Automated Author ProfileChakrabarty, T.
Chakrabarty, T.
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: Depression is common in Alzheimer's and vascular dementia and is associated with poorer outcomes; however, less is known about the impact of depression on frontotemporal dementia (FTD). Here, we conducted a meta-analysis of diagnostic methods and the prevalence of depressive symptoms in FTD. Methods: PubMed, EMBASE and PsychINFO were queried for ‘depression' and/or ‘depressive mood' in behavioral- and language-variant FTD. The prevalence and diagnosis of depressive symptoms were extracted from relevant studies and the results pooled using a random-effects model. Results: We included 29 studies in this meta-analysis, with sample sizes ranging from 3 to 73 (n = 870). The omnibus estimated event rate of depressed mood was 0.334 (33%; 95% CI: 0.268-0.407). Symptoms were most commonly assessed via standardized neuropsychiatric rating scales, with other methods including subjective caregiver reports and chart reviews. The study results were heterogeneous due to the variability in diagnostic methods. Conclusions: Depressive symptoms similar to those in other dementias are commonly detected in FTD. However, the diagnostic methods are heterogeneous, and symptoms of depression often overlap with manifestations of FTD. Having a standardized diagnostic approach to depression in FTD will greatly facilitate future research in this area.
Authors
- Chakrabarty, T. ;
- Sepehry, A.A. ;
- Jacova, C. ;
- Hsiung G.-Y.R.
Background: Depression is common in Alzheimer's and vascular dementia and is associated with poorer outcomes; however, less is known about the impact of depression on frontotemporal dementia (FTD). Here, we conducted a meta-analysis of diagnostic methods and the prevalence of depressive symptoms in FTD. Methods: PubMed, EMBASE and PsychINFO were queried for ‘depression' and/or ‘depressive mood' in behavioral- and language-variant FTD. The prevalence and diagnosis of depressive symptoms were extracted from relevant studies and the results pooled using a random-effects model. Results: We included 29 studies in this meta-analysis, with sample sizes ranging from 3 to 73 (n = 870). The omnibus estimated event rate of depressed mood was 0.334 (33%; 95% CI: 0.268-0.407). Symptoms were most commonly assessed via standardized neuropsychiatric rating scales, with other methods including subjective caregiver reports and chart reviews. The study results were heterogeneous due to the variability in diagnostic methods. Conclusions: Depressive symptoms similar to those in other dementias are commonly detected in FTD. However, the diagnostic methods are heterogeneous, and symptoms of depression often overlap with manifestations of FTD. Having a standardized diagnostic approach to depression in FTD will greatly facilitate future research in this area.
Authors
- Chakrabarty, T. ;
- Sepehry, A.A. ;
- Jacova, C. ;
- Hsiung G.-Y.R.