What does this research mean for the field?

SII (HR 1.002), SIRI (HR 1.984), and NHR (HR 1.692) are independent risk factors for aortic dissection, while LHR (HR 0.211) is a protective factor. Novelty: ClaimNovelty.NOVEL_FINDING. Consensus alignment: ConsensusAlignment.NEUTRAL.

What question did this study set out to answer?

This study investigates the relationship between six inflammatory-metabolic indexes and the risk of aortic dissection.

January 10, 2026BMC Cardiovascular Disorders0 citationsOpen Access

Systemic inflammatory and metabolic indexes for aortic dissection: a machine learning analysis

WDWenyuan DongTongji Hospital WAWusimanjiang AizimaitijiangTongji Hospital HJHongcheng JiangHubei Provincial Hospital of Traditional Chinese Medicine

Key Result

SII (HR 1.002), SIRI (HR 1.984), and NHR (HR 1.692) are independent risk factors for aortic dissection, while LHR (HR 0.211) is a protective factor.

Key Points

This study investigates the relationship between six inflammatory-metabolic indexes and the risk of aortic dissection.
Enrolled a total of 1,959 patients
Used propensity score matching to reduce confounding
Applied multivariable logistic regression models for associations
Conducted restricted cubic spline analysis to examine dose–response relationships
Evaluated discriminative performance using ROC curve and machine learning algorithms
Identified SII, SIRI, and NHR as independent risk factors for aortic dissection
LHR was found to be a protective factor
Demonstrated nonlinear relationships for SII, SIRI, and LHR
XGBoost model achieved the best performance with an AUC of 0.883
ROC curve analysis showed AUC values from 0.740 to 0.835 for distinguishing aortic dissection

Structured PICO

Are systemic inflammatory and metabolic indexes (SII, SIRI, NHR, LHR, MHR, PHR) associated with the risk of aortic dissection and can they discriminate its presence?

Population

1,959 participants, comprising 1,012 patients with aortic dissection (AD) from a Chinese hospital (mean age 54.1, 79.9% male) and 951 control participants from the US NHANES database. Exclusions: intramural hematoma, penetrating atherosclerotic ulcer, aortic aneurysm, prior AD, age <18, pregnant, onset >14 days.

Intervention

Measurement of six systemic inflammatory and metabolic indexes: systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil to HDL-C ratio (NHR), platelet to HDL-C ratio (PHR), lymphocyte to HDL-C ratio (LHR), and monocyte to HDL-C ratio (MHR).

Comparator

Control group of participants without aortic dissection from the NHANES database, matched using 1:1 propensity score matching.

Outcome

Association between inflammatory-metabolic indexes and the risk of aortic dissection, and their discriminative performance (AUC).surrogate

Systemic inflammatory and metabolic indexes, particularly SIRI, NHR, and SII, are independently associated with aortic dissection risk and can be integrated into machine learning models to accurately discriminate its presence.

Main Result

Absolute Event Rate: 0% vs 0%

Abstract

Inflammation plays a crucial role in the development of aortic dissection. The systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) are widely used surrogate markers for systemic inflammation, while the neutrophil to high-density lipoprotein cholesterol ratio (NHR), platelet to high-density lipoprotein cholesterol ratio (PHR), lymphocyte to high-density lipoprotein cholesterol ratio (LHR), and monocyte to high-density lipoprotein cholesterol ratio (MHR) incorporate high-density lipoprotein, reflecting both inflammatory and metabolic status. However, there is currently a lack of studies systematically comparing the associations between different inflammatory and metabolic surrogate markers and the risk of AD. Therefore, this study aims to investigate the relationship between these six inflammatory-metabolic indexes and the risk of aortic dissection, as well as evaluate their discriminative value for this condition. This study aims to clarify the relationship between the inflammatory metabolic markers and aortic dissection. This study enrolled a total of 1,959 patients. First, Propensity score matching (PSM) was applied to minimize confounding bias. Subsequently, multivariable logistic regression models were used to evaluate the associations between inflammatory indexes and AD risk. Restricted cubic spline (RCS) analysis was performed to explore potential nonlinear dose–response relationships. The discriminative performance of inflammatory indexes was assessed using receiver operating characteristic (ROC) curve. Furthermore, six machine learning algorithms were implemented for feature importance analysis. After adjusting for potential confounding factors, we identified SII 1.002 (95% CI: 1.001–1.002), SIRI 1.984 (95% CI: 1.702–2.352), and NHR 1.692 (95% CI: 1.499–1.928) as independent risk factors for AD development, while LHR 0.211 (95% CI: 0.143–0.304) served as an independent protective factor. Dose–response analysis demonstrated a linear association between NHR and AD risk ( P for Nonlinear = 0.02), whereas SII, SIRI and LHR showed nonlinear relationships ( P for Nonlinear < 0.001). ROC curve analysis revealed that the four inflammatory indexes had AUC values ranging from 0.740 to 0.835 for distinguishing AD and its clinical subtypes. Among the six machine learning algorithms evaluated, the XGBoost model demonstrated the best performance, achieving an area under the receiver operating characteristic curve (AUC) of 0.883. Among these six systemic Inflammatory and Metabolic indexes, the SII, SIRI, NHR, and LHR indexes demonstrate significant associations with the presence of aortic dissection. Further prospective validation in larger, multicenter cohorts is warranted to confirm their clinical utility before integration into diagnostic workflows.

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