No abstract

Introduction Lateral abdominal radiograph is suggested as an alternative to coronary artery computed tomography (CT) in evaluating vascular calcification. Simple scoring systems including pelvic radiograph scoring and abdominal scoring system were utilized to study their correlation with coronary artery calcification. Methods In 106 MHD patients, coronary artery CT, lateral abdominal, and pelvic radiograph were taken. The Agatston scoring system was applied to evaluate the degree of coronary artery calcification which was categorized according to Agatston coronary artery calcification score (CACS) 30, 100, 400, and 1000. Abdominal aortic calcification was scored by 4-scored and 24-scored systems. Pelvic artery calcification was scored by a 4-scored system. Sensitivities and specificities of abdominal aortic calcification scores and pelvic artery calcification scores to predict different categories of coronary artery calcification were analyzed. We studied the diagnostic capability of abdominal aorta calcification and pelvic artery calcification to predict different CACS categories by calculating likelihood ratios. Receiver operator characteristic curves were used to determine the area under the curve for each of these testing procedures. Findings The prevalence was 48(45.3%), 15 (14.2%), 11 (10.4%), 11 (10.4%), and 11 (10.4%) for CACs > 0, 30, 100, 400, and 1000, respectively. The degree of CACs was positively correlated with patient age, prevalence of diabetes, abdominal aorta scores, and pelvic calcification scores. The areas under the curves for different CACS by all X-ray scoring systems were above 0.70 except pelvic 4-scored system for diagnosing CACS 30, without significant difference (P > 0.05). Discussion Both lateral abdominal and pelvic plain radiographs were demonstrated as acceptable alternatives to CT in evaluating vascular calcification.

Defining Vitamin K deficiency by %ucOC, suboptimal vitamin K levels appear common in Chinese MHD patients. Time on dialysis and LDL cholesterol level predict vitamin K deficiency.