Evidence map›Paper›PMID 42458296›Full record

ArticleBMC neurology2026

Association of high-sensitivity C-reactive protein-triglyceride glucose index and stroke outcomes: results from the China National Stroke Registry III.

Liye Dai, Yiting Sun, Jinfeng Yin, Yong Jiang, Hao Li, Yongjun Wang, Xia Meng

Abstract read
In one paragraph

Article in BMC neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Liye Dai *National Collaborating Center for Neurological Disorders Prevention (NCCNDP), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yiting Sun *Department of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Jinfeng YinChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yong JiangNational Collaborating Center for Neurological Disorders Prevention (NCCNDP), Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Hao LiChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Yongjun WangDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Xia MengChina National Clinical Research Center for Neurological Diseases, Beijing Tiantan Hospital, Capital Medical University, Beijing, China. mengxia45@163.com.ORCID http://orcid.org/0000-0002-8764-9739

Funding

Beijing Hospitals Authority Clinical Medicine Development of special funding support ZLRK202312Beijing Municipal Science and Technology Project Z241100009024046Chinese Academy of Medical Sciences Innovation Fund for Medical Sciences 2019-I2M-5-029National Key Research and Development Program of China 2021ZD0200801National Key Research and Development Program of China 2022YFC2502400National Key Research and Development Program of China 2022YFC2502404
6 · The paper itself

Abstract

backgroundThe high-sensitivity C-reactive protein-triglyceride glucose index (hsCTI) is an integrated biomarker reflecting systemic inflammation and insulin resistance. This study aimed to evaluate the association between hsCTI levels and the risk of stroke recurrence in a large, real-world cohort.

methodsWe analyzed data from the China National Stroke Registry-III, including patients with acute ischemic stroke or transient ischemic attack (TIA). The hsCTI was calculated as 0.412 × ln(hsCRP [mg/L]) + ln(TG [mg/dL] × FPG [mg/dL]/2). Outcomes included stroke recurrence, ischemic stroke recurrence, and composite vascular events. Kaplan-Meier curves and Cox proportional hazards models were employed to evaluate the association between hsCTI and clinical outcomes, stratified by sex, age, and glycemic status. The area under the curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were calculated to evaluate the incremental risk prediction capabilities of hsCTI and TyG index beyond traditional risk factors.

resultsAmong 4,969 included patients (67.8% male), those in the highest hsCTI quartile (Q4) experienced increased risks of recurrent stroke and composite vascular events during a maximum follow-up of 5 years. Compared with the lowest quartile, Q4 was associated with significantly elevated 3-month stroke recurrence (adjusted hazard ratio [aHR], 1.83; 95% CI, 1.23-2.73) and composite vascular events (aHR, 2.04; 95% CI, 1.38-3.00), with associations remaining significant at 1 year. The prognostic value was most pronounced in individuals aged ≥ 60 years. Subgroup analyses identified significant interactions between hsCTI and age (P for interaction = 0.009), as well as National Institutes of Health Stroke Scale (NIHSS) score at admission (P for interaction = 0.017). Adding hsCTI to the reference model significantly improved clinical risk prediction (all P < 0.001for NRI and IDI).

conclusionsElevated baseline hsCTI level was associated with an increased risk of stroke recurrence and composite vascular events. HsCTI may serve as a potential biomarker for identifying residual vascular risks.

Indexed as

Blood GlucoseC-Reactive ProteinIschemic StrokeStrokeTriglyceridesAgedBiomarkersChinaFemaleHumansIschemic Attack, TransientMaleMiddle AgedRecurrenceRegistriesRisk FactorsBiomarkersBlood GlucoseC-Reactive ProteinTriglyceridesChina National Stroke Registry-IIIHigh-sensitivity C-reactive protein-triglyceride glucose indexInflammationInsulin resistanceStroke

Identifiers

PMID42458296
PMCPMC13491855

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.