Robert Entjes
A5066569849- Sepsis Diagnosis and Treatment
- Respiratory Support and Mechanisms
- Machine Learning in Healthcare
- Intensive Care Unit Cognitive Disorders
- COVID-19 Clinical Research Studies
- Emergency and Acute Care Studies
- Coronary Interventions and Diagnostics
- Family and Patient Care in Intensive Care Units
- Non-Invasive Vital Sign Monitoring
- Cardiovascular Disease and Adiposity
- Chronic Disease Management Strategies
- Nosocomial Infections in ICU
- Central Venous Catheters and Hemodialysis
- Advanced Causal Inference Techniques
- Chronic Obstructive Pulmonary Disease (COPD) Research
- Cardiac Imaging and Diagnostics
- COVID-19 diagnosis using AI
- Acute Myocardial Infarction Research
- COVID-19 and healthcare impacts
Reinier de Graaf Hospital
2022
Admiraal De Ruyter Ziekenhuis
2021-2022
Catharina Ziekenhuis
2011
Radboud University Nijmegen
2011
The Coronavirus disease 2019 (COVID-19) pandemic has underlined the urgent need for reliable, multicenter, and full-admission intensive care data to advance our understanding of course investigate potential treatment strategies. In this study, we present Dutch Data Warehouse (DDW), first multicenter electronic health record (EHR) database with from critically ill COVID-19 patients.
Determining the optimal timing for extubation can be challenging in intensive care. In this study, we aim to identify predictors failure critically ill patients with COVID-19.We used highly granular data from 3464 adult COVID multicenter Dutch Data Warehouse, including demographics, clinical observations, medications, fluid balance, laboratory values, vital signs, and life support devices. All intubated at least one attempt were eligible analysis. Transferred patients, admitted less than 24...
For mechanically ventilated critically ill COVID-19 patients, prone positioning has quickly become an important treatment strategy, however, is labor intensive and comes with potential adverse effects. Therefore, identifying which intubated patients will benefit may help allocate resources. From the multi-center Dutch Data Warehouse of ICU from 25 hospitals, we selected all 3619 episodes in 1142 invasively patients. We excluded longer than 24 h. Berlin ARDS criteria were not formally...
To assess, validate and compare the predictive performance of models for in-hospital mortality COVID-19 patients admitted to intensive care unit (ICU) over two different waves infections. Our were built with high-granular Electronic Health Records (EHR) data versus less-granular registry data. Observational study all 19 Dutch ICUs participating in both national quality National Intensive Care Evaluation (NICE) EHR-based Data Warehouse (hereafter EHR). Multiple developed on from first 24 h...
Abstract Background The identification of risk factors for adverse outcomes and prolonged intensive care unit (ICU) stay in COVID-19 patients is essential prognostication, determining treatment intensity, resource allocation. Previous studies have determined on admission only, included a limited number predictors. Therefore, using data from the highly granular multicenter Dutch Data Warehouse, we developed machine learning models to identify ICU mortality, ventilator-free days ICU-free...
Background: Aims of this study were to investigate the prevalence and incidence catheter-related infection, identify risk factors, determine relation infection with mortality in critically ill COVID-19 patients. Methods: This was a retrospective cohort central venous catheters (CVCs) Eligible CVC insertions required an indwelling time at least 48 hours identified using full-admission electronic health record database. Risk factors logistic regression. Differences survival rates day 28...
The COVID-19 pandemic continues to overwhelm intensive care units (ICUs) worldwide, and improved prediction of mortality among patients could assist decision making in the ICU setting. In this work, we report on development validation a dynamic model specifically for critically ill discuss its potential utility ICU.
As coronavirus disease 2019 is a novel disease, treatment strategies continue to be debated. This provides the intensive care community with unique opportunity as population of patients requiring invasive mechanical ventilation relatively homogeneous compared other ICU populations. We hypothesize that novelty and uncertainty over its similarity noncoronavirus acute respiratory distress syndrome resulted in substantial practice variation between hospitals during first second waves...
Despite the recent progress in field of causal inference, to date there is no agreed upon methodology glean treatment effect estimation from observational data. The consequence on clinical practice that, when lacking results a randomized trial, medical personnel left without guidance what seems be effective real-world scenario. This article proposes pragmatic obtain preliminary but robust studies, provide front-line clinicians with degree confidence their strategy. Our study design applied...
Abstract Background: Identification of distinct clinical phenotypes in critically ill COVID-19 patients could improve understanding the disease heterogeneity and enable prognostic predictive enrichment facilitating more personalized treatment. However, previous attempts did not take into account temporal dynamics disease. By including dimension time, we aim to gain further insights COVID-19. Methods: We used highly granular data from 3202 adult COVID multicenter Dutch Data Warehouse that...