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Delirium prediction in the intensive care unit: comparison of two delirium prediction models

Overview of attention for article published in Critical Care, May 2018
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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100 X users
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1 Facebook page
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1 Google+ user

Citations

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51 Dimensions

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160 Mendeley
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Title
Delirium prediction in the intensive care unit: comparison of two delirium prediction models
Published in
Critical Care, May 2018
DOI 10.1186/s13054-018-2037-6
Pubmed ID
Authors

Annelies Wassenaar, Lisette Schoonhoven, John W. Devlin, Frank M. P. van Haren, Arjen J. C. Slooter, Philippe G. Jorens, Mathieu van der Jagt, Koen S. Simons, Ingrid Egerod, Lisa D. Burry, Albertus Beishuizen, Joaquim Matos, A. Rogier T. Donders, Peter Pickkers, Mark van den Boogaard

Abstract

Accurate prediction of delirium in the intensive care unit (ICU) may facilitate efficient use of early preventive strategies and stratification of ICU patients by delirium risk in clinical research, but the optimal delirium prediction model to use is unclear. We compared the predictive performance and user convenience of the prediction  model for delirium (PRE-DELIRIC) and early prediction model for delirium (E-PRE-DELIRIC) in ICU patients and determined the value of a two-stage calculation. This 7-country, 11-hospital, prospective cohort study evaluated consecutive adults admitted to the ICU who could be reliably assessed for delirium using the Confusion Assessment Method-ICU or the Intensive Care Delirium Screening Checklist. The predictive performance of the models was measured using the area under the receiver operating characteristic curve. Calibration was assessed graphically. A physician questionnaire evaluated user convenience. For the two-stage calculation we used E-PRE-DELIRIC immediately after ICU admission and updated the prediction using PRE-DELIRIC after 24 h. In total 2178 patients were included. The area under the receiver operating characteristic curve was significantly greater for PRE-DELIRIC (0.74 (95% confidence interval 0.71-0.76)) compared to E-PRE-DELIRIC (0.68 (95% confidence interval 0.66-0.71)) (z score of - 2.73 (p < 0.01)). Both models were well-calibrated. The sensitivity improved when using the two-stage calculation in low-risk patients. Compared to PRE-DELIRIC, ICU physicians (n = 68) rated the E-PRE-DELIRIC model more feasible. While both ICU delirium prediction models have moderate-to-good performance, the PRE-DELIRIC model predicts delirium better. However, ICU physicians rated the user convenience of E-PRE-DELIRIC superior to PRE-DELIRIC. In low-risk patients the delirium prediction further improves after an update with the PRE-DELIRIC model after 24 h. ClinicalTrials.gov, NCT02518646 . Registered on 21 July 2015.

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 160 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 160 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 20 13%
Other 18 11%
Student > Master 18 11%
Student > Ph. D. Student 14 9%
Researcher 12 8%
Other 30 19%
Unknown 48 30%
Readers by discipline Count As %
Medicine and Dentistry 47 29%
Nursing and Health Professions 28 18%
Neuroscience 7 4%
Business, Management and Accounting 6 4%
Agricultural and Biological Sciences 2 1%
Other 21 13%
Unknown 49 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 59. 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 18 June 2019.
All research outputs
#728,549
of 25,492,047 outputs
Outputs from Critical Care
#515
of 6,572 outputs
Outputs of similar age
#16,165
of 340,716 outputs
Outputs of similar age from Critical Care
#15
of 87 outputs
Altmetric has tracked 25,492,047 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,572 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.8. This one has done particularly well, scoring higher than 92% 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 340,716 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% 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 83% of its contemporaries.