Evidence map›Paper›PMID 41580789›Full record

ArticleLipids in health and disease2026

Prognostic value of the triglyceride-glucose index combined with atherogenic index of plasma for all-cause mortality in critically ill patients with chronic heart failure: a machine learning-driven retrospective cohort study.

Wei Guo, Yuchen Cui, Shaohua Yan, Siyu Che, Ning Sun, Yin Mei, Di Guo, Lingling Cui, Jiefu Yang, Hua Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Lipids in health and disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Observational
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

10 authors.

Wei GuoDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China.
Yuchen CuiDepartment of Stomatology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100020, China.
Shaohua YanDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China.
Siyu CheShanxi Bethune Hospital, Shanxi Academy of Medical Sciences, Third Hospital of Shanxi Medical University, Tongji Shanxi Hospital, Taiyuan, 030032, China.
Ning SunDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China.
Yin MeiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China.
Di GuoDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China.
Lingling CuiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China.
Jiefu YangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China. yangjiefu2011@126.com.
Hua WangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, No.1 Da Hua Road, Dong Dan, Beijing, 100730, China. wanghua2764@bjhmoh.cn.

Funding

the CAMS Innovation Fund for Medical Sciences 2021-I2M-1-050the National High-Level Hospital Clinical Research Funding BJYY-2023-070the Noncommunicable Chronic Diseases-National Science and Technology Major Project No: 2023ZD0504603
6 · The paper itself

Abstract

backgroundThe triglyceride-glucose index (TyG) and atherogenic index of plasma (AIP) are emerging metabolic biomarkers associated with cardiovascular diseases. However, their combination prognostic value in patients with critical chronic heart failure (CHF) remains unclear. This study aimed to evaluate the combined predictive effect of these two biomarkers and clarify their interactive patterns in this association.

methods1,238 patients were recruited via the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, with a median age of 71 years. Multivariable Cox regression, Kaplan-Meier analysis, and receiver operating characteristic (ROC) curve were employed to explore associations between TyG, AIP, and mortality. Mediation analysis was applied to assess their bidirectional mediation effects. Additionally, we developed a machine learning-driven prediction model, which was further utilized to evaluate the two indicators' incremental predictive value.

results1,238 patients were included, with 478 (38.61%) dying during follow-up. Fully adjusted Cox regression models revealed that the high TyG and high AIP group was associated with the highest risk of mortality relative to the low TyG and low AIP group (14-day HR 2.18, 95% Cl: 1.44-3.31; 365-day HR 1.92, 95% Cl: 1.38-2.68). ROC analyses demonstrated that the combined TyG-AIP outperformed either marker alone in predicting mortality at all follow-up observation time points (all P < 0.05). Mediation analysis revealed that TyG mediated the effect of AIP on mortality across all time frames, with a more pronounced effect at 365 days (65.47%) than at 14 days (37.32%). In contrast, AIP served as a mediator in the association between TyG and short-term mortality only (14-day: 30.39%; 30-day: 25.76%). The random forest model confirmed that the incorporation of both the TyG index and AIP remarkably improved predictive capability, corroborating their combined incremental value.

conclusionCombined elevation of TyG and AIP was independently related to an elevated risk of mortality in patients with critical CHF. Combined assessment of these biomarkers may facilitate the early recognition of high-risk subjects and support stage-specific metabolic interventions.

Indexed as

AtherosclerosisBlood GlucoseHeart FailureMachine LearningTriglyceridesAgedBiomarkersChronic DiseaseCritical IllnessFemaleHumansKaplan-Meier EstimateMaleMiddle AgedPrognosisProportional Hazards ModelsBiomarkersBlood GlucoseTriglyceridesAll-cause mortalityAtherogenic index of plasmaChronic heart failureMachine learningTriglyceride-glucose index

Identifiers

PMID41580789
PMCPMC12910808

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.