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The relationship between serum potassium, potassium variability and in-hospital mortality in critically ill patients and a before-after analysis on the impact of computer-assisted potassium control

Overview of attention for article published in Critical Care, December 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • Average Attention Score compared to outputs of the same age and source

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12 X users
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1 Google+ user

Citations

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53 Dimensions

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84 Mendeley
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Title
The relationship between serum potassium, potassium variability and in-hospital mortality in critically ill patients and a before-after analysis on the impact of computer-assisted potassium control
Published in
Critical Care, December 2015
DOI 10.1186/s13054-014-0720-9
Pubmed ID
Authors

Lara Hessels, Miriam Hoekstra, Lisa J Mijzen, Mathijs Vogelzang, Wim Dieperink, Annemieke Oude Lansink, Maarten W Nijsten

Abstract

IntroductionThe relationship between potassium regulation and outcome is not known. Our first aim was to determine the relationship between potassium levels and variability in ICU stay and outcome. The second aim was to evaluate the impact of a computer-assisted potassium regulation protocol.MethodsWe performed a retrospective before-after study including all patients >15 years admitted to the ICU of our university teaching hospital for more than 24 hours between 2002 and 2011. Potassium control was fully integrated with computerized glucose control (GRIP-II). The potassium metrics that we determined included mean potassium, potassium variability (defined as the standard deviation of all potassium levels), percentage of ICU-time below and above the reference range (3.5 through 5.0 mmol/L). These metrics were determined for the first ICU day (early phase) and the subsequent ICU days (late phase, that is day 2 to day 7). We also compared potassium metrics and in-hospital mortality before and after GRIP-II was implemented in 2006.ResultsOf all 22,347 ICU admissions, 10,451 (47%) patients were included. A total of 206,987 potassium measurements were performed in these patients. 4,664 (45%) patients were regulated by GRIP-II. The overall in-hospital mortality was 22%. There was a U-shaped relationship between the potassium level and in-hospital mortality (P <0.001). Moreover, potassium variability was independently associated with outcome. After implementing GRIP-II, in the late phase the time below 3.5 mmol/l decreased from 9.2% to 3.9% and the time above 5.0 mmol/L decreased from 6.1% to 5.2% and potassium variability decreased from 0.31 to 0.26 mmol/L (all P <0.001). The overall decrease in hospital mortality from 23.3% before GRIP-II to 19.9% (P <0.001) after the introduction of GRIP-II was not related to a specific potassium subgroup.ConclusionsHypokalemia and hyperkalemia and potassium variability were independently associated with increased mortality. Computerized potassium control clearly resulted in improved potassium metrics.

X Demographics

X Demographics

The data shown below were collected from the profiles of 12 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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 1%
Netherlands 1 1%
Brazil 1 1%
Unknown 81 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 18%
Researcher 12 14%
Student > Bachelor 9 11%
Other 9 11%
Student > Master 8 10%
Other 17 20%
Unknown 14 17%
Readers by discipline Count As %
Medicine and Dentistry 48 57%
Nursing and Health Professions 6 7%
Pharmacology, Toxicology and Pharmaceutical Science 3 4%
Mathematics 2 2%
Biochemistry, Genetics and Molecular Biology 2 2%
Other 7 8%
Unknown 16 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 8. 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 January 2016.
All research outputs
#4,782,524
of 25,463,724 outputs
Outputs from Critical Care
#3,256
of 6,566 outputs
Outputs of similar age
#71,902
of 396,045 outputs
Outputs of similar age from Critical Care
#271
of 466 outputs
Altmetric has tracked 25,463,724 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 6,566 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 gotten more attention than average, scoring higher than 50% 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 396,045 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 81% of its contemporaries.
We're also able to compare this research output to 466 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.