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Background <p>Coronary artery calcification (CAC) is a pathological manifestation of coronary atherosclerosis in chronic kidney disease (CKD) patients. CAC on non-gated chest CT images can be precisely quantified through deep learning algorithms. Nevertheless, the relationship between deep learning-based coronary artery calcium score (DL-CACS) and the progression of CKD remains unclear.</p> Methods <p>Between January 2017 and June 2022, data from individuals with CKD were retrospectively collected. All enrolled participants had undergone non-gated chest CT scans and were stratified by DL-CACS at baseline: 0, 1-100, 101–400, and &gt; 400 Agatston units (AU). The primary outcome of this study was a composite endpoint related to CKD progression, defined as either a ≥ 50% decrease in eGFR from baseline or the initiation of kidney replacement therapy during follow-up. The secondary outcome was major adverse cardiovascular events (MACEs), including cardiac death, non-fatal myocardial infarction, revascularization, rehospitalization resulting from heart failure or aggravated angina and all-cause mortality.</p> Results <p>Among the 509 patients with CKD (median age: 64.00 [57.00-70.50] years old; 317 men) finally included in this study, 155 (30.5%) patients achieved primary outcome during the follow-up period of 2152 person-years. Compared to individuals without CAC, higher DL-CACS was greatly associated with CKD progression. In the fully adjusted hazard models, the hazard ratio of DL-CACS of 1-100 was 2.27 (95% confidence interval [CI], 1.26–4.10), 3.75 (95% CI, 2.01-7.00) for DL-CACS of 101–400, and 4.52 (95% CI, 2.45–8.33) for DL-CACS &gt; 400. The sensitivity analyses yielded similar results with primary findings. Of the 48 patients experienced the secondary outcome of MACEs, DL-CACS of 1-100, 101–400, and &gt; 400 were associated with HRs of 1.65 (95% CI, 0.39–7.06), 5.46 (95% CI, 1.41–21.14), and 11.60 (95% CI, 3.09–43.58), respectively, in the final hazard models.</p> Conclusions <p>Higher DL-CACS is associated with an increased risk of CKD progression. Associations with MACE were directionally consistent but imprecise, reflecting the limited events and wide confidence intervals.</p>

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Association between deep learning-based coronary artery calcium score on non-gated chest CT and progression of chronic kidney disease: a retrospective observational cohort study

  • 期刊论文

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  • 发表日期：

    2026年4月24日

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  • Kai Yang,
  • Meiling Li,
  • Jiayu Wang,
  • Yarong Yu,
  • Lihua Yu,
  • Xu Dai,
  • Dijia Wu,
  • Jiayin Zhang

摘要

Background

Coronary artery calcification (CAC) is a pathological manifestation of coronary atherosclerosis in chronic kidney disease (CKD) patients. CAC on non-gated chest CT images can be precisely quantified through deep learning algorithms. Nevertheless, the relationship between deep learning-based coronary artery calcium score (DL-CACS) and the progression of CKD remains unclear.

Methods

Between January 2017 and June 2022, data from individuals with CKD were retrospectively collected. All enrolled participants had undergone non-gated chest CT scans and were stratified by DL-CACS at baseline: 0, 1-100, 101–400, and > 400 Agatston units (AU). The primary outcome of this study was a composite endpoint related to CKD progression, defined as either a ≥ 50% decrease in eGFR from baseline or the initiation of kidney replacement therapy during follow-up. The secondary outcome was major adverse cardiovascular events (MACEs), including cardiac death, non-fatal myocardial infarction, revascularization, rehospitalization resulting from heart failure or aggravated angina and all-cause mortality.

Results

Among the 509 patients with CKD (median age: 64.00 [57.00-70.50] years old; 317 men) finally included in this study, 155 (30.5%) patients achieved primary outcome during the follow-up period of 2152 person-years. Compared to individuals without CAC, higher DL-CACS was greatly associated with CKD progression. In the fully adjusted hazard models, the hazard ratio of DL-CACS of 1-100 was 2.27 (95% confidence interval [CI], 1.26–4.10), 3.75 (95% CI, 2.01-7.00) for DL-CACS of 101–400, and 4.52 (95% CI, 2.45–8.33) for DL-CACS > 400. The sensitivity analyses yielded similar results with primary findings. Of the 48 patients experienced the secondary outcome of MACEs, DL-CACS of 1-100, 101–400, and > 400 were associated with HRs of 1.65 (95% CI, 0.39–7.06), 5.46 (95% CI, 1.41–21.14), and 11.60 (95% CI, 3.09–43.58), respectively, in the final hazard models.

Conclusions

Higher DL-CACS is associated with an increased risk of CKD progression. Associations with MACE were directionally consistent but imprecise, reflecting the limited events and wide confidence intervals.