| Title |
Influence of ABCB1 and CYP3A5 gene polymorphisms on pharmacokinetics of apixaban in patients with atrial fibrillation and acute stroke
|
|---|---|
| Published in |
Pharmacogenomics and Personalized Medicine, March 2018
|
| DOI | 10.2147/pgpm.s157111 |
| Pubmed ID | |
| Authors |
Alexander Valerevich Kryukov, Dmitry Alekseevich Sychev, Denis Anatolevich Andreev, Kristina Anatolievna Ryzhikova, Elena Anatolievna Grishina, Anastasia Vladislavovna Ryabova, Mark Alekseevich Loskutnikov, Valeriy Valerevich Smirnov, Olga Dmitrievna Konova, Irina Andreevna Matsneva, Pavel Olegovich Bochkov |
X Demographics
The data shown below were collected from the profiles of 5 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 States | 3 | 60% |
| Italy | 1 | 20% |
| Japan | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
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 % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 16% |
| Student > Ph. D. Student | 8 | 16% |
| Researcher | 4 | 8% |
| Student > Postgraduate | 3 | 6% |
| Lecturer | 2 | 4% |
| Other | 6 | 12% |
| Unknown | 18 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 11 | 22% |
| Pharmacology, Toxicology and Pharmaceutical Science | 7 | 14% |
| Biochemistry, Genetics and Molecular Biology | 5 | 10% |
| Computer Science | 2 | 4% |
| Psychology | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 20 | 41% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 28 January 2020.
All research outputs
#8,413,871
of 25,748,735 outputs
Outputs from Pharmacogenomics and Personalized Medicine
#1
of 1 outputs
Outputs of similar age
#135,566
of 345,946 outputs
Outputs of similar age from Pharmacogenomics and Personalized Medicine
#1
of 1 outputs
Altmetric has tracked 25,748,735 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 1 research outputs from this source. They receive a mean Attention Score of 3.2. This one scored the same or higher as 0 of them.
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 345,946 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them