Evidence map›Paper›PMID 41327338›Full record

ArticleLipids in health and disease2025

Association of the atherogenic index of plasma with in-hospital mortality in patients with sepsis-induced coagulopathy.

Han Zeng, Chenxi Ma, Rui Zheng, Chenxin Jiang, Yuhao Zhong, Songzan Qian, Yiyi Shi

Abstract read
In one paragraph

Article in Lipids in health and disease, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Han Zeng *The First School of Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Chenxi Ma *The Second School of Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Rui ZhengDepartment of Critical Care Medicine, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China.
Chenxin JiangThe First School of Medicine, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Yuhao ZhongRenji College, Wenzhou Medical University, Wenzhou, Zhejiang, China.
Songzan QianDepartment of Intensive Care Unit, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China. qiansongzan@wmu.edu.cn.
Yiyi ShiDepartment of Anesthesiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China. 80603424@qq.com.

Funding

National College Students Innovation and Entrepreneurship Training Program 202410343083
6 · The paper itself

Abstract

backgroundFew inexpensive early parameters are available to describe sepsis-induced coagulopathy (SIC) in practice. The atherogenic index of plasma (AIP = log₁₀[TG/HDL-C]) integrates triglyceride excess and HDL-C depletion—metabolic shifts implicated in endothelial injury and thrombosis. We evaluated the association between the AIP and in-hospital mortality in patients with SIC.

methodsWe performed a retrospective cohort study of patients with SIC admitted to the ICU of the First Affiliated Hospital of Wenzhou Medical University (2017–2023). The primary outcome was in-hospital mortality. Multivariable logistic models adjusted sequentially for age/sex and Boruta/LASSO-selected covariates (age, SOFA score, albumin, sodium, potassium, ventilation, and renal diseases) plus major comorbidities. Dose–response was assessed by restricted cubic splines. Sensitivity analyses were performed using different SIC criteria and alternative adjustment strategies to verify robustness. Machine learning (CatBoost, RF, LR, and MLP) classifiers were compared for discrimination and calibration.

results1096 patients were included. Higher baseline AIP was associated with increased mortality across models (per-SD OR 1.29, 95% CI 1.09–1.53, fully adjusted). Restricted cubic splines supported an approximately linear association. The logistic model reached an AUROC of 0.71 in the test set, with a positive net benefit on decision curve analysis. Additional machine-learning models showed comparable discrimination in the test set (AUROC around 0.70). SHAP analysis indicated that ventilation contributed most strongly to model predictions, with AIP also emerging as an important prognostic feature.

conclusionsA higher AIP is linked to increasing in-hospital mortality in SIC patients, which aligns with the metabolic–vascular disturbances that the AIP captures. When used as a complementary measure, the AIP may aid early clinical appraisal without implying stand-alone prognostication.

Indexed as

AtherosclerosisBlood Coagulation DisordersHospital MortalitySepsisAgedCholesterol, HDLFemaleHumansIntensive Care UnitsLogistic ModelsMaleMiddle AgedRetrospective StudiesTriglyceridesCholesterol, HDLTriglyceridesAtherogenic index of plasmaDyslipidemiaIn-hospital mortalityIntensive care unitsSepsisSepsis-induced coagulopathy

Identifiers

PMID41327338
PMCPMC12777205

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.