Impact of Measured and Predicted Prosthesis-Patient Mismatch After Transcatheter Aortic Valve Replacement.

Prosthesis-patient mismatch after transcatheter aortic valve replacement (TAVR) can be measured echocardiographically (measured prosthesis-patient mismatch [PPMm]) or predicted (predicted prosthesis-patient mismatch [PPMp]) using published effective orifice area (EOA) reference values. However, the clinical implications of PPM post-TAVR remain unclear. This study aimed to elucidate the prevalence of PPMm and PPMp post-TAVR and their impact on mortality in a large international cohort. The IMPPACT TAVR (Impact of Measured or Predicted Prosthesis-pAtient mismatCh after TAVR) registry included 38,808 TAVR patients from 26 international centers. Valve Academic Research Consortium 3 criteria were used to define prosthesis-patient mismatch severity. EOA was determined echocardiographically (PPMm) or predicted (PPMp) based on core lab-derived EOA reference values. The primary endpoint was 2-year all-cause mortality. The prevalence of PPMp (moderate: 6.8%, severe: 0.6%) was significantly lower than that of PPMm (moderate: 20.7%, severe: 4.3%; P < 0.001) with negligible correlation between the 2 methods (Kendall's tau c correlation coefficient: 0.063; P < 0.001). In unadjusted analyses, severe PPMm adversely influenced 2-year survival (HR: 1.22; 95% CI: 1.02-1.45; P = 0.027), whereas severe PPMp was not associated with outcomes (HR: 0.81; 95% CI: 0.55-1.19; P = 0.291). After adjusting for confounders, neither PPMm nor PPMp had a significant effect on 2-year all-cause mortality. PPMm and PPMp were associated with different patient characteristics, with PPMm tending toward worse (especially low flow) and PPMp toward better (especially women) survival. After adjusting for confounders, neither PPMm nor PPMp significantly affected 2-year all-cause mortality. Hence, valve selection should not solely be based on hemodynamics but rather on a holistic approach, including patient and procedural specifics.

Guthoff H ，Abdel-Wahab M ，Kim WK ，Witberg G ，Wienemann H ，Thurow M ，Shamekhi J ，Eckel C ，von der Heide I ，Veulemans V ，Landt M ，Barbanti M ，Finkelstein A ，Schewel J ，Van Mieghem N ，Adrichem R ，Toggweiler S ，Rheude T ，Nombela-Franco L ，Amat-Santos IJ ，Ruile P ，Estévez-Loureiro R ，Bunc M ，Branca L ，De Backer O ，Tarantini G ，Mylotte D ，Arzamendi D ，Pauly M ，Bleiziffer S ，Renker M ，Al-Kassou B ，Möllmann H ，Ludwig S ，Zeus T ，Tamburino C ，Schmidt T ，Rück A ，von Stein P ，Thiele H ，Abdelhafez A ，Adam M ，Baldus S ，Rudolph T ，Mauri V ，IMPPACT TAVR Investigators ... -  《-》

Comparison of Two Modern Survival Prediction Tools, SORG-MLA and METSSS, in Patients With Symptomatic Long-bone Metastases Who Underwent Local Treatment With Surgery Followed by Radiotherapy and With Radiotherapy Alone.

Survival estimation for patients with symptomatic skeletal metastases ideally should be made before a type of local treatment has already been determined. Currently available survival prediction tools, however, were generated using data from patients treated either operatively or with local radiation alone, raising concerns about whether they would generalize well to all patients presenting for assessment. The Skeletal Oncology Research Group machine-learning algorithm (SORG-MLA), trained with institution-based data of surgically treated patients, and the Metastases location, Elderly, Tumor primary, Sex, Sickness/comorbidity, and Site of radiotherapy model (METSSS), trained with registry-based data of patients treated with radiotherapy alone, are two of the most recently developed survival prediction models, but they have not been tested on patients whose local treatment strategy is not yet decided. (1) Which of these two survival prediction models performed better in a mixed cohort made up both of patients who received local treatment with surgery followed by radiotherapy and who had radiation alone for symptomatic bone metastases? (2) Which model performed better among patients whose local treatment consisted of only palliative radiotherapy? (3) Are laboratory values used by SORG-MLA, which are not included in METSSS, independently associated with survival after controlling for predictions made by METSSS? Between 2010 and 2018, we provided local treatment for 2113 adult patients with skeletal metastases in the extremities at an urban tertiary referral academic medical center using one of two strategies: (1) surgery followed by postoperative radiotherapy or (2) palliative radiotherapy alone. Every patient's survivorship status was ascertained either by their medical records or the national death registry from the Taiwanese National Health Insurance Administration. After applying a priori designated exclusion criteria, 91% (1920) were analyzed here. Among them, 48% (920) of the patients were female, and the median (IQR) age was 62 years (53 to 70 years). Lung was the most common primary tumor site (41% [782]), and 59% (1128) of patients had other skeletal metastases in addition to the treated lesion(s). In general, the indications for surgery were the presence of a complete pathologic fracture or an impending pathologic fracture, defined as having a Mirels score of ≥ 9, in patients with an American Society of Anesthesiologists (ASA) classification of less than or equal to IV and who were considered fit for surgery. The indications for radiotherapy were relief of pain, local tumor control, prevention of skeletal-related events, and any combination of the above. In all, 84% (1610) of the patients received palliative radiotherapy alone as local treatment for the target lesion(s), and 16% (310) underwent surgery followed by postoperative radiotherapy. Neither METSSS nor SORG-MLA was used at the point of care to aid clinical decision-making during the treatment period. Survival was retrospectively estimated by these two models to test their potential for providing survival probabilities. We first compared SORG to METSSS in the entire population. Then, we repeated the comparison in patients who received local treatment with palliative radiation alone. We assessed model performance by area under the receiver operating characteristic curve (AUROC), calibration analysis, Brier score, and decision curve analysis (DCA). The AUROC measures discrimination, which is the ability to distinguish patients with the event of interest (such as death at a particular time point) from those without. AUROC typically ranges from 0.5 to 1.0, with 0.5 indicating random guessing and 1.0 a perfect prediction, and in general, an AUROC of ≥ 0.7 indicates adequate discrimination for clinical use. Calibration refers to the agreement between the predicted outcomes (in this case, survival probabilities) and the actual outcomes, with a perfect calibration curve having an intercept of 0 and a slope of 1. A positive intercept indicates that the actual survival is generally underestimated by the prediction model, and a negative intercept suggests the opposite (overestimation). When comparing models, an intercept closer to 0 typically indicates better calibration. Calibration can also be summarized as log(O:E), the logarithm scale of the ratio of observed (O) to expected (E) survivors. A log(O:E) > 0 signals an underestimation (the observed survival is greater than the predicted survival); and a log(O:E) < 0 indicates the opposite (the observed survival is lower than the predicted survival). A model with a log(O:E) closer to 0 is generally considered better calibrated. The Brier score is the mean squared difference between the model predictions and the observed outcomes, and it ranges from 0 (best prediction) to 1 (worst prediction). The Brier score captures both discrimination and calibration, and it is considered a measure of overall model performance. In Brier score analysis, the "null model" assigns a predicted probability equal to the prevalence of the outcome and represents a model that adds no new information. A prediction model should achieve a Brier score at least lower than the null-model Brier score to be considered as useful. The DCA was developed as a method to determine whether using a model to inform treatment decisions would do more good than harm. It plots the net benefit of making decisions based on the model's predictions across all possible risk thresholds (or cost-to-benefit ratios) in relation to the two default strategies of treating all or no patients. The care provider can decide on an acceptable risk threshold for the proposed treatment in an individual and assess the corresponding net benefit to determine whether consulting with the model is superior to adopting the default strategies. Finally, we examined whether laboratory data, which were not included in the METSSS model, would have been independently associated with survival after controlling for the METSSS model's predictions by using the multivariable logistic and Cox proportional hazards regression analyses. Between the two models, only SORG-MLA achieved adequate discrimination (an AUROC of > 0.7) in the entire cohort (of patients treated operatively or with radiation alone) and in the subgroup of patients treated with palliative radiotherapy alone. SORG-MLA outperformed METSSS by a wide margin on discrimination, calibration, and Brier score analyses in not only the entire cohort but also the subgroup of patients whose local treatment consisted of radiotherapy alone. In both the entire cohort and the subgroup, DCA demonstrated that SORG-MLA provided more net benefit compared with the two default strategies (of treating all or no patients) and compared with METSSS when risk thresholds ranged from 0.2 to 0.9 at both 90 days and 1 year, indicating that using SORG-MLA as a decision-making aid was beneficial when a patient's individualized risk threshold for opting for treatment was 0.2 to 0.9. Higher albumin, lower alkaline phosphatase, lower calcium, higher hemoglobin, lower international normalized ratio, higher lymphocytes, lower neutrophils, lower neutrophil-to-lymphocyte ratio, lower platelet-to-lymphocyte ratio, higher sodium, and lower white blood cells were independently associated with better 1-year and overall survival after adjusting for the predictions made by METSSS. Based on these discoveries, clinicians might choose to consult SORG-MLA instead of METSSS for survival estimation in patients with long-bone metastases presenting for evaluation of local treatment. Basing a treatment decision on the predictions of SORG-MLA could be beneficial when a patient's individualized risk threshold for opting to undergo a particular treatment strategy ranged from 0.2 to 0.9. Future studies might investigate relevant laboratory items when constructing or refining a survival estimation model because these data demonstrated prognostic value independent of the predictions of the METSSS model, and future studies might also seek to keep these models up to date using data from diverse, contemporary patients undergoing both modern operative and nonoperative treatments. Level III, diagnostic study.

Lee CC ，Chen CW ，Yen HK ，Lin YP ，Lai CY ，Wang JL ，Groot OQ ，Janssen SJ ，Schwab JH ，Hsu FM ，Lin WH ... -  《-》

Valve Performance Between Latest-Generation Balloon-Expandable and Self-Expandable Transcatheter Heart Valves in a Small Aortic Annulus.

Transcatheter aortic valve replacement (TAVR) using a self-expandable valve (SEV) promotes better hemodynamics compared with a balloon-expandable valve (BEV) in a small aortic annulus (SAA). The authors sought to compare hemodynamic properties and clinical outcomes between the latest-generation BEV and SEV after TAVR for SAA. We retrospectively analyzed 1,227 patients undergoing TAVR for aortic stenosis with SAA, defined as an annulus area ≤430 mm2, using the BEV (SAPIEN3 Ultra RESILIA, Edwards Lifesciences) and SEV (Evolut FX, Medtronic). The impact of valve design on severe prosthesis-patient mismatch, aortic valve mean pressure gradient ≥20 mm Hg, paravalvular leakage (PVL) ≥ mild, new permanent pacemaker implantation (PMI), and modified VARC-3 device success at discharge was evaluated using logistic regression and propensity score analysis. Of 1,227 patients, 798 (65.0%) underwent TAVR with BEV implantation. TAVR using BEV had a relatively higher rate of severe prosthesis-patient mismatch (OR: 1.74; 95% CI: 0.54-5.62) and significantly higher incidence of mean pressure gradient ≥20 mm Hg (OR: 2.05; 95% CI: 0.91-4.62) than that using SEV. By contrast, the BEV showed significantly lower incidence of PVL ≥ mild (OR: 0.19; 95% CI: 0.14-0.26), and new PMI (OR: 0.53; 95% CI: 0.33-0.86). The rate of device success was comparable between the BEV and the SEV. These results were confirmed by propensity score analysis. In TAVR for SAA, SEV demonstrated better hemodynamics than the latest BEV, whereas the latest BEV had lower incidences of PVL ≥ mild and new PMI than the SEV.

Hioki H ，Yamamoto M ，Shirai S ，Ohno Y ，Yashima F ，Naganuma T ，Yamawaki M ，Watanabe Y ，Yamanaka F ，Mizutani K ，Ryuzaki T ，Noguchi M ，Izumo M ，Takagi K ，Asami M ，Ueno H ，Nishina H ，Otsuka T ，Suzuyama H ，Yamasaki K ，Nishioka K ，Hachinohe D ，Fuku Y ，Hayashida K ，OCEAN-TAVI Investigators ... -  《-》

Discongruence Index　- Simple Indicator to Predict Prosthesis-Patient Mismatch After Transcatheter Aortic Valve Replacement.

de Agustin JA ，Islas F ，Jimenez-Quevedo P ，Nombela-Franco L ，Rueda Liñares A ，Mahia P ，Marcos-Alberca P ，Pozo E ，Gomez de Diego JJ ，Luaces M ，Nuñez-Gil IJ ，Garcia-Fernandez MÁ ，Fernandez-Ortiz A ，Macaya C ，Perez de Isla L ... -  《-》

Impact of burden and distribution of aortic valve calcification on the hemodynamic performance and procedural outcomes of a self-expanding, intra-annular transcatheter aortic valve system.

Aortic valve calcification (AVC) has been explored as a powerful predictor of procedural complications in patients undergoing transcatheter aortic valve implantation (TAVI). However, little evidence exists on its impact on intra-annular devices' performance. We aimed to investigate the impact of AVC burden and distribution pattern on the occurrence of paravalvular leak (PVL), conduction disturbances requiring permanent pacemaker implantation (PPI) and 30-day clinical outcomes in patients undergoing TAVI with a self-expanding, intra-annular device. According to AVC, 103 patients enrolled in a single medical centre from November 2019 to December 2022 were divided into tertiles. Valve Academic Research Consortium (VARC)-3 definitions were used to classify procedural complications and outcomes. Patients in the highest AVC tertile showed an increased occurrence of mild or more PVL and conduction disorders (p < 0.001 and p = 0.006). AVC tertiles (highest tertile) emerged as an independent predictor of PVL (OR 7.32, 95%CI 3.10-17.28, p < 0.001) and post-TAVI conduction disturbances (OR 3.73, 95%CI 1.31-10.60, p = 0.013) but not of PPI (OR 1.44, 95%CI 0.39-5.35, p = 0.579). Considering calcium distribution, ROC analyses revealed that annular AVC but not left ventricle outflow tract (LVOT) calcium burden significantly indicated the development of PVL (AUC 0.863, 0.77-0.93, p < 0.001) and conduction disorders/PPI (AUC 0.797, 0.70-0.89, p < 0.001 and 0.723, 0.58-0.86, p = 0.018, respectively). After adjustment for age and sex, the highest tertile remained an independent predictor of the 30-day composite outcome (death, myocardial infarction, stroke, major vascular complications, type 3/4 bleedings, acute kidney injury, PPI and ≥ moderate PVL) (OR 3.26; 95%CI 1.26-8.40, p = 0.014). A higher AVC is associated with an increased risk of PVL and conduction disturbances after TAVI with a self-expanding, intra-annular device. However, our findings suggest a minor role for LVOT calcification compared with annular AVC in the performance of this specific prosthesis.

Nusca A ，Viscusi MM ，Circhetta S ，Cammalleri V ，Mangiacapra F ，Ricottini E ，Melfi R ，Gallo P ，Cocco N ，Rinaldi R ，Grigioni F ，Ussia GP ... -  《-》