| Title |
Improvement in Cardiovascular Risk Prediction with Electronic Health Records
|
|---|---|
| Published in |
Journal of Cardiovascular Translational Research, March 2016
|
| DOI | 10.1007/s12265-016-9687-z |
| Pubmed ID | |
| Authors |
Mindy M. Pike, Paul A. Decker, Nicholas B. Larson, Jennifer L. St. Sauver, Paul Y. Takahashi, Véronique L. Roger, Walter A. Rocca, Virginia M. Miller, Janet E. Olson, Jyotishman Pathak, Suzette J. Bielinski |
| Abstract |
The aim of this study was to compare the QRISKII, an electronic health data-based risk score, to the Framingham Risk Score (FRS) and atherosclerotic cardiovascular disease (ASCVD) score. Risk estimates were calculated for a cohort of 8783 patients, and the patients were followed up from November 29, 2012, through June 1, 2015, for a cardiovascular disease (CVD) event. During follow-up, 246 men and 247 women had a CVD event. Cohen's kappa statistic for the comparison of the QRISKII and FRS was 0.22 for men and 0.23 for women, with the QRISKII classifying more patients in the higher-risk groups. The QRISKII and ASCVD were more similar with kappa statistics of 0.49 for men and 0.51 for women. The QRISKII shows increased discrimination with area under the curve (AUC) statistics of 0.65 and 0.71, respectively, compared to the FRS (0.59 and 0.66) and ASCVD (0.63 and 0.69). These results demonstrate that incorporating additional data from the electronic health record (EHR) may improve CVD risk stratification. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 4 | 50% |
| United States | 2 | 25% |
| Spain | 1 | 13% |
| Unknown | 1 | 13% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 38% |
| Members of the public | 3 | 38% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
| Practitioners (doctors, other healthcare professionals) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 1% |
| Switzerland | 1 | 1% |
| Unknown | 67 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 15 | 22% |
| Student > Bachelor | 9 | 13% |
| Student > Ph. D. Student | 8 | 12% |
| Student > Master | 8 | 12% |
| Student > Doctoral Student | 5 | 7% |
| Other | 12 | 17% |
| Unknown | 12 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 33% |
| Computer Science | 9 | 13% |
| Nursing and Health Professions | 3 | 4% |
| Biochemistry, Genetics and Molecular Biology | 3 | 4% |
| Engineering | 3 | 4% |
| Other | 11 | 16% |
| Unknown | 17 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 11. 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 25 January 2018.
All research outputs
#2,762,431
of 22,856,968 outputs
Outputs from Journal of Cardiovascular Translational Research
#48
of 576 outputs
Outputs of similar age
#45,603
of 300,116 outputs
Outputs of similar age from Journal of Cardiovascular Translational Research
#3
of 10 outputs
Altmetric has tracked 22,856,968 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 576 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 91% 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 300,116 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 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 7 of them.