ArticleJACC. Case reports2025
Machine Learning-Based CCTA-Guided Intensive Atheroprotective Strategy in a Middle-Aged INOCA Patient With Challenging Arterial Features.
Article in JACC. Case reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundManagement of ischemia with nonobstructive coronary arteries (INOCA) remains insufficiently defined in current guidelines, particularly when complicated by symptomatic myocardial bridging, evolving nonobstructive atherosclerosis, and systemic inflammation. Such overlapping mechanisms create complex diagnostic and therapeutic challenges that require individualized care. CASE SUMMARY: A 39-year-old man with recurrent chest discomfort, left anterior descending myocardial bridging, and suspected microvascular dysfunction was found to have progressive high-risk atherosclerosis and elevated systemic inflammatory burden, despite the absence of obstructive coronary disease. Multimodal imaging-including coronary computed tomography angiography with machine learning (ML)-based ischemia risk scoring and pericoronary adipose tissue analysis-enabled precise characterization of both functional and structural risk. A tailored, intensive regimen targeting lipid lowering, myocardial unloading, and inflammation control led to regression of high-risk plaque features, reduction in pericoronary adipose tissue attenuation, normalization of inflammatory markers, and complete resolution of symptoms over 15 months. WHY BEYOND THE GUIDELINES: No established guideline recommendations address INOCA with concurrent symptomatic myocardial bridging, subclinical plaque progression, and residual inflammatory risk. A multimodal, off-label pharmacologic strategy was required to stabilize disease activity and restore functional status. DISCUSSION: This case underscores the utility of phenotype-specific, imaging-guided therapy in complex INOCA presentations. Integration of ML-enhanced coronary computed tomography angiography and individualized prevention enabled both anatomic regression and physiologic recovery in a high-risk but nonobstructive phenotype. TAKE-HOME MESSAGES: INOCA with symptomatic myocardial bridging and inflammation may require off-label, intensive therapy. ML-enhanced multimodal imaging facilitates dynamic risk stratification and tailored treatment adjustments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.