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Multinational development and validation of an early prediction model for delirium in ICU patients

Overview of attention for article published in Intensive Care Medicine, April 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

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1 blog
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14 X users

Citations

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141 Dimensions

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233 Mendeley
Title
Multinational development and validation of an early prediction model for delirium in ICU patients
Published in
Intensive Care Medicine, April 2015
DOI 10.1007/s00134-015-3777-2
Pubmed ID
Authors

A. Wassenaar, M. van den Boogaard, T. van Achterberg, A. J. C. Slooter, M. A. Kuiper, M. E. Hoogendoorn, K. S. Simons, E. Maseda, N. Pinto, C. Jones, A. Luetz, A. Schandl, W. Verbrugghe, L. M. Aitken, F. M. P. van Haren, A. R. T. Donders, L. Schoonhoven, P. Pickkers

Abstract

Delirium incidence in intensive care unit (ICU) patients is high and associated with poor outcome. Identification of high-risk patients may facilitate its prevention. To develop and validate a model based on data available at ICU admission to predict delirium development during a patient's complete ICU stay and to determine the predictive value of this model in relation to the time of delirium development. Prospective cohort study in 13 ICUs from seven countries. Multiple logistic regression analysis was used to develop the early prediction (E-PRE-DELIRIC) model on data of the first two-thirds and validated on data of the last one-third of the patients from every participating ICU. In total, 2914 patients were included. Delirium incidence was 23.6 %. The E-PRE-DELIRIC model consists of nine predictors assessed at ICU admission: age, history of cognitive impairment, history of alcohol abuse, blood urea nitrogen, admission category, urgent admission, mean arterial blood pressure, use of corticosteroids, and respiratory failure. The area under the receiver operating characteristic curve (AUROC) was 0.76 [95 % confidence interval (CI) 0.73-0.77] in the development dataset and 0.75 (95 % CI 0.71-0.79) in the validation dataset. The model was well calibrated. AUROC increased from 0.70 (95 % CI 0.67-0.74), for delirium that developed <2 days, to 0.81 (95 % CI 0.78-0.84), for delirium that developed >6 days. Patients' delirium risk for the complete ICU length of stay can be predicted at admission using the E-PRE-DELIRIC model, allowing early preventive interventions aimed to reduce incidence and severity of ICU delirium.

X Demographics

X Demographics

The data shown below were collected from the profiles of 14 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 233 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Korea, Republic of 1 <1%
Denmark 1 <1%
Unknown 231 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 37 16%
Student > Ph. D. Student 28 12%
Researcher 20 9%
Student > Bachelor 17 7%
Other 15 6%
Other 54 23%
Unknown 62 27%
Readers by discipline Count As %
Medicine and Dentistry 74 32%
Nursing and Health Professions 45 19%
Neuroscience 8 3%
Psychology 6 3%
Agricultural and Biological Sciences 5 2%
Other 25 11%
Unknown 70 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 January 2022.
All research outputs
#2,124,719
of 22,882,389 outputs
Outputs from Intensive Care Medicine
#1,573
of 4,993 outputs
Outputs of similar age
#28,989
of 265,104 outputs
Outputs of similar age from Intensive Care Medicine
#9
of 87 outputs
Altmetric has tracked 22,882,389 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,993 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one has gotten more attention than average, scoring higher than 68% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 265,104 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 87 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.