Publications by authors named "Noortje Zelis"

Introduction: In the Netherlands, most emergency department (ED) patients are referred by a general practitioner (GP) or a hospital specialist. Early risk stratification during telephone referral could allow the physician to assess the severity of the patients' illness in the prehospital setting. We aim to assess the discriminatory value of the acute internal medicine (AIM) physicians' clinical intuition based on telephone referral of ED patients to predict short-term adverse outcomes, and to investigate on which information their predictions are based.

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Background: For most acute conditions, the phase prior to emergency department (ED) arrival is largely unexplored. However, this prehospital phase has proven an important part of the acute care chain (ACC) for specific time-sensitive conditions, such as stroke and myocardial infarction. For patients with undifferentiated complaints, exploration of the prehospital phase of the ACC may also offer a window of opportunity for improvement of care.

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Introduction: Prediction models for identifying emergency department (ED) patients at high risk of poor outcome are often not externally validated. We aimed to perform a head-to-head comparison of the discriminatory performance of several prediction models in a large cohort of ED patients.

Methods: In this retrospective study, we selected prediction models that aim to predict poor outcome and we included adult medical ED patients.

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Background: Data on hyperglycemia and glucose variability in relation to diabetes mellitus, either known or unknown in ICU-setting in COVID-19, are scarce. We prospectively studied daily glucose variables and mortality in strata of diabetes mellitus and glycosylated hemoglobin among mechanically ventilated COVID-19 patients.

Methods: We used linear-mixed effect models in mechanically ventilated COVID-19 patients to investigate mean and maximum difference in glucose concentration per day over time.

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Background: There is growing awareness that sex differences are associated with different patient outcomes in a variety of diseases. Studies investigating the effect of patient sex on sepsis-related mortality remain inconclusive and mainly focus on patients with severe sepsis and septic shock in the intensive care unit. We therefore investigated the association between patient sex and both clinical presentation and 30-day mortality in patients with the whole spectrum of sepsis severity presenting to the emergency department (ED) who were admitted to the hospital.

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Introduction: Coronavirus disease 2019 (COVID-19) has a high burden on the healthcare system. Prediction models may assist in triaging patients. We aimed to assess the value of several prediction models in COVID-19 patients in the emergency department (ED).

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Article Synopsis
  • The study aimed to assess the effectiveness of the RISE UP score in predicting 30-day mortality for older patients with COVID-19 in emergency departments.
  • A retrospective analysis was conducted using data from 642 adult patients diagnosed with COVID-19, revealing a 26% mortality rate within 30 days.
  • The RISE UP score demonstrated strong predictive capability, with lower scores indicating better outcomes and higher scores correlating with increased mortality and ICU admissions.
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Objective: Older emergency department (ED) patients are at high risk of mortality, and it is important to predict which patients are at highest risk. Biomarkers such as lactate, high-sensitivity cardiac troponin T (hs-cTnT), N-terminal pro-B-type natriuretic peptide (NT-proBNP), D-dimer and procalcitonin may be able to identify those at risk. We aimed to assess the discriminatory value of these biomarkers for 30-day mortality and other adverse outcomes.

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Background: Older emergency department (ED) patients often have complex problems and severe illnesses with a high risk of adverse outcomes. It is likely that these older patients are troubled with concerns, which might reflect their preferences and needs concerning medical care. However, data regarding this topic are lacking.

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Introduction: Early differentiation between emergency department (ED) patients with and without corona virus disease (COVID-19) is very important. Chest CT scan may be helpful in early diagnosing of COVID-19. We investigated the diagnostic accuracy of CT using RT-PCR for SARS-CoV-2 as reference standard and investigated reasons for discordant results between the two tests.

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Background/objectives: Currently, accurate clinical models that predict short-term mortality in older (≥ 65 years) emergency department (ED) patients are lacking. We aimed to develop and validate a prediction model for 30-day mortality in older ED patients that is easy to apply using variables that are readily available and reliably retrievable during the short phase of an ED stay.

Methods: Prospective multi-centre cohort study in older medical ED patients.

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Background: Older patients (≥65 years old) experience high rates of adverse outcomes after an emergency department (ED) visit. Reliable tools to predict adverse outcomes in this population are lacking. This manuscript comprises a study protocol for the Risk Stratification in the Emergency Department in Acutely Ill Older Patients (RISE UP) study that aims to identify predictors of adverse outcome (including triage- and risk stratification scores) and intends to design a feasible prediction model for older patients that can be used in the ED.

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Background: Older emergency department (ED) patients are at risk for adverse outcomes, however, it is hard to predict these. We aimed to assess the discriminatory value of clinical intuition, operationalized as disease perception, self-rated health and first clinical impression, including the 30-day surprise question (SQ: "Would I be surprised if this patient died in the next 30 days" of patients, nurses and physicians. Endpoints used to evaluate the discriminatory value of clinical intuition were short-term (30-day) mortality and other adverse outcomes (intensive/medium care admission, prolonged length of hospital stay, loss of independent living or 30-day readmission).

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