AimsIn patients with aortic stenosis (AS), risk stratification for aortic valve replacement (AVR) relies mainly on valve-related factors, symptoms and co-morbidities. We sought to evaluate the prognostic impact of a newly-defined staging classification characterizing the extent of extravalvular (extra-aortic valve) cardiac damage among patients with severe AS undergoing AVR.Methods and resultsPatients with severe AS from the PARTNER 2 trials were pooled and classified according to the presence or absence of cardiac damage as detected by echocardiography prior to AVR: no extravalvular cardiac damage (Stage 0), left ventricular damage (Stage 1), left atrial or mitral valve damage (Stage 2), pulmonary vasculature or tricuspid valve damage (Stage 3), or right ventricular damage (Stage 4). One-year outcomes were compared using Kaplan–Meier techniques and multivariable Cox proportional hazards models were used to identify 1-year predictors of mortality. In 1661 patients with sufficient echocardiographic data to allow staging, 47 (2.8%) patients were classified as Stage 0, 212 (12.8%) as Stage 1, 844 (50.8%) as Stage 2, 413 (24.9%) as Stage 3, and 145 (8.7%) as Stage 4. One-year mortality was 4.4% in Stage 0, 9.2% in Stage 1, 14.4% in Stage 2, 21.3% in Stage 3, and 24.5% in Stage 4 (Ptrend < 0.0001). The extent of cardiac damage was independently associated with increased mortality after AVR (HR 1.46 per each increment in stage, 95% confidence interval 1.27–1.67, P < 0.0001).ConclusionThis newly described staging classification objectively characterizes the extent of cardiac damage associated with AS and has important prognostic implications for clinical outcomes after AVR.

BACKGROUND Little is known about the incidence of prosthesis-patient mismatch (PPM) and its impact on outcomes after transcatheter aortic valve replacement (TAVR). OBJECTIVES The objectives of this study were: 1) to compare the incidence of PPM in the transcatheter and surgical aortic valve replacement (SAVR) randomized (RCT) arms of the PARTNER-I trial Cohort A; and 2) to assess the impact of PPM on regression of left ventricular (LV) hypertrophy and mortality in these 2 arms and in the TAVR nonrandomized continued access (NRCA) Registry cohort. METHODS The PARTNER trial Cohort A randomized patients 1:1 to TAVR or bioprosthetic SAVR. Postoperative PPM was defined as absent if indexed effective orifice area >0.85, moderate ≥0.65 but ≤0.85, or severe <0.65 cm2/m2. LV mass regression and mortality were analyzed using the SAVR-RCT (n = 270), TAVR-RCT (n = 304) and TAVR-NRCA (n = 1637) cohorts. RESULTS Incidence of PPM was 60.0% (severe: 28.1%) in SAVR-RCT versus 46.4% (severe: 19.7%) in TAVR-RCT (p < 0.001) and 43.8% (severe: 13.6%) in TAVR-NRCA. In patients with aortic annulus diameter < 20 mm, severe PPM developed in 33.7% undergoing SAVR compared to 19.0% undergoing TAVR (p = 0.002). PPM was an independent predictor of less LV mass regression at 1 year in SAVR-RCT (p = 0.017) and TAVR-NRCA (p = 0.012) but not in TAVRRCT (p = 0.35). Severe PPM was an independent predictor of 2-year mortality in SAVR-RCT (hazard ratio [HR]: 1.78; p = 0.041) but not in TAVR-RCT (HR: 0.58; p = 0.11). In the TAVRNRCA, severe PPM was not a predictor of 1-year mortality in the whole cohort (HR: 1.05; p = 0.60) but did independently predict mortality in the subset of patients with no post-procedural aortic regurgitation (HR: 1.88; p = 0.02). CONCLUSIONS In patients with severe aortic stenosis and high surgical risk, PPM is more frequent and more often severe following SAVR than TAVR. Patients with PPM after SAVR have worse survival and less LV mass regression than those without PPM. Severe PPM also has a significant impact on survival after TAVR in the subset of patients with no post-procedural aortic regurgitation. TAVR may be preferable to SAVR in patients with a small aortic annulus who are susceptible to PPM to avoid its adverse impact on LV mass regression and survival.

In this retrospective subanalysis of high-risk, symptomatic aortic stenosis patients in the PARTNER trial, female subjects had lower late mortality with TAVR versus SAVR. This was especially true among patients suitable for transfemoral access and suggests that TAVR may be preferred over surgery for high-risk female patients. A randomized, controlled trial conducted specifically in female patients is necessary to properly study differences in mortality between treatment modalities. (THE PARTNER TRIAL: Placement of AoRTic TraNscathetER Valve Trial; NCT00530894).

