Diagnosis and Management of Patients with Cardiac Sarcoidosis by a Regional Specialist Service

An MDT-based CS service model can provide multi-faceted care to patients, without major short-term adverse outcomes. The service model replicability and long-term outcomes require further assessment.

Authors

Institutions

Publication Details

Journal
Diseases
Published
2026-02-17
DOI
https://doi.org/10.3390/diseases14020076
Primary Topic
Sarcoidosis and Beryllium Toxicity Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Diagnosis and Management of Patients with Cardiac Sarcoidosis by a Regional Specialist Service

Sabina Dizdarevic, Achuth Hosur, Susan Ellery, Alexander Liu et al.
Diseases
Sarcoidosis and Beryllium Toxicity Research
article

Diagnosis and Management of Patients with Cardiac Sarcoidosis by a Regional Specialist Service

Sabina Dizdarevic, Achuth Hosur, Susan Ellery, Alexander Liu, Nitasha Singh, Victoria Parish, J. W. McCready, Rebecca Godfrey, Rachel Buxton-Thomas, Raj Selvaraju, John Silberbauer, Emine Cicek, Imad Mohamed Imran, Ana Frappell, Eleonora Manca, Otto Fenske
article en

Abstract

An MDT-based CS service model can provide multi-faceted care to patients, without major short-term adverse outcomes. The service model replicability and long-term outcomes require further assessment.

DiseasesVol. 14(2)
Brighton and Sussex Medical School (GB), University of Sussex (GB), Royal Sussex County Hospital (GB)
Good health and well-being
Openalex Percentile: Top 51%
Sarcoidosis and Beryllium Toxicity Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.