Diagnostic Value of Aortic Valve Calcification Levels in the Assessment of Low-Gradient Aortic Stenosis.

BACKGROUND: In patients with low-gradient aortic stenosis (AS) and low transvalvular flow, dobutamine stress echocardiography (DSE) is recommended to determine AS severity, whereas the degree of aortic valve calcification (AVC) supposedly correlates with AS severity according to current European and American guidelines. OBJECTIVES: The purpose of this study was to assess the relationship between AVC and AS severity as determined using echocardiography and DSE in patients with aortic valve area <1 cm2 and peak aortic valve velocity <4.0 m/s. METHODS: All patients underwent DSE to determine AS severity and multislice computed tomography to quantify AVC. Receiver-operating characteristics curve analysis was used to assess the diagnostic value of AVC for AS severity grading as determined using echocardiography and DSE in men and women. RESULTS: A total of 214 patients were included. Median age was 78 years (25th-75th percentile: 71-84 years) and 25% were women. Left ventricular ejection fraction was reduced (<50%) in 197 (92.1%) patients. Severe AS was diagnosed in 106 patients (49.5%). Moderate AS was diagnosed in 108 patients (50.5%; in 77 based on resting transthoracic echocardiography, in 31 confirmed using DSE). AVC score was high (≥2,000 for men or ≥1,200 for women) in 47 (44.3%) patients with severe AS and in 47 (43.5%) patients with moderate AS. AVC sensitivity was 44.3%, specificity was 56.5%, and positive and negative predictive values for severe AS were 50.0% and 50.8%, respectively. Area under the receiver-operating characteristics curve was 0.508 for men and 0.524 for women. CONCLUSIONS: Multi-slice computed tomography-derived AVC scores showed poor discrimination between grades of AS severity using DSE and cannot replace DSE in the diagnostic work-up of low-gradient severe AS.

Correlation between 3D-QCA based FFR and quantitative lumen assessment by IVUS for left main coronary artery stenoses.

OBJECTIVES: We aimed to evaluate the feasibility of using three dimensional-quantitative coronary angiography (3D-QCA) based fractional flow reserve (FFR) (vessel fractional flow reserve [vFFR], CAAS8.1, Pie Medical Imaging) and to correlate vFFR values with intravascular ultrasound (IVUS) for the evaluation of intermediate left main coronary artery (LMCA) stenosis. BACKGROUND: 3D-QCA derived FFR indices have been recently developed for less invasive functional lesion assessment. However, LMCA lesions were vastly under-represented in first validation studies. METHODS: This observational single-center cohort study enrolled consecutive patients with stable angina, unstable angina, or non-ST-segment elevation myocardial infarction and nonostial, intermediate grade LMCA stenoses who underwent IVUS evaluation. vFFR was computed based on two angiograms with optimal LMCA stenosis projection and correlated with IVUS-derived minimal lumen area (MLA). RESULTS: A total of 256 patients with intermediate grade LMCA stenosis evaluated with IVUS were screened for eligibility; 147 patients met the clinical inclusion criteria and had a complete IVUS LMCA footage available, of them, 63 patients (63 lesions) underwent 3D-QCA and vFFR analyses. The main reason for screening failure was insufficient quality of the angiogram (51 patients,60.7%). Mean age was 65 ± 11 years, 75% were male. Overall, mean MLA within LMCA was 8.77 ± 3.17 mm2 , while mean vFFR was 0.87 ± 0.09. A correlation was observed between vFFR and LMCA MLA (r = .792, p = .001). The diagnostic accuracy of vFFR ≤0.8 in identifying lesions with MLA < 6.0 mm2 (sensitivity 98%, specificity 71.4%, area under the curve (AUC) 0.95, 95% confidence interval (CI) 0.89-1.00, p = .001) was good. CONCLUSIONS: In patients with good quality angiographic visualization of LMCA and available complete LMCA IVUS footage, 3D-QCA based vFFR assessment of LMCA disease correlates well to LMCA MLA as assessed by IVUS.

A value-based healthcare approach: Health-related quality of life and psychosocial functioning in women with Turner syndrome.

OBJECTIVE: As part of the value-based healthcare programme in our hospital, a set of patient-reported outcome measures was developed together with patients and implemented in the dedicated Turner Syndrome (TS) outpatient clinic. This study aims to investigate different aspects of health-related quality of life (HR-QoL) and psychosocial functioning in women with TS in order to establish new possible targets for therapy. DESIGN/PARTICIPANTS: A comprehensive set of questionnaires (EQ-5D, PSS-10, CIS-20, Ferti-QoL, FSFI) was developed and used to capture different aspects of HR-QoL and psychosocial functioning in a large cohort of adult women with Turner syndrome. All consecutive women, ≥18 years, who visited the outpatient clinic of our tertiary centre were eligible for inclusion. RESULTS: Of the eligible 201 women who were invited to participate, 177 women (age 34 ± 12 years, mean ± SD) completed at least one of the validated questionnaires (88%). Women with TS reported a lower health-related quality of life (EQ-5D: 0.857 vs 0.892, P = .003), perceived more stress (PSS-10:14.7 vs 13.3; P = .012) and experienced increased fatigue (CIS-20: P < .001) compared to the general Dutch population. A relationship between noncardiac comorbidities (eg diabetes, orthopaedic complaints) and HR-QoL was found (R = .508). CONCLUSIONS: We showed that TS women suffer from impaired HR-QoL, more perceived stress and increased fatigue compared to healthy controls. A relationship between noncardiac comorbidities and HR-QoL was found. Especially perceived stress and increased fatigue can be considered targets for improvement of HR-QoL in TS women.

