Frontiers in Cardiovascular Medicine最新文献

Objective: To evaluate the effect of malnutrition assessed by the Geriatric Nutritional Risk Index (GNRI) on major adverse cardiac and cerebrovascular events (MACCE) in the elderly patients after endovascular aortic aneurysm repair (EVAR).

Materials and methods: This was a retrospective cohort study of elderly patients who underwent EVAR in a tertiary hospital. Malnutrition status was assessed by the GNRI. The primary outcome was MACCE. The predictive ability of the GNRI was compared with both the Revised Cardiac Risk Index (RCRI) and the modified Frailty Index (mFI) using Receiver operating characteristic (ROC) curve.

Result: A total of 453 patients underwent EVAR November 2015 and January 2020 was retrospectively analyzed, equally divided into three (low/medium/high) groups according to GNRI values which ranked from low to high. Five (1.10%) patients were lost in follow-up after surgery, and the median length of follow-up was 28.00 (15.00-47.00) months. The high GNRI values reduced length of hospital stay following EVAR in comparison to patients in low GNRI values group (β 9.67, 95% CI 4.01-23.32, p = 0.0113; adjusted β -1.96, 95% CI -3.88, -0.05, p = 0.0454). GNRI status was associated with a significantly increased risk of long-term mortality after EVAR (Medium GNRI, unadjusted HR 0.40, 95%CI 0.23-0.70, p = 0.0014; adjusted HR 0.47, 95%CI 0.26-0.84, p = 0.0107; high GNRI, 0.27 95%CI 0.14-0.55; p = 0.0003; adjusted HR 0.32 95%CI 0.15-0.68, p = 0.0029). Both medium and high GNRI values were linked to significantly reduced risks of MACCE compared to low GNRI score patients (Medium GNRI, unadjusted HR 0.34, 95%CI 0.13-0.88, p = 0.00265; adjusted HR 0.37, 95%CI 0.14-0.96, p = 0.0408; High GNRI, 0.26 95%CI 0.09-0.78; p = 0.0168; adjusted HR 0.21 95%CI 0.06-0.73, p = 0.0029). Compared with the RCRI and mFI, the GNRI had better discrimination in predicting long-term MACCE. An area under the curve (AUC) for GNRI mFI, and RCRI is 0.707, 0.614 and 0.588, respectively. (Z statistic, GNRI vs. mFI, p = 0.0475; GNRI vs. RCRI, p = 0.0017).

Conclusion: Malnutrition assessed by the GNRI may serve as a useful predictor of long-term MACCE in elderly patients after EVAR, with preferable discrimination abilities compared with both RCRI and mFI.

Background: Previous studies have established a correlation between systemic lupus erythematosus (SLE) and cardiovascular health, but the potential causal effects of SLE on heart function and structure remain poorly understood. Cardiovascular magnetic resonance imaging (CMR), a novel non-invasive technique, provides a unique assessment of cardiovascular structure and function, making it an essential tool for evaluating the risk of heart disease. In this study, we performed a Mendelian randomization analysis to determine the causal relationship between SLE and CMR traits.

Methods: Genetic variants independently linked to SLE were selected from a genome-wide association study (GWAS) containing 5,201 cases and 9,066 controls as instrumental variables. A set of 82 CMR traits was obtained from a recent GWAS, serving as preclinical indicators and providing preliminary insights into the morphology and function of the four cardiac chambers and two aortic segments. Primary analysis employed a two-sample Mendelian randomization study using the inverse-variance weighted method. Heterogeneity testing, sensitivity analyses, and instrumental variable strength assessments confirmed the robustness of the findings.

Results: SLE exhibited a correlation with increased stroke volume (β_LVSV = 0.007, P = 0.045), regional peak circumferential strain (β_{Ecc_AHA_9} = 0.013, P = 0.002; β_{Ecc_AHA_12} = 0.009, P = 0.043; β_{Ecc_AHA_14} = 0.013, P = 0.006), and global peak circumferential strain of the LV (β_{Ecc_global} = 0.010, P = 0.022), as well as decreased regional radial strain (β_{Err_AHA_11} = -0.010, P = 0.017).

