The U-shaped correlation between the systemic immune-inflammation index and all-cause and cardiovascular mortality in hyperlipidemic patients: findings from NHANES 1999–2018

BACKGROUND: The relationship of systemic immune-inflammation index (SII) with mortality in hyperlipidemic patients remains unknown. In the present work, we evaluated SII for its ability to predict mortality incidence and examined its relationship with mortality of hyperlipidemic individuals. METHODS: Altogether 27,903 hyperlipidemic cases were collected during 1999-2018 following the National Health and Nutrition Examination Survey (NHANES). SII was determined with complete blood count parameters. Our main results included all-cause and cardiovascular disease (CVD) mortality. We conducted Kaplan-Meier survival, restricted cubic spline (RCS), and Cox proportional hazards model analyses to assess the connection of SII to mortality among hyperlipidemic patients. To ensure that these results were reliable, we also conducted sensitivity and subgroup analyses. RESULTS: < 0.0001) of hyperlipidemic individuals. According to our threshold analysis results, thresholds for lnSII were 6.08 and 5.96. Subgroup and sensitivity analyses yielded reliable results. CONCLUSIONS: For representative hyperlipidemic patients, SII shows the non-linear, U-shaped relationship with all-cause and CVD mortality.

Authors

Institutions

Publication Details

Journal
Annals of Medicine
Published
2026-04-13
DOI
https://doi.org/10.1080/07853890.2026.2656098
Primary Topic
Inflammatory Biomarkers in Disease Prognosis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

The U-shaped correlation between the systemic immune-inflammation index and all-cause and cardiovascular mortality in hyperlipidemic patients: findings from NHANES 1999–2018

Dongchi Ma, Chuyun Xu, Qiongyu Zhou, Jiaying Yu et al.
Annals of Medicine
Inflammatory Biomarkers in Disease Prognosis
article

The U-shaped correlation between the systemic immune-inflammation index and all-cause and cardiovascular mortality in hyperlipidemic patients: findings from NHANES 1999–2018

Dongchi Ma, Chuyun Xu, Qiongyu Zhou, Jiaying Yu, Lili Yang
article en

Abstract

BACKGROUND: The relationship of systemic immune-inflammation index (SII) with mortality in hyperlipidemic patients remains unknown. In the present work, we evaluated SII for its ability to predict mortality incidence and examined its relationship with mortality of hyperlipidemic individuals. METHODS: Altogether 27,903 hyperlipidemic cases were collected during 1999-2018 following the National Health and Nutrition Examination Survey (NHANES). SII was determined with complete blood count parameters. Our main results included all-cause and cardiovascular disease (CVD) mortality. We conducted Kaplan-Meier survival, restricted cubic spline (RCS), and Cox proportional hazards model analyses to assess the connection of SII to mortality among hyperlipidemic patients. To ensure that these results were reliable, we also conducted sensitivity and subgroup analyses. RESULTS: < 0.0001) of hyperlipidemic individuals. According to our threshold analysis results, thresholds for lnSII were 6.08 and 5.96. Subgroup and sensitivity analyses yielded reliable results. CONCLUSIONS: For representative hyperlipidemic patients, SII shows the non-linear, U-shaped relationship with all-cause and CVD mortality.

Annals of MedicineVol. 58(1)
Zhejiang Chinese Medical University (CN), Westlake University (CN), Affiliated Hangzhou First People's Hospital, Westlake University, School of Medicine (CN)
Good health and well-being
Openalex Percentile: Top 18%
Inflammatory Biomarkers in Disease Prognosis
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.