The rapid technological developments of the past decade and the changes in echocardiographic practice brought about by these developments have resulted in the need for updated recommendations to the previously published guidelines for cardiac chamber quantification, which was the goal of the joint writing group assembled by the American Society of Echocardiography and the European Association of Cardiovascular Imaging. This document provides updated normal values for all four cardiac chambers, including three-dimensional echocardiography and myocardial deformation, when possible, on the basis of considerably larger numbers of normal subjects, compiled from multiple databases. In addition, this document attempts to eliminate several minor discrepancies that existed between previously published guidelines.

https://biblio.ugent.be/publication/5953422/file/5953443.pdf

Recommendations for cardiac chamber quantification by echocardiography in adults: an update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging.

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It is important that the medical profession play a significant role in critically evaluating the use of diagnostic procedures and therapies as they are introduced in the detection, management,

/pdf/acc-aha-2006-guidelines-for-the-management-of-patients-with-27qfh9fc7i.pdf

ACC/AHA 2006 Guidelines for the Management of Patients With Valvular Heart Disease

WRITING GROUP MEMBERS Emelia J. Benjamin, MD, SCM, FAHA Michael J. Blaha, MD, MPH Stephanie E. Chiuve, ScD Mary Cushman, MD, MSc, FAHA Sandeep R. Das, MD, MPH, FAHA Rajat Deo, MD, MTR Sarah D. de Ferranti, MD, MPH James Floyd, MD, MS Myriam Fornage, PhD, FAHA Cathleen Gillespie, MS Carmen R. Isasi, MD, PhD, FAHA Monik C. Jiménez, ScD, SM Lori Chaffin Jordan, MD, PhD Suzanne E. Judd, PhD Daniel Lackland, DrPH, FAHA Judith H. Lichtman, PhD, MPH, FAHA Lynda Lisabeth, PhD, MPH, FAHA Simin Liu, MD, ScD, FAHA Chris T. Longenecker, MD Rachel H. Mackey, PhD, MPH, FAHA Kunihiro Matsushita, MD, PhD, FAHA Dariush Mozaffarian, MD, DrPH, FAHA Michael E. Mussolino, PhD, FAHA Khurram Nasir, MD, MPH, FAHA Robert W. Neumar, MD, PhD, FAHA Latha Palaniappan, MD, MS, FAHA Dilip K. Pandey, MBBS, MS, PhD, FAHA Ravi R. Thiagarajan, MD, MPH Mathew J. Reeves, PhD Matthew Ritchey, PT, DPT, OCS, MPH Carlos J. Rodriguez, MD, MPH, FAHA Gregory A. Roth, MD, MPH Wayne D. Rosamond, PhD, FAHA Comilla Sasson, MD, PhD, FAHA Amytis Towfighi, MD Connie W. Tsao, MD, MPH Melanie B. Turner, MPH Salim S. Virani, MD, PhD, FAHA Jenifer H. Voeks, PhD Joshua Z. Willey, MD, MS John T. Wilkins, MD Jason HY. Wu, MSc, PhD, FAHA Heather M. Alger, PhD Sally S. Wong, PhD, RD, CDN, FAHA Paul Muntner, PhD, MHSc On behalf of the American Heart Association Statistics Committee and Stroke Statistics Subcommittee Heart Disease and Stroke Statistics—2017 Update

Heart Disease and Stroke Statistics—2017 Update: A Report From the American Heart Association

ACC/AHA guidelines for the management of patients with ST-elevation myocardial infarction--executive summary: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines (Writing Committee to Revise the 1999 Guidelines for the Management of Patients With Acute Myocardial Infarction).

Jeffrey L. Anderson, MD, FACC, FAHA, Chair 

Jonathan L. Halperin, MD, FACC, FAHA, Chair-Elect 

Nancy M. Albert, PhD, RN, FAHA

Biykem Bozkurt, MD, PhD, FACC, FAHA

Ralph G. Brindis, MD, MPH, MACC

Mark A. Creager, MD, FACC, FAHA[#][1]

Lesley H. Curtis, PhD, FAHA

David DeMets, PhD[#][1]

Robert A

/pdf/2014-aha-acc-hrs-guideline-for-the-management-of-patients-1v8ficsqox.pdf

2014 AHA/ACC/HRS Guideline for the Management of Patients With Atrial Fibrillation: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines and the Heart Rhythm Society

Long-Term Survival Following Aortic Valve Replacement among High-Risk Elderly Patients in the United States: Insights from the STS Adult Cardiac Surgery Database, 1991-2007

Computer-based training initiatives for education in surgical decision making

Quality Improvement and Risk Stratification for Congenital Cardiac Surgery

In the current issue of Circulation , Gupta et al1 describe a new model for the prediction of cardiac risk after noncardiac surgery. The authors note that perioperative myocardial infarction varies considerably from patient to patient and from procedure to procedure and is associated with very significant morbidity and mortality. The thrust of their argument is that, if patients at higher risk for myocardial infarction and cardiac arrest are identified preoperatively, many could potentially benefit from the optimization of their cardiac status before elective surgery, or, indeed, further consideration should be given as to whether or not an operation is advised. Goldman et al, in a very important 1977 article,2 proposed a multifactorial index for cardiac risk in noncardiac surgical procedures. This has been the gold standard for many years. This article was further modified by Lee, Goldman, et al in 1999,3 when they proposed a simple index …

Objective assessment of cardiac risk for noncardiac surgical patients: an up-to-date simplified approach.

The use of statistical risk models has become an integral part of cardiovascular medicine. Risk assessment for transcatheter aortic valve replacement (TAVR) is particularly challenging because of the need to predict risk for surgical aortic valve replacement as well as the risk of the TAVR procedure itself. In the United States, Society of Thoracic Surgeons (STS) risk models are typically used to estimate surgical aortic valve replacement risk to categorize TAVR candidates into low-, intermediate-, or high-risk groups. These STS models are fully disclosed in the literature and provided to all STS database participants, thereby making them readily available for widespread use.1 As pointed out by Rogers et al,2 the models must be used carefully, with full recognition of their designed features. Temporal changes in the patient population and procedural outcomes are known to occur, so the models are frequently updated to accurately reflect these changes. As illustrated by Rogers et al,2 inaccuracies and misclassification are likely if models developed for a certain year are applied to a patient population from a different year. This clearly constitutes a misuse of the STS surgical aortic valve replacement risk models. Another misuse of STS models is seen in the unfortunate tendency to use STS models to predict the risk of the TAVR procedure itself. There is widespread recognition that this yields inadequate estimates of TAVR risk.3,4 Statistical risk models are designed to predict risk only for the population used to develop the models. To predict the risk of TAVR procedures, then, one should use risk models that have been developed solely for a TAVR population.3,5 Such models based entirely on a TAVR population have recently been published,6-8 and heart teams should be encouraged to use these models to estimate the risk of TAVR procedures. Of these, the model from the STS/American College of Cardiology Transcatheter Valve Therapy Registry is based on the largest patient cohort and uses a “real-world” experience to predict inhospitalTAVRmortality.8 Othermodelsattempttopredictlongerterm mortality, albeit from a select clinical trial population.6 Prediction of adverse outcomes is clearly important, but especially in the TAVR population, there is a compelling need to also predict patient benefit. Even if there is a low chance of adverse events, the procedure should not be performed unless there is a reasonable probability of providing a tangible benefit. It may be possible to infer benefit by comparing preprocedure and postprocedure measurements of parameters that reflect physiologic status. Examples include grip strength and the 5-m walk test to measure frailty9 and the Kansas City Cardiomyopathy Questionnaire10 to quantitate symptoms of heart failure. If these metrics can be collected before and after the procedure, it then becomes possible to develop statistical models to predict preprocedure/postprocedure difference based on specific patient characteristics. If the preprocedure/ postprocedure difference is a reflection of “benefit,” then developing predictive models of patient benefit should be straightforward. The ability to objectively predict patient benefit as well as patient risk will be critically important in the highrisk TAVR population. Statistical models to predict patient benefit are being developed by the Transcatheter Valve Therapy Registry and should provide a significant upgrade in our ability to evaluate candidates for the TAVR procedure. The unique aspects of TAVR have hastened the development of a new generation of predictive models. Reliance on models designed for other purposes should appropriately diminish as these newer, more procedure-specific models come on line as the standard for TAVR risk assessment.

Fred H. Edwards

Papers

Long-Term Survival Following Aortic Valve Replacement among High-Risk Elderly Patients in the United States: Insights from the STS Adult Cardiac Surgery Database, 1991-2007

Computer-based training initiatives for education in surgical decision making

Quality Improvement and Risk Stratification for Congenital Cardiac Surgery

Objective assessment of cardiac risk for noncardiac surgical patients: an up-to-date simplified approach.

Use of Society of Thoracic Surgeons Risk Models in the Assessment of Patients Who Underwent a Transcatheter Aortic Valve Replacement.