Evidence map›Paper›PMID 42245430›Full record

ArticleJournal of Appalachian health2026

Infective Endocarditis Hospitalizations in Kentucky, 2008-2018: Spatial and Temporal Trends.

Meera Marji, Steve Browning, W Jay Christian, Richard Charnigo, Steve W Leung, Anna Kucharska-Newton

Abstract read
In one paragraph

Article in Journal of Appalachian health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Meera MarjiUniversity of Kentucky.
Steve BrowningUniversity of Kentucky.
W Jay ChristianUniversity of Kentucky.
Richard CharnigoUniversity of Kentucky.
Steve W Leung
Anna Kucharska-Newton

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Infective endocarditis (IE) hospitalization rates have increased significantly in the last decade, primarily due to the opioid epidemic. In 2016, Kentucky (KY) ranked among the top ten states for opioid-related overdose deaths, but limited data exist on IE trends in KY. Purpose: This study seeks to examine county-level spatial and temporal trends in IE hospitalization rates in KY. Methods: Hospital inpatient discharge data from 2008-2018 for KY residents aged 18 and older were analyzed. IE admissions and drug use status were identified using ICD-9 & 10 diagnosis codes. U.S. Census data calculated yearly IE hospitalization rates per 100,000 residents. Joinpoint regression identified periods with significant rate changes and calculated annual percent change (APC). Poisson modeling in SaTScan conducted spatiotemporal cluster analysis at the county level and calculated the relative risk (RR) of IE hospitalizations within identified clusters. Results: During 2008-2018, we observed 17,787 IE hospital admissions, including 3,577 associated with intravenous drug use (IDU-IE). Medicaid patients were more prevalent in the IDU-IE group compared to the non-IDU-IE group (75% vs. 15%). IDU-IE hospitalization rates increased from 1.2 to 27.3 per 100,000 residents between 2008 - 2018. Joinpoint regression for IDU-IE identified a significant upward trend from 2013-2018 with an APC of 71.3% (95% CI: 47.8, 98.5). The spatiotemporal analysis identified seven significant IE hospitalization clusters, with the largest (RR=2.06, p. Implications: IDU-IE hospitalization rates increased significantly from 2013-2018, while non-IDU-IE rates decreased over the study period.

Indexed as

Appalachiageospatial clustersinfective endocarditisopioid epidemic

Identifiers

PMID42245430
PMCPMC13233083

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.