Automated Author ProfileSales, Catherine M.
Tulane University
Sales, Catherine M.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.2 (sum of 1 dataset Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Background: Recent publications have emphasized the importance of a multidisciplinary strategy for maximum conservation and utilization of lung biopsy material for advanced testing, which may determine therapy. This paper quantifies the effect of a multidisciplinary strategy implemented to optimize and increase tissue volume in CT-guided transthoracic needle core lung biopsies. The strategy was three-pronged: (1) once there was confidence diagnostic tissue had been obtained and if safe for the patient, additional biopsy passes were performed to further increase volume of biopsy material, (2) biopsy material was placed in multiple cassettes for processing, and (3) all tissue ribbons were conserved when cutting blocks in the histology laboratory. This study quantifies the effects of strategies #1 and #2. Design: This retrospective analysis comparing CT-guided lung biopsies from 2007 and 2012 (before and after multidisciplinary approach implementation) was performed at a single institution. Patient medical records were reviewed and main variables analyzed include biopsy sample size, radiologist, number of blocks submitted, diagnosis, and complications. The biopsy sample size measured was considered to be directly proportional to tissue volume in the block. Results: Biopsy sample size increased 2.5 fold with the average total biopsy sample size increasing from 1.0 cm (0.9–1.1 cm) in 2007 to 2.5 cm (2.3–2.8 cm) in 2012 (P<0.0001). The improvement was statistically significant for each individual radiologist. During the same time, the rate of pneumothorax requiring chest tube placement decreased from 15% to 7% (P = 0.065). No other major complications were identified. The proportion of tumor within the biopsy material was similar at 28% (23%–33%) and 35% (30%–40%) for 2007 and 2012, respectively. The number of cases with at least two blocks available for testing increased from 10.7% to 96.4% (P<0.0001). Conclusions: The effect of this multidisciplinary strategy to CT-guided lung biopsies was effective in significantly increasing tissue volume and number of blocks available for advanced diagnostic testing.
Authors
- Ferguson, Philip E. ;
- Sales, Catherine M. ;
- Hodges, Dalton C. ;
- Sales, Elizabeth W.