↓ Skip to main content

Identification of major cardiovascular events in patients with diabetes using primary care data

Overview of attention for article published in BMC Health Services Research, April 2016
Altmetric Badge

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 (87th percentile)
  • High Attention Score compared to outputs of the same age and source (86th percentile)

Mentioned by

news
1 news outlet
twitter
9 X users

Citations

dimensions_citation
12 Dimensions

Readers on

mendeley
49 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Identification of major cardiovascular events in patients with diabetes using primary care data
Published in
BMC Health Services Research, April 2016
DOI 10.1186/s12913-016-1361-2
Pubmed ID
Authors

Koen Bernardus Pouwels, Jaco Voorham, Eelko Hak, Petra Denig

Abstract

Routine primary care data are increasingly being used for evaluation and research purposes but there are concerns about the completeness and accuracy of diagnoses and events captured in such databases. We evaluated how well patients with major cardiovascular disease (CVD) can be identified using primary care morbidity data and drug prescriptions. The study was conducted using data from 17,230 diabetes patients of the GIANTT database and Dutch Hospital Data register. To estimate the accuracy of the different measures, we analyzed the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) relative to hospitalizations and/or records with a diagnosis indicating major CVD, including ischaemic heart diseases and cerebrovascular events. Using primary care morbidity data, 43 % of major CVD hospitalizations could be identified. Adding drug prescriptions to the search increased the sensitivity up to 94 %. A proxy of at least one prescription of either a platelet aggregation inhibitor, vitamin k antagonist or nitrate could identify 85 % of patients with a history of major CVD recorded in primary care, with an NPV of 97 %. Using the same proxy, 57 % of incident major CVD recorded in primary or hospital care could be identified, with an NPV of 99 %. A substantial proportion of major CVD hospitalizations was not recorded in primary care morbidity data. Drug prescriptions can be used in addition to diagnosis codes to identify more patients with major CVD, and also to identify patients without a history of major CVD.

X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Unknown 48 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 6 12%
Student > Ph. D. Student 6 12%
Researcher 5 10%
Student > Bachelor 5 10%
Student > Doctoral Student 3 6%
Other 9 18%
Unknown 15 31%
Readers by discipline Count As %
Medicine and Dentistry 10 20%
Pharmacology, Toxicology and Pharmaceutical Science 7 14%
Nursing and Health Professions 4 8%
Economics, Econometrics and Finance 2 4%
Unspecified 1 2%
Other 7 14%
Unknown 18 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 27 April 2016.
All research outputs
#2,259,378
of 24,337,175 outputs
Outputs from BMC Health Services Research
#902
of 8,201 outputs
Outputs of similar age
#36,767
of 304,925 outputs
Outputs of similar age from BMC Health Services Research
#14
of 94 outputs
Altmetric has tracked 24,337,175 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,201 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.2. This one has done well, scoring higher than 88% 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 304,925 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 87% of its contemporaries.
We're also able to compare this research output to 94 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.