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Development and validation of a prehospital prediction model for acute traumatic coagulopathy

Overview of attention for article published in Critical Care, November 2016
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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 (84th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
20 tweeters

Citations

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19 Dimensions

Readers on

mendeley
61 Mendeley
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Title
Development and validation of a prehospital prediction model for acute traumatic coagulopathy
Published in
Critical Care, November 2016
DOI 10.1186/s13054-016-1541-9
Pubmed ID
Authors

Ithan D. Peltan, Ali Rowhani-Rahbar, Lisa K. Vande Vusse, Ellen Caldwell, Thomas D. Rea, Ronald V. Maier, Timothy R. Watkins

Abstract

Acute traumatic coagulopathy (ATC) is a syndrome of early, endogenous clotting dysfunction that afflicts up to 30% of severely injured patients, signaling an increased likelihood of all-cause and hemorrhage-associated mortality. To aid identification of patients within the likely therapeutic window for ATC and facilitate study of its mechanisms and targeted treatment, we developed and validated a prehospital ATC prediction model. Construction of a parsimonious multivariable logistic regression model predicting ATC - defined as an admission international normalized ratio >1.5 - employed data from 1963 severely injured patients admitted to an Oregon trauma system hospital between 2008 and 2012 who received prehospital care but did not have isolated head injury. The prediction model was validated using data from 285 severely injured patients admitted to a level 1 trauma center in Seattle, WA, USA between 2009 and 2013. The final Prediction of Acute Coagulopathy of Trauma (PACT) score incorporated age, injury mechanism, prehospital shock index and Glasgow Coma Score values, and prehospital cardiopulmonary resuscitation and endotracheal intubation. In the validation cohort, the PACT score demonstrated better discrimination (area under the receiver operating characteristic curve 0.80 vs. 0.70, p = 0.032) and likely improved calibration compared to a previously published prehospital ATC prediction score. Designating PACT scores ≥196 as positive resulted in sensitivity and specificity for ATC of 73% and 74%, respectively. Our prediction model uses routinely available and objective prehospital data to identify patients at increased risk of ATC. The PACT score could facilitate subject selection for studies of targeted treatment of ATC.

Twitter Demographics

The data shown below were collected from the profiles of 20 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Mexico 1 2%
Unknown 59 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 9 15%
Other 8 13%
Student > Ph. D. Student 8 13%
Student > Bachelor 8 13%
Student > Doctoral Student 6 10%
Other 13 21%
Unknown 9 15%
Readers by discipline Count As %
Medicine and Dentistry 36 59%
Nursing and Health Professions 6 10%
Agricultural and Biological Sciences 3 5%
Computer Science 2 3%
Psychology 1 2%
Other 5 8%
Unknown 8 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 02 December 2016.
All research outputs
#1,944,541
of 17,362,547 outputs
Outputs from Critical Care
#1,765
of 5,317 outputs
Outputs of similar age
#38,945
of 244,979 outputs
Outputs of similar age from Critical Care
#168
of 253 outputs
Altmetric has tracked 17,362,547 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,317 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.7. This one has gotten more attention than average, scoring higher than 66% 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 244,979 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 84% of its contemporaries.
We're also able to compare this research output to 253 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.