Risk prediction models and scores in hypertrophic cardiomyopathy

2021 ◽  
Vol 27 ◽  
Author(s):  
Thomas D. Gossios ◽  
Konstantinos Savvatis ◽  
Thomas Zegkos ◽  
Despina Parcharidou ◽  
Haralambos I Karvounis ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hypertrophic Cardiomyopathy ◽  
Risk Stratification ◽  
Prediction Models ◽  
Risk Category ◽  
Predictive Capacity ◽  
European Guidelines ◽  
Device Implantation ◽  
Increased Risk ◽  
Risk Stratum

: Hypertrophic cardiomyopathy (HCM) has historically been linked with sudden cardiac death (SCD). Currently, it is well established that only a subset of patients is at the highest risk stratum for such a catastrophic event. Detection of patients belonging to this high-risk category can allow for timely defibrillator implantation, changing the natural history of HCM. Inversely, device implantation in patients deemed at low risk leads to an unnecessary burden of device complications with no apparent protective benefit. Previous studies have identified a series of markers, now considered as established risk factors, with genetic testing and newer imaging allowing for the detection of novel, highly promising indices of increased risk for SCD. Despite the identification of a number of risk factors, there is noticeable discrepancy on the utility of such factors for risk stratification between the current American and European guidelines. We sought to systematically review the data available on these two approaches, presenting their rationale and respective predictive capacity, also discussing the potential of novel markers to augment the precision of currently used risk stratification models for SCD in HCM.

scholarly journals Application of Standardised Effect Sizes to Hospital Discharge Outcomes for People with Diabetes

2020 ◽  
Author(s):  
Tim David Robbins ◽  
Sarah N. Lim Choi Keung ◽  
Sailesh Sankar ◽  
Harpal Randeva ◽  
Theodoros N. Arvanitis
Keyword(s):  
Risk Factors ◽  
Risk Stratification ◽  
Prediction Models ◽  
Significant Risk ◽  
Research Literature ◽  
Effect Sizes ◽  
Tertiary Referral Centre ◽  
Increased Risk ◽  
Patients With Diabetes ◽  
Discharge From Hospital

Abstract Background: Patients with diabetes are at an increased risk of readmission and mortality when discharged from hospital. Existing research identifies statistically significant risk factors that are thought to underpin these outcomes. Increasingly, these risk factors are being used to create risk prediction models, and target risk modifying interventions. These risk factors are typically reported in the literature accompanied by unstandardized effect sizes, which makes comparisons difficult. We demonstrate an assessment of variation between standardised effect sizes for such risk factors across care outcomes and patient cohorts. Such an approach will support development of more rigorous risk stratification tools and better targeting of intervention measures. Methods: Data was extracted from the electronic health record of a major tertiary referral centre, over a 3-year period, for all patients discharged from hospital with a concurrent diagnosis of diabetes mellitus. Risk factors selected for extraction were pre-specified according to a systematic review of the research literature. Standardised effect sizes were calculated for all statistically significant risk factors, and compared across patient cohorts and both readmission & mortality outcome measures. Results: Data was extracted for 46,357 distinct admissions patients, creating a large dataset of approximately 10,281,400 data points. The calculation of standardized effect size measures allowed direct comparison. Effect sizes were noted to be larger for mortality compared to readmission, as well as for being larger for surgical and type 1 diabetes cohorts of patients. Conclusions: The calculation of standardised effect sizes is an important step in evaluating risk factors for healthcare events. This will improve our understanding of risk and support the development of more effective risk stratification tools to support patients to make better informed decisions at discharge from hospital.

Abstract 14760: Myocardial Scarring by Magnetic Resonance Predicts Sudden Cardiac Death in Pediatric Patients With Hypertrophic Cardiomyopathy

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Lars Grosse-Wortmann ◽  
Laurine van der Wal ◽  
Aswathy Vaikom House ◽  
Lee Benson ◽  
Raymond Chan
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Hypertrophic Cardiomyopathy ◽  
Sudden Cardiac Death ◽  
Cardiac Death ◽  
Pediatric Patients ◽  
Risk Markers ◽  
C Statistic ◽  
Increased Risk ◽  
Traditional Risk Factors

Introduction: Cardiovascular magnetic resonance (CMR) with late gadolinium enhancement (LGE) has been shown to be an independent predictor of sudden cardiac death (SCD) in adults with hypertrophic cardiomyopathy (HCM). The clinical significance of LGE in pediatric HCM patients is unknown. Hypothesis: LGE improves the SCD risk prediction in children with HCM. Methods: We retrospectively analyzed the CMR images and reviewed the outcomes pediatric HCM patients. Results: Amongst the 720 patients from 30 centers, 73% were male, with a mean age of 14.2±4.8 years. During a mean follow up of 2.6±2.7 years (range 0-14.8 years), 34 experienced an episode of SCD or equivalent. LGE (Figure 1A) was present in 34%, with a mean burden of 14±21g, or 2.5±8.2g/m2 (6.2±7.7% of LV myocardium). The presence of ≥1 adult traditional risk factor (family history of SCD, syncope, LV thickness >30mm, non-sustained ventricular tachycardia on Holter) was associated with an increased risk of SCD (HR=4.6, p<0.0001). The HCM Risk-Kids score predicted SCD (p=0.002). The presence of LGE was strongly associated with an increased risk (HR=3.8, p=0.0003), even after adjusting for traditional risk factors (HR adj =3.2, p=0.003) or the HCM Risk-Kids score (HR adj =3.5, p=0.003). Furthermore, the burden of LGE was associated with increased risk (HR=2.1/10% LGE, p<0.0001). LGE burden remained independently associated with an increased risk for SCD after adjusting for traditional risk factors (HRadj=1.5/10% LGE, p=0.04) or HCM Risk-Kids (HRadj=1.9/10% LGE, p=0.0018, Figure 1B). The addition of LGE burden improved the predictive model using traditional risk markers (C statistic 0.67 vs 0.77, p=0.003) and HCM Risk-Kids (C statistic 0.68 vs 0.74, p=0.045). Conclusions: Quantitative LGE is an independent risk factor for SCD in pediatric patients with HCM and improves the performance of traditional risk markers and the HCM Risk-Kids Score for SCD risk stratification in this population.

scholarly journals A data-driven approach to predict daily risk of Clostridium difficile infection at two large academic health centers

2017 ◽  
Vol 4 (suppl_1) ◽  
pp. S403-S404
Author(s):  
Maggie Makar ◽  
Jeeheh Oh ◽  
Christopher Fusco ◽  
Joseph Marchesani ◽  
Robert McCaffrey ◽  
...  
Keyword(s):  
Risk Factors ◽  
Clostridium Difficile ◽  
Risk Stratification ◽  
Clostridium Difficile Infection ◽  
Prediction Models ◽  
The United States ◽  
Data Driven ◽  
Discriminative Performance ◽  
Adult Inpatient ◽  
Data Driven Approach

Abstract Background An estimated 293,300 healthcare-associated cases of Clostridium difficile infection (CDI) occur annually in the United States. Prior research on risk-prediction models for CDI have focused on a small number of risk factors with the goal of developing a model that works well across hospitals. We hypothesize that risk factors are, in part, hospital-specific. We applied a generalizable machine learning approach to discovering, or “learning”, hospital-specific risk-stratification models using electronic health record (EHR) data collected during the course of patient care from the Massachusetts General Hospital (MGH) and the University of Michigan Health System (UM). Methods We utilized EHR data from 115,958 adult inpatient admissions from 2012–2014 (MGH) and 258,050 adult inpatient admissions from 2010–2016 (UM) (Fig 1). We extracted patient demographics, admission details, patient history, and daily hospitalization details, resulting in 2,964 and 4,739 features in the MGH and UM models, respectively. We used L2 regularized logistic regression to learn the models and measured the discriminative performance of the models on a year of held-out data from each hospital. Results The MGH and UM models achieved AUROCs of 0.74 (CI: 0.73–0.75) and 0.77 (CI: 0.75–0.80), respectively. The relative importance of risk factors varied significantly across hospitals. In particular, in-hospital locations appeared in the set of top risk factors at one hospital and in the set of protective factors at the other. On average, both models were able to predict CDI five days in advance of clinical diagnosis (Fig 2). Conclusion We used EHR data to generate a daily estimate of the risk of CDI for each inpatient hospitalization. We applied a generalizable data-driven approach to existing data from two large institutions with different patient populations and different data formats and content. In contrast to approaches that focus on learning models that apply generally across hospitals, our proposed approach yields risk stratification models tailored to an institution’s EHR system and patient population. In turn, these hospital-specific models could allow for earlier and more accurate identification of high-risk patients. Disclosures All authors: No reported disclosures.

scholarly journals Carbon Monoxide Diffusion Capacity as a Severity Marker in Pulmonary Hypertension

2021 ◽  
Vol 11 (1) ◽  
pp. 132
Author(s):  
Eleni Diamanti ◽  
Vasiliki Karava ◽  
Patrick Yerly ◽  
John David Aubert
Keyword(s):  
Carbon Monoxide ◽  
Pulmonary Hypertension ◽  
Risk Stratification ◽  
Information Criterion ◽  
Risk Category ◽  
Free Survival ◽  
Diffusion Capacity ◽  
European Guidelines ◽  
Treatment Naïve ◽  
Risk Stratification Score

Carbon monoxide diffusion capacity (DLCO) is negatively associated with patient survival in idiopathic pulmonary hypertension (PH), but is not included in the risk stratification score proposed by the 2015 European guidelines. Since 2015, several new stratification scores based on a 3- or 4-severity scale have been explored. This retrospective cohort single-center study sought to investigate the association between DLCO and PH severity and survival. We included 85 treatment-naive patients with precapillary PH and DLCO measurement at diagnosis. DLCO status, based on lower and upper quartiles ranges, was added to a 3- and a 4-strata modified-risk assessment. DLCO was strongly associated with transplant-free survival (HR 0.939, 95% CI: 0.908–0.971, p < 0.001). In the intermediate and high-risk categories, DLCO was associated with transplant-free survival, irrespective of the risk category (HR 0.934, 95% CI: 0.880–0.980, p = 0.005). The correlation between modified-risk category and transplant-free survival was significant (HR 4.60, 95% CI: 1.294–16.352, p = 0.018). Based on the Akaike information criterion (AIC) levels, the 3- and 4-strata modified-risk stratification fits our results better than the conventional stratification. Low DLCO is associated with patient transplant-free survival, independently of the risk category. Inclusion of DLCO into a PH risk stratification score seems promising and needs further investigation.

scholarly journals Long-term risk of sudden cardiac death in hypertrophic cardiomyopathy - a cardiac magnetic resonance outcome study

2021 ◽  
Vol 22 (Supplement_1) ◽  
Author(s):  
A Seitz ◽  
S Greulich ◽  
D Herter ◽  
F Guenther ◽  
S Probst ◽  
...  
Keyword(s):  
Risk Factors ◽  
Cardiac Magnetic Resonance ◽  
Hypertrophic Cardiomyopathy ◽  
Risk Stratification ◽  
Cardiac Death ◽  
Risk Models ◽  
Lv Mass ◽  
Lge Cmr

Abstract Funding Acknowledgements Type of funding sources: Foundation. Main funding source(s): Robert Bosch Stiftung; Deutsche Forschungsgemeinschaft Background Sudden cardiac death (SCD) is an appalling complication of hypertrophic cardiomyopathy (HCM). There is an ongoing discussion about the optimal SCD risk stratification strategy in HCM since established SCD risk models have suboptimal discriminative power. Objective To evaluate the prognostic value of late gadolinium enhancement (LGE) cardiac magnetic resonance (CMR) for SCD risk stratification compared to the ESC SCD risk score and traditional SCD risk factors in an &gt;10-year follow-up study. Methods 220 consecutive patients with HCM and LGE-CMR were enrolled. Follow-up data was available in 203 patients (median age 58 years, 61% male) after a median follow-up period of 10.4 years. Results LGE was present in 70% of patients with a median LGE amount of 1.6%, the median ESC 5-year SCD risk score was 1.84. In the overall cohort, SCD rates were 2.3% at 5 years, 4.8% at 10 years, and 15.7% at 15 years, independent from established risk models. A LGE amount of &gt;5% (LV mass) portends the highest risk for SCD with SCD prevalences of 5.5% at 5 years, 13.0% at 10 years and 33.3% at 15 years. Conversely, patients with no or ≤5% LGE amount (of LV mass) have favorable prognosis. Conclusions LGE-CMR in HCM patients allows effective 10-year SCD risk stratification beyond established risk factors. LGE amount might be added to established risk models to improve its discriminatory power. Specifically, patients with &gt;5% amount of LGE should be carefully monitored and might be adequate candidates for primary prevention ICD during the clinical long-term course. Abstract Figure.

Abstract 16484: Primary Prevention Implantable Cardioverter Defibrillator Utilization for Hypertrophic Cardiomyopathy in US vs Non-US: Findings From the Share Registry

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Victor Nauffal ◽  
Peter Marstrand ◽  
Larry Han ◽  
iacopo olivotto ◽  
Adam S Helms ◽  
...  
Keyword(s):  
Risk Factors ◽  
Hypertrophic Cardiomyopathy ◽  
Primary Prevention ◽  
Risk Score ◽  
Implantable Cardioverter Defibrillators ◽  
Icd Implantation ◽  
European Guidelines ◽  
The Us ◽  
The Difference ◽  
European Society Of Cardiology

Introduction: Risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM) has evolved with notable differences in international practice trends and US vs