An OCT-based calcium scoring system can help to identify lesions that would benefit from plaque modification prior to stent implantation. Lesions with calcium deposit with maximum angle >180°, maximum thickness >0.5 mm, and length >5 mm may be at risk of stent underexpansion.
Angiographic detection of target lesion coronary calcium (compared to intravascular imaging) has not changed in the past 2 decades, and angiographically invisible calcium (only detectable by IVUS or OCT) did not appear to inhibit stent expansion.
The CTA-derived J-CTO score was a more useful predictor of both procedural success and 30-min wire crossing than the J-CTO score derived from conventional angiography.
Aims
The risk of adverse events in atrial fibrillation (AF) patients was commonly stratified by risk factors or clinical risk scores. Risk factors often do not occur in isolation and are often found in multimorbidity ‘clusters’ which may have prognostic implications. We aimed to perform cluster analysis in a cohort of AF patients and to assess the outcomes and prognostic implications of the identified comorbidity cluster phenotypes.
Methods and results
The Fushimi AF Registry is a community-based prospective survey of the AF patients in Fushimi-ku, Kyoto, Japan. Hierarchical cluster analysis was performed on 4304 patients (mean age: 73.6 years, female; 40.3%, mean CHA2DS2-VASc score 3.37 ± 1.69), using 42 baseline clinical characteristics. On hierarchical cluster analysis, AF patients could be categorized into six statistically driven comorbidity clusters: (i) younger ages (mean age: 48.3 years) with low prevalence of risk factors and comorbidities (n = 209); (ii) elderly (mean age: 74.0 years) with low prevalence of risk factors and comorbidities (n = 1301); (iii) those with high prevalence of atherosclerotic risk factors, but without atherosclerotic disease (n = 1411); (iv) those with atherosclerotic comorbidities (n = 440); (v) those with history of any-cause stroke (n = 681); and (vi) the very elderly (mean age: 83.4 years) (n = 262). Rates of all-cause mortality and major adverse cardiovascular or neurological events can be stratified by these six identified clusters (log-rank test; P < 0.001 and P < 0.001, respectively).
Conclusions
We identified six clinically relevant phenotypes of AF patients on cluster analysis. These phenotypes can be associated with various types of comorbidities and associated with the incidence of clinical outcomes.
Clinical Trial Registration Information
https://www.umin.ac.jp/ctr/index.htm. Unique identifier: UMIN000005834.
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