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Do Risk Prediction Models for Postoperative Delirium Consider Patients’ Preoperative Medication Use?

Overview of attention for article published in Drugs & Aging, February 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (76th percentile)
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

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Title
Do Risk Prediction Models for Postoperative Delirium Consider Patients’ Preoperative Medication Use?
Published in
Drugs & Aging, February 2018
DOI 10.1007/s40266-018-0526-6
Pubmed ID
Authors

Gizat M. Kassie, Tuan A. Nguyen, Lisa M. Kalisch Ellett, Nicole L. Pratt, Elizabeth E. Roughead

Abstract

Medicines are potentially modifiable risk factors for postoperative delirium. However, the extent to which preoperative medicines are included in risk prediction models (RPMs) is unknown. This systematic review aimed to assess the extent of inclusion of preoperative medications in RPMs for postoperative delirium. Articles were systematically searched from MEDLINE, EMBASE and CINAHL using Medical Subject Headings (MeSH) where possible and keywords for postoperative delirium and prediction model. Studies published until May 2017 with a primary outcome of postoperative delirium that developed an RPM containing preoperative patient information were considered. Where a study had two cohorts, a derivation and a validation cohort, findings from the derivation cohort were extracted and reported. Eighteen prospective and one retrospective cohort studies were included for review. Of the 19 studies, only nine considered preoperative medication data, with medications appearing as predictor variables in five models. There was wide variability in the factors included in the final models, with the most frequent predictors being age and cognitive impairment, appearing in 13 (68%) and 11 (58%) RPMs, respectively. While medications are commonly cited risk factors for delirium, they are not adequately considered when developing RPMs. Future studies aiming to develop an RPM for postoperative delirium should include preoperative medication data as a potential predictor variable because of the modifiable nature of medication use and its impact on other factors commonly in models, such as cognition.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 44 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 44 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 23%
Researcher 8 18%
Student > Bachelor 3 7%
Other 3 7%
Student > Ph. D. Student 3 7%
Other 7 16%
Unknown 10 23%
Readers by discipline Count As %
Medicine and Dentistry 16 36%
Nursing and Health Professions 4 9%
Pharmacology, Toxicology and Pharmaceutical Science 3 7%
Psychology 2 5%
Computer Science 2 5%
Other 7 16%
Unknown 10 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 04 August 2018.
All research outputs
#5,159,720
of 25,208,845 outputs
Outputs from Drugs & Aging
#353
of 1,298 outputs
Outputs of similar age
#106,408
of 451,304 outputs
Outputs of similar age from Drugs & Aging
#8
of 22 outputs
Altmetric has tracked 25,208,845 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,298 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.2. This one has gotten more attention than average, scoring higher than 72% 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 451,304 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 76% of its contemporaries.
We're also able to compare this research output to 22 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.