Conclusions: This research presents evidence of a potential causal association between traits of SLE and alterations in cardiac function, guiding cardiac examinations and disease prevention in lupus patients.

Background: Cardiac rupture (CR) after acute myocardial infarction (AMI) is a fatal mechanical complication. The early identification of factors related to CR in high-risk cases may reduce mortality. The purpose of our study was to discover relevant risk factors for CR after AMI and in-hospital mortality from CR.

Methods: In this study, we enrolled 1,699 AMI cases from October 2013 to May 2020. A total of 51 cases were diagnosed with CR. Clinical diagnostic information was recorded and analyzed retrospectively. We randomly matched these cases with AMI patients without CR in a 1:4 ratio. Univariate and multivariate logistic regression and stratifying analysis were used to identify risk factors for CR. Univariate and multivariate Cox regression hazard analysis and stratifying analysis were used to assess predictors of in-hospital mortality from CR.

Results: The incidence of CR after AMI was 3.0% and in-hospital mortality was approximately 57%. Multivariate logistic regression analysis identified that white blood cell count, neutrophil percentage, anterior myocardial infarction, a Killip class of >II, and albumin level were independently associated with CR (p < 0.05). Stratifying analysis showed that age, systolic blood pressure, and bicarbonate were independent risk factors for female CR (p < 0.05) but not male CR. Triglyceride and cardiac troponin I were independent risk factors for male CR (p < 0.05) but not female CR. Anterior myocardial infarction, a Killip class of >II, and neutrophil percentage were independent risk factors for male and female CR (p < 0.05). Multivariate Cox regression analysis showed that the time from symptom to CR and the site of CR were independent predictors for in-hospital mortality from CR (p < 0.05). Stratification analysis indicated that risk factors did not differ based on gender, but platelet counts were predictors for in-hospital mortality in female and male CR.

Conclusion: Low albumin, a high white blood cell count, neutrophil percentage, anterior myocardial infarction, and a Killip class of >II were independent and significant predictors for CR. However, risk factors are different in male and female CR. The time from symptom to CR, the site of CR, and platelet counts were independent predictors for in-hospital mortality from CR. These may be helpful in the early and accurate identification of high-risk patients with CR and the assessment of prognosis. In addition, gender differences should be considered.

Background: The Mendelian randomization approach uses genetic variants as instrumental variables to study the causal association between the risk factors and health outcomes of interest. We aimed to examine the relation between alcohol consumption and cardiovascular risk factors using two genetic variants as instrumental variables: alcohol dehydrogenase 1B (ADH1B) rs1229984 and aldehyde dehydrogenase 2 (ALDH2) rs671.

Methods: Using data collected in the Taiwan Biobank-an ongoing, prospective, population-based cohort study-our analysis included 129,032 individuals (46,547 men and 82,485 women) with complete data on ADH1B rs1229984 and ALDH2 rs671 genotypes and alcohol drinking status. We conducted instrumental variables regression analysis to examine the relationship between alcohol drinking and body mass index (BMI), systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glucose, glycated hemoglobin (HbA1c), triglycerides, high-density lipoprotein cholesterol (HDLc), and low-density lipoprotein cholesterol (LDLc).

Results: In the rs1229984-instrumented analysis, alcohol drinking was only associated with higher levels of SBP in men and lower levels of DBP in women. In the rs671-instrumented analysis, alcohol drinking was associated with higher levels of BMI, SBP, DBP, fasting glucose, triglycerides, HDLc and lower levels of LDLc in men; alcohol drinking was associated with higher levels of HDLc and lower levels of SBP, HbA1c, and triglycerides in women.

