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External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement—a protocol for a systematic review

Overview of attention for article published in Systematic Reviews, December 2017
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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 (82nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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1 blog
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2 X users

Citations

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2 Dimensions

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38 Mendeley
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Title
External validation of type 2 diabetes computer simulation models: definitions, approaches, implications and room for improvement—a protocol for a systematic review
Published in
Systematic Reviews, December 2017
DOI 10.1186/s13643-017-0664-7
Pubmed ID
Authors

Katherine Ogurtsova, Thomas L. Heise, Ute Linnenkamp, Charalabos-Markos Dintsios, Stefan K. Lhachimi, Andrea Icks

Abstract

Type 2 diabetes mellitus (T2DM), a highly prevalent chronic disease, puts a large burden on individual health and health care systems. Computer simulation models, used to evaluate the clinical and economic effectiveness of various interventions to handle T2DM, have become a well-established tool in diabetes research. Despite the broad consensus about the general importance of validation, especially external validation, as a crucial instrument of assessing and controlling for the quality of these models, there are no systematic reviews comparing such validation of diabetes models. As a result, the main objectives of this systematic review are to identify and appraise the different approaches used for the external validation of existing models covering the development and progression of T2DM. We will perform adapted searches by applying respective search strategies to identify suitable studies from 14 electronic databases. Retrieved study records will be included or excluded based on predefined eligibility criteria as defined in this protocol. Among others, a publication filter will exclude studies published before 1995. We will run abstract and full text screenings and then extract data from all selected studies by filling in a predefined data extraction spreadsheet. We will undertake a descriptive, narrative synthesis of findings to address the study objectives. We will pay special attention to aspects of quality of these models in regard to the external validation based upon ISPOR and ADA recommendations as well as Mount Hood Challenge reports. All critical stages within the screening, data extraction and synthesis processes will be conducted by at least two authors. This protocol adheres to PRISMA and PRISMA-P standards. The proposed systematic review will provide a broad overview of the current practice in the external validation of models with respect to T2DM incidence and progression in humans built on simulation techniques. PROSPERO CRD42017069983 .

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X Demographics

The data shown below were collected from the profiles of 2 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 18%
Student > Master 6 16%
Student > Ph. D. Student 6 16%
Student > Doctoral Student 4 11%
Professor 2 5%
Other 3 8%
Unknown 10 26%
Readers by discipline Count As %
Medicine and Dentistry 11 29%
Nursing and Health Professions 3 8%
Business, Management and Accounting 2 5%
Biochemistry, Genetics and Molecular Biology 2 5%
Psychology 2 5%
Other 5 13%
Unknown 13 34%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 12 January 2018.
All research outputs
#3,574,420
of 23,015,156 outputs
Outputs from Systematic Reviews
#648
of 2,006 outputs
Outputs of similar age
#77,835
of 441,864 outputs
Outputs of similar age from Systematic Reviews
#24
of 56 outputs
Altmetric has tracked 23,015,156 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 2,006 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.8. This one has gotten more attention than average, scoring higher than 67% 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 441,864 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 82% of its contemporaries.
We're also able to compare this research output to 56 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 57% of its contemporaries.