Plasma atherogenic indices are independent predictors of slow coronary flow
Abstract Background Although the pathophysiology of coronary slow flow (CSF) has not been fully elucidated, emerging data increasingly support potential role for subclinical diffuse atherosclerosis in the etiology of CSF. We aimed to investigate relationship between atherogenic indices and CSF. Meth...
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| Format: | Article |
| Language: | English |
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BMC
2021-12-01
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| Series: | BMC Cardiovascular Disorders |
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| Online Access: | https://doi.org/10.1186/s12872-021-02432-5 |
| _version_ | 1818969366252748800 |
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| author | Abdulmecit Afsin Hakan Kaya Arif Suner Kader Eliz Uzel Nurbanu Bursa Yusuf Hosoglu Fethi Yavuz Ramazan Asoglu |
| author_facet | Abdulmecit Afsin Hakan Kaya Arif Suner Kader Eliz Uzel Nurbanu Bursa Yusuf Hosoglu Fethi Yavuz Ramazan Asoglu |
| author_sort | Abdulmecit Afsin |
| collection | DOAJ |
| description | Abstract Background Although the pathophysiology of coronary slow flow (CSF) has not been fully elucidated, emerging data increasingly support potential role for subclinical diffuse atherosclerosis in the etiology of CSF. We aimed to investigate relationship between atherogenic indices and CSF. Methods 130 patients with CSF diagnosed according to Thrombolysis in Myocardial Infarction (TIMI)-frame count (TFC) method and 130 controls who had normal coronary flow (NCF) were included in this retrospective study. Atherogenic indices (atherogenic index of plasma [AIP], Castelli risk indices I and II [CRI-I and II]) were calculated using conventional lipid parameters. Results The logistic regression analyses demonstrated that AIP (OR, 5.463; 95% confidence interval [CI], 1.357–21.991; p = 0.017) and CRI-II (OR, 1.624; 95% CI, 1.138–2.319; p = 0.008) were independent predictors of CSF. Receiver operating characteristic analysis showed that the optimal cutoff value to predict the occurrence of CSF was 0.66 for AIP (sensitivity, 59%; specificity, 73%; area under curve [AUC], 0.695; p < 0.001) and 3.27 for CRI-II (sensitivity, 60%; specificity, 79%; AUC, 0.726; p < 0.001). Conclusions AIP and CRI-II levels were independent predictors of CSF. Prospective studies in larger cohorts of patients may elucidate the role of atherogenic dyslipidemia in the pathophysiology of CSF. |
| first_indexed | 2024-12-20T14:19:26Z |
| format | Article |
| id | doaj.art-de63837dbc5745a694ef33b0192f74b6 |
| institution | Directory Open Access Journal |
| issn | 1471-2261 |
| language | English |
| last_indexed | 2024-12-20T14:19:26Z |
| publishDate | 2021-12-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Cardiovascular Disorders |
| spelling | doaj.art-de63837dbc5745a694ef33b0192f74b62022-12-21T19:37:57ZengBMCBMC Cardiovascular Disorders1471-22612021-12-012111910.1186/s12872-021-02432-5Plasma atherogenic indices are independent predictors of slow coronary flowAbdulmecit Afsin0Hakan Kaya1Arif Suner2Kader Eliz Uzel3Nurbanu Bursa4Yusuf Hosoglu5Fethi Yavuz6Ramazan Asoglu7Department of Cardiology, Adiyaman Training and Research HospitalDepartment of Cardiology, Faculty of Medicine, Adiyaman UniversityDepartment of Cardiology, Faculty of Medicine, Adiyaman UniversityDepartment of Cardiology, Adiyaman Training and Research HospitalDepartment of Statistics, Faculty of Science, Hacettepe UniversityDepartment of Cardiology, Adiyaman Training and Research HospitalDepartment of Cardiology, Faculty of Medicine, Adiyaman UniversityDepartment of Cardiology, Adiyaman Training and Research HospitalAbstract Background Although the pathophysiology of coronary slow flow (CSF) has not been fully elucidated, emerging data increasingly support potential role for subclinical diffuse atherosclerosis in the etiology of CSF. We aimed to investigate relationship between atherogenic indices and CSF. Methods 130 patients with CSF diagnosed according to Thrombolysis in Myocardial Infarction (TIMI)-frame count (TFC) method and 130 controls who had normal coronary flow (NCF) were included in this retrospective study. Atherogenic indices (atherogenic index of plasma [AIP], Castelli risk indices I and II [CRI-I and II]) were calculated using conventional lipid parameters. Results The logistic regression analyses demonstrated that AIP (OR, 5.463; 95% confidence interval [CI], 1.357–21.991; p = 0.017) and CRI-II (OR, 1.624; 95% CI, 1.138–2.319; p = 0.008) were independent predictors of CSF. Receiver operating characteristic analysis showed that the optimal cutoff value to predict the occurrence of CSF was 0.66 for AIP (sensitivity, 59%; specificity, 73%; area under curve [AUC], 0.695; p < 0.001) and 3.27 for CRI-II (sensitivity, 60%; specificity, 79%; AUC, 0.726; p < 0.001). Conclusions AIP and CRI-II levels were independent predictors of CSF. Prospective studies in larger cohorts of patients may elucidate the role of atherogenic dyslipidemia in the pathophysiology of CSF.https://doi.org/10.1186/s12872-021-02432-5Coronary slow flowFrame countAtherogenic index of plasmaCastelli risk indicesCoronary interventionCardiovascular risk factors |
| spellingShingle | Abdulmecit Afsin Hakan Kaya Arif Suner Kader Eliz Uzel Nurbanu Bursa Yusuf Hosoglu Fethi Yavuz Ramazan Asoglu Plasma atherogenic indices are independent predictors of slow coronary flow BMC Cardiovascular Disorders Coronary slow flow Frame count Atherogenic index of plasma Castelli risk indices Coronary intervention Cardiovascular risk factors |
| title | Plasma atherogenic indices are independent predictors of slow coronary flow |
| title_full | Plasma atherogenic indices are independent predictors of slow coronary flow |
| title_fullStr | Plasma atherogenic indices are independent predictors of slow coronary flow |
| title_full_unstemmed | Plasma atherogenic indices are independent predictors of slow coronary flow |
| title_short | Plasma atherogenic indices are independent predictors of slow coronary flow |
| title_sort | plasma atherogenic indices are independent predictors of slow coronary flow |
| topic | Coronary slow flow Frame count Atherogenic index of plasma Castelli risk indices Coronary intervention Cardiovascular risk factors |
| url | https://doi.org/10.1186/s12872-021-02432-5 |
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