Evidence map›Paper›PMID 39582034›Full record

ArticleDiabetology & metabolic syndrome2024

The systemic immune-inflammation index and systemic inflammation response index are useful for predicting mortality in patients with diabetic nephropathy.

Fan Zhang, Yan Han, Yonghua Mao, Wenjian Li

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Article in Diabetology & metabolic syndrome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 2 of them syntheses that pooled it.

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13citing papers in PubMed, 2 pooled it
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1 · What the graph read from it

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3 · Its place in the literature

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13 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Fan ZhangChangzhou Clinical College, Xuzhou Medical University, Changzhou, 213001, China.
Yan HanChangzhou Clinical College, Xuzhou Medical University, Changzhou, 213001, China.
Yonghua MaoChangzhou Clinical College, Xuzhou Medical University, Changzhou, 213001, China.
Wenjian LiChangzhou Clinical College, Xuzhou Medical University, Changzhou, 213001, China. 760020240117@xzhmu.edu.cn.

Funding

Changzhou Third People's Hospital Key Talents Project
6 · The paper itself

Abstract

backgroundThis study investigated the correlation between the systemic immune-inflammation index (SII) and the systemic inflammation response index (SIRI) and all-cause, cardiovascular, and kidney disease mortality in patients with diabetic nephropathy (DN). It aimed to provide a new predictive assessment tool for the clinic and a scientific basis for managing inflammation in DN.

methodsThe data utilized in this study were obtained from the National Health and Nutrition Examination Survey (NHANES) database, spanning 1999 to 2018. A total of 2641 patients diagnosed with DN were included in the analysis. The association between SII and SIRI levels and mortality in patients with DN was investigated using multivariate Cox proportional risk regression models. These relationships were further validated by Kaplan-Meier survival curves and restricted cubic spline (RCS) modeling, and subgroup analyses were performed to explore the heterogeneity among different characteristic subgroups.

resultsThe multivariate Cox regression analysis indicated that SII and SIRI levels were independently associated with all-cause mortality and cardiovascular mortality in patients with DN. SIRI levels were found to be an independently associated factor with kidney disease mortality in patients with DN. Patients in the highest quartile of SII and SIRI exhibited a 1.49-fold and 1.62-fold increased risk of all-cause mortality, respectively, compared to patients in the lowest quartile. The risk of cardiovascular mortality was 1.31 and 1.73 times higher than that in patients in the lowest quartile, respectively. The risk of kidney disease mortality in patients in the highest quartile of SIRI was 2.74 times higher than that in patients in the lowest quartile. Kaplan-Meier survival curve and RCS analyses further confirmed the positive association between SII and SIRI and mortality and a significant nonlinear relationship between SII and all-cause mortality. The SII and SIRI indices offer incremental value in model predictive power for mortality in patients with DN. Subgroup analyses demonstrated that the correlation between SII and SIRI and mortality risk was stable but heterogeneous across different subgroups.

conclusionSII and SIRI can be utilized as biomarkers for forecasting the likelihood of all-cause and cardiovascular mortality in patients with DN.

Indexed as

All-cause mortalityCardiovascular mortalityDiabetic nephropathyKidney disease mortalitySystemic immune-inflammation indexSystemic inflammation response index

Identifiers

PMID39582034
PMCPMC11587540

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.