 concentrations (2.0; 4.0; 8.4; 13.7 ng/mL) measured on the same day or with 5 days interval was less than 25%. The r.sup.2 of the suPARnostic Quick Test compared to the suPARnostic ELISA is 0.875. Analysis of suPAR level was handled by trained medical students according to the manufacturer's instructions, available on-site full-time for non-stop inclusion of eligible subjects. All suPAR levels were analyzed as quickly as possible and always within two hours following blood sampling and immediately reported.
Information to Physicians
[0065] The suPAR level was presented to the attending physicians through the electronic systems LABKA, OPUS and Cetrea. LABKA II (v. 2.5.0.H2, Computer Sciences Corporation (CSC)) is the clinical laboratory information system used to request blood work and view results from laboratory analysis. OPUS (OPUS Arbejdsplads, v. 2.5.0.0, Computer Sciences Corporation (CSC)) is the electronic database of medical records. The emergency wards in the EDs are monitored by the Cetrea system, which is presented by several large screen monitors in the ED and presents a rough overview of the ward (patient data and status, possible diagnosis, route of admission) used by physicians and nurses. Prior to the study, all physicians working in the emergency department were informed in writing about the prognostic abilities of suPAR in unselected subjects, and in regard to specific diagnoses in the form of a review of published literature, as well as pocket cards providing unadjusted mortality rates from 10,000 subjects from similar EDs.
[0066] The participating doctors and nurses were informed that they should consider the high risk connected with increased suPAR levels, and clinical reconsideration was advised when encountering a subject with an unexplained high suPAR, in which case an individual intervention should be scheduled based on symptoms and objective findings for the particular clinical issue, for example referral to a specialist, follow-up consultation with general practitioner, positron emission tomography scan or other diagnostic procedures or scanning methods. On the other hand, a low suPAR should promote faster discharge. The doctors were informed of specific cut-of values with regard to suPAR and age and the mortality risk associated with those values (
[0067] For the sake of clarity, the information on the card, as shown in
[0069] Interpretation [0070] Elevated values are observed in pathological conditions and correlate with the patient's mortality risk. [0071] Highly elevated values (>9) are observed in patients with multiple chronic diseases and/or serious and life-threatening conditions like severe sepsis or seriously impaired organ function. Mortality risk is highly increased. [0072] Moderately elevated values (about 4-9) are, for example, observed in the following conditions: Infections, cancer, COPD, cardiovascular diseases, dementia, diabetes, hepatic and renal diseases. Mortality risk and readmission risk are increased. [0073] Low values (<3) indicate a good prognosis.
[0074] Comments [0075] The suPAR level should be considered in conjunction with medical history, clinical findings, and other paraclinical findings. [0076] If the suPAR level is elevated for no obvious reason, further investigation for an unacknowledged disease may be considered. [0077] A low suPAR level indicates a low mortality risk and a low risk of critical illness and may support a decision to discharge the subject.
suPAR Level and Mortality Risk
[0078] Subjects below the age of 70:
TABLE-US-00002 suPAR (ng/mL) 30 days 90 days All (n = 5925) 1.4% 2.5% 0-3 (n = 3852) 0.2% 0.5% 3-6 (n = 1661) 1.7% 3.4% 6-9 (n = 287) 7.3% 11.1% >9 (n = 169) 16.6% 23.1%
[0079] Subjects above the age of 70:
TABLE-US-00003 suPAR (ng/mL) 30 days 90 days All (n = 3666) 8.8% 15.3% 0-3 (n = 750) 2.3% 3.5% 3-6 (n = 1970) 5.3% 10.9% 6-9 (n = 567) 16.6% 28.1% >9 (n = 379) 27.7% 43.0% [0080] Source: The emergency departments at Hvidovre Hospital and HiHerod Hospital, Denmark n=9591.
[0081] To assess the quality of the data, and whether the physicians received and considered the suPAR level in the initial evaluation of subjects, a questionnaire was sent to 200 randomly selected physicians at the participating hospitals, asking: [0082] Did you see the suPAR level of your subject? [0083] Did you feel informed in the prognostic ability of suPAR? [0084] How often did you include suPAR in your combined assessment of your subject? [0085] How often did the suPAR level influence your clinical decision? [0086] How often were you surprised by a high suPAR level? [0087] How often were you surprised by a low suPAR level?
