ArticleFrontiers in cardiovascular medicine2026
Optimize speckle-tracking echocardiography screening in CKD patients: a TyG index-based nomogram model.
Article in Frontiers in cardiovascular medicine, 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
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Chronic kidney disease (CKD) patients with worsening left ventricular (LV) systolic function face significantly poorer clinical outcomes. While speckle-tracking echocardiography (STE)-derived global longitudinal strain (GLS) can sensitively detect early LV systolic dysfunction, indiscriminate routine STE screening in CKD populations may lead to unnecessary healthcare resource utilization. Therefore, identifying CKD patients at high risk of concurrent abnormal GLS in clinical practice may help optimize the selective use of STE. Notably, the triglyceride-glucose (TyG) index, as a reliable and readily accessible indicator for assessing insulin resistance, has demonstrated a close association with GLS in multiple studies. Therefore, this study aimed to develop a TyG index-based model to predict the risk of abnormal GLS in CKD patients, thereby providing a basis for optimizing screening strategies using STE. Methods: This prospective cross-sectional study enrolled CKD patients from the Fifth Affiliated Hospital of Sun Yat-sen University between July 2023 to July 2024. All CKD patients underwent clinical examination, biochemistry measurement and transthoracic echocardiography. Results: Among 260 initially screened CKD patients, 212 were included after exclusions (median age: 47 years, male: 58%). Multivariable analysis identified male sex (OR = 2.77), diastolic blood pressure (OR = 1.07), high-density lipoprotein (OR = 0.36) and TyG index (OR = 4.55) as independent predictors of reduced GLS (< 20%). The developed nomogram model demonstrated robust predictive performance (AUC 0.838-0.842) and clinical utility across multiple risk thresholds in both training and validation cohorts. Conclusion: The developed nomogram model could serve as an effective screening tool to optimize STE utilization in CKD patients, thereby conserving medical resources.
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.