The efficacy of high-protein nutritional support on mortality, clinical outcomes, and nutritional adequacy in critically ill patients: a double‑center randomized controlled trial

Authors

Institutions

Publication Details

Journal
Nutrition & Metabolism
Published
2025-10-08
DOI
https://doi.org/10.1186/s12986-025-01003-1
Citations
3
Primary Topic
Clinical Nutrition and Gastroenterology
Type
article
Field-Weighted Citation Impact
3.36

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The efficacy of high-protein nutritional support on mortality, clinical outcomes, and nutritional adequacy in critically ill patients: a double‑center randomized controlled trial

Mohaddeseh Badpeyma, Majid Khadem‐Rezaiyan, Alireza Sedaghat, Mohammad Bagherniya et al.
3 citations
Nutrition & Metabolism
Clinical Nutrition and Gastroenterology
3.36
article

The efficacy of high-protein nutritional support on mortality, clinical outcomes, and nutritional adequacy in critically ill patients: a double‑center randomized controlled trial

Mohaddeseh Badpeyma, Majid Khadem‐Rezaiyan, Alireza Sedaghat, Mohammad Bagherniya, Ahmad Bagheri Moghaddam, Farzaneh Fazeli, Golnaz Ranjbar, Fatemeh Sistanian, Abdolreza Norouzy
article en
3 citations

Abstract

No abstract available for this paper.
Nutrition & MetabolismVol. 22(1)
Isfahan University of Medical Sciences (IR), Iran University of Medical Sciences (IR), Tabriz University of Medical Sciences (IR), Mashhad University of Medical Sciences (IR)
Mashhad University of Medical Sciences
Openalex Percentile: Top 8%
Clinical Nutrition and Gastroenterology
3.36
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.