Abstract 129: Clinical Predictive Models for Valvular Heart Disease: A Systematic Review of the Literature

2017 ◽  
Vol 10 (suppl_3) ◽  
Author(s):  
Benjamin S Wessler ◽  
Muhammad Ajlan ◽  
Christine Lundquist ◽  
Zuhair Natto ◽  
Jessica Paulus ◽  
...  
Keyword(s):  
Systematic Review ◽  
Heart Disease ◽  
Predictive Models ◽  
Valvular Heart Disease ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Surgical Interventions ◽  
Percutaneous Interventions ◽  
C Statistic ◽  
Original Report

Objectives: Pre-procedure risk assessment is central to clinical decision making for patients with advanced valvular heart disease (VHD) and treatments are increasingly being offered to patients with elevated pre-procedure risk. While there are numerous clinical predictive models (CPMs) available for patients with VHD, the relative performance of these CPMs is largely unknown. Here we describe the performance of CPMs available for patients with VHD with specific attention to whether CPMs have been externally validated. Methods: To identify CPMs for patients with VHD, we conducted a systematic review of the Tufts PACE CPM Registry, a comprehensive database of cardiovascular CPMs. For each identified CPM for patients with VHD, we performed a complete citation search using Scopus to identify any external validations of these models published in other articles. We extracted information on CPM performance in both the original report and also the external validations. For external validations we calculated the relative percent decrease in discrimination. Results: We identified 41 CPMs predicting outcomes for patients with VHD. 33 (81%) predict outcomes following surgical intervention, 5 (12%) predict outcomes following percutaneous interventions, and 3 (7%) predict outcomes in the absence of intervention. Only 30/41 (73%) of the CPMs report a c-statistic. The median reported c- statistic was 0.77 [IQR, 0.04] for CPMs predicting outcomes following surgical interventions, 0.68 [IQR, 0.04] for CPMs for percutaneous interventions, and 0.83 [IQR, 0.07] for CPMs predicting outcomes in the absence of intervention. While a total of 69 external validations of these CPMs have been published, only 21 (51%) of the CPMs have ever been externally validated. For external validations that report c- statistics, we noted a median percent decrement in discrimination of -27.6% [IQR, -37.4] ( Figure) . Conclusion: While there are numerous CPMs for patients with VHD, performance is often incompletely reported and half of these CPMs have never been externally validated. The CPMs that have been externally validated generally show substantially worse discrimination in external datasets compared to the derivation datasets.

Valvular Heart Disease

2014 ◽  
pp. 819-829
Author(s):  
Christian T. Ruff ◽  
Patrick T. O’Gara
Keyword(s):  
Heart Disease ◽  
Natural History ◽  
Valvular Heart Disease ◽  
Clinical Decision Making ◽  
Ventricular Remodeling ◽  
Vitamin K Antagonists ◽  
Clinical Decision ◽  
Physiological Importance ◽  
Treatment And Prevention ◽  
Cardiopulmonary Performance

The physiological importance of valvular heart disease relates to its effects on cardiopulmonary performance. Symptom onset equates with a distinct change in natural history. The development of atrial fibrillation (AF), ventricular remodeling, hypertrophy, and/or pump dysfunction impacts long-term survival. Diagnosis is most commonly triggered by the appreciation of a heart murmur, following which a decision is made regarding the need for echocardiography for further assessment. Many heart murmurs are benign and need not prompt additional testing. Institution of medical therapy to ameliorate symptoms or prevent complications, such as the use of vitamin K antagonists for patients, should be coupled with an appraisal of the indications for surgical or percutaneous intervention. An integrated understanding of natural history based on the severity of the valve lesion within the context of individual patient comorbidities is the foundation for appropriate clinical decision making. We review here the major valve lesions; treatment and prevention of infective endocarditis are covered elsewhere.

Clinical models to predict response and survival in metastatic melanoma (MM) patients (pts) treated with anti-PD-1 alone (PD1) or combined with ipilimumab (IPI+PD1).

