Abstract 4367146: Coronary Artery Calcium Scoring Accuracy in Iran: A Meta-Analysis and Systematic Review
Bibliographic record
Abstract
Introduction/Background: Coronary artery Calcium Scoring (CACS) has been recognized as a risk predictor of major cardiovascular events in high income countries. However, more research is needed on the applicability of CACS in countries with developing economies. Research Questions/Hypothesis: In this meta-analysis, we examine the prevalence of CAC and the diagnostic performance of CACS when compared to conventional or CT coronary angiography in Iran. Methods/Approach: The authors searched the PubMed, SCOPUS, and World of Science databases for peer-reviewed studies evaluating populations in Iran between 2010-2025 in accordance with PRISMA guidelines. We examined the relationship between CACS and obstructive (≥50% stenosis) coronary artery disease as diagnosed by CT or conventional coronary angiography. Results/Data: A total of 11 studies were included for a total of 7095 patients. Mean age was 57 ± 13.21, 61% male. Risk factors included hypertension (38.8%), hypercholesterolemia (38.7%), smoking, (24.7%) and/or diabetes (23.6%). All studies except one (90.9%) included patients with an intermediate pretest probability of cardiovascular disease. All studies except one (90.9%) used CT scanners with ≥ 64 detector rows. The pooled prevalence of CAC>0 was 56.3% (95% CI 47.9%-64.7%). 3039/7095 patients (43.1%, 95% CI 33.5-52.6) had CACS of 0. When compared to angiography results, of six studies with reported data, 33.5% (95%CI=13.6-53.4) of patients had no coronary artery stenosis. Of five studies reporting data, 50.2% (95%CI=32.3-68) of patients had obstructive coronary artery disease. Using angiography results as the gold standard, the pooled (random-effects model) negative predictive value (NPV) from five studies was 0.929 (95%CI=0.63-0.99). Sensitivity, specificity, and positive predictive value (PPV) were 0.921 (95%CI=0.876-0.966), 0.667 (95%CI=0.566-0.767), and 0.82 (95%CI=0.76-0.881). Overall heterogeneity was high (I2>75%) and study bias was moderate (Newcastle-Ottawa scale score mean 7.18). Conclusion: Among patients with at least an intermediate pretest probability of cardiovascular disease in Iran, prevalence of CACS=0 was similar to previously published studies in high income countries. However, pooled NPV was lower while pooled PPV was higher than previously published. Additional research is needed on understanding why pooled NPV and PPV vary from high income countries.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.013 | 0.026 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".