Repeated Echocardiograms Do Not Provide Incremental Prognostic Value to Single Echocardiographic Assessment in Minimally Symptomatic Patients with Chronic Heart Failure: Results of the Bio-SHiFT Study.

BACKGROUND: We aimed to compare the prognostic value of a single "baseline" echocardiogram with repeated echocardiography in stable chronic heart failure (CHF) patients. We hypothesized that repeated echocardiograms would contain incremental prognostic information. METHODS: In the prospective Bio-SHiFT study, we performed 332 echocardiograms in 106 patients during a median follow-up of 2.3 years. The endpoint comprised HF hospitalization, left ventricular (LV) assist device implantation, heart transplantation, and cardiovascular death. We compared hazard ratios (HRs; adjusted for N-terminal pro-brain natriuretic peptide) from Cox models for the first available measurement with HRs from joint models, which model individual trajectories based on the repeated measurements and link these to the time-to-event data. RESULTS: The mean age of the patients was 58.1 years; 78.3% were male, 12.6% had New York Heart Association class >II, all had reduced ejection fraction, and the most common HF etiologies were cardiomyopathies (51%) and ischemia (40%). The endpoint occurred in 25 patients. Both the single measurements and the temporal trajectories were significantly associated with the endpoint (adjusted HR Cox model [95% CI] vs adjusted HR joint model [95% CI]): LV ejection fraction, 1.47 (0.93-2.31) vs 1.77 (1.13-2.93); diastolic LV diameter, 1.64 (1.09-2.47) vs 1.68 (1.12-2.57); systolic LV diameter, 1.72 (1.10-2.69) vs 1.68 (1.13-2.63); systolic left atrial diameter, 1.88 (1.18-3.00) vs 2.60 (1.48-4.97); E/A ratio, 2.73 (1.42-5.26) vs 3.87 (1.75-10.13); and E/e' ratio, 2.30 (1.38-3.84) vs 2.99 (1.68-6.19). None of the trajectories from the investigated parameters showed worsening prior to events. CONCLUSIONS: Although single baseline or repeatedly measured echocardiographic parameters were associated with the endpoint, all parameters remained on average stable during the 2.3 years of follow-up in this largely minimally symptomatic CHF cohort. Thus, regular echocardiographic monitoring of systolic or diastolic LV function within this time frame does not carry incremental prognostic information over a single baseline measurement.

SYNTAX score in relation to intravascular ultrasound and near-infrared spectroscopy for the assessment of atherosclerotic burden in patients with coronary artery disease.

AIMS: The aim of this study was to examine the relationship between the anatomical SYNTAX score (SXscore), derived from all three coronary arteries, and coronary wall pathology measured by radiofrequency intravascular ultrasound (RF-IVUS) and near-infrared spectroscopy (NIRS) in a single non-culprit segment. METHODS AND RESULTS: In patients referred for coronary angiography (N=88) or PCI (N=592) for stable angina or acute coronary syndrome, the SYNTAX score calculator (www.syntaxscore.com) was used to determine the SXscore before PCI, if applicable. RF-IVUS and/or NIRS were performed in a non-stenotic 40 mm study segment following the clinically indicated angiography/PCI. After adjustment for multiple confounders, a higher SXscore was associated with higher segmental plaque volume in the study segment (2.21 mm3 per SXscore point, 95% CI: 0.92-3.50, p-value 0.001), as well as with higher volume of fibrous (0.93 mm3 per point) and fibro-fatty tissue (0.29 mm3 per point). A higher SXscore was also associated with a higher NIRS-derived lipid core burden index (LCBI) in the full study segment (1.35 units per SXscore point, 95% CI: 0.22-2.47, p-value 0.019). Importantly, SXscore correlated with the fatty/fibro-fatty and LCBI signals despite adjusting for plaque burden. CONCLUSIONS: In patients with CAD, higher SXscores are associated with higher atherosclerotic burden as assessed by RF-IVUS and NIRS in a single non-stenotic coronary artery segment.

Personalized dynamic risk assessment in nephrology is a next step in prognostic research.

In nephrology, repeated measures are frequently available (glomerular filtration rate or proteinuria) and linked to adverse outcomes. However, several features of these longitudinal data should be considered before making such inferences. These considerations are discussed, and we describe how joint modeling of repeatedly measured and time-to-event data may help to assess disease dynamics and to derive personalized prognosis. Joint modeling combines linear mixed-effects models and Cox regression model to relate patient-specific trajectory to their prognosis. We describe several aspects of the relationship between time-varying markers and the endpoint of interest that are assessed with real examples to illustrate the aforementioned aspects of the longitudinal data provided. Thus, joint models are valuable statistical tools for study purposes but also may help health care providers in making well-informed dynamic medical decisions.

A simple risk chart for initial risk assessment of 30-day mortality in patients with cardiogenic shock from ST-elevation myocardial infarction.

AIMS: Early risk stratification is important in patients with cardiogenic shock from ST-elevation myocardial infarction (STEMI). We aimed to develop a simple risk chart that includes clinical parameters that are readily available at time of hospital admission to assess risk of 30-day mortality. METHODS AND RESULTS: A series of 544 STEMI patients admitted to undergo primary percutaneous coronary intervention and presenting with cardiogenic shock were included between 2000 and 2012. Overall 30-day mortality was 38.4% and did not change over the years (p-trend=0.64). Baseline variables that were available at time of hospital admission were entered into a logistic regression model in a forward stepwise manner. Only age (odds ratio (OR) per year 1.05, 95% confidence interval (CI) 1.04-1.07, p<0.001), initial serum lactate level (OR per mmol/l 1.17, 95% CI 1.11-1.24, p<0.001) and initial creatinine level above the upper limit of normal (OR 2.89, 95% CI 1.90-4.37, p<0.001) remained independent predictors, and were subsequently used to develop a risk chart that stratifies risk of 30-day mortality into categories ranging from 0-20% to 80-100%. The calibration plot showed a close relationship between expected and observed mortality. The risk chart had a higher discriminative accuracy than the GRACE score (c-index 0.75 vs. 0.66, p=0.009). Adding variables that were obtained from coronary angiography and during clinical course did not significantly improve discriminative accuracy of risk chart (c-index 0.77, p=0.48). CONCLUSION: Mortality of patients with cardiogenic shock from STEMI undergoing primary percutaneous coronary intervention can be well predicted already at time of hospital admission by a risk chart that uses only three variables, namely, age, initial serum lactate and creatinine level.

Development and validation of a cardiovascular risk assessment model in patients with established coronary artery disease.

Appropriate risk stratification of patients with established, stable coronary artery disease could contribute to the prevention of recurrent cardiovascular events. The purpose of the present study was to develop and validate risk prediction models for various cardiovascular end points in the EURopean trial On reduction of cardiac events with Perindopril in stable coronary Artery disease (EUROPA) database, consisting of 12,218 patients with established coronary artery disease, with a median follow-up of 4.1 years. Cox proportional hazards models were used for model development. The end points examined were cardiovascular mortality, noncardiovascular mortality, nonfatal myocardial infarction, coronary artery bypass grafting, percutaneous coronary intervention, resuscitated cardiac arrest, and combinations of these end points. The performance measures included Nagelkerke's R², time-dependent area under the receiver operating characteristic curves, and calibration plots. Backward selection resulted in a prediction model for cardiovascular mortality (464 events) containing age, current smoking, diabetes mellitus, total cholesterol, body mass index, previous myocardial infarction, history of congestive heart failure, peripheral vessel disease, previous revascularization, and previous stroke. The model performance was adequate for this end point, with a Nagelkerke R² of 12%, and an area under the receiver operating characteristic curve of 0.73. However, the performance of models constructed for nonfatal and combined end points was considerably worse, with an area under the receiver operating characteristic curve of about 0.6. In conclusion, in patients with established coronary artery disease, the risk of cardiovascular mortality during longer term follow-up can be adequately predicted using the clinical characteristics available at baseline. However, the prediction of nonfatal outcomes, both separately and combined with fatal outcomes, poses major challenges for clinicians and model developers.

Microsimulation for clinical decision-making in individual patients with established coronary artery disease: a concept.

BACKGROUND: In cardiovascular disease, numerous evidence-based prognostic models have been created, usually based on regression analyses of isolated patient datasets. They tend to focus on one outcome event, based on just one baseline evaluation of the patient, and fail to take the disease process in its dynamic nature into account. We present so-called microsimulation as an attractive alternative for clinical decision-making in individual patients. We aim to further familiarize clinicians with the concept of microsimulation and to inform them about the modeling process. METHODS AND RESULTS: We describe the modeling process, advantages and disadvantages of microsimulation. We illustrate the concept using a hypothetical 60-year-old patient, with several cardiac risk factors, who is hospitalized for myocardial infarction. By using microsimulation, we calculate this patient's probability of death. In our example, this particular patient's estimated life expectancy turns out to be 8.9 years. While calculating this life expectancy, we were able to account for multiple outcome events and changing patient characteristics. CONCLUSIONS: Microsimulation takes into account the dynamic nature of coronary artery disease by estimating most likely outcomes regarding a broad range of clinical events. Moreover, microsimulation can be used to evaluate treatment effects by estimating the event-free life expectancy with and without treatment. Hence, microsimulation has several advantages compared to modeling techniques such as regression.