Harnessing radiomics and nutritional metrics to predict long-term survival in Fournier’s gangrene patients

Despite a mild trend, none of the sarcopenia models were able to predict long-term mortality in FG patients in our cohort. This well-known, cost-effective nutritional predictor still requires further research to optimize its utilization in the FG patient population.

Authors

Institutions

Publication Details

Journal
Urologia Journal
Published
2025-02-16
DOI
https://doi.org/10.1177/03915603251318502
Citations
2
Primary Topic
Hematological disorders and diagnostics
Type
article
Field-Weighted Citation Impact
4.51
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Harnessing radiomics and nutritional metrics to predict long-term survival in Fournier’s gangrene patients

Borivoj Golijanin, Benjamin Ahn, Kamil Malshy, Madeline Cancian et al.
2 citations
Urologia Journal
Hematological disorders and diagnostics
4.51
article

Harnessing radiomics and nutritional metrics to predict long-term survival in Fournier’s gangrene patients

Borivoj Golijanin, Benjamin Ahn, Kamil Malshy, Madeline Cancian, Stephen Schmit, K. Miller, John R. Morgan, Amir Farah, Dragan Golijanin
article en
2 citations

Abstract

Despite a mild trend, none of the sarcopenia models were able to predict long-term mortality in FG patients in our cohort. This well-known, cost-effective nutritional predictor still requires further research to optimize its utilization in the FG patient population.

Urologia JournalVol. 92(3)
Medical College of Wisconsin (US), Brown University (US), Miriam Hospital (US)
Zero hunger
Openalex Percentile: Top 8%
Hematological disorders and diagnostics
4.51
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.