Decreased eGFR Is Associated With Ischemic Stroke in Patients With Dilated Cardiomyopathy

Impact of Concurrent Ischaemic Stroke on Unfavourable Outcomes in Men and Women with Dilated Cardiomyopathy

Background

Growing evidence suggests that concurrent ischaemic stroke (IS) exacerbates the prognosis of patients with dilated cardiomyopathy (DCM) and that this effect may be further influenced by sex. However, the exact effect of sex remains unclear. This study aimed to explore the effects of the relevant risk factors on the prognosis of patients with DCM and concurrent IS. Considering the sex differences in DCM, this study further investigated the impact of concurrent IS on the prognosis of men and women with DCM.

Methods

A total of 632 patients with DCM enrolled between 2016 and 2021 were included in this study. Clinical data were obtained from medical records, and all participants were followed up in the outpatient clinic or by telephone for at least 1 year. A Cox proportional hazards model and Kaplan-Meier curves were used to evaluate the effects of concurrent IS on the prognosis of patients with DCM.

Results

Patients with DCM complicated with IS (DCM-IS) had significantly lower cumulative survival rates than patients with DCM without IS (non-IS) (74.6% vs. 84.2%, χ 2 = 6.85, p = 0.009). Additionally, IS was associated with greater risks of death and heart transplantation (HTx) in men (75.8% vs. 85.1%, χ 2 = 5.02, p = 0.025), but not in women (71.0% vs. 81.5%, χ 2 = 1.91, p = 0.167).

Conclusions

This large-scale multicentre prospective cohort study demonstrated a poorer prognosis in patients with concurrent DCM and IS, particularly among men. Patients with DCM should not be overlooked in IS screening, emphasis should be placed on the occurrence of IS in patients with DCM. Early and proactive secondary prevention of cerebrovascular diseases might improve the prognosis of DCM patients. More intervention studies focusing on men with DCM complicated with IS should be prioritised.

Risk factors and a Bayesian network model to predict ischemic stroke in patients with dilated cardiomyopathy

OBJECTIVE

This study aimed to identify risk factors and create a predictive model for ischemic stroke (IS) in patients with dilated cardiomyopathy (DCM) using the Bayesian network (BN) approach.

MATERIALS AND METHODS

We collected clinical data of 634 patients with DCM treated at three referral management centers in Beijing between 2016 and 2021, including 127 with and 507 without IS. The patients were randomly divided into training (441 cases) and test (193 cases) sets at a ratio of 7:3. A BN model was established using the Tabu search algorithm with the training set data and verified with the test set data. The BN and logistic regression models were compared using the area under the receiver operating characteristic curve (AUC).

RESULTS

Multivariate logistic regression analysis showed that hypertension, hyperlipidemia, atrial fibrillation/flutter, estimated glomerular filtration rate (eGFR), and intracardiac thrombosis were associated with IS. The BN model found that hyperlipidemia, atrial fibrillation (AF) or atrial flutter, eGFR, and intracardiac thrombosis were closely associated with IS. Compared to the logistic regression model, the BN model for IS performed better or equally well in the training and test sets, with respective accuracies of 83.7 and 85.5%, AUC of 0.763 [95% confidence interval (CI), 0.708-0.818] and 0.822 (95% CI, 0.748-0.896), sensitivities of 20.2 and 44.2%, and specificities of 98.3 and 97.3%.

CONCLUSION

Hypertension, hyperlipidemia, AF or atrial flutter, low eGFR, and intracardiac thrombosis were good predictors of IS in patients with DCM. The BN model was superior to the traditional logistic regression model in predicting IS in patients with DCM and is, therefore, more suitable for early IS detection and diagnosis, and could help prevent the occurrence and recurrence of IS in this patient cohort.

Long-term ambient hydrocarbons exposure and incidence of ischemic stroke

Exposure to air pollutants is known to have adverse effects on human health; however, little is known about the association between hydrocarbons in air and an ischemic stroke (IS) event. We investigated whether long-term exposure to airborne hydrocarbons, including volatile organic compounds, increased IS risk. This retrospective cohort study included 283,666 people aged 40 years or older in Taiwan. Cox proportional hazards regression analysis was used to fit single- and multiple-pollutant models for two targeted pollutants, total hydrocarbons (THC) and nonmethane hydrocarbons (NMHC), and estimated the risk of IS. Before controlling for multiple pollutants, hazard ratios (HRs) of IS with 95% confidence intervals for the overall population were 2.69 (2.64-2.74) at 0.16-ppm increase in THC and 1.62 (1.59-1.66) at 0.11-ppm increase in NMHC. For the multiple-pollutant models controlling for PM2.5, the adjusted HR was 3.64 (3.56-3.72) for THC and 2.21 (2.16-2.26) for NMHC. Our findings suggest that long-term exposure to THC and NMHC may be a risk factor for IS development.