EXPLORING THE UTILITY OF A CVD RISK PREDICTING RETINAL AI MODEL IN IDENTIFYING CACS OVER 400 IN PATIENTS WITH AND WITHOUT DIABETES

IF 5.9 Q1 CARDIAC & CARDIOVASCULAR SYSTEMS

American journal of preventive cardiology Pub Date : 2025-09-01 DOI:10.1016/j.ajpc.2025.101179

Dongjin Nam MD , Sahil Thakur MBBS, MS, PhD , A.V. Rukmini MBBS, MD, PhD , Jaewon Seo BE , Jungkyung Cho MD , Junseok Park MD , Tae Hyun Park MD , Tyler Hyungtaek Rim MD, MBA, PhD , Sung Soo Kim MD, PhD , Chan Joo Lee MD, MM, PhD , Sungha Park MD, MM, PhD

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引用次数: 0

Abstract

Therapeutic Area

ASCVD/CVD Risk Assessment

Background

Dr. Noon CVD, a CVD risk prediction model based on retinal-imaging has been shown to estimate probability of coronary artery calcium (CAC). Dr.Noon risk categories (low, moderate, high) have shown performance comparable to conventional CAC risk categories (0, 1-99, ≥100) in predicting 5- year cardiovascular risk. For guiding intensive preventive strategies, CACS ≥400 is considered clinically significant. The current study explored the utility of Dr. Noon CVD to identify CACS ≥400 in patients with and without diabetes mellitus (DM).

Methods

This analysis included 1,252 participants from the CMERC-HI cohort classified into six groups based on Dr. Noon CVD risk level (low [<31], moderate [<41], high [41–51], very high [>51]) and DM status. non-DM with low (1a), moderate (2a), high (3a) and very high (4a) risk; and DM with low (1b), moderate (2b), high (3b) and very high (4b) risk. We performed ROC analysis of the Dr. Noon CVD score for predicting CACS ≥400 and compared AUCs by DM status. Prevalence of CACS ≥400 was assessed for each group and logistic regression models calculated odds ratios (ORs), adjusting for cardiovascular risk factors.

Results

CACS ≥400 was present in 189 patients (15.1%). AUC was 0.787 (non-DM) and 0.758 (DM) with no significant difference (p=0.4186). Sensitivity and specificity across Dr. Noon CVD risk categories were comparable between DM and non-DM groups. The proportion of patients with CACS ≥400 increased incrementally from Group 1a (0.6%, 1 of 155) to Group 4b (43.0%, 64 of 149). In non-DM patients, both high- and very high-risk groups showed significantly higher odds of CACS ≥400, with clear separation even between high and very high-risk (OR=4.17, p<0.001). In DM patients, only the very high-risk group showed significant elevation vs. high-risk (OR=3.81, p<0.001), while high-risk alone was not distinguishable from lower-risk groups.

Conclusions

In addition to identifying 5y-CVD risk, Dr. Noon CVD could also be used to identify patients at increased risk of having a CACS ≥400. Future studies could evaluate the effectiveness of using Dr. Noon CVD when stratified using both Dr. Noon CVD risk category and diabetes status. Further analysis could support its clinical applicability for targeted preventive interventions.

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探索CVD风险预测视网膜ai模型在糖尿病患者和非糖尿病患者中识别cacs超过400的效用

治疗领域ascvd /CVD风险评估基于视网膜成像的CVD风险预测模型已经被证明可以估计冠状动脉钙化（CAC）的概率。Dr.Noon风险分类（低、中、高）在预测5年心血管风险方面的表现与传统CAC风险分类（0,1 -99,≥100）相当。对于指导强化预防策略，CACS≥400被认为具有临床意义。目前的研究探讨了Dr. Noon CVD在伴有和不伴有糖尿病（DM）的患者中识别CACS≥400的效用。方法本分析纳入了来自CMERC-HI队列的1252名参与者，根据Dr. Noon心血管疾病风险水平（低[<；31]、中度[<；41]、高[41 - 51]、极高[>；51]）和糖尿病状态分为6组。低（1a）、中（2a）、高（3a）和极高（4a）风险的非糖尿病患者；DM为低（1b）、中（2b）、高（3b）和极高（4b）风险。我们对Dr. Noon CVD评分进行ROC分析，以预测CACS≥400，并比较糖尿病状态的auc。评估各组CACS≥400的患病率，并通过logistic回归模型计算优势比（ORs），调整心血管危险因素。结果scacs≥400的患者189例（15.1%）。AUC分别为0.787（非DM）和0.758 (DM)，差异无统计学意义（p=0.4186）。Dr. Noon心血管疾病风险类别的敏感性和特异性在糖尿病组和非糖尿病组之间具有可比性。CACS≥400的患者比例从1a组（0.6%，155人中的1人）逐渐增加到4b组（43.0%，149人中的64人）。在非糖尿病患者中，高、高危组CACS≥400的几率均显著高于高危组，甚至在高、高危组之间也有明显的差异（OR=4.17, p<0.001）。在DM患者中，只有非常高危组与高危组出现显著升高（OR=3.81, p<0.001），而高危组与低危组无明显区别。结论：除了识别5y-CVD风险外，Dr. Noon CVD还可用于识别CACS≥400风险增加的患者。未来的研究可以评估使用Dr. Noon心血管疾病风险类别和糖尿病状态分层时使用Dr. Noon心血管疾病的有效性。进一步的分析可以支持其在针对性预防干预方面的临床适用性。

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