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Background: Measuring fractional flow reserve (FFR) with a pressure wire remains underutilized because of the invasiveness of guide wire placement or the need for a hyperemic stimulus. FFR derived from routine coronary angiography (FFR angio ) eliminates both of these requirements and displays FFR values of the entire coronary tree. The FFR angio Accuracy versus Standard FFR (FAST-FFR) study is a prospective, multicenter, international trial with the primary goal of determining the accuracy of FFR angio . Methods: Coronary angiography was performed in a routine fashion in patients with suspected coronary artery disease. FFR was measured in vessels with coronary lesions of varying severity using a coronary pressure wire and hyperemic stimulus. Based on angiograms of the respective arteries acquired in ≥2 different projections, on-site operators blinded to FFR then calculated FFR angio using proprietary software. Coprimary end points were the sensitivity and specificity of the dichotomously scored FFR angio for predicting pressure wire–derived FFR using a cutoff value of 0.80. The study was powered to meet prespecified performance goals for sensitivity and specificity. Results: Ten centers in the United States, Europe, and Israel enrolled a total of 301 subjects and 319 vessels meeting inclusion/exclusion criteria which were included in the final analysis. The mean FFR was 0.81 and 43% of vessels had an FFR≤0.80. The per-vessel sensitivity and specificity were 94% (95% CI, 88% to 97%) and 91% (86% to 95%), respectively, both of which exceeded the prespecified performance goals. The diagnostic accuracy of FFR angio was 92% overall and remained high when only considering FFR values between 0.75 to 0.85 (87%). FFR angio values correlated well with FFR measurements ( r =0.80, P <0.001) and the Bland–Altman 95% confidence limits were between −0.14 and 0.12. The device success rate for FFR angio was 99%. Conclusions: FFR angio measured from the coronary angiogram alone has a high sensitivity, specificity, and accuracy compared with pressure wire–derived FFR. FFR angio has the promise to substantially increase physiological coronary lesion assessment in the catheterization laboratory, thereby potentially leading to improved patient outcomes. Clinical Trial Registration: URL: https://www.clinicaltrials.gov . Unique Identifier: NCT03226262.

Objective Examine the relationship between left ventricular mass (LVM) regression and clinical outcomes after transcatheter aortic valve replacement (TAVR). Background LVM regression after valve replacement for aortic stenosis (AS) is assumed to be a favorable effect of LV unloading, but its relationship to improved clinical outcomes is unclear. Methods Of 2115 patients with symptomatic AS at high surgical risk receiving TAVR in the PARTNER randomized trial or continued access registry, 690 had both severe LVH (LVM index [LVMi] ³149 g/m2 men, ³122 g/m2 women) at baseline and an LVMi measurement 30 days post-TAVR. Clinical outcomes were compared for patients with greater than vs. lesser than median percent change in LVMi between baseline and 30 days using Cox proportional hazard models to evaluate event rates from 30 to 365 days. Results Compared to patients with lesser regression, patients with greater LVMi regression had a similar rate of all-cause mortality (14.1% vs. 14.3%, p=0.99), but a lower rate of rehospitalization (9.5% vs. 18.5%, HR 0.50; 95% CI, 0.32–0.78; p=0.002) and a lower rate of rehospitalizations specifically for heart failure (7.3% vs. 13.6%, p=0.01). The association with a lower rate of hospitalizations was consistent across sub-groups and remained significant after multivariable adjustment (HR 0.53; 95% CI, 0.34–0.84; p=0.007). Patients with greater LVMi regression had lower BNP (p=0.002) and a trend toward better quality of life (p=0.06) at 1 year compared to those with lesser regression. Conclusions In high-risk patients with severe AS and severe LVH undergoing TAVR, those with greater early LV mass regression had half the rate of rehospitalization over the subsequent year.

Background The rapidly expanding field of microbiome studies offers investigators a large choice of methods for each step in the process of determining the microorganisms in a sample. The human cervicovaginal microbiome affects female reproductive health, susceptibility to and natural history of many sexually transmitted infections, including human papillomavirus (HPV). At present, long-term behavior of the cervical microbiome in early sexual life is poorly understood. Methods The V6 and V6–V9 regions of the 16S ribosomal RNA gene were amplified from DNA isolated from exfoliated cervical cells. Specimens from 10 women participating in the Natural History Study of HPV in Guanacaste, Costa Rica were sampled successively over a period of 5–7 years. We sequenced amplicons using 3 different platforms (Sanger, Roche 454, and Illumina HiSeq 2000) and analyzed sequences using pipelines based on 3 different classification algorithms (usearch, RDP Classifier, and pplacer). Results Usearch and pplacer provided consistent microbiome classifications for all sequencing methods, whereas RDP Classifier deviated significantly when characterizing Illumina reads. Comparing across sequencing platforms indicated 7%–41% of the reads were reclassified, while comparing across software pipelines reclassified up to 32% of the reads. Variability in classification was shown not to be due to a difference in read lengths. Six cervical microbiome community types were observed and are characterized by a predominance of either G. vaginalis or Lactobacillus spp. Over the 5–7 year period, subjects displayed fluctuation between community types. A PERMANOVA analysis on pairwise Kantorovich-Rubinstein distances between the microbiota of all samples yielded an F -test ratio of 2.86 (p<0.01), indicating a significant difference comparing within and between subjects’ microbiota. Conclusions Amplification and sequencing methods affected the characterization of the microbiome more than classification algorithms. Pplacer and usearch performed consistently with all sequencing methods. The analyses identified 6 community types consistent with those previously reported. The long-term behavior of the cervical microbiome indicated that fluctuations were subject dependent.

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