| Title |
A Novel Scoring System for Prediction of Disease Severity in COVID-19
|
|---|---|
| Published in |
Frontiers in Cellular and Infection Microbiology, June 2020
|
| DOI | 10.3389/fcimb.2020.00318 |
| Pubmed ID | |
| Authors |
Chi Zhang, Ling Qin, Kang Li, Qi Wang, Yan Zhao, Bin Xu, Lianchun Liang, Yanchao Dai, Yingmei Feng, Jianping Sun, Xuemei Li, Zhongjie Hu, Haiping Xiang, Tao Dong, Ronghua Jin, Yonghong Zhang |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 170 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 13% |
| Student > Bachelor | 17 | 10% |
| Student > Master | 16 | 9% |
| Other | 15 | 9% |
| Student > Doctoral Student | 14 | 8% |
| Other | 34 | 20% |
| Unknown | 52 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 45 | 26% |
| Nursing and Health Professions | 14 | 8% |
| Computer Science | 11 | 6% |
| Agricultural and Biological Sciences | 7 | 4% |
| Biochemistry, Genetics and Molecular Biology | 4 | 2% |
| Other | 33 | 19% |
| Unknown | 56 | 33% |
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 23 December 2021.
All research outputs
#17,719,424
of 22,753,345 outputs
Outputs from Frontiers in Cellular and Infection Microbiology
#4,042
of 6,348 outputs
Outputs of similar age
#282,480
of 396,506 outputs
Outputs of similar age from Frontiers in Cellular and Infection Microbiology
#135
of 198 outputs
Altmetric has tracked 22,753,345 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 6,348 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.3. This one is in the 24th percentile – i.e., 24% 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 396,506 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 24th percentile – i.e., 24% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 198 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.