Data Collection
[0088] Results of blood sample analyses including suPAR level were obtained from the LABKA II database. Using the unique Danish central person registration number (CPR-number), demographic data and mortality were obtained from the Central Civil Registry where all residents in Denmark are registered. Data on admissions, discharges, and diagnoses were obtained from the National Patient Registry (NPR). NPR contains information coded according to the International Statistical Classification of Disease, 10th revision (ICD-10) on primary diagnosis of discharge (A-diagnosis) and comorbidity (B-diagnoses). Laboratory values were obtained through LABKA (the clinical laboratory information system research database in Northern and Central Denmark; Grann et al (2011) Clin. Epidemiol. 3, 133-138). In the data analysis, the suPAR level from the index admission was linked with the data above to examine the primary and secondary outcomes.
Statistical Analysis
[0089] Patients admitted in each intervention or control cycle were followed as a single cohort and data were analyzed as randomized. The two groups were assessed for comparability of the following variables: age, sex, and Charlson score. Differences in mean age of more than 5 years and/or an absolute Charlson Comorbidity Index score of 2 or more were adjusted for in the final analysis. Patient data were analyzed according to the arm of the trial to which the patient was admitted during index admission, according to the randomization scheme (Table 1) corresponding to the intention-to-treat principle. A weighted Cox model was used to compare mortality at 10 months after inclusion of the last subject. Subjects were censored if their first readmission was in the opposite group to their index admission. As this censoring is likely to be dependent censoring (a readmission is rarely a positive prognostic signal), we employed Inverse Probability of Censoring Weighting (IPCW) where subjects readmitted to their own treatment group were up-weighted to compensate. We employed stabilized weights such that the reweighted sample had the same implied sample size throughout follow-up. Due to the design, time since index admission was the only covariate that needs to be included in the weights. Reweighing was done for every two weeks of follow-up. We did not censor nor reweight for 2nd or later readmissions, since the weights would become highly unstable and it was not likely that the presence or absence of an initial suPAR measurement would be important for clinical decisions at this stage. Furthermore, a traditional intention-to-treat analysis was performed. Notable difference between the results of the two analysis strategies were considered critically. Kaplan-Meier plots were used to illustrate survival. Unpaired T-test was used to compare length of stay. P<0.05 was considered significant. Subgroup analysis of the following groups was performed: subjects aged 65 years and above, and patients discharged with diagnoses of surgical conditions, cancer, infections, and cardiovascular disease.
[0090] At follow-up (10 months after inclusion of last patient) the following data was collected from the central Danish Patient Registry: [0091] Contacts with the healthcare system (including all historical contacts) [0092] Information regarding admissions (date, time and place of admittance and discharge) [0093] Diagnoses (historical and in relation to index admission). [0094] Date of death or emigration
[0095] Diagnoses obtained from the national patient registry were coded with the ICD-10 system. The original chapters were used to group patients according to diagnoses. Primary diagnosis was used with construction subgroups, and both primary and secondary diagnoses will be used to calculate the Charlson score. The following will define the subgroups: Cancer: Chapter II: Neoplasms (COO-D48). Cardiovascular disease: Chapter IX (100-199). Infections: Chapter I: A00-699+J00-J22++N10-N11+N30-N31. Neurological disease: Chapter VI(G00-G99). Surgical conditions: Presence of surgical procedure code divided into different specialities (general, orthopedic, other).
EXAMPLE 4
[0096] The Negative Predictive Value of suPAR Aids in Discharge Decisions
[0097] Background: The TRIAGE 111-trial is a cross-over, cluster-randomized, parallel-group, prospective, interventional trial, with the hospitals as units of randomization and the patients as the units of analysis. The trial design has been published previously (Sandø A, Schultz M, Eugen-Olsen J, et al (2016) “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. 24(1):100. doi:10.1186/s13049-016-0290-8). We conducted the TRIAGE III-trial at the EDs of two large hospitals: Bispebjerg University Hospital and Herlev University Hospital, both located in the Capital Region of Denmark and with 70,000 and 85,000 annual admissions, respectively. By using cluster design and designating hospitals as the units of randomization, we ensured that unselected patients with different chronic- and acute diseases were included in both groups as well as a consecutive and full inclusion rate. The trial had five months of inclusion from Jan. 11, 2016 and ended as planned on Jun. 6, 2016 with a subsequent 10-month follow-up concluded on Apr. 6, 2017. The patients included are shown in
[0098] Aim of study: To determine whether providing the doctors and nurses in the ED with the patient suPAR value can affect the decision of “admit or discharge” and whether providing suPAR can lead to shorter hospital length of stay.
Methods:
[0099] suPAR levels were measured using the CE/IVD approved suPARnostic quick triage test and reader (ViroGates NS, Denmark). Data were acquired from the Danish National Patient Registry (NPR) and the Civil Registration System (CRS) at the end of follow-up (10 months after the last patient were included). All patient contacts are registered in the NPR and vital status is registered in the CRS. Data on blood tests, including plasma suPAR level, was extracted from the electronical hospital database “LABKA”. For inclusion in the trial, patients were required to have a contact in the NPR within six hours of registered blood tests in LABKA within the inclusion period and an age ≥16 years. Admissions at the pediatric, obstetric and gynaecological departments were not included. The index admission was defined as the first admission in the trial inclusion-period.
