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Dive into the research topics where Sandra N. Stapel is active.

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Featured researches published by Sandra N. Stapel.


European Journal of Clinical Nutrition | 2018

Bioelectrical impedance analysis-derived phase angle at admission as a predictor of 90-day mortality in intensive care patients

Sandra N. Stapel; W.G. Looijaard; I. Dekker; Armand R. J. Girbes; Peter J.M. Weijs; Heleen M. Oudemans-van Straaten

Background/ObjectivesA low bioelectrical impedance analysis (BIA)-derived phase angle (PA) predicts morbidity and mortality in different patient groups. An association between PA and long-term mortality in ICU patients has not been demonstrated before. The purpose of the present study was to determine whether PA on ICU admission independently predicts 90-day mortality.Subjects/ methodsThis prospective observational study was performed in a mixed university ICU. BIA was performed in 196 patients within 24 h of ICU admission. To test the independent association between PA and 90-day mortality, logistic regression analysis was performed using the APACHE IV predicted mortality as confounder. The optimal cutoff value of PA for mortality prediction was determined by ROC curve analysis. Using this cutoff value, patients were categorized into low or normal PA group and the association with 90-day mortality was tested again.ResultsThe PA of survivors was higher than of the non-survivors (5.0° ± 1.3° vs. 4.1° ± 1.2°, p < 0.001). The area under the ROC curve of PA for 90-day mortality was 0.70 (CI 0.59–0.80). PA was associated with 90-day mortality (OR = 0.56, CI: 0.38–0.77, p = 0.001) on univariate logistic regression analysis and also after adjusting for BMI, gender, age, and APACHE IV on multivariable logistic regression (OR = 0.65, CI: 0.44–0.96, p = 0.031). A PA < 4.8° was an independent predictor of 90-day mortality (adjusted OR = 3.65, CI: 1.34–9.93, p = 0.011).ConclusionsPhase angle at ICU admission is an independent predictor of 90-day mortality. This biological marker can aid in long-term mortality risk assessment of critically ill patients.


Critical Care | 2017

VCO2-derived energy expenditure: do not throw the baby out with the bath water!

Sandra N. Stapel; Paul W.G. Elbers; Heleen M. Oudemans-van Straaten

With great interest we read the retrospective study performed by Oshima et al. [1] evaluating whether VCO2based energy expenditure (EE-VCO2) could be considered as an alternative to EE measured by indirect calorimetry. This study followed several prospective studies reporting good agreement between EE-VCO2 and EE measured by indirect calorimetry [2, 3]. Indeed, in their retrospective cohort of 278 mechanically ventilated patients, the authors found a low bias of −48 kcal/day for EE-VCO2, when calculated with a fixed respiratory quotient (RQ) of 0.85. They reported 5%-accuracy rates of 46% and 10%accuracy rates of 77% for EE-VCO2. This indicates that EE-VCO2 is unreliable in some patients, likely due to extreme RQs or to high ventilator rates as observed in young children [4]. The weak spot of using EE-VCO2 is that an RQ has to be assumed in order to derive the unknown oxygen consumption (VO2) needed to calculate EE according to the Weir formula: EE(kcal/day) = 1.44 × (3.94 × VO2(mL/min) + 1.11 ×VCO2(mL/min)). However, despite high 10%-accuracy rates, the authors considered a 10% difference in measured and calculated EE clinically unacceptable and concluded that EE-VCO2 should not be considered as an alternative to EE measured by indirect calorimetry. First and foremost, we agree with the authors that indirect calorimetry remains the gold standard for assessment of EE in mechanically ventilated patients. However, we regret that the authors failed to mention that EE-VCO2 should be considered as the best alternative for clinicians not having access to indirect calorimetry. Unfortunately, few units have indirect calorimetry available and, more importantly, the most validated system (Deltatrac) is no longer being manufactured and new devices are not accurate [5]. Many ICU clinicians still rely on predictive equations that have repeatedly proven to be inaccurate, leading to deleterious overand underfeeding. The results of the Oshima study underscore findings in prospective studies in ICU patients that EE-VCO2 has good accuracy and is superior to predictive equations [2, 3]. Furthermore, when using built-in capnographs and flow meters, VCO2 is available from the ventilator and EE-VCO2 can be used to assess EE continuously. Continuous measurement is important because EE varies over the day and during ICU stay. This is an advantage of EE-VO2 over the short-term EE measurements by indirect calorimetry. Therefore, awaiting new, affordable, and accurate indirect calorimeters, EE-VCO2 appears to be the best alternative in spite of its known limitations. Thus, the use of EE-VCO2 assuming an RQ of 0.85, rather than applying predictive equations, is currently recommended to reduce overand underfeeding.


