Elderly Patiënts Clinical Trial
Official title:
Risk Stratification in Elderly Patients in the Emergency Department
Procedures for identification of high-risk elderly patients in the emergency department are
lacking.
We aim to identify early risk factors associated with an adverse outcome in elderly patients
who visit the emergency department (ED). Second, we aim to find practical tools to identify
those elderly patients who are at risk for an adverse outcome in an early stage (by applying
and testing triage and risk stratification scores, clinical impression and laboratory
results).
With the results of this study, we intend to develop a clinical prediction model to identify
older emergency department patients with an increased risk of adverse outcomes.
Background:
Elderly patients (≥65 years of age) constitute an increasing population in emergency
departments (EDs) in many countries. These patients are largely different from younger
patients and undoubtedly need different approaches in acute care. Commonly used triage
systems are not validated in elderly patients. We hypothesize that this factor contributes to
a lack of recognition of patients at risk for adverse events or death.
Aim of the study:
- At first, we will try to identify early risk factors associated with adverse outcome
such as age, the premorbid state (comorbidity, living status and cognitive/functional
state), medication use, vital signs, and number of previous visits to the ED.
- Secondly, we will investigate the discriminating power of several triage and risk
stratification scores. In our study, we will retrieve and validate the following triage
and risk stratification scores: The Manchester Triage System (MTS) triage score, the
Acute Physiology and Chronic Health Evaluation II (APACHE II) score and the
Identification of Seniors At Risk-Hospitalised Patients (ISAR-HP) score for all
hospitalized patients. Furthermore, we will calculate four well-known disease specific
stratification scores: The Glasgow-Blatchford Bleeding (GBS Score) for patients with an
upper gastrointestinal bleeding, the Abbreviated Mortality ED Sepsis (abbMEDS) score and
Sepsis-related Organ Failure Assessment (SOFA) score and the Confusion, Urea,
Respiration, Blood pressure, Age >65 years (CURB-65) score.
- Thirdly, we will investigate the predictive value of the clinical impression of
professionals (doctor/nurse) and the disease perception of patient/companion.
- Fourth, we will investigate the predictive value of laboratory tests (routine tests and
biomarkers like lactate, N-terminal pro-B-type natriuretic peptide (NT-pro-BNP),
high-sensitivity troponin (hs-TnT), procalcitonin (PCT) and d-dimer.
- At last, we intend to develop a clinical prediction model for short-term mortality and
test the predictive ability of this model for the other adverse outcomes/endpoints. This
model will be validated in an external cohort.
Study procedure:
The design is a multi-center prospective observational cohort study. The study will take
place in Zuyderland MC in Heerlen and Maastricht UMC+ in the Netherlands. On presentation to
the ED the patients will be given information about the study and informed consent will be
signed. The patient or family member/companion, the nurse and the doctor will be asked to
fill out a questionnaire in the ED (5 questions for patient/family and 9 questions for doctor
or nurse). These questions will be used for evaluation of the clinical impression of the
doctor/nurse and disease perception by the patient/companion. At the ED, 2 extra venous
samples and one arterial blood gas sample will be taken in patients participating in the
study in Zuyderland M.C. Blood gas analysis will take place immediately and the results will
be presented to the attending doctor. Analysis of the biomarkers from the venous blood
samples will take place after a few weeks and the results will be blinded in this study.
Routine laboratory test will be analyzed in both hospitals. During the days and weeks after
inclusion, data will be obtained from patients medical records. During the days and weeks
after inclusion, data will be obtained from patients medical records. All patients will be
followed up for 30 days and if possible for one year.
;