Background: The American Heart Association recently introduced the concept of cardiovascular-kidney-metabolic (CKM) syndrome, highlighting the increasing importance of the complex interplay between metabolic, renal, and cardiovascular diseases (CVD). While substantial evidence supports a correlation between the estimated glucose disposal rate (eGDR) and CVD events, its predictive value compared with other insulin resistance (IR) indices, such as triglyceride–glucose (TyG) index, TyG-waist circumference, TyG-body mass index, TyG-waist-to-height ratio, triglyceride-to-high density lipoprotein cholesterol ratio, and the metabolic score for insulin resistance, remains unclear. Methods: This prospective cohort study utilized data from the China Health and Retirement Longitudinal Study (CHARLS). The individuals were categorized into four subgroups based on the quartiles of eGDR. The associations between eGDR and incident CVD were evaluated using multivariate logistic regression analyses and restricted cubic spline. Seven machine learning models were utilized to assess the predictive value of the eGDR index for CVD events. To assess the model’s performance, we applied receiver operating characteristic (ROC) and precision-recall (PR) curves, calibration curves, and decision curve analysis. Results: A total of 4,950 participants (mean age: 73.46 ± 9.93 years), including 50.4% females, were enrolled in the study. During follow-up between 2011 and 2018, 697 (14.1%) participants developed CVD, including 486 (9.8%) with heart disease and 263 (5.3%) with stroke. The eGDR index outperformed six other IR indices in predicting CVD events, demonstrating a significant and linear relationship with all outcomes. Each 1-unit increase in eGDR was associated with a 14%, 14%, and 19% lower risk of CVD, heart disease, and stroke, respectively, in the fully adjusted model. The incorporation of the eGDR index into predictive models significantly improved prediction performance for CVD events, with the area under the ROC and PR curves equal to or exceeding 0.90 in both the training and testing sets. Conclusions: The eGDR index outperforms six other IR indices in predicting CVD, heart disease, and stroke in individuals with CKM syndrome stages 0–3. Its incorporation into predictive models enhances risk stratification and may aid in the early identification of high-risk individuals in this population. Further studies are needed to validate these findings in external cohorts. Graphical

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While several indicators have been studied, the association of body roundness index (BRI) with non-alcoholic fatty liver disease (NAFLD) remains unclear. We aimed to explore the association between BRI and ultrasound-defined NAFLD. The sample dataset was extracted from the National Health and Nutrition Examination Survey (NHANES) during the period of 2017–2018. The diagnosis of NAFLD was determined based on the controlled attenuated parameter (CAP≥248 dB/m) score of liver ultrasound transient elastography (LUTE). Participants with excessive alcohol use and viral hepatitis were excluded. To delve deeper into the relationship, Multivariable logistic regression with adjustment for confounding variables and smoothing curve analysis was used to investigate the association and nonlinear relationships between BRI and NAFLD. Among 4210 individuals aged 20 years or older included in the study, 28.2 % had NAFLD. Compared to the first tertile, BRI notably increased the risk of NAFLD 3.53-fold [95 % confidence interval (CI) = 2.73–4.57] in the second tertile and 7.00-fold (95%CI = 5.29–9.27) in the third tertile after adjusting for multiple covariates (P for trend <0.001). Furthermore, when BRI was treated as a continuous variable, one unit of increment in BRI was associated with 41 % higher odds of NAFLD [adjusted odds ratio (aOR) = 1.41; 95%CI = 1.34–1.48; P < 0.001]. The associations of BRI with NAFLD persisted in all subgroup analyses. A smoothing curve fitting demonstrated that the relationship between BRI and NAFLD was a nonlinear connection. The risk of NAFLD increased significantly when BRI was lower than 4.82, after which the curve showed a modest ascent. Higher BRI was consistently associated with an increased risk of NAFLD in US adults. BRI is a risk factor for NAFLD, and there is an imperative to give more attention to lowering the BRI.

Patent foramen ovale (PFO) is a remnant of the fetal circulation exist in 20% of the general population. The purpose of our study was to compare of transthoracic echocardiography (TTE) and contrast-transcranial Doppler sonography (c-TCD) in the diagnosis and quantification of PFO with or without the Valsalva maneuver (VM). We studied 106 patients with a high clinical suspicion for PFO prospectively. Simultaneous c-TCD and TTE were conducted using agitated saline solution to detect right to left shunt (RLS). To classify RLS, mainly PFO, we applied a 4-level visual classification for c-TCD test: no occurrence of micro-embolic signals; grade I, 1 to 10 signals; grade II, 10 to 30 signals but not curtain; and grade III, curtain pattern. We used the number of micro-bubbles appeared in left atrium per frame image to define classification for TTE test: no occurrence of micro-bubbles; grade I, 1 to 10 micro-bubbles; grade II, 10 to 30 micro-bubbles; and grade III, more than 30 micro-bubbles or left atrium nearly filled with micro-bubbles or left atrial opacity. Statistical analyses were performed using SPSS Version 18.0. RLS was detected in 36.0% in c-TCD test and in 46% in TTE test at rest (P = 0.158). And during the VM, RLS was detected in 99.0% in c-TCD test and in 83.0% in TTE test (P < 0.001). Compared with the positive results of c-TCD and TTE at rest, the positive results of them with VM is more higher, respectively (all P < 0.001). The VM obviously increased the number of micro-bubbles shunting. Both c-TCD and TTE should used as initial screening tool for PFO. VM increases the size of shunt. VM resulted in detection of more RLS both in c-TCD and TTE tests.