Frontiers in Cardiovascular Medicine最新文献

Objectives: To develop and validate a nomogram for predicting hospitalization-associated disability in older patients with acute heart failure.

Design: A single-center cohort study.

Setting and participants: This study was carried out in the Cardiovascular Disease Center of a large tertiary-care hospital in China. Between December 2024 and February 2025, 480 older patients with acute heart failure were enrolled.

Methods: Hospitalization-associated disability was defined as a decline of 5 points or more in the Barthel Index from admission to discharge. Predictor screening involved univariable logistic regression, Spearman's correlation, and Least Absolute Shrinkage and Selection Operator regression. Variables retained were entered into a multivariable logistic regression model, and significant predictors were used to construct a nomogram for predicting hospitalization-associated disability. Model performance was assessed in terms of discrimination, calibration, and clinical utility.

Results: The incidence of hospitalization-associated disability was 41.88%. A 12-variable nomogram was developed, incorporating age, ejection fraction, emergency admission, comorbidity burden, cognitive function, nutritional risk, pre-admission activities of daily living, pre-admission instrumental activities of daily living, physical mobility, sleep disturbance, depressive symptoms, and perceived social support. The nomogram demonstrated robust discrimination, with the area under the receiver operating characteristic curve of 0.841 and 0.786 in the training and testing sets, respectively. Calibration was accurate in both sets. The training set achieved a mean absolute error of 0.037 and a Brier score of 0.154, while the testing set showed 0.026 and 0.188, accompanied by non-significant Hosmer-Lemeshow test results. Decision curve and clinical impact analyses further supported favorable clinical utility.

Conclusions and implications: A 12-variable nomogram was developed and validated in older individuals with acute heart failure, enabling early identification of hospitalization-associated disability risk and supporting personalized care strategies.

Background: This study intends to establish and validate an interpretable machine learning (ML) model based on clinical features for early prediction of the risk of post-percutaneous coronary intervention (PCI) in-hospital heart failure (HF) in patients with acute ischemic heart disease (AIHD).

Methods: This study retrospectively included AIHD patients who underwent PCI at the Affiliated Guangzhou Hospital of TCM of Guangzhou University of Chinese Medicine from January 2023 to May 2025. LASSO regression was utilized for feature screening first, and then seven predictive models for HF risk in AIHD patients were established using ML algorithms. The model performance was fully assessed on the validation set through the area under the curve (AUC) with 95% CI, calibration curve and expected calibration error, recall, F1-score, positive predictive value, negative predictive value, and accuracy, and internal validation was conducted using the Bootstrap method. In addition, feature importance was evaluated by SHapley Additive exPlanations (SHAP) values, and individualized predictions were explained by Local Interpretable Model-Agnostic Explanations (LIME).

Results: Two hundred and three patients with AIHD were ultimately included, of whom 55 (27.1%) experienced in-hospital HF. Of the seven ML models, the random forest (RF) model demonstrated optimal performance on the validation set, with an AUC of 0.70 (95% CI 0.53-0.84) and an accuracy of 0.77; the calibration curve revealed high agreement between predicted and actual risks. Twelve predictive features associated with endpoint events were identified by LASSO regression, and the top five features contributing to the predictive efficacy of the RF model were age, monocyte count, heart rate, platelet count, and mean platelet volume according to the ranking of feature importance. In addition, the contribution of features to the prediction of HF risk was visualized by SHAP summary plots and LIME.Finally, an open Web-based prediction tool was deployed.

Conclusion: This exploratory study developed a random forest (RF) model to predict the risk of post-PCI in-hospital HF in patients with AIHD. Based on the SHAP and LIME methods, the clinical interpretability of the model was significantly enhanced. Future research with larger sample sizes is warranted to optimize the training set and validate the generalizability of the model.

Introduction and objectives: The specific risk factors contributing to coronary artery disease (CAD) in individuals with metabolic-associated fatty liver disease (MAFLD) have not been comprehensively examined. Given the critical role of inflammation in the pathogenesis of atherosclerotic cardiovascular disease (ASCVD), the monocyte to high-density lipoprotein cholesterol ratio (MHR) has emerged as a novel and significant inflammatory biomarker linked to CAD. Therefore, the primary objective of this study was to identify the risk factors associated with CAD in the MAFLD population, to analyze and compare MHR levels in MAFLD patients with and without concurrent CAD, and to evaluate the diagnostic and predictive value of MHR for CAD incidence within this high-risk cohort.

