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Fan Z, Wu C, Wang C, Liu C, Fang L, Ma L, Zou W, Yuan B, Ji Z, Cai B, Liu G. Impact of Concurrent Ischaemic Stroke on Unfavourable Outcomes in Men and Women with Dilated Cardiomyopathy. Rev Cardiovasc Med 2024; 25:215. [PMID: 39076319 PMCID: PMC11270057 DOI: 10.31083/j.rcm2506215] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2023] [Revised: 01/27/2024] [Accepted: 02/01/2024] [Indexed: 07/31/2024] Open
Abstract
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.
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Affiliation(s)
- Zexin Fan
- Department of Neurology, The Second Hospital of Shanxi Medical University, 030001 Taiyuan, Shanxi, China
| | - Chao Wu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
| | - Chaobin Wang
- Department of Neurology, Beijing Fangshan District Liangxiang Hospital, 102401 Beijing, China
| | - Chun Liu
- Department of Neurology, Mechinka Hospital, Dnipro State Medical University, 49044 Dnipro, Ukraine
| | - Libo Fang
- Department of Neurology, Beijing Fuxing Hospital, Capital Medical University, 100038 Beijing, China
| | - Lin Ma
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
| | - Wenlong Zou
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
| | - Boyi Yuan
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
| | - Zeyu Ji
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
| | - Bin Cai
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
| | - Guangzhi Liu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, 100029 Beijing, China
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Fan ZX, Wang CB, Fang LB, Ma L, Niu TT, Wang ZY, Lu JF, Yuan BY, Liu GZ. Risk factors and a Bayesian network model to predict ischemic stroke in patients with dilated cardiomyopathy. Front Neurosci 2022; 16:1043922. [PMID: 36440270 PMCID: PMC9683474 DOI: 10.3389/fnins.2022.1043922] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 10/25/2022] [Indexed: 04/03/2024] Open
Abstract
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.
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Affiliation(s)
- Ze-Xin Fan
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Chao-Bin Wang
- Department of Neurology, Beijing Fangshan District Liangxiang Hospital, Beijing, China
| | - Li-Bo Fang
- Department of Neurology, Beijing Fuxing Hospital, Capital Medical University, Beijing, China
| | - Lin Ma
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Tian-Tong Niu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Ze-Yi Wang
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Jian-Feng Lu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Bo-Yi Yuan
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
| | - Guang-Zhi Liu
- Department of Neurology, Beijing Anzhen Hospital, Capital Medical University, Beijing, China
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Zhang HW, Kok VC, Chuang SC, Tseng CH, Lin CT, Li TC, Sung FC, Wen CP, Hsiung CA, Hsu CY. Long-term ambient hydrocarbons exposure and incidence of ischemic stroke. PLoS One 2019; 14:e0225363. [PMID: 31800599 PMCID: PMC6892494 DOI: 10.1371/journal.pone.0225363] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2019] [Accepted: 11/03/2019] [Indexed: 02/07/2023] Open
Abstract
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.
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Affiliation(s)
- Han-Wei Zhang
- Ph.D. Program for Aging, China Medical University, Taichung, Taiwan
- Department of Electrical and Computer Engineering, Institute of Electrical Control Engineering, National Chiao Tung University, Hsinchu, Taiwan
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
- * E-mail:
| | - Victor C. Kok
- Disease Informatics Research Group, Asia University Taiwan, Taichung, Taiwan
- Department of Internal Medicine, Kuang Tien General Hospital, Taichung, Taiwan
| | - Shu-Chun Chuang
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Chun-Hung Tseng
- Department of Neurology, China Medical University Hospital, and School of Medicine, China Medical University, Taichung, Taiwan
| | - Chin-Teng Lin
- Brain Research Center, National Chiao Tung University, Hsinchu, Taiwan
- Department of Electrical and Computer Engineering, Institute of Electrical Control Engineering, National Chiao Tung University, Hsinchu, Taiwan
- Centre for Artificial Intelligence School of Software, Faculty of Engineering & IT, University of Technology Sydney Broadway 2007, Sydney, New South Wales, Australia
| | - Tsai-Chung Li
- Graduate Institute of Biostatistics, College of Public Health, China Medical University, Taichung, Taiwan
- Department of Healthcare Administration, College of Health Science, Asia University, Taichung, Taiwan
| | - Fung-Chang Sung
- Graduate Institute of Clinical Medical Science and School of Medicine, College of Medicine, China Medical University, Taichung, Taiwan
| | - Chi Pang Wen
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Chao A. Hsiung
- Institute of Population Health Sciences, National Health Research Institutes, Zhunan, Taiwan
| | - Chung Y. Hsu
- Graduate Institute of Biomedical Science, China Medical University, Taichung, Taiwan
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