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Mendeley readers
Attention Score in Context
| Title |
Clinical Utility of a Plasma Protein Classifier for Indeterminate Lung Nodules
|
|---|---|
| Published in |
Lung, September 2015
|
| DOI | 10.1007/s00408-015-9800-0 |
| Pubmed ID | |
| Authors |
Anil Vachani, Zane Hammoud, Steven Springmeyer, Neri Cohen, Dao Nguyen, Christina Williamson, Sandra Starnes, Stephen Hunsucker, Scott Law, Xiao-Jun Li, Alexander Porter, Paul Kearney |
| Abstract |
Evaluation of indeterminate pulmonary nodules is a complex challenge. Most are benign but frequently undergo invasive and costly procedures to rule out malignancy. A plasma protein classifier was developed that identifies likely benign nodules that can be triaged to CT surveillance to avoid unnecessary invasive procedures. The clinical utility of this classifier was assessed in a prospective-retrospective analysis of a study enrolling 475 patients with nodules 8-30 mm in diameter who had an invasive procedure to confirm diagnosis at 12 sites. Using this classifier, 32.0 % (CI 19.5-46.7) of surgeries and 31.8 % (CI 20.9-44.4) of invasive procedures (biopsy and/or surgery) on benign nodules could have been avoided. Patients with malignancy triaged to CT surveillance by the classifier would have been 24.0 % (CI 19.2-29.4). This rate is similar to that described in clinical practices (24.5 % CI 16.2-34.4). This study demonstrates the clinical utility of a non-invasive blood test for pulmonary nodules. |
Mendeley readers
The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 42 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 17% |
| Student > Ph. D. Student | 6 | 14% |
| Student > Master | 5 | 12% |
| Other | 4 | 10% |
| Student > Bachelor | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 13 | 31% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 17% |
| Medicine and Dentistry | 6 | 14% |
| Biochemistry, Genetics and Molecular Biology | 4 | 10% |
| Computer Science | 3 | 7% |
| Chemistry | 2 | 5% |
| Other | 5 | 12% |
| Unknown | 15 | 36% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 30 August 2018.
All research outputs
#2,285,413
of 22,835,198 outputs
Outputs from Lung
#49
of 885 outputs
Outputs of similar age
#30,304
of 245,080 outputs
Outputs of similar age from Lung
#4
of 26 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 885 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done particularly well, scoring higher than 94% 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 245,080 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 87% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.