دورية أكاديمية
Prevalence and Prediction of Obstructive Coronary Artery Disease in Patients Referred for Valvular Heart Surgery
| العنوان: | Prevalence and Prediction of Obstructive Coronary Artery Disease in Patients Referred for Valvular Heart Surgery |
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| المؤلفون: | Lappe, Jason M., Grodin, Justin L., Wu, Yuping, Silverman, Corinne Bott, Cho, Leslie |
| المصدر: | Mathematics Faculty Publications |
| بيانات النشر: | EngagedScholarship@CSU |
| سنة النشر: | 2015 |
| المجموعة: | Cleveland State University: EngagedScholarship@CSU |
| مصطلحات موضوعية: | Mathematics |
| الوصف: | Current guidelines recommend a coronary evaluation before valvular heart surgery (VHS). Diagnostic coronary angiography is recommended in patients with known coronary artery disease (CAD) and those with high pretest probability of CAD. In patients with low or intermediate pretest probability of CAD, the guidelines recommend coronary computed tomographic angiography. However, there are no tools available to objectively assess a patient’s risk for obstructive CAD before VHS. To address this deficit, 5,360 patients without histories of CAD who underwent diagnostic coronary angiography as part of preoperative evaluation for VHS were identified. Obstructive CAD was defined as ≥50% stenosis in ≥1 artery. Of the patients assessed, 1,035 (19.3%) were found to have obstructive CAD. Through multivariate analysis, age, gender, diabetes, renal dysfunction, hyperlipidemia, and a family history of premature CAD were found to be associated with the presence of obstructive CAD (p <0.001 for all). After adjustment, the specific dysfunctional valve was not associated with the presence of obstructive CAD. Patients were then randomly split into derivation and validation cohorts. Within the derivation cohort, using only age, gender, and the presence or absence of risk factors, a model was constructed to predict the risk for obstructive CAD (C statistic 0.766, 95% confidence interval 0.750 to 0.783). The risk prediction model performed well within the validation cohort (C statistic 0.767, 95% confidence interval 0.751 to 0.784, optimism 0.004). The bias-corrected C statistic for the model was 0.765 (95% confidence interval 0.748 to 0.782). In conclusion, this novel risk prediction tool can be used to objectively risk-stratify patients who undergo preoperative evaluation before VHS and to facilitate appropriate triage to computed tomographic angiography or diagnostic coronary angiography. |
| نوع الوثيقة: | text |
| وصف الملف: | application/pdf |
| اللغة: | unknown |
| العلاقة: | https://engagedscholarship.csuohio.edu/scimath_facpub/218Test; https://engagedscholarship.csuohio.edu/context/scimath_facpub/article/1226/viewcontent/uc.pdfTest |
| DOI: | 10.1016/j.amjcard.2015.03.063 |
| الإتاحة: | https://doi.org/10.1016/j.amjcard.2015.03.063Test https://engagedscholarship.csuohio.edu/scimath_facpub/218Test https://engagedscholarship.csuohio.edu/context/scimath_facpub/article/1226/viewcontent/uc.pdfTest |
| حقوق: | http://creativecommons.org/licenses/by-nc-nd/4.0Test/ |
| رقم الانضمام: | edsbas.410EA810 |
| قاعدة البيانات: | BASE |
| DOI: | 10.1016/j.amjcard.2015.03.063 |
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