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.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Automated Decision Support for Drug-Induced Long QT.
|
|---|---|
| Published in |
South Dakota Medicine, March 2020
|
| Pubmed ID | |
| Authors |
Roxana A Lupu, Heidi Twedt, Sreekanth Chavour, Eric A Larson |
| Abstract |
Advancements in clinical informatics and translational genomics are changing the way we practice medicine. Automated decision support currently helps providers adjust prescribing patterns to reduce the likelihood of QT prolongation based upon drug-drug interaction. A similar approach is being explored for drug-gene interaction. Like many adverse drug reactions, QT prolongation can be influenced by variability in genetic factors. However, drug-induced QT prolongation can occur in the absence of any known ion channel gene abnormalities. We therefore review differences between congenital long QT syndrome and drug-induced long QT syndrome, and we underscore the need for decision support that integrates EKG data. |
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 States | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Practitioners (doctors, other healthcare professionals) | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 4 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 2 | 50% |
| Student > Doctoral Student | 1 | 25% |
| Unknown | 1 | 25% |
| Readers by discipline | Count | As % |
|---|---|---|
| Nursing and Health Professions | 1 | 25% |
| Business, Management and Accounting | 1 | 25% |
| Computer Science | 1 | 25% |
| Unknown | 1 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 11 March 2020.
All research outputs
#18,054,148
of 23,197,711 outputs
Outputs from South Dakota Medicine
#66
of 189 outputs
Outputs of similar age
#252,523
of 359,465 outputs
Outputs of similar age from South Dakota Medicine
#3
of 7 outputs
Altmetric has tracked 23,197,711 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 189 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one has gotten more attention than average, scoring higher than 59% 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 359,465 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.