| Title |
A nomogramic model based on clinical and laboratory parameters at admission for predicting the survival of COVID-19 patients
|
|---|---|
| Published in |
BMC Infectious Diseases, November 2020
|
| DOI | 10.1186/s12879-020-05614-2 |
| Pubmed ID | |
| Authors |
Xiaojun Ma, Huifang Wang, Junwei Huang, Yan Geng, Shuqi Jiang, Qiuping Zhou, Xuan Chen, Hongping Hu, Weifeng Li, Chengbin Zhou, Xinglin Gao, Na Peng, Yiyu Deng |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Saudi Arabia | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 88 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 88 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 11% |
| Researcher | 8 | 9% |
| Student > Bachelor | 8 | 9% |
| Other | 7 | 8% |
| Student > Ph. D. Student | 5 | 6% |
| Other | 12 | 14% |
| Unknown | 38 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 20 | 23% |
| Nursing and Health Professions | 6 | 7% |
| Psychology | 3 | 3% |
| Agricultural and Biological Sciences | 2 | 2% |
| Arts and Humanities | 2 | 2% |
| Other | 15 | 17% |
| Unknown | 40 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 15 November 2022.
All research outputs
#4,051,209
of 23,114,117 outputs
Outputs from BMC Infectious Diseases
#1,295
of 7,755 outputs
Outputs of similar age
#108,301
of 507,181 outputs
Outputs of similar age from BMC Infectious Diseases
#34
of 174 outputs
Altmetric has tracked 23,114,117 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,755 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.3. This one has done well, scoring higher than 83% 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 507,181 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 78% of its contemporaries.
We're also able to compare this research output to 174 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.