ArticleDiabetology & metabolic syndrome2026
Comparison of CTI and its modified indices in predicting cardiovascular disease risk across different glycemic statuses: a nationwide prospective cohort study.
Article in Diabetology & metabolic syndrome, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
backgroundThe C-reactive protein-triglyceride glucose index (CTI) has emerged as a promising composite biomarker for cardiovascular disease (CVD) risk. However, whether incorporating obesity-related metrics such as waist circumference (WC), body mass index (BMI), or waist-to-height ratio (WHtR) into CTI to form modified indices such as CTI-WC, CTI-BMI, and CTI-WHtR improves predictive performance remains uncertain. The performance of these modified indices requires validation in large-scale prospective cohorts stratified by glycemic status.
methodsThis study used data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020, involving 7,579 participants aged ≥ 45 years. Multivariate Cox regression and restricted cubic splines (RCSs) analyses were used to assess the associations of the CTI and its modified indices with CVD risk. To compare the predictive performance, time-dependent Harrell's C-indices, integrated discrimination improvement and net reclassification index were utilized. Weighted quantile sum (WQS) regression was used to evaluate component contributions.
resultsDuring a mean follow-up of 8.28 years, 1,871 (24.69%) participants experienced their first CVD event. The CTI and its modified indices were effective in predicting CVD incidence in the general population. RCS analysis revealed positive linear dose-response relationships between these indices and CVD risk in the general population, which persisted in both normal glucose regulation (NGR) and prediabetes mellitus (Pre-DM) patients. WQS regression analysis revealed that, in the general population, TG contributed the most to CVD risk in the CTI, while WC, BMI, and WHtR had greater weights in their modified indices. In the general population, all modified CTI indices demonstrated superior predictive ability than did the original CTI (C-index: CTI-WC 0.619, CTI-WHtR 0.616, CTI-BMI 0.614, and CTI 0.612). In the population with NGR, Pre-DM, and DM, the predictive capability of CTI-WC is superior to that of the original CTI, with its C-index being greater across all these populations.
conclusionsThe CTI and its modified indices are effective in predicting CVD risk in the general population. The modified CTI indices, especially the CTI-WC, show superior predictive ability across different glycemic statuses. These findings suggest that incorporating obesity-related metrics into the CTI may enhance its utility for CVD risk prediction.
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.