Clinical Nutrition | 2015

SUN-PP072: High Protein Feeding is Beneficial for Older Sarcopenic ICU Patients

W.G. Looijaard; Sandra N. Stapel; H.M. Oudemans-van Straaten; Peter J.M. Weijs

of their body weight. Logistic regression analysis found that absence of enteral feeding was a risk factor for infectious complications: odds ratio (OR) = 3.8; 95% confidence interval (CI): 1.64 8.79; P= 0.0018; and a risk factor for ICU mortality OR = 2.97; 95%CI 1.02 8.67; P= 0.045. Conclusion: Although the studies and guidelines showed that patients with acute severe pancreatitis should begin EN early, in our clinical practice we still do not use routinely EN in these patients. Failure to use the gastrointestinal (GI) tract in patients with severe acute pancreatitis leads to greater incidence of infectious complications and ICU mortality.


Journal of Parenteral and Enteral Nutrition | 2012

Optimal Protein and Energy Nutrition Decreases Mortality in Mechanically Ventilated, Critically Ill Patients: A Prospective Observational Cohort Study

Peter J.M. Weijs; Sandra N. Stapel; Sabine Dorine Willemine de Groot; Ronald H. Driessen; Evelien de Jong; Armand R. J. Girbes; Rob J. M. Strack van Schijndel; Albertus Beishuizen


Critical Care | 2014

Low skeletal muscle area is a risk factor for mortality in mechanically ventilated critically ill patients.

Peter J.M. Weijs; W.G. Looijaard; I. Dekker; Sandra N. Stapel; Armand Rj Girbes; Heleen M. Oudemans-van Straaten; Albertus Beishuizen


Critical Care | 2015

Ventilator-derived carbon dioxide production to assess energy expenditure in critically ill patients: proof of concept

Sandra N. Stapel; Harm-Jan de Grooth; Hoda Alimohamad; Paul Elbers; Armand R. J. Girbes; Peter J.M. Weijs; Heleen M. Oudemans-van Straaten


Critical Care | 2016

Skeletal muscle quality as assessed by CT-derived skeletal muscle density is associated with 6-month mortality in mechanically ventilated critically ill patients

W.G. Looijaard; I. Dekker; Sandra N. Stapel; Armand R. J. Girbes; Jos W. R. Twisk; Heleen M. Oudemans-van Straaten; Peter J.M. Weijs


Clinical Nutrition | 2017

MON-P021: Stepwise Increase in Protein Delivery in the First 14 Days of Admission is Associated with Improved 6-Month Outcome in Sarcopenic Critically Ill Patients

W.G. Looijaard; I. Dekker; Sandra N. Stapel; H. Oudemans; Peter J.M. Weijs


Clinical Nutrition | 2015

OR006: The Relationship Between Bia- and CT-Derived Muscle Mass in Critically Ill Patients

W.G. Looijaard; Sandra N. Stapel; S. Remmelzwaal; I. Dekker; Peter J.M. Weijs; H.M. Oudemans-van Straaten


Clinical Nutrition | 2014

PP016-SUN: Outstanding abstract: Risk Assessment of Critically Ill Intensive Care Patients: Use of Bioelectrical Impedance

Sandra N. Stapel; Peter J.M. Weijs; I. Dekker; H.M. Oudemans-van Straaten

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Peter J.M. Weijs

VU University Medical Center

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W.G. Looijaard

VU University Medical Center

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I. Dekker

VU University Medical Center

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Armand R. J. Girbes

VU University Medical Center

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Armand Rj Girbes

VU University Medical Center

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Evelien de Jong

VU University Medical Center

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Harm-Jan de Grooth

VU University Medical Center

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