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Turk Kardiyol Dern Ars. 2019 Jan;47(1):21-28. doi: 10.5543/tkda.2018.60497.

The association between left ventricular mass index and coronary collateral circulation in patients with chronic total occlusion.

Author information

1
Department of Cardiology, Türkiye Yüksek İhtisas Training and Research Hospital, Ankara, Turkey. dr.elifhande@gmail.com.

Abstract

OBJECTIVE:

Left ventricular (LV) hypertrophy predisposes the myocardium to ischemia through several mechanisms. The LV mass index (LVMI) is used as a readily available and reliable measurement of LV hypertrophy. The LVMI can also be used to evaluate LV remodeling. The hypothesis of this study was that LV hypertrophy might augment coronary collateralization in patients with chronic total occlusion (CTO) and the aim was to research any association between LVMI and collateral formation in CTO. As a secondary goal, specific LV geometric types that might be associated with collateral presence were also investigated.

METHODS:

A total of 305 patients with CTO were included and categorized into 4 groups based on Rentrop grade.

RESULTS:

The LVMI demonstrated an incremental linear trend as the Rentrop grade increased. In the receiver operating characteristic curve, the likelihood that a cut-off value of 100.1 g/m2 would accurately differentiate patients with collaterals from those without collaterals was 75.8%, with 68.5% sensitivity and 68.6% specificity. A 1 gram/m2 increase in LVMI was associated with a 7.5% greater likelihood of collateral development. In addition, compared with normal geometry, the presence of eccentric hypertrophy was associated with 6.7 times higher odds of the presence of coronary collaterals.

CONCLUSION:

The results of this study indicated that a greater LVMI predicted coronary collateral presence. Furthermore, having an eccentric geometric type of hypertrophy increased the likelihood of coronary collaterals more than other geometries. This finding signified that in addition to LV wall thickness, the type of hypertrophy was also decisive in predicting collateral presence.

PMID:
30628897
DOI:
10.5543/tkda.2018.60497
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