Why the study?
The study investigated the relationship between the Gensini score and periprocedural myocardial infarction.
Does a higher Gensini score predict periprocedural myocardial infarction in patients undergoing single coronary artery revascularization?
Does a higher Gensini score predict periprocedural myocardial infarction in patients undergoing single coronary artery revascularization?
The Gensini score is an independent predictor of periprocedural myocardial infarction in patients undergoing single-vessel PCI, with scores >22.5 indicating a higher risk of myocardial injury.
Gensini score may stratify periprocedural MI risk in single-vessel PCI; hypothesis-generating and requires prospective validation before clinical adoption.
The Gensini score (GS) is a convenient, powerful tool for assessing the severity and complexity of coronary artery diseases. Our research investigated the relationship between the GS and periprocedural myocardial infarction (PMI). We recruited 4949 patients (3366 men, 1583 women; mean age 66.45 ± 10.09 years) with a single coronary artery revascularization. Based on the tertile of the GS 20 and 36, the population was divided into 3 groups: Low Group (0 < GS ≤ 20, N = 1809); Intermediate Group (20 < GS ≤ 36, N = 1579); High Group (GS > 36, N = 1561). PMI3 represented the endpoint for cTnI > 3-fold upper reference limit, while PMI5 represented the endpoint for cTnI > 5-fold upper reference limit. The incidence of PMI of High Group was statistically higher than that of Intermediate Group (P < .05), while that of Intermediate Group was statistically higher than Low Group (P < .05). With the adjustment of some general variables, GS was an independent significantly predictor for PMI3 (β = 0.006, P < .05) and PMI5 (β = 0.007, P < .05). Following receiver operating characteristic curve analysis, the optimal cut-off value to predict PMI are 22.5 for PMI3 and 27 for PMI5. The GS was an independent predictor of PMI in the single-coronary revascularization population. Additionally, the 22.5 of GS was the optimal cut-off value for determining the presence of PMI3, while the 27 of GS for PMI5.
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Wang et al. (2022) studied this question.
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