Hospital Universitari Arnau de Vilanova, Lleida - Espanha.
Institut de Recerca Biomédica de Lleida (IRBLleida), Lleida - Espanha.
Arq Bras Cardiol. 2022 Nov;119(5):705-713. doi: 10.36660/abc.20220176.
Cutoff thresholds for the "resting full-cycle ratio" (RFR) oscillate in different series, suggesting that population characteristics may influence them. Likewise, predictors of discordance between the RFR and fractional flow reserve (FFR) have been documented. The RECOPA Study showed that diagnostic capacity is reduced in the RFR "grey zone", requiring the performance of FFR to rule out or confirm ischemia.
To determine predictors of discordance, integrate the information they provide in a clinical-physiological index, the "Adjusted RFR", and compare its agreement with the FFR.
Using data from the RECOPA Study, predictors of discordance with respect to FFR were determined in the RFR "grey zone" (0.86 to 0.92) to construct an index ("Adjusted RFR") that would weigh RFR together with predictors of discordance and evaluate its agreement with FFR.
A total of 156 lesions were evaluated in 141 patients. Predictors of discordance were: chronic kidney disease, previous ischemic heart disease, lesions not involving the anterior descending artery, and acute coronary syndrome. Though limited, the "Adjusted RFR" improved the diagnostic capacity compared to the RFR in the "grey zone" (AUC-RFR = 0.651 versus AUC-"Adjusted RFR" = 0.749), also showing an improvement in all diagnostic indices when optimal cutoff thresholds were established (sensitivity: 59% to 68%; specificity: 62% to 75%; diagnostic accuracy: 60% to 71%; positive likelihood ratio: 1.51 to 2.34; negative likelihood ratio: 0.64 to 0.37).
Adjusting the RFR by integrating the information provided by predictors of discordance to obtain the "Adjusted RFR" improved the diagnostic capacity in our population. Further studies are required to evaluate whether clinical-physiological indices improve the diagnostic capacity of RFR or other coronary indices.
“静息全周期比”（RFR）的截断值在不同系列中波动，这表明人群特征可能会影响它们。同样，也有研究记录了 RFR 与血流储备分数（FFR）不相符的预测因素。RECOPA 研究表明，RFR“灰色地带”的诊断能力降低，需要进行 FFR 以排除或确认缺血。
确定不相符的预测因素，将它们提供的信息整合到一个临床生理指数“调整后的 RFR”中，并比较其与 FFR 的一致性。
利用 RECOPA 研究的数据，在 RFR“灰色地带”（0.86 至 0.92）中确定与 FFR 不相符的预测因素，构建一个指数（“调整后的 RFR”），该指数将 RFR 与不相符的预测因素相结合，并评估其与 FFR 的一致性。
共评估了 141 例患者的 156 个病变。不相符的预测因素为：慢性肾脏病、既往缺血性心脏病、不涉及前降支的病变和急性冠脉综合征。尽管有限，但与 RFR 在“灰色地带”（AUC-RFR=0.651 与 AUC-“调整后的 RFR”=0.749）相比，“调整后的 RFR”提高了诊断能力，当建立最佳截断值时，所有诊断指数也都有所提高（敏感性：59%至 68%；特异性：62%至 75%；诊断准确性：60%至 71%；阳性似然比：1.51 至 2.34；阴性似然比：0.64 至 0.37）。
通过整合不相符的预测因素提供的信息来调整 RFR，以获得“调整后的 RFR”，提高了我们人群的诊断能力。需要进一步研究以评估临床生理指数是否可以提高 RFR 或其他冠状动脉指数的诊断能力。