[0100] Analysis included all patients participating in the TRIAGE III trial and compared those who had a suPAR measurement (N=7,905) with those who did not (N=8,896). Differences were compared using student's T- and Wilcoxon tests. P<0.05 was considered statistically significant. Statistics were carried out using R version 1.0.136 (The R Foundation for Statistical Computing).
Outcomes
[0101] The endpoints for the negative predictive value of suPAR were: [0102] (I) Short admissions (<24 h) to the ED. Is there a difference in the number of patients discharged from hospital (stay shorter than 24 hours from Index) when comparing those patients who had their suPAR measured compared to those who did not? [0103] (II) Length of stay. Is there a difference in the length of hospital stay of patients when comparing those patients who had their suPAR measured compared to those who did not?
[0104] Results: During the study, 16801 patients were included. Mean age was 60 years (SD 20) and 47.8% were men. 7905 patients had a suPAR measurement at admission and 8896 patients did not have suPAR measured (controls) (
[0105] With regard to endpoint I, patients who had a suPAR measurement were significantly more often discharged within 24 hours compared to those without suPAR measurement (50.2% (3,966 patients) vs. 48.6% (4,317 patients), absolute difference: 1.6% (95% CI 0.08-3.12); P=0.039) (
[0106] With regard to endpoint II, patients with a suPAR measurement had a 6.5 hour shorter length of hospital stay compared to patients without suPAR measurement (4.31 days (7.35) vs. 4.58 days (9.37), difference: 0.27 days (95% CI 0.01-0.53), P=0.043) (
Mortality in Patients Discharged within 24 Hours
[0107] All-cause mortality within 30 days among early discharged patients occurred in 52 patients (1.3%) in the suPAR group and in 77 patients (1.8%) in the control group. The unadjusted Cox model found a trend towards lower mortality in the suPAR group compared to control: Hazard ratio (HR), 0.73; 95% confidence interval (CI) 0.52 to 1.04; P=0.084.
[0108] During the median 12-months of follow-up, 225 (5.7%) of the patients died, which was less than among early discharged patients in the control arm where 256 (6.7%) died during follow-up (P=0.05). In patients that were discharged within 24 hours, the AUC for predicting 30-day mortality was 0.92 (95% CI: 0.90-0.95)
Readmissions in Patients Discharged within 24 Hours
[0109] With regard to 30-day readmission, 336 (8.5%) patients in the suPAR group were readmitted, while 331 (7.7%) patients in the control group were readmitted, P=0.18. For 90-day readmission, 490 patients (12.4%) vs. 552 patients (12.8%) were readmitted in the suPAR group and control group, respectively (P=0.57).
[0110] Discussion: The study showed that knowledge of patient's suPAR level at the Emergency Department led to earlier discharged patients and overall shorter length of stay. Even though more patients were discharged in the suPAR group compared with controls, there was no difference with regard to readmissions or mortality. Thus, early discharge based on suPAR is safe and feasible. Improving patient flow and earlier discharge of patients where admission might not be necessary will benefit both patients in need of hospital treatment and low-risk patients who can be discharged without being exposed to the risks of hospitalization, such as in-hospital infections, loss of muscle mass and loss of personal income if the patient is working. For the hospital, the shorter admission observed in patients that had suPAR measured at admission (6 hours shorter in the suPAR arm), leads to economic savings.
[0111] The fact that the AUC of suPAR became very high among those early discharged shows that the doctors used the positive predictive value of suPAR and kept patients more than 24 hours in hospital if suPAR was elevated. The high AUC of 0.92 thus reflects that those early discharged were the low risk patients and those who were sent home to die (e.g. to hospice or retirement home).
EXAMPLE 5
[0112] Positive Predictive Value of suPAR
[0113] Background: suPAR has previously been shown to be a strong predictor of outcome in retrospective studies. However, it was unknown whether giving the doctors information on the suPAR level could alter the outcome/change the prognosis. In the TRIAGE III Intervention study, suPAR was measured at time of admission using the suPARnostic Quick Test in 7,905 patients. Comparison is made to the 8896 patients in the control arm (without suPAR measurement) (
[0114] Methods: suPAR levels were measured using the CE/IVD approved suPARnostic quick triage test and reader (ViroGates NS, Denmark). The discriminative ability of suPAR with regard to mortality at one and ten months was assessed by using area under the curve (AUC) for receiver operating characteristics (ROC).
