ArticleInternational journal of surgery (London, England)2026
The C-reactive protein-triglyceride glucose index (CTI) predicts mortality in cardiovascular-kidney-metabolic syndrome: a dual-cohort study with machine learning validation.
Article in International journal of surgery (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- Metabolic Indices of Atherogenicity, Insulin Resistance, and Inflammation (AIP, TyG, and CTI) and the Risk of Renal Function Decline in Early-Stage CKM Syndrome: A Nationwide Prospective Cohort Study.Journal of clinical medicine · 2026Article
- Association of 14 triglyceride-glucose (TyG)-related indices with new-onset cardiovascular disease in middle-aged and older adults: evidence from the CHARLS and ELSA aging cohorts.Cardiovascular diabetology · 2026Article
- Association of the estimated glucose disposal rate combined with a body shape index with all-cause and cardiovascular-specific mortality among individuals with cardiovascular-kidney-metabolic syndrome.Cardiovascular diabetology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundCardiova scular-kidney-metabolic (CKM) syndrome urgently requires accessible biomarkers for stratification of death risk. This study validated the predictive value of a novel inflammatory metabolic biomarker, the C-reactive protein-triglyceride-glucose index (CTI), for all-cause and cardiovascular mortality in dual U.S. and Chinese cohorts and developed a survival analysis machine learning (ML) model.
methodsWe integrated data from the National Health and Nutrition Examination Survey (NHANES, n = 8784) and China Health and Retirement Longitudinal Study (CHARLS, n = 7745). Multivariate Cox regression was used to evaluate the associations between CTI (formula: 0.412 × Ln(C-reactive protein) + Ln[triglycerides × fasting blood glucose/2]) and mortality. Seven ML models were built using the NHANES data, with CHARLS as the external validation set. SHapley Additive exPlanations (SHAP) clarified the prediction mechanisms.
resultsPer 1-standard deviation increase in CTI, all-cause mortality risk increased significantly (NHANES: hazard ratios (HRs) = 1.31, 95% confidence interval (CI): 1.19-1.44; CHARLS: HR = 1.67, 95% CI: 1.44-1.93), and cardiovascular mortality increased by 35% in NHANES (HR = 1.35, P < 0.001). The Random Survival Forest (RSF) model performed best: internal validation area under the curve (AUC) = 0.866 (NHANES) with the highest time-dependent Concordance Index, and external validation in CHARLS yielded AUCs of 0.811 (3-year), 0.804 (5-year), and 0.775 (9/12-year), outperforming other models. SHAP analysis identified age (42.2% contribution) and CTI (10.1%) as key predictors, with age, CTI, and systolic blood pressure acting via independent main effects, whereas estimated glomerular filtration rate exerted an influence primarily through synergistic interactions.
conclusionCTI, a novel inflammatory metabolic biomarker, reliably predicts all-cause and cardiovascular mortality in CKM syndrome, with consistent validation across NHANES and CHARLS. The NHANES-derived RSF model (AUC > 0.86) combines high accuracy and clinical utility, and is supported by stable external validation in CHARLS and sensitivity analyses. SHAP-based mechanistic insights further enable personalized risk assessments.
Indexed as
Identifiers
What Socratic holds
Registered trials
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.