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https://hdl.handle.net/11499/47714
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DC Field | Value | Language |
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dc.contributor.author | Kilic O. | - |
dc.contributor.author | Buber I. | - |
dc.contributor.author | Kahraman F. | - |
dc.date.accessioned | 2023-01-09T21:29:44Z | - |
dc.date.available | 2023-01-09T21:29:44Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 1022-386X | - |
dc.identifier.uri | https://doi.org/10.29271/jcpsp.2022.12.1519 | - |
dc.identifier.uri | https://hdl.handle.net/11499/47714 | - |
dc.description.abstract | Objective: To investigate the usability of leuko-glycemic index (LGI) at chronic coronary syndromes (CCS) class 1 for determining the extent and severity of coronary artery disease (CAD). Study Design: An observational study. Place and Duration of Study: Department of Cardiology, University of Pamukkale University Hospital, Turkey, between September 2021 and January 2022. Methodology: One hundred and thirty-four patients, whose myocardial perfusion scintigraphy (MPS) was requested due to CCS class 1, and on whom a coronary angiogram (CAG) was performed due to evidence of ischemia, were analysed. Blood samples were taken from the patients during their hospitalisation before CAG. LGI was calculated as mg/dl.mm3 by multiplying both values and dividing by a thousand. The patients were analysed in two groups according to the critical stenosis and non-critical stenosis detected in the coronary arteries. Results: The LGI was recorded as 480 mg/dl.mm3 (407-603) vs. 572 mg/dl.mm3 (433-877), p=0.006, and the Gensini score (6 (3-10) vs 40 (23-60), p<0.001) was significantly higher in the critical CAD group. A significant relationship has detected the increase in LGI and the extensity and severity of CAD (Unadjusted; OR (95% CI); 1.003 (1.001 – 1.004) p=0.002, adjusted; OR (95% CI); 1.002 (1.001 – 1.004) p=0.004). Conclusion: A high LGI was a predictor of CAD severity among CCS class 1 patients and was found to correlate with the Gensini score. The use of this simple and inexpensive index, together with other non-invasive tests before CAG, may provide some knowledge about the severity of CAD. © 2022 College of Physicians and Surgeons Pakistan. All rights reserved. | en_US |
dc.language.iso | en | en_US |
dc.publisher | College of Physicians and Surgeons Pakistan | en_US |
dc.relation.ispartof | Journal of the College of Physicians and Surgeons Pakistan | en_US |
dc.rights | info:eu-repo/semantics/openAccess | en_US |
dc.subject | Coronary artery disease | en_US |
dc.subject | Leukocyte glucose index | en_US |
dc.subject | Myocardial perfusion scintigraphy | en_US |
dc.subject | adult | en_US |
dc.subject | aged | en_US |
dc.subject | Article | en_US |
dc.subject | blood analysis | en_US |
dc.subject | cardiology | en_US |
dc.subject | chronic disease | en_US |
dc.subject | controlled study | en_US |
dc.subject | coronary angiography | en_US |
dc.subject | coronary artery disease | en_US |
dc.subject | coronary artery obstruction | en_US |
dc.subject | disease severity | en_US |
dc.subject | female | en_US |
dc.subject | heart muscle ischemia | en_US |
dc.subject | hospitalization | en_US |
dc.subject | human | en_US |
dc.subject | Leukocyte Glucose Index | en_US |
dc.subject | major clinical study | en_US |
dc.subject | male | en_US |
dc.subject | myocardial perfusion imaging | en_US |
dc.subject | observational study | en_US |
dc.subject | prediction | en_US |
dc.subject | retrospective study | en_US |
dc.subject | scoring system | en_US |
dc.subject | Turkey (republic) | en_US |
dc.subject | coronary artery disease | en_US |
dc.subject | diagnostic imaging | en_US |
dc.subject | leukocyte | en_US |
dc.subject | stenosis, occlusion and obstruction | en_US |
dc.subject | turkey (bird) | en_US |
dc.subject | glucose | en_US |
dc.subject | Constriction, Pathologic | en_US |
dc.subject | Coronary Artery Disease | en_US |
dc.subject | Glucose | en_US |
dc.subject | Humans | en_US |
dc.subject | Leukocytes | en_US |
dc.subject | Turkey | en_US |
dc.title | Predicting the Severity of Coronary Artery Disease: Can the Leukocyte Glucose Index be Used? | en_US |
dc.type | Article | en_US |
dc.identifier.volume | 32 | en_US |
dc.identifier.issue | 12 | en_US |
dc.identifier.startpage | 1519 | en_US |
dc.identifier.endpage | 1523 | en_US |
dc.identifier.doi | 10.29271/jcpsp.2022.12.1519 | - |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.authorscopusid | 57202998990 | - |
dc.authorscopusid | 57188731100 | - |
dc.authorscopusid | 55660928600 | - |
dc.identifier.pmid | 36474367 | en_US |
dc.identifier.scopus | 2-s2.0-85143411382 | en_US |
dc.identifier.wos | WOS:000933519600002 | en_US |
dc.identifier.scopusquality | Q3 | - |
item.languageiso639-1 | en | - |
item.fulltext | With Fulltext | - |
item.openairetype | Article | - |
item.cerifentitytype | Publications | - |
item.grantfulltext | open | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
crisitem.author.dept | 14.02. Internal Medicine | - |
Appears in Collections: | PubMed İndeksli Yayınlar Koleksiyonu / PubMed Indexed Publications Collection Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection Tıp Fakültesi Koleksiyonu WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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Predicting the Severity of Coronary.pdf | 471.13 kB | Adobe PDF | View/Open |
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