odwy3t2

Property	Value
?:abstract	OBJECTIVES: The authors sought to develop an automated algorithm using pre-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) pullback recordings to predict post-PCI physiological results in the pre-PCI phase. BACKGROUND: Both FFR and percent FFR increase measured after PCI showed incremental prognostic implications. However, there is no current method to predict post-PCI physiological results using physiological assessment in the pre-PCI phase. METHODS: An automated algorithm that analyzes instantaneous FFR gradient per unit time (dFFR(t)/dt) was developed from the derivation cohort (n = 30). Using dFFR(t)/dt, the pattern of atherosclerotic disease in each patient was classified into 3 groups (major, mixed, and minor FFR gradient groups) in both the internal validation cohort with constant pullback method (n = 234) and the external validation cohort with nonstandardized pullback methods (n = 252). All patients in the validation cohorts underwent PCI on the basis of pre-PCI FFR ≤0.80. Suboptimal post-PCI physiological results were defined as both post-PCI FFR <0.84 and percent FFR increase ≤15%. From the derivation cohort, cutoffs of dFFR(t)/dt for major and minor FFR gradient were 0.035/s and 0.015/s, respectively. RESULTS: In validation cohorts, dFFR(t)/dt showed significant correlations with percent FFR increase (R = 0.801; p < 0.001) and post-PCI FFR (R = 0.099; p = 0.029). In both the internal and external validation cohorts, the major FFR gradient group showed significantly higher post-PCI FFR and percent FFR increase compared with those in the mixed or minor FFR gradient groups (all p values <0.001). The proportions of suboptimal post-PCI physiological results were significantly different among 3 groups (10.4% vs. 25.8% vs. 45.7% for the major, mixed, and minor FFR gradient groups, respectively; p < 0.001) in validation cohorts. Absence of major FFR gradient lesion (odds ratio: 2.435, 95% [CI]: 1.252 to 4.734; p = 0.009) and presence of minor FFR gradient lesion (odds ratio: 2.756, 95% confidence interval: 1.629 to 4.664; p < 0.001) were independent predictors for suboptimal post-PCI physiological results. CONCLUSIONS: The automated algorithm analyzing pre-PCI pullback curve was able to predict post-PCI physiological results. The incidence of suboptimal post-PCI physiological results was significantly different according to algorithm-based classifications in the pre-PCI physiological assessment. (Automated Algorithm Detecting Physiologic Major Stenosis and Its Relationship with Post-PCI Clinical Outcomes [Algorithm-PCI]; NCT04304677).
is ?:annotates of	<https://research.tib.eu/covid-19/entity/7odwy3t2_hasAnnotation_C1261287>
?:creator	<https://research.tib.eu/covid-19/entity/Lee%2C_Seung_Hun%3B_Shin%2C_Doosup%3B_Lee%2C_Joo_Myung%3B_Lefieux%2C_Adrien%3B_Molony%2C_David%3B_Choi%2C_Ki_Hong%3B_Hwang%2C_Doyeon%3B_Lee%2C_Hyun-Jong%3B_Jang%2C_Ho-Jun%3B_Kim%2C_Hyun_Kuk%3B_Ha%2C_Sang_Jin%3B_Kwak%2C_Jae-Jin%3B_Park%2C_Taek_Kyu%3B_Yang%2C_Jeong_Hoon%3B_Song%2C_Young_Bin%3B_Hahn%2C_Joo-Yong%3B_Doh%2C_Joon-Hyung%3B_Shin%2C_Eun-Seok%3B_Nam%2C_Chang-Wook%3B_Koo%2C_Bon-Kwon%3B_Choi%2C_Seung-Hyuk%3B_Gwon%2C_Hyeon-Cheol>
?:journal	JACC_cardiovasc._interv
?:license	unk
?:publication_isRelatedTo_Disease	<https://research.tib.eu/covid-19/entity/COVID-19>
?:source	WHO
?:title	Automated Algorithm Using Pre-Intervention Fractional Flow Reserve Pullback Curve to Predict Post-Intervention Physiological Results
?:type	<https://research.tib.eu/covid-19/vocab/Publication>
?:who_covidence_id	#33069650
?:year	2020

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?:abstract

OBJECTIVES: The authors sought to develop an automated algorithm using pre-percutaneous coronary intervention (PCI) fractional flow reserve (FFR) pullback recordings to predict post-PCI physiological results in the pre-PCI phase. BACKGROUND: Both FFR and percent FFR increase measured after PCI showed incremental prognostic implications. However, there is no current method to predict post-PCI physiological results using physiological assessment in the pre-PCI phase. METHODS: An automated algorithm that analyzes instantaneous FFR gradient per unit time (dFFR(t)/dt) was developed from the derivation cohort (n = 30). Using dFFR(t)/dt, the pattern of atherosclerotic disease in each patient was classified into 3 groups (major, mixed, and minor FFR gradient groups) in both the internal validation cohort with constant pullback method (n = 234) and the external validation cohort with nonstandardized pullback methods (n = 252). All patients in the validation cohorts underwent PCI on the basis of pre-PCI FFR ≤0.80. Suboptimal post-PCI physiological results were defined as both post-PCI FFR <0.84 and percent FFR increase ≤15%. From the derivation cohort, cutoffs of dFFR(t)/dt for major and minor FFR gradient were 0.035/s and 0.015/s, respectively. RESULTS: In validation cohorts, dFFR(t)/dt showed significant correlations with percent FFR increase (R = 0.801; p < 0.001) and post-PCI FFR (R = 0.099; p = 0.029). In both the internal and external validation cohorts, the major FFR gradient group showed significantly higher post-PCI FFR and percent FFR increase compared with those in the mixed or minor FFR gradient groups (all p values <0.001). The proportions of suboptimal post-PCI physiological results were significantly different among 3 groups (10.4% vs. 25.8% vs. 45.7% for the major, mixed, and minor FFR gradient groups, respectively; p < 0.001) in validation cohorts. Absence of major FFR gradient lesion (odds ratio: 2.435, 95% [CI]: 1.252 to 4.734; p = 0.009) and presence of minor FFR gradient lesion (odds ratio: 2.756, 95% confidence interval: 1.629 to 4.664; p < 0.001) were independent predictors for suboptimal post-PCI physiological results. CONCLUSIONS: The automated algorithm analyzing pre-PCI pullback curve was able to predict post-PCI physiological results. The incidence of suboptimal post-PCI physiological results was significantly different according to algorithm-based classifications in the pre-PCI physiological assessment. (Automated Algorithm Detecting Physiologic Major Stenosis and Its Relationship with Post-PCI Clinical Outcomes [Algorithm-PCI]; NCT04304677).

is ?:annotates of