Automated Author ProfileShireman, T.I.
Shireman, T.I.
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: 1.6 (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: Our understanding of the effectiveness of cardioprotective medications in maintenance dialysis patients is based upon drug exposures assessed at a single point in time. We employed a novel, time-dependent approach to modeling medication use over time to examine outcomes in a large national cohort. Methods: We linked Medicaid prescription claims with United States Renal Data System registry data and Medicare claims for 52,922 hypertensive maintenance dialysis patients. All-cause mortality and a combined cardiovascular disease (CVD)-endpoint were modeled as functions of exposure to cardioprotective antihypertensive medications (renin angiotensin system antagonists, β-adrenergic blockers, and calcium channel blockers) measured with three time-dependent covariates (weekly exposure status, proportion of prior weeks with exposure, and number of switches in exposure status) and with propensity adjustment. Results: Current cardioprotective medication exposure status as compared to not exposed was associated with lower adjusted hazard ratios (AHRs) for mortality, though the magnitude depended upon the proportion of prior weeks with medication (duration) and the number of switches between active and non-active use (switches) (AHR range 0.54-0.90). Combined CVD-endpoints depended upon the proportion of weeks on medication: AHR = 1.18 for 10% and AHR = 0.90 for 90% of weeks. Combined CVD-endpoint was also lower for patients with fewer switches. Conclusions: Effectiveness depends not only on having a drug available but is tempered by duration and stability of use, likely reflecting variation in clinical stability and patient behavior.
Authors
- Shireman, T.I. ;
- Phadnis, M.A. ;
- Wetmore, J.B. ;
- Zhou, X. ;
- Rigler, S.K. ;
- Spertus, J.A. ;
- Ellerbeck, E.F. ;
- Mahnken, J.D.
Background/Aims: Our understanding of the effectiveness of cardioprotective medications in maintenance dialysis patients is based upon drug exposures assessed at a single point in time. We employed a novel, time-dependent approach to modeling medication use over time to examine outcomes in a large national cohort. Methods: We linked Medicaid prescription claims with United States Renal Data System registry data and Medicare claims for 52,922 hypertensive maintenance dialysis patients. All-cause mortality and a combined cardiovascular disease (CVD)-endpoint were modeled as functions of exposure to cardioprotective antihypertensive medications (renin angiotensin system antagonists, β-adrenergic blockers, and calcium channel blockers) measured with three time-dependent covariates (weekly exposure status, proportion of prior weeks with exposure, and number of switches in exposure status) and with propensity adjustment. Results: Current cardioprotective medication exposure status as compared to not exposed was associated with lower adjusted hazard ratios (AHRs) for mortality, though the magnitude depended upon the proportion of prior weeks with medication (duration) and the number of switches between active and non-active use (switches) (AHR range 0.54-0.90). Combined CVD-endpoints depended upon the proportion of weeks on medication: AHR = 1.18 for 10% and AHR = 0.90 for 90% of weeks. Combined CVD-endpoint was also lower for patients with fewer switches. Conclusions: Effectiveness depends not only on having a drug available but is tempered by duration and stability of use, likely reflecting variation in clinical stability and patient behavior.
Authors
- Shireman, T.I. ;
- Phadnis, M.A. ;
- Wetmore, J.B. ;
- Zhou, X. ;
- Rigler, S.K. ;
- Spertus, J.A. ;
- Ellerbeck, E.F. ;
- Mahnken, J.D.