| Title |
Support of personalized medicine through risk-stratified treatment recommendations - an environmental scan of clinical practice guidelines
|
|---|---|
| Published in |
BMC Medicine, January 2013
|
| DOI | 10.1186/1741-7015-11-7 |
| Pubmed ID | |
| Authors |
Tsung Yu, Daniela Vollenweider, Ravi Varadhan, Tianjing Li, Cynthia Boyd, Milo A Puhan |
| Abstract |
Risk-stratified treatment recommendations facilitate treatment decision-making that balances patient-specific risks and preferences. It is unclear if and how such recommendations are developed in clinical practice guidelines (CPGs). Our aim was to assess if and how CPGs develop risk-stratified treatment recommendations for the prevention or treatment of common chronic diseases. |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United Kingdom | 1 | 1% |
| Spain | 1 | 1% |
| Australia | 1 | 1% |
| Unknown | 97 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 18 | 18% |
| Student > Master | 16 | 16% |
| Student > Ph. D. Student | 15 | 15% |
| Professor | 5 | 5% |
| Student > Postgraduate | 5 | 5% |
| Other | 16 | 16% |
| Unknown | 25 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 37 | 37% |
| Nursing and Health Professions | 6 | 6% |
| Biochemistry, Genetics and Molecular Biology | 4 | 4% |
| Engineering | 4 | 4% |
| Economics, Econometrics and Finance | 3 | 3% |
| Other | 17 | 17% |
| Unknown | 29 | 29% |
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 21 January 2013.
All research outputs
#3,506,525
of 22,691,736 outputs
Outputs from BMC Medicine
#1,865
of 3,400 outputs
Outputs of similar age
#37,374
of 282,271 outputs
Outputs of similar age from BMC Medicine
#55
of 75 outputs
Altmetric has tracked 22,691,736 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 3,400 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 43.6. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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 282,271 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 86% of its contemporaries.
We're also able to compare this research output to 75 others from the same source and published within six weeks on either side of this one. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.