Conclusion: Using Mendelian randomization analysis, some of our study results among men echoed findings from the previous systematic review, suggesting that alcohol drinking may be causally associated with higher levels of BMI, SBP, DBP, fasting glucose, triglycerides, HDLc, and lower levels of LDLc. Although alcohol drinking is beneficial to a few cardiovascular risk factors, it is detrimental to many others. The assumptions that underlie the Mendelian randomization approach should also be carefully examined when interpreting findings from such studies.

Objective: This study aimed to develop a predictive model for assessing bleeding risk in dual antiplatelet therapy (DAPT) patients.

Methods: A total of 18,408 DAPT patients were included. Data on patients' demographics, clinical features, underlying diseases, past history, and laboratory examinations were collected from Affiliated Dongyang Hospital of Wenzhou Medical University. The patients were randomly divided into two groups in a proportion of 7:3, with the most used for model development and the remaining for internal validation. LASSO regression, multivariate logistic regression, and six machine learning models, including random forest (RF), k-nearest neighbor imputing (KNN), decision tree (DT), extreme gradient boosting (XGBoost), light gradient boosting machine (LGBM), and Support Vector Machine (SVM), were used to develop prediction models. Model prediction performance was evaluated using area under the curve (AUC), calibration curves, decision curve analysis (DCA), clinical impact curve (CIC), and net reduction curve (NRC).

Results: The XGBoost model demonstrated the highest AUC. The model features were comprised of seven clinical variables, including: HGB, PLT, previous bleeding, cerebral infarction, sex, Surgical history, and hypertension. A nomogram was developed based on seven variables. The AUC of the model was 0.861 (95% CI 0.847-0.875) in the development cohort and 0.877 (95% CI 0.856-0.898) in the validation cohort, indicating that the model had good differential performance. The results of calibration curve analysis showed that the calibration curve of this nomogram model was close to the ideal curve. The clinical decision curve also showed good clinical net benefit of the nomogram model.

Conclusions: This study successfully developed a predictive model for estimating bleeding risk in DAPT patients. It has the potential to optimize treatment planning, improve patient outcomes, and enhance resource utilization.

Background and aims: Ultrasound derived carotid intima-media thickness (cIMT) is valuable for cardiovascular risk stratification. We assessed the relative importance of traditional atherosclerosis risk factors and plasma proteins in predicting cIMT measured nearly a decade later.

Method: We examined 6,136 UK Biobank participants with 1,461 proteins profiled using the proximity extension assay applied to their baseline blood draw who subsequently underwent a cIMT measurement. We implemented linear regression, stepwise Akaike Information Criterion-based, and the least absolute shrinkage and selection operator (LASSO) models to identify potential proteomic as well as non-proteomic predictors. We evaluated our model performance using the proportion variance explained (R ²).

Result: The mean time from baseline assessment to cIMT measurement was 9.2 years. Age, blood pressure, and anthropometric related variables were the strongest predictors of cIMT with fat-free mass index of the truncal region being the strongest predictor among adiposity measurements. A LASSO model incorporating variables including age, assessment center, genetic risk factors, smoking, blood pressure, trunk fat-free mass index, apolipoprotein B, and Townsend deprivation index combined with 97 proteins achieved the highest R ² (0.308, 95% C.I. 0.274, 0.341). In contrast, models built with proteins alone or non-proteomic variables alone explained a notably lower R ² (0.261, 0.228-0.294 and 0.260, 0.226-0.293, respectively). Chromogranin b (CHGB), Cystatin-M/E (CST6), leptin (LEP), and prolargin (PRELP) were the proteins consistently selected across all models.

Conclusion: Plasma proteins add to the clinical and genetic risk factors in predicting a cIMT measurement. Our findings implicate blood pressure and extracellular matrix-related proteins in cIMT pathophysiology.

