Table · dataset · 2026
Data Sheet 1_Growing public interest and regional disparities of cardiorenal syndrome in the United States.pdf
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Background<p>Public awareness and regional engagement with cardiorenal syndrome (CRS) remain poorly understood.
Description
We examined temporal trends and geographic patterns of U.S. public interest in CRS and their relationship with disease burden.</p>Methods<p>Google Trends™ data (2004–2025) annual relative search interest (RSI) for CRS. CRS-related mortality was derived from CDC WONDER (2007–2020) using hypertensive heart and chronic kidney disease deaths.
Temporal trends were assessed via augmented Dickey-Fuller tests and linear regression. Associations between RSI and mortality were evaluated using Pearson correlation, AR(1) modeling, first-difference, and cumulative change analysis. State-level correlations were examined with and without adjustment for income, education, and insurance coverage.</p>Results<p>Both RSI and mortality exhibited strong non-stationary upward trend (p = 0.98 and 0.42).
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Raw data showed a strong correlation analysis (r = 0.79, p = 0.001); but first-differenced year-over-year changes were not significant (r = −0.36, p = 0.23), consistent with AR(1) modeling (β=1.58, p = 0.11). Cumulative changes remained strongly correlated (r = 0.80, p = 0.001), indicating parallel long-term trajectories. Findings were consistent with varying ICD-10 code definitions for CRS-related mortality.
Geographically, RSI was highest in West Virginia and lowest in Texas and Georgia. State-level RSI showed no correlation with age-adjusted mortality, both unadjusted (r = −0.09, p = 0.52) and after adjustment for median income, educational, and insurance coverage (β=0.03, p = 0.75).</p>Conclusion<p>Public interest in CRS has grown in parallel with mortality, reflecting its increasing epidemiological relevance. However, the lack of geographic correlation between search interest and mortality—even after socioeconomic adjustment—suggests awareness gaps and highlights opportunities for targeted education and resource allocation.</p>
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Where it is published
- DOI doi.org/10.3389/fdgth.2026.1803510.s001 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
Provenance · 1 source records, 19 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| figshare | oai:figshare.com:article/33772213 | 12 d ago | JSON v1 |
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| concepts[field].anzsrc:field:440304 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['mortality'] |
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| concepts[field].local:field:ocean-atmospheric | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| description | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/description |
| license | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/rights |
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| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |