Predicting the pressure of the total cavopulmonary connection: clinical testing of a mathematical equation. (23rd August 2019)

• Record Type: Journal Article
• Authors: Di Molfetta, Arianna; Iacobelli, Roberta; Rotella, Silvia; Gagliardi, Maria G.; Amodeo, Antonio; Formigari, Roberto; Pasquini, Luciano; Iorio, Salvatore F.; Guccione, Paolo
• Is Part Of: Cardiology in the young. Volume 29:Number 8(2019)
• Page Start: 1066
• Page End: 1071
• Publication Date: 2019-08-23
• Subjects: Fontan, -- single ventricle, -- pressure, -- cavopulmonary anastomosis; Pediatric cardiology -- Periodicals; 618.9212
• DOI: 10.1017/S1047951119001513
• Languages: English
• ISSNs: 1047-9511

Abstract

Abstract: Introduction: Some authors advocate the use of a dedicated formula to predict the Fontan pressure starting from pre-Fontan catheterisation data. This paper aims at testing the predictive value of the mentioned formula through a retrospective clinical study. Methods and Results: Pre-Fontan catheterisation data and Fontan pressure measured at the completion were retrospectively collected. Pre-Fontan data were used to calculate the predicted pressure in the Fontan system. The predicted values were compared to the Fontan pressure measured at the Fontan completion and with the needs for fenestration. One hundred twenty-four Fontan patients were retrospectively enrolled (At Fontan: median age 30.73 [24.70–37.20] months, median weight 12.00 [10.98–14.15] kg). Fontan conduit was fenestrated in 78 patients. A poor correlation (r 2 = 0.05128) between the measured and predicted data for non-fenestrated patients was observed. In the case of Fontan-predicted pressure <17.59 mmHg, the formula identified a good short-term clinical outcome with a sensitivity of 92%. Conclusion: The proposed formula showed a poor capability in estimating the actual pressure into the Fontan system and in identifying patients needing fenestration. As the pressure into the Fontan system is determined by multiple factors, the tested formula could be an additional data in a multi-parametric approach.