[0115] P<0.05 was considered statistically significant. Statistics were performed in R version 1.0.136 (The R Foundation for Statistical Computing) and figures were created with Graphpad Prism, version 7.02.
Results:
[0116] suPAR and mortality. The median suPAR level of patients who survived was significantly lower than the suPAR level of patients who died during follow-up, both at 30 days (4.0 ng/ml (IQR 2.9-5.7) vs. 8.3 ng/ml (IQR 5.9-11.7), p<0.001) and 10 months (3.8 ng/ml (IQR 2.8-5.3) vs. 6.9 ng/ml (IQR 5.1-10.1), p<0.001). SuPAR had a high prognostic power for predicting 30-days and 10-months mortality (AUCs: 30 days: 0.83 (95% CI: 0.81-0.84); 10 months: 0.80 (95% CI: 0.79-0.82). In comparison with age and routine biomarkers, suPAR had superior prognostic power regarding mortality at all follow-up times (Table 2: AUC for suPAR and other routine biomarkers and age) (
TABLE-US-00004 TABLE 2 Area Under the Curve (AUC)for the routine measured biomarkers and age Mortality Mortality 30 days Mortality 90 days All follow-up Age 0.777 0.774 0.781 C-reactive 0.738 0.729 0.702 protein Hemoglobin 0.701 0.721 0.729 Sodium 0.582 0.597 0.604 Potassium 0.578 0.574 0.564 Albumin 0.777 0.763 0.732 Creatinine 0.622 0.607 0.604 Leucocytes 0.654 0.627 0.580 ALAT.sup.1 0.511 0.530 0.550 suPAR 0.835 0.815 0.802
Adding suPAR to Algorithm Significantly Improves Outcome Prediction .sup.1 Alanine aminotransferase
[0117] To determine whether suPAR provides an additional and independent value to a combined model of all predictive routine markers, two models were made: one without suPAR but containing all the variables found significant in Table 2, and another model including these variables and suPAR.
[0118] For the prediction of 30-day mortality, the first model (without suPAR) provides an AUC of 0.860 (95% CI 0.84-0.86). Addition of suPAR significantly improved this model, AUC 0.896 (95% CI 0.88-0.90), p=0.007. The increase in sensitivity and specificity can be seen in
[0119] Similarly, for the determination of 90-day mortality, the model without suPAR provided an AUC of 0.854 (95% CI: 0.84-0.85). When including suPAR, the model significantly improved to an AUC of 0.878 (95% CI: 0.86-0.88), p=0.001 (
Measuring suPAR at Admission and Difference in Mortality Between Patients with or without suPAR Measurement
[0120] With regard to mortality in the suPAR intervention arm versus the control, we observed a mortality rate of 13.9% in the intervention arm compared to 14.3% in the control arm corresponding to 36 fewer mortalities in the intervention arm. The difference in mortality between the suPAR Intervention arm and control arm was strongly observed at Bispebjerg Hospital, Copenhagen, Denmark. At Bispebjerg Hospital, 3451 patients were included in the suPAR intervention arm and 3569 in the control arm. During follow-up, 427 patients died in the suPAR intervention arm (12.4%) which was a significant lower mortality than was observed in the control arm (515 died (14.4%), p<0.05.
[0121] Discussion: In this study, it is shown that suPAR is superior to other biomarkers with regard to outcome prediction compared with other investigated biomarkers, including a combined model of commonly used routine blood tests, in predicting short-term mortality. It is of interest that suPAR, in contrast to other biomarkers, is stronger than age in prediction of outcome. Also, adding suPAR to an algorithm of all the routine biomarkers significantly improved the prediction of both 30- and 90-day mortality. With regard to prevention of mortality, less mortality was observed in the intervention arm compared with the control arm. The effect of informing the doctors of suPAR level was of most value in patients with well-functioning clinical signs, e.g. in those triaged in the low risk category or having a low Early warning score (EWS or NEWS) where a severe disease, if present, is not recognised without the suPAR measurement.
[0122] The prognostic abilities of suPAR have been studied retrospectively before, and the biomarker has been shown to be associated with risk of mortality and adverse events. However, previous studies have not investigated the clinical impact of interventions on patients when giving the doctors “real time” information on the suPAR level while the patient was present in the ED. Hence, it was until now unknown whether knowledge of suPAR while the patient is present can change the outcome of the patient.
[0123] This study shows for the first time that knowledge of suPAR led to more early discharges in the Intervention arm compared with control. With regard to mortality in those early discharged, fewer patients died in the intervention arm compared with control, demonstrating that both the negative and positive predictive value of providing “real time” suPAR levels to the doctors and nurses aids in better admission and discharge decisions in the Emergency Departments.