Both pelvic radiography and lateral abdominal radiography correlate well with coronary artery calcification measured by computed tomography in hemodialysis patients: A cross‐sectional study
Bibliographic record
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".