Automated Author ProfileÁ., Gil
Á., Gil
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: 0.7 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Background/Aims: We aimed to evaluate the use of a continuous metabolic syndrome (MetS) score and to assess the associations of this score with risk biomarkers of inflammation, endothelial damage and cardiovascular disease (CVD) in prepubertal children. Methods: A total of 677 prepubertal children (295 obese, 146 overweight, and 236 normal-weight) were recruited. MetS traits, markers of inflammation, endothelial damage and CVD risk were measured, and a continuous MetS score was calculated, consisting of the sum/5 of the standardised scores of the MetS components. Results: The continuous MetS score was significantly associated with active plasminogen activator inhibitor-1 (r = 0.406, p < 0.001), adiponectin (r = -0.212, p < 0.001), resistin (r = 0.263, p < 0.001), C-reactive protein (r = 0.254, p < 0.001), tumour necrosis factor alpha (r = 0.120, p = 0.003), myeloperoxidase (r = 0.188, p < 0.001) and sE-selectin (r = 0.278, p < 0.001). Children in the normal-weight, overweight and obese groups with MetS totalled 0 (0%), 1 (0.7%) and 24 (8.7%), respectively, whereas the at-risk children identified using the continuous MetS score in each group totalled 2 (0.85%), 17 (11.6%) and 167 (56.6%), respectively. Conclusions: The association of the continuous MetS score with specific risk biomarkers of inflammation, endothelial damage and CVD supports its use in the early identification of children at increased risk of metabolic dysfunction.
Authors
- Olza, J. ;
- Aguilera, C.M. ;
- Gil-Campos, M. ;
- Leis, R. ;
- Bueno, G. ;
- Valle, M. ;
- Cañete, R. ;
- Tojo, R. ;
- Moreno, L.A. ;
- Á., Gil
Background/Aims: We aimed to evaluate the use of a continuous metabolic syndrome (MetS) score and to assess the associations of this score with risk biomarkers of inflammation, endothelial damage and cardiovascular disease (CVD) in prepubertal children. Methods: A total of 677 prepubertal children (295 obese, 146 overweight, and 236 normal-weight) were recruited. MetS traits, markers of inflammation, endothelial damage and CVD risk were measured, and a continuous MetS score was calculated, consisting of the sum/5 of the standardised scores of the MetS components. Results: The continuous MetS score was significantly associated with active plasminogen activator inhibitor-1 (r = 0.406, p < 0.001), adiponectin (r = -0.212, p < 0.001), resistin (r = 0.263, p < 0.001), C-reactive protein (r = 0.254, p < 0.001), tumour necrosis factor alpha (r = 0.120, p = 0.003), myeloperoxidase (r = 0.188, p < 0.001) and sE-selectin (r = 0.278, p < 0.001). Children in the normal-weight, overweight and obese groups with MetS totalled 0 (0%), 1 (0.7%) and 24 (8.7%), respectively, whereas the at-risk children identified using the continuous MetS score in each group totalled 2 (0.85%), 17 (11.6%) and 167 (56.6%), respectively. Conclusions: The association of the continuous MetS score with specific risk biomarkers of inflammation, endothelial damage and CVD supports its use in the early identification of children at increased risk of metabolic dysfunction.
Authors
- Olza, J. ;
- Aguilera, C.M. ;
- Gil-Campos, M. ;
- Leis, R. ;
- Bueno, G. ;
- Valle, M. ;
- Cañete, R. ;
- Tojo, R. ;
- Moreno, L.A. ;
- Á., Gil