2019 ◽  
Vol 37 (15_suppl) ◽  
pp. 9542-9542
Author(s):  
Ines Esteves Domingues Pires Da Silva ◽  
Tasnia Ahmed ◽  
Serigne Lo ◽  
Rajat Rai ◽  
Jessica Louise Smith ◽  
...  
Keyword(s):  
Predictive Models ◽  
Clinical Decision Making ◽  
External Validation ◽  
Prognostic Index ◽  
Primary Melanoma ◽  
Progression Free Survival ◽  
Clinical Decision ◽  
Monocyte Count ◽  
C Statistic ◽  
Mutational Status

9542 Background: Currently there are no robust biomarkers to predict immunotherapy response in MM. Specific clinical and molecular variables have been proposed, but in most cases, these factors have been studied individually. We sought to build a predictive model for response rate (RR), progression-free survival (PFS) and overall survival (OS), by including clinical data available at the point of treatment selection for MM pts treated with PD1 or IPI+PD1. Methods: 786 MM pts were included in 4 cohorts; 447 pts treated with PD1 (discovery, n = 343; validation, n = 104) and 339 pts treated with IPI+PD1 (discovery, n = 229; validation, n = 110). Demographics, disease characteristics and baseline blood parameters were examined. Predictive models were selected using multivariate Cox proportional hazard model, logistic regression and LASSO. ROC curve analyses were performed for each model and validation was measured by discrimination índex (c-statistic). Results: Predictive models for RR and PFS in PD1 pts (AUC = 0.69 and AUC = 0.71, respectively) included mutational status (HR for PFS: BRAF 1; NRAS 0.68; WT 0.57; P = 0.002), primary melanoma site (HR for PFS: occult 1; head and neck 0.67, others 1.04; P = 0.052), elevated LDH (HR for PFS: 1.77, P < 0.0001) and monocyte count > median (HR for PFS: 1.56, P = 0.003). Predictive models for RR and PFS in IPI+PD1 treated pts (AUC = 0.71 and AUC = 0.73, respectively) included AJCC stage M1C/M1D (HR for PFS: 2.12, P = 0.009), elevated LDH (HR for PFS: 2.65, P < 0.0001), liver mets (HR for PFS: 1.63, P = 0.038) and basophil count > median (HR for PFS: 0.50, P = 0.003). ECOG ≥ 1, elevated LDH and brain mets associated with worse OS and were included in predictive models for OS in PD1 (AUC = 0.74) and IPI+PD1 (AUC = 0.85). These models showed consistency with internal and external validation (c-statistic: < 10% difference between the original model and validations for all outcomes). Conclusions: A combination of routinely collected clinical factors are highly predictive of outcome in MM pts treated with PD1 and IPI+PD1. A prognostic index will be presented for each treatment. Such tools may be practical, cheap and valuable for clinical decision making.

Multiple and mixed valvular heart disease

2021 ◽  
pp. 223-232
Author(s):  
Philippe Unger ◽  
Madalina Garbi
Keyword(s):  
Heart Disease ◽  
Valvular Heart Disease ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Integrative Approach ◽  
Vena Contracta ◽  
Regurgitant Orifice Area ◽  
Valve Lesion ◽  
Valve Lesions ◽  
Stenotic Lesions

Multiple and mixed valvular heart disease are highly prevalent. Multiple valvular heart disease is the combination of stenotic and/or regurgitant lesions occurring on two or more cardiac valves. Mixed valvular heart disease is the combination of stenotic and regurgitant lesions on the same valve. Several haemodynamic interactions may impact their clinical expression and may result in diagnostic pitfalls. Accurate quantification of the valve lesions requires the use of methods that are less dependent on loading conditions, such as planimetry for stenotic lesions, and assessment of the effective regurgitant orifice area and vena contracta for regurgitant lesions. The assessment should address the diagnosis and severity of each single valve lesion as well as the overall consequences resulting from the combination of all lesions. Clinical decision-making should be based on an integrative approach including echocardiography and other imaging modalities.

scholarly journals Appropriate use criteria for cardiovascular magnetic resonance imaging (CMR): SIC—SIRM position paper part 1 (ischemic and congenital heart diseases, cardio-oncology, cardiac masses and heart transplant)

2021 ◽  
Vol 126 (3) ◽  
pp. 365-379
Author(s):  
Gianluca Pontone ◽  
Ernesto Di Cesare ◽  
Silvia Castelletti ◽  
Francesco De Cobelli ◽  
Manuel De Lazzari ◽  
...  
Keyword(s):  
Heart Disease ◽  
Magnetic Resonance ◽  
Heart Transplant ◽  
Congenital Heart ◽  
Clinical Decision Making ◽  
Heart Diseases ◽  
Integrated Approach ◽  
Clinical Decision ◽  
Italian Society ◽  
Cardiac Masses

AbstractCardiac magnetic resonance (CMR) has emerged as new mainstream technique for the evaluation of patients with cardiac diseases, providing unique information to support clinical decision-making. This document has been developed by a joined group of experts of the Italian Society of Cardiology and Italian society of Radiology and aims to produce an updated consensus statement about the current state of technology and clinical applications of CMR. The writing committee consisted of members and experts of both societies who worked jointly to develop a more integrated approach in the field of cardiac radiology. Part 1 of the document will cover ischemic heart disease, congenital heart disease, cardio-oncology, cardiac masses and heart transplant.

