Evidence map›Paper›PMID 41024001›Full record

ArticleLipids in health and disease2025

The C-reactive protein-triglyceride-glucose index (CTI) as a predictor of mortality and hospital stay in critically ill patients: a retrospective cohort study.

Huijian Wang, Longlong Hu, Yang Chen, Huabin He, Yijun Huang, Ruyi Tao, Shiyuan Li, Renqiang Yang

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. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

8 authors.

Huijian WangDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China.
Longlong HuDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China.
Yang ChenDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China.
Huabin HeDepartment of Cardiovascular Medicine, Jiu jiang No. 1 People's Hospital, Jiujiang, 332000, China.
Yijun HuangDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China.
Ruyi TaoDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China.
Shiyuan LiDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China.
Renqiang YangDepartment of Cardiovascular Medicine, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi, 330006, China. Yang.RQ@ncu.edu.cn.

Funding

This research was funded by the National Natural Science Foundation of China No. 81960081
6 · The paper itself

Abstract

backgroundPopulation aging has increased the demand for intensive care, with critically ill patients facing high mortality and prolonged hospital stays. New biomarkers are needed to predict outcomes early. The C-reactive protein-triglyceride-glucose index (CTI) integrates insulin resistance and inflammation, but its Link to outcomes in critically ill patients is unknown. This study aims to investigate the association between CTI and 30-day and 365-day all-cause mortality and length of hospital stay in critically ill patients.

methodsThis retrospective study utilized data from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database, including 2,428 ICU patients admitted from 2008 to 2022. The primary outcomes were 30-day and 365-day all-cause mortality, while secondary outcomes included length of hospital stay and ICU stay. CTI was calculated based on biochemical data (CRP, triglycerides, and glucose). Kaplan-Meier survival analysis, Cox regression models, and mediation analysis were employed to assess the relationship between CTI and clinical outcomes.

resultsHigher CTI levels were associated with increased all-cause mortality at both 30 days (HR: 1.81, 95% CI: 1.31-2.52, P < 0.001 for the highest quartile) and 365 days (HR: 1.80, 95% CI: 1.43-2.28, P < 0.001 for the highest quartile). CTI exhibited a Linear relationship with mortality, with each unit increase in CTI corresponding to a 25% increase in 30-day mortality and a 26% increase in 365-day mortality. Nutritional risk, assessed by the Geriatric Nutritional Risk Index (GNRI) levels, significantly mediated the association between CTI and mortality, with a stronger effect observed in long-term outcomes. Furthermore, CTI outperformed the triglyceride-glucose (TyG) index and C-reactive protein (CRP) in predicting mortality, and the results remained consistent after adjusting for baseline severity scores. Additionally, higher CTI levels were associated with longer hospital and ICU stays (β = 0.44 days and β = 0.22 days, respectively, P < 0.001).

conclusionsCTI is a robust predictor of mortality and hospital stay duration in critically ill patients, integrating the effects of insulin resistance and inflammation. Nutritional risk plays a significant mediating role in the association between CTI and mortality, particularly in long-term outcomes. CTI may serve as a valuable tool for early risk stratification and clinical decision-making in the ICU setting.

Indexed as

Blood GlucoseC-Reactive ProteinCritical IllnessTriglyceridesAgedBiomarkersFemaleHospital MortalityHumansIntensive Care UnitsKaplan-Meier EstimateLength of StayMaleMiddle AgedRetrospective StudiesBiomarkersBlood GlucoseC-Reactive ProteinTriglyceridesAll-cause mortalityC-reactive protein-triglyceride-glucose indexIntensive care unitsMIMIC-IV

Identifiers

PMID41024001
PMCPMC12481762

What OpenQuestion 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 OpenQuestion graph.