Materials and methods: In total, 251 patients with MAFLD, comprising 151 individuals with CAD and 100 without CAD, were included in the study conducted at the First People's Hospital of Yangquan. The diagnosis of CAD was established through coronary angiography. Biochemical indices were collected and subjected to logistic regression analysis to identify markers that exhibited differential expression between MAFLD patients with CAD and those without CAD. These markers were subsequently integrated into a diagnostic model. The predictive efficacy of this model was evaluated using Decision Curve Analysis (DCA). Furthermore, the relationship between the MHR and other markers was examined using Spearman's correlation analysis.

Results: Gender, age, white blood cell count (WBC), total cholesterol (TC), and the MHR were identified as significant risk factors for CAD in patients with MAFLD. Based on the area under the curve (AUC) value, the diagnostic model incorporating these five risk factors demonstrated robust diagnostic performance, with an AUC of 0.809. The DCA further validated its diagnostic effectiveness. Additionally, MHR was found to possess substantial diagnostic value for the occurrence of CAD events in MAFLD patients, with an AUC of 0.701. Further analysis of MHR quartiles revealed that patients in the highest quartile exhibited a significantly elevated risk of CAD compared to those in the other three quartiles. Moreover, significant correlations were observed between MHR and body mass index, WBC, uric acid, creatinine and triglycerides.

Conclusion: The findings confirmed the importance of gender, age, WBC, TC, and MHR in predicting the occurrence of CAD in MAFLD populations, with MHR showing higher predictive value.

Objective: To evaluate the effectiveness and safety of combining Shixiao Powder with Western medicine for treating coronary heart disease-induced angina.

Methods: The databases CNKI, VIP, Wanfang, SinoMed, PubMed, Embase, Web of Science, and Cochrane were searched until March 19th, 2024 for randomized controlled studies on the treatment of angina pectoris in coronary heart disease using Shixiao Powder combined with Western medicine. Quality assessment was conducted using the Cochrane Collaboration's tool. Heterogeneity was tested using the Chi-squared-based Q statistic test and I2 statistic.

Results: The study included a total of 15 articles, with 1204 patients in the cohort, divided into 625 cases in the observation group and 579 cases in the control group. Compared to Western medicine alone, the combination of Shixiao powder and Western medicine significantly improved the effective rate in treating angina pectoris of coronary heart disease [RR = 1.25, 95%Cl (1.18-1.32), P < 0.00001]. The improvement in ECG ST segment was superior [RR = 1.32, 95%Cl (1.21-1.43), P < 0.00001]. Additionally, there was a decrease in serum CRP level [WMD=-0.8, 95%Cl (-1.43-0.18), Z = 2.52, P = 0.012 < 0.05]. The assessment of publication bias concluded that there was no publication bias, suggesting that the conclusions of this study are accurate and reliable.

Conclusion: The current evidence supports that combining Shixiao Powder with Western medicine effectively and safely treats angina pectoris associated with coronary heart disease.

Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/recorddashboard, PROSPERO CRD42024537794.

Objectives: Postoperative neurological complications (PONC), which are associated with substantial morbidity and mortality, represent a prevalent clinical challenge following surgical repair of acute type A aortic dissection (AAD). This study aimed to identify novel biomarkers for the early diagnosis of PONC, facilitating timely clinical intervention.

Methods: We established deep hypothermic circulatory arrest (DHCA) rat models, extracted total RNA from the hippocampus of rats (DHCA and control groups), performed microRNA (miRNA) sequencing, screened for differentially expressed genes (DEGs) between the two groups, and analysed their associated biological processes and pathways. A cohort of 95 patients with AAD was included in this study. Comprehensive clinical assessments and a standardized neuropsychological test battery were systematically conducted. Serum miR-29 levels were quantified via reverse transcription quantitative real-time polymerase chain reaction.