With the development of neonatal medicine, more and more extremely preterm infants have been treated. How to deal with hypotension is a big challenge for neonatologist in the process of diagnosis and treatment. The lack of uniformity in the definition of hypotension, challenges in measuring blood pressure accurately, and insufficient consistency between digital hypotension and hypoperfusion are the primary causes. How to check for hypotension and monitor blood pressure is thoroughly explained in the article. To give neonatologists a resource for the clinical management of hypotension in extremely preterm.

Background: There is limited knowledge regarding the association between heart rate (HR) during different exercise phases and coronary artery disease (CAD). This study aimed to evaluate the relationship between four exercise-related HR metrics detected by cardiopulmonary exercise testing (CPET) and CAD. These metrics include HR at the anaerobic threshold (HR_AT), HR at respiratory compensatory point (HR_RCP), maximal HR (HR_max), and HR 60 s post-exercise (HR_Rec60s).

Methods: The 705 participants included 383 with CAD and 322 without CAD in Beijing Hospital, who underwent CPET between January 2021 and December 2022. The Logistic regression analysis was applied to estimate the odds ratio and the 95% confidence interval. Additionally, the multivariable Logistic regression analyses with restricted cubic splines were conducted to characterize the dose-response association and explore whether the relationship was linear or nonlinear.

Results: Our primary finding indicates that for each one-beat increase in HR_AT, there is a 2.8% reduction in the adjusted risk of CAD in the general population. Similarly, a one-beat increase in HR_RCP corresponds to a 2.6% reduction in the adjusted risk of CAD. Subgroup analyses revealed significant interactions between HR_AT and factors such as sex, hypertension, and lung cancer, as well as between HR_RCP and sex and hypertension, in relation to CAD. The dose-response analysis further confirmed that higher HR_AT and HR_RCP are associated with a reduced risk of CAD.

Conclusion: These results are suggestive of a good association between HR_AT, HR_RCP, and CAD. The lower HR_AT, and HR_RCP are signs of poor HR response to exercise in CAD. HR_AT and HR_RCP are potentially good indicators of poor HR response to exercise without considering maximal effort.

Background: Previous studies proposed the predictive value of baseline serum uric acid (SUA) in the prognosis of coronary artery bypass grafting (CABG) patients. The association of perioperative SUA variation with in-hospital adverse outcomes in CABG patients is unknown.

Methods: A total of 2,453 patients were included in the study and were divided into four groups (G1-G4) according to perioperative SUA variation (ΔSUA) (G1, ΔSUA ≤ -90 μmol/L; G2, -90 μmol/L < ΔSUA < 0; G3, 0 ≤ ΔSUA < 30 μmol/L; G4, 30 μmol/L ≤ ΔSUA.) The basic characteristics and incidence of adverse outcomes were compared between the groups in the overall population and the subgroups. Multivariate logistic regression was performed to explore the association between perioperative SUA increases and adverse outcomes, and receiver operating characteristic analysis was used to obtain the cutoff value of SUA increases.

Results: The patients had a mean age of 60.9 years and the majority were males (76.7%). In the group with the most significant increase in SUA (G4), incidences of in-hospital all-cause death and fatal arrhythmia were higher than in other groups in the overall population and the subgroups. Multivariate logistic regression showed that an increase in the SUA level of ≥30 µmol/L was significantly associated with in-hospital all-cause death and fatal arrhythmia, independent of the baseline SUA level and renal function. This association was significant in most subgroups for in-hospital fatal arrhythmia and in the ≥60 years, myocardial infarction, and female subgroups for in-hospital all-cause death. The cutoff values of SUA increases in the overall population were 54.5 µmol/L for in-hospital all-cause death and 42.6 µmol/L for in-hospital fatal arrhythmia.

Conclusions: The perioperative SUA increase significantly correlated with a higher incidence of in-hospital all-cause death and fatal arrhythmia in CABG patients, independent of the baseline SUA level and renal function. Perioperative SUA variation may provide complementary information in the identification of patients potentially at risk.