Daniel Hernández-Vaquero

Patient prosthesis mismatch in adult congenital heart disease

Patient prosthesis mismatch (PPM) was originally described by Rahimtoola almost four decades ago as follows: “the effective prosthetic valve area, after insertion into the patient, is less than that of a normal human valve”.1 That is, PPM is a situation in which the area of a perfectly functioning prosthetic valve is too small for the body surface area (BSA) of that patient. So, the indexed effective orifice area (IEOA) defined as the ratio between the effective orifice area (EOA) of a prosthetic valve and the BSA of that patient is the optimal parameter to calculate PPM.nnDue to its ability to maintain high transvalvular pressure gradients, the existence of PPM can lead to adverse outcomes and worse quality of life. After the aortic valve replacement (AVR), these high-pressure gradients result in a slowing or absence of LV mass regression, which hampers LV function recovery and favours myocardial ischaemia even with normal coronary arteries due to increased myocardial demand and decreased coronary flow reserve (figure 1).2nnnnFigurexa01 nPathophysiological mechanisms of patient prosthesis mismatch (PPM).nnnnDuring these four decades, a huge number of articles and reviews on the prevalence and clinical impact of PPM have obtained different results. Several reasons are responsible for these controversial findings. First, different …

External validation of the EuroSCORE II risk stratification model in the USA

The accuracy of any predictive model depends largely on the homogeneity between the population used to create the system and the study population. For this reason, the article by Osnabrugge et al. [1] analysing the performance of EuroSCORE II in a large US database is of great relevance. Furthermore, these authors investigated the implications of this performance for the selection of patients as candidates for transcatheter aortic valve implantation (TAVI). The external validation of any predictive system is usually measured in terms of calibration and discrimination [2]. Calibration is the agreement between model predictions and observed event incidences. For instance, if a model predicts a 10% mortality risk (expected mortality), the observed mortality incidence should be 10 of 100 patients for a perfect calibration. For patients who underwent aortic valve replacement (AVR), these authors found that the calibration of EuroSCORE II was almost perfect with an observed/expected ratio of 0.96, indicating that, overall, the predicted mortality was very close to reality. Interestingly, this model under-predicted in low-risk patients and over-predicted in high-risk patients (Fig. 3; [1]). Discrimination, which is a measure of how well the model can separate those who will develop the event from those who will not, is of most interest when classification into groups is the goal, for example low, intermediate or high risk for surgical treatment [2]. Therefore, discrimination is crucial when defining which patients are candidates for TAVI. The area under the receiver operator curve (AUC) is the most popular measure of discrimination and indicates the probability that a randomly selected patient who will develop the event has a higher risk score than a randomly selected patient who will not develop the event. Subsequently, an AUC of 0.5 indicates no predictive ability, whereas an AUC of 1.0 represents perfect discrimination. Although Osnabrugge et al. [1] showed a good calibration for patients who underwent AVR, discrimination measured by the AUC was only 0.71. This means that, 29% of the time (1–0.71), this system gives a lower predicted risk for a patient who will develop the event than for a patient who will not [2]. Under this circumstance, we believe that the ability of the EuroSCORE II to identify patients at low or high risk is only moderate and, therefore, decisionmaking should not be based on this model in the USA. Moreover, the discrimination of the Society of Thoracic Surgeons-Predicted Risk of Mortality (STS-PROM) is only slightly superior [1], and so this should be taken into account when analysing the results of some clinical trials that have used this model to select patients for transcatheter procedures [3].

The Prevalence of Patient-Prosthesis Mismatch Can Be Reduced Using the Trifecta Aortic Prosthesis

BACKGROUNDnSome important studies have shown that patient-prosthesis mismatch is a frequent occurrence after surgical aortic valve replacement that impairs survival. The Trifecta valve (St. Jude Medical Inc, St. Paul, MN) has special architecture designed to achieve the best hemodynamic profile. The aim of this study was to determine the prevalence of mismatch when using this prosthesis.nnnMETHODSnThis study included 1,302 patients at 3 months postoperatively, 339 patients with a Trifecta prosthesis and 963 patients (the control group) with a Mitroflow aortic valve (Sorin Group Inc, Mitroflow Division, Vancouver, Canada). Multinomial multivariate logistic regression was calculated to estimate the association between the Trifecta prosthesis and moderate or severe patient-prosthesis mismatch.nnnRESULTSnAny degree of mismatch was present in 5.9% of the Trifecta group and in 42.4% in the Mitroflow group. Moderate patient-prosthesis mismatch was present in 3.8% of the patients with a Trifecta valve and in 32.6% in the Mitroflow group. Severe mismatch was present in 2.1% of the patients with a Trifecta prosthesis and in 9.8% of the patients with a Mitroflow valve. All differences were statistically significant (p < 0.001). The odds ratio of the Trifecta prosthesis as protector against mismatch was 16.9 (95% confidence interval, 9.5 to 30.4) and 11.9 (95% confidence interval, 5.3 to 26.7) for moderate or severe mismatch, respectively.nnnCONCLUSIONSnThe prevalence of patient-prosthesis mismatch using the Trifecta aortic prosthesis is extraordinary low. This finding may have great clinical repercussions in patients undergoing surgical aortic valve replacement.

Considerations on the poor discriminatory power of the FRANCE-2 risk score

To the Editor, The developers1 of the first rigorous predictive model for mortality after transcatheter aortic valve implantation (TAVI) have overcome the limitations of the previous surgical scores. While EuroSCORE I is an old and redundant model based on data of 1995 and derived from a highly heterogeneous patient group with different operations, techniques and demographics, this predictive model is based on new results of a remarkably homogeneous population (72.4% >80u2005years of age and all treated with TAVI procedures).1 Moreover, while EuroSCORE II developers included variables that were not significantly associated with the event by multivariate regression and did not analyse some important variables, …

Performance of euroscore ii compared with its predecessors in octogenarian patients undergoing aortic valve replacement

Logistic EuroSCORE overestimates the risk profile of octogenarians undergoing aortic valve replacement by traditional surgery. EuroSCORE II, that was created in an attempt to improve this previous version, has been evaluated in the general population. However, to our knowledge, there are no studies evaluating the predictive performance of EuroSCORE II in the elderly population undergoing surgery for aortic valve replacement despite the fact that the majority of patients receiving transcatheter techniques are octogenarians and this new version is being used for the selection of high-risk surgical patients.

Letter by Hernández-Vaquero et al Regarding Article, “Saphenous Vein Graft Failure After Coronary Artery Bypass Surgery: Insights From PREVENT IV”

Hess and colleagues1 are to be commended for their study of the predictors of saphenous vein graft failure (VGF) after coronary artery bypass grafting. To do this, they analyzed >30 variables in 1828 patients and created a rigorous logistic regression model using data from the Project of Ex Vivo Vein Graft Engineering via Transfection IV (PREVENT IV) trial.2 The final result was that poor target artery quality, longer duration of surgery, use of …

Mid-term impact of patient-prosthesis mismatch on young and middle-aged patients undergoing surgery due to severe aortic stenosis

Methods All patients younger than 70 years of age undergoing isolated aortic valve replacement from October 2005 to October 2011 were analyzed. Patient-prosthesis mismatch was defined as the indexed effective orifice area ≤ 0,85cm2/m2. We studied the impact of patient-prosthesis mismatch on mid-term overall mortality, cardiac events and New York Heart Association functional class using an analysis stratified for propensity score. Cardiac events were defined as cardiac death, sudden death, hospital readmission due to angina, syncope or heart failure or reoperation on aortic prosthesis.

Aortic valve replacement in octogenarians: performance analysis of EuroSCORE II

Background EuroSCORE has been proposed to identify patients at high risk for surgical aortic valve replacement and estimate for them the risk-benefit of percutaneous implantation. However, it has been clearly demonstrated that this system overestimates mortality, particularly in the elderly population undergoing surgery for aortic valve replacement. An actualized model called EuroSCORE II has been recently proposed to predict mortality after cardiac surgery but it has not been validated yet in the elderly population undergoing aortic valve replacement. We aimed to validate the new risk model in an octogenarian population who underwent surgery for aortic valve replacement in our center. Methods