Results: Transcriptomic profiling of the rat hippocampus under DHCA/cardiopulmonary bypass (CPB) revealed 31 differentially expressed miRNAs (FC > 1.5, P < 0.05), with miR-29a-5p and miR-29b-3p showing the most significant dysregulation. Functional enrichment analysis revealed that MAPK signalling and cellular junction pathways are involved in blood-brain barrier modulation. To translate these findings clinically, we analysed a cohort of 95 AAD patients. Compared with patients without PONC, those who developed PONC had significantly longer CPB duration [164.00 (137.00-193.00) vs. 140.00 (120.25-161.00) min; P = 0.012], higher preoperative interleukin-6 levels [106.60 (87.80-154.90) vs. 47.00 (35.45-71.73) pg/mL; P < 0.001], and altered miR-29 expression profiles. Multivariate analysis confirmed that preoperative miR-29b-3p (OR = 2.53, 95% CI 1.17-5.47) and postoperative miR-29a-5p (OR = 0.21, 95% CI 0.05-0.96) were independent predictors of PONC. The nomogram demonstrated robust discrimination (AUC = 0.867) and clinical utility (net benefit = 0.23), with 30-day survival analysis revealed an increased risk of mortality associated with miR-29b-3p (P = 0.041).

Conclusions: This study identified dysregulated miR-29 as a key mechanism linked to PONC after CPB/DHCA and validated circulating miR-29b-3p as an independent predictor of PONC and mortality in AAD patients, providing a basis for early risk assessment.

Aims: Systemic inflammation (SI), indicated by elevated C-reactive protein (CRP) levels, is known to increase the risk of major adverse cardiovascular events (MACE) and mortality. This study aims to investigate the association between SI and mortality in the Danish population diagnosed with atherosclerotic cardiovascular disease ASCVD and chronic kidney disease CKD.

Methods: We identified 19,159 individuals with incident ASCVD and CKD between 2012 and 2022 in Danish national health registers. SI was defined by at least two CRP measurements between 2 mg/L and 20 mg/L within a six-month period. Cox proportional hazards models were employed to assess the relationship between SI and mortality, adjusting for relevant confounders.

Results: Among the cohort, 68% were observed with SI. SI were associated with significantly higher risk of mortality, with a hazard ratio (HR) of 2.06 (95% CI: 1.92-2.21) for death and 1.66 (95% CI: 1.57-1.77) for 'MACE or death'. The results were consistent in all subgroup analyses and sensitivity analyses, including in men and women separately, and using different definitions of SI.

Conclusion: This study demonstrates that SI is prevalent among patients with ASCVD and CKD being strongly associated with higher risk of mortality and MACE. These findings suggest that SI could serve as a valuable marker to identify patients with ASCVD and CKD who are at particularly high risk and may benefit from targeted preventive interventions.

Atrial fibrillation (AF) and coronary artery disease (CAD) are among the most frequent cardiovascular diseases and leading causes of morbidity/mortality worldwide. The concomitant presence of AF and CAD is relatively common, as the association is supported not only by shared atherosclerotic risk factors, but also by a pathophysiological link. Patients with a history of AF have been described as at increased risk of CAD, in particular acute myocardial infarction (AMI), through several mechanisms, such as increased oxidative stress, systemic inflammation, increased platelet aggregation. On the other hand, up to 10% of patients with AMI are at risk of developing new-onset atrial fibrillation (NOAF). In the past, any type of NOAF during AMI was considered identical and equally associated with a worse outcome. More recently, increasing evidence supports the pathophysiological and nosological difference between early NOAF (occurring within the first 24 h after the index event and associated with atrial ischaemia, oxidative stress and a better outcome) and late NOAF (occurring after 24 h and correlated with increased left atrial pressures, deterioration of haemodynamic status, elevated left ventricular filling pressures and a worse outcome). In this review, we summarise the available evidence on the epidemiology, pathophysiology, risk stratification, and management of the complex two-way relationship between AF and CAD.

Objective: The Albumin-to-D-dimer ratio (ADR), a novel systemic inflammatory marker, has been linked to adverse outcomes in patients with cardiovascular disease. However, limited research has explored its prognostic value in ST-elevation myocardial infarction (STEMI) survivors following hospital discharge. This study aimed to evaluate the prognostic significance of ADR in hospital-discharged STEMI patients.

Methods: In this retrospective study, we analyzed data from 2,675 STEMI patients admitted to our hospital between January 2014 and December 2021. Patients were stratified into two groups based on their natural logarithmic ADR (Ln ADR): a high Ln ADR group (≥3.998) and a low Ln ADR group (<3.998). Univariate and multivariate Cox regression analyses were performed to assess the association between Ln ADR levels and clinical outcomes, including all-cause mortality and new-onset stroke.

Results: Over a mean follow-up period of 1,013 days (interquartile range: 466-1,449 days), the incidence of major adverse cardiovascular events (MACE) was significantly higher in the low Ln ADR group compared to the high Ln ADR group (20.87% vs. 12.33%, P < 0.001). This disparity was particularly evident in all-cause mortality (6.58% vs. 1.00%, P < 0.001) and new-onset stroke (4.19% vs. 0.90%, P < 0.001). Multivariate analysis revealed that low Ln ADR was an independent predictor of all-cause mortality (HR = 2.46, 95% CI: 1.25-4.81, P = 0.009) and new-onset stroke (HR = 2.93, 95% CI: 1.35-6.35, P = 0.006).

Conclusions: Reduced ADR levels were independently associated with increased long-term all-cause mortality and new-onset stroke in STEMI patients following hospital discharge. These findings suggest that ADR may serve as a valuable prognostic marker for risk stratification in this population.

Objective: To compare the application value differences of PCAT radiomic features, clinical risk features and computed tomography (CT)-derived parameters in predicting Major adverse cardiovascular events (MACE) in patients with/without diabetes.

Methods: Retrospective analysis included 1,000 coronary atherosclerosis patients undergoing Coronary CT angiography (CCTA) (with/without diabetes: 274/726) from the Eighth Affiliated Hospital of Southern Medical University. Clinical/CT data were collected, extracting 285 PCAT radiomic features from three major coronaries. Least absolute shrinkage and selection operator regression identified MACE-associated radiomic features. Patients underwent random 6:4 training/testing cohort split. Four predictive models were constructed: Model 1 (clinical factors), Model 2 (imaging factors), Model 3 (imaging-radiomic features), Model 4 (all factors).

Results: In the training set, Model 4 showed the best performance: The area under the curves (AUC) of 0.803 [95% confidence interval (CI): 0.756-0.850] and 0.854 (95% CI: 0.779-0.929) for groups with/without diabetes, respectively. Model 3 outperformed Model 2 in patients without diabetes (p < 0.05), but not significantly in diabetic patients (p > 0.05).

Conclusion: PCAT radiomics, CT-derived parameters, and plaque features demonstrate differential predictive value for MACE in patients with/without diabetes. Combining these with clinical risk factors provides most effective model for both.

Aim: To assess the predictive value of serum lipoprotein(a) [Lp(a)] for contrast-induced nephropathy in patients with type 2 diabetes mellitus (T2DM).

Methods: Consecutive T2DM patients who underwent coronary angiography (CAG) or percutaneous coronary intervention (PCI) between January 2019 and December 2021 were enrolled. Baseline Lp(a) was measured before the operation. CIN was defined as an increase in serum creatinine of more than 25% or 44 μmol within 72 h of contrast administration. The relationship between Lp(a) and CIN risk was analyzed.

Results: A total of 928 T2DM patients were included. CIN developed in 11.1% (103/928) of patients. The Lp(a) level was significantly higher in patients with CIN than in non-CIN patients (311.12 ± 278.66 vs. 254.19 ± 274.56 mg/L, P = 0.048). Patients were divided into three groups based on Lp(a) levels: <150 mg/L (n = 428), 150 mg/L-300 mg/L (n = 266), and ≥300 mg/L (n = 234). Each group stratified by increasing Lp(a) concentrations had incrementally greater risks of CIN (7.2% vs. 12% vs. 17.1%, P < 0.001). Multivariate logistic regression analysis showed that patients with Lp(a) ≥300 mg/L had a 2.41-fold higher risk of CIN than those with Lp(a)< 150 mg/L (OR = 2.41, 95% CI: 1.38-4.21, P = 0.002). Additionally, for each increase of 1 logarithmic unit in Lp(a), the risk of CIN increased by 1.27 times (OR = 1.27, 95% CI: 1.01-1.64, P = 0.045).

Conclusions: A higher serum Lp(a) level indicates an increased risk of CIN in T2DM patients undergoing CAG or PCI and can serve as an independent predictor of CIN in this population. This study's findings will aid in the clinical prevention and treatment of contrast agent-induced kidney disease.