Head‐to‐Head Comparison of Learning Curves Between QFR and FFRangio Software Users

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Hauptverfasser: Adil Salihu, Jade Zulauff, Mehdi Ali Gadiri, Anais Metzinger, Joanne Muller, Ioannis Skalidis, David Meier, Nathalie Noirclerc, Sarah Mauler‐Wittwer, Aurelia Zimmerli, Olivier Muller, Stephane Fournier
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author Adil Salihu
Jade Zulauff
Mehdi Ali Gadiri
Anais Metzinger
Joanne Muller
Ioannis Skalidis
David Meier
Nathalie Noirclerc
Sarah Mauler‐Wittwer
Aurelia Zimmerli
Olivier Muller
Stephane Fournier
author_facet Adil Salihu
Jade Zulauff
Mehdi Ali Gadiri
Anais Metzinger
Joanne Muller
Ioannis Skalidis
David Meier
Nathalie Noirclerc
Sarah Mauler‐Wittwer
Aurelia Zimmerli
Olivier Muller
Stephane Fournier
Adil Salihu
Jade Zulauff
Mehdi Ali Gadiri
Anais Metzinger
Joanne Muller
Ioannis Skalidis
David Meier
Nathalie Noirclerc
Sarah Mauler‐Wittwer
Aurelia Zimmerli
Olivier Muller
Stephane Fournier
collection Wiley Open Access
contents Head‐to‐Head Comparison of Learning Curves Between QFR and FFRangio Software Users Adil Salihu Jade Zulauff Mehdi Ali Gadiri Anais Metzinger Joanne Muller Ioannis Skalidis David Meier Nathalie Noirclerc Sarah Mauler‐Wittwer Aurelia Zimmerli Olivier Muller Stephane Fournier Catheterization and Cardiovascular Interventions ABSTRACTBackgroundQuantitative flow ratio (QFR) and FFRangio are angiography‐based technologies used to perform functional assessment of coronary lesions from angiographic images, validated across multiple clinical studies. There is limited information on the learning curves associated with each technology.AimsThis study aims to compare the learning curves of QFR and FFRangio in evaluating coronary stenoses, focusing on changes in analysis speed and accuracy compared to invasive measurements.MethodsA team of five blinded investigators, including two nurses, one medical student, and one physician in training, underwent identical standardized training on both technologies. The time taken for each analysis and the computed FFR values were documented and compared against the invasive gold standard.ResultsA total of 270 lesions (54 coronary lesions in 44 patients) were retrospectively analyzed. The median invasive FFR value was 0.88 [IQR 0.5, 0.9]. The median time for analysis with QFR and FFRangio was 245 [IQR 62, 319] and 252 [IQR 82, 315] s, respectively (p = 0.171). Both QFR and FFRangio demonstrated a significant reduction in the time required for analysis as experience increased (p < 0.01). Regarding accuracy, the median difference with invasive FFR for QFR and FFRangio was 0.06 [IQR: 0, 0.12] and 0.06 [IQR: 0, 0.12], respectively (p = 0.620). Both technologies reached a performance plateau early on, exhibiting comparable results throughout the study.ConclusionInitial training in QFR and FFRangio enables quick attainment of maximal performance, but further practice primarily enhances analysis speed while maintaining accuracy, for both software. 10.1002/ccd.31384 http://onlinelibrary.wiley.com/termsAndConditions#vor
doi_str_mv 10.1002/ccd.31384
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spellingShingle Head‐to‐Head Comparison of Learning Curves Between QFR and FFRangio Software Users
Adil Salihu
Jade Zulauff
Mehdi Ali Gadiri
Anais Metzinger
Joanne Muller
Ioannis Skalidis
David Meier
Nathalie Noirclerc
Sarah Mauler‐Wittwer
Aurelia Zimmerli
Olivier Muller
Stephane Fournier
Catheterization and Cardiovascular Interventions
Head‐to‐Head Comparison of Learning Curves Between QFR and FFRangio Software Users Adil Salihu Jade Zulauff Mehdi Ali Gadiri Anais Metzinger Joanne Muller Ioannis Skalidis David Meier Nathalie Noirclerc Sarah Mauler‐Wittwer Aurelia Zimmerli Olivier Muller Stephane Fournier Catheterization and Cardiovascular Interventions ABSTRACTBackgroundQuantitative flow ratio (QFR) and FFRangio are angiography‐based technologies used to perform functional assessment of coronary lesions from angiographic images, validated across multiple clinical studies. There is limited information on the learning curves associated with each technology.AimsThis study aims to compare the learning curves of QFR and FFRangio in evaluating coronary stenoses, focusing on changes in analysis speed and accuracy compared to invasive measurements.MethodsA team of five blinded investigators, including two nurses, one medical student, and one physician in training, underwent identical standardized training on both technologies. The time taken for each analysis and the computed FFR values were documented and compared against the invasive gold standard.ResultsA total of 270 lesions (54 coronary lesions in 44 patients) were retrospectively analyzed. The median invasive FFR value was 0.88 [IQR 0.5, 0.9]. The median time for analysis with QFR and FFRangio was 245 [IQR 62, 319] and 252 [IQR 82, 315] s, respectively (p = 0.171). Both QFR and FFRangio demonstrated a significant reduction in the time required for analysis as experience increased (p < 0.01). Regarding accuracy, the median difference with invasive FFR for QFR and FFRangio was 0.06 [IQR: 0, 0.12] and 0.06 [IQR: 0, 0.12], respectively (p = 0.620). Both technologies reached a performance plateau early on, exhibiting comparable results throughout the study.ConclusionInitial training in QFR and FFRangio enables quick attainment of maximal performance, but further practice primarily enhances analysis speed while maintaining accuracy, for both software. 10.1002/ccd.31384 http://onlinelibrary.wiley.com/termsAndConditions#vor
title Head‐to‐Head Comparison of Learning Curves Between QFR and FFRangio Software Users
topic Catheterization and Cardiovascular Interventions
url https://onlinelibrary.wiley.com/doi/10.1002/ccd.31384