Association between inflammation indicators (MLR, NLR, SII, SIRI, and AISI) and erectile dysfunction in US adults: NHANES 2001–2004

MLR is potentially more effective than other biomarkers (NLR, SIRI, AISI, SII) in predicting ED. Men with elevated MLR levels should be particularly aware of their increased risk of developing ED.

Authors

Institutions

Publication Details

Journal
Journal of Health Population and Nutrition
Published
2024-10-26
DOI
https://doi.org/10.1186/s41043-024-00667-4
Citations
13
Primary Topic
Sexual function and dysfunction studies
Type
article
Field-Weighted Citation Impact
5.01
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Association between inflammation indicators (MLR, NLR, SII, SIRI, and AISI) and erectile dysfunction in US adults: NHANES 2001–2004

Hongping Cheng, Mixue Guo, Huqiang Dong, Heng Liu
13 citations
Journal of Health Population and Nutrition
Sexual function and dysfunction studies
5.01
article

Association between inflammation indicators (MLR, NLR, SII, SIRI, and AISI) and erectile dysfunction in US adults: NHANES 2001–2004

Hongping Cheng, Mixue Guo, Huqiang Dong, Heng Liu
article en
13 citations

Abstract

MLR is potentially more effective than other biomarkers (NLR, SIRI, AISI, SII) in predicting ED. Men with elevated MLR levels should be particularly aware of their increased risk of developing ED.

Journal of Health Population and NutritionVol. 43(1)
Hubei University of Medicine (CN), Ningxia Medical University (CN)
Zero hunger
Openalex Percentile: Top 3%
Sexual function and dysfunction studies
5.01
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.