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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Computing limits on medicine risks based on collections of individual case reports
|
|---|---|
| Published in |
Theoretical Biology and Medical Modelling, March 2014
|
| DOI | 10.1186/1742-4682-11-15 |
| Pubmed ID | |
| Authors |
Ola Caster, G Niklas Norén, I Ralph Edwards |
| Abstract |
Quantifying a medicine's risks for adverse effects is crucial in assessing its value as a therapeutic agent. Rare adverse effects are often not detected until after the medicine is marketed and used in large and heterogeneous patient populations, and risk quantification is even more difficult. While individual case reports of suspected harm from medicines are instrumental in the detection of previously unknown adverse effects, they are currently not used for risk quantification. The aim of this article is to demonstrate how and when limits on medicine risks can be computed from collections of individual case reports. |
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 % |
|---|---|---|
| United Kingdom | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 3 | 27% |
| Lecturer > Senior Lecturer | 1 | 9% |
| Student > Ph. D. Student | 1 | 9% |
| Other | 1 | 9% |
| Student > Master | 1 | 9% |
| Other | 1 | 9% |
| Unknown | 3 | 27% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 6 | 55% |
| Agricultural and Biological Sciences | 1 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Unknown | 3 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 March 2014.
All research outputs
#14,777,143
of 22,749,166 outputs
Outputs from Theoretical Biology and Medical Modelling
#163
of 287 outputs
Outputs of similar age
#126,035
of 223,836 outputs
Outputs of similar age from Theoretical Biology and Medical Modelling
#4
of 10 outputs
Altmetric has tracked 22,749,166 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 287 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 41st percentile – i.e., 41% 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 223,836 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
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 6 of them.