ArticleScientific reports2026
Nonlinear association of residual cholesterol to high-density lipoprotein cholesterol ratio with diabetes mellitus: a retrospective cohort study.
Article in Scientific reports, 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Diabetes mellitus is a major public health challenge in the world, and the role of lipid metabolism disorder in its pathogenesis has attracted much attention. The ratio of residual cholesterol to high-density lipoprotein cholesterol (RC/HDL-C), as a comprehensive index of atherosclerosis and anti-atherosclerotic lipid load, has shown predictive value in cardiovascular diseases, but its relationship with diabetes mellitus has not been clear. Therefore, we conducted a retrospective cohort study to investigate the relationship between RC/HDL-C and the risk of diabetes mellitus. This study was based on open data from the Murakami Memorial Hospital Health Screening Cohort in Japan. A total of 15,216 subjects without diabetes mellitus at baseline were included. The association between RC/HDL-C and diabetes mellitus risk was assessed by Cox proportional risk regression modeling. Restricted cubic spline (RCS) and smoothed curve fitting were used to explore the nonlinear association of RC/HDL-C with diabetes mellitus. Sensitivity analyses (excluding people of advanced age, obesity and hypertension) and subgroup analyses were performed to verify the robustness of the results. During median follow-up, 340 (2.23%) new cases of diabetes mellitus developed. After correcting for confounders, each 1-unit increase in RC/HDL-C was associated with a 5.21-fold increase in the risk of diabetes mellitus (HR 5.21, 95% CI 2.59-10.52; P < 0.001). The RCS model revealed a nonlinear association between RC/HDL-C and diabetes mellitus risk with a threshold point of 0.41. When RC/HDL-C ≤ 0.41, RC/HDL-C was significantly and positively associated with the risk of diabetes mellitus (HR 50.6, 95% CI 6.4-403.4; P < 0.001). In contrast, when RC/HDL-C > 0.41, RC/HDL-C was not associated with an increased risk of diabetes mellitus (HR 2.5, 95% CI 1.0-6.5; P = 0.053). Sensitivity and subgroup analyses showed that the positive association between RC/HDL-C and risk of diabetes mellitus was stable and consistent in the general population. This study revealed a nonlinear association between RC/HDL-C and the risk of developing diabetes mellitus through large-scale cohort data. This finding not only provides a new biomarker for early risk prediction of diabetes mellitus, but also deepens the understanding of lipid metabolic imbalance in the pathogenesis of diabetes mellitus. This study provides new ideas for early risk stratification and individualized lipid management in diabetes mellitus.
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.