Abstract 223: Non-Cardiac Comorbidities in Predictive Models for Valvular Heart Disease Interventions

2016 ◽  
Vol 9 (suppl_2) ◽  
Author(s):  
Benjamin Wessler ◽  
Christine Lundquist ◽  
Gowri Raman ◽  
Jennifer Lutz ◽  
Jessica Paulus ◽  
...  
Keyword(s):  
Heart Disease ◽  
Predictive Models ◽  
Valvular Heart Disease ◽  
De Novo ◽  
Predictive Analytics ◽  
Model Performance ◽  
Median Number ◽  
Valve Surgery ◽  
Comorbid Condition ◽  
Comorbid Conditions

Background: Interventions for patients with valvular heart disease (VHD) now include both surgical and percutaneous procedures. As a result, treatments are being offered to increasingly complex patients with a significant burden of non-cardiac comorbid conditions. There is a major gap in our understanding of how various comorbidities relate to prognosis following interventions for VHD. Here we describe how comorbidities are handled in clinical predictive models for patients undergoing interventions for VHD. Methods: We queried the Tufts Predictive Analytics and Comparative Effectiveness (PACE) Clinical Prediction Model (CPM) Registry to identify de novo CPMs for patients undergoing VHD interventions. We systematically extracted information on the non-cardiac comorbidities contained in the CPMs and also measures of model performance. Results: From January 1990- May 2012 there were 12 CPMs predicting measures of morbidity or mortality for patients undergoing interventions for VHD. There were 2 CPMs predicting outcomes for isolated aortic valve replacement, 3 CPMs predicting outcomes for isolated mitral valve surgery, and 7 models predicting outcomes for a combination of valve surgery subtypes. Ten out of twelve (83%) of the CPMs for patients undergoing interventions for VHD predicted mortality. The median number of non-cardiac comorbidities included in the CPMs was 4 (range 0-7). All of the CPMs predicting mortality included at least 1 comorbid condition. The top 3 most common comorbidities included in these CPMs were, renal dysfunction (10/12, 83%), prior CVA (7/12, 58%) and measures of BMI/BSA (7/12, 58%). Diabetes was present in only 25% (3/12) of the models and chronic lung disease in only 17% (2/12). Conclusions: Non-cardiac comorbidities are frequently found in CPMs predicting morbidity and mortality following interventions for VHD. There is significant variation in the number and type of specific comorbid conditions included in these CPMs. More work is needed to understand the directionality, magnitude, and consistency of effect of these non-cardiac comorbid conditions for patients undergoing interventions for VHD.

scholarly journals Diagnostic utility of the Active Compression Test for the superior labrum anterior posterior tear: A systematic review

2018 ◽  
Vol 11 (5) ◽  
pp. 321-331
Author(s):  
Cody Davis ◽  
Jenna Immormino ◽  
Brendan M Higgins ◽  
Kyle Clark ◽  
Samuel Engebose ◽  
...  
Keyword(s):  
Systematic Review ◽  
Diagnostic Accuracy ◽  
Compression Test ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Risk Of Bias ◽  
Pretest Probability ◽  
Positive Finding ◽  
Negative Finding ◽  
Superior Labrum

Background The Active Compression Test has been proposed to have high diagnostic accuracy for superior labrum anterior to posterior tears. The aim of this systematic review was to compile the available evidence for this test and evaluate its diagnostic accuracy. Methods The databases PubMed, Embase, Cochrane, CINAHL, and SCOPUS were searched for case control, diagnostic studies that evaluated the Active Compression Test between 1999 (date of test introduction) and February 2018. Two independent review authors screened the search results, assessed the risk of bias using QUADAS-2, and extracted the data. Results Eighteen studies (pooled sample = 3091) were included in this review. Twelve out of 18 studies either had high or unclear risk of bias (66.6%). Results from the pooled analysis of all 18 studies provided that the Active Compression Test is more sensitive (71.5: 95% CI = 68.8, 74.0) than specific (51.9: 95% CI = 50.7, 53.1) and only marginally influenced posttest probability from a pretest probability of 31.7–40.72% with a positive finding and a pretest probability of 31.7–20.33% with a negative finding. Discussion The Active Compression Test has both limited screening and confirmation ability; therefore, we do not advocate for its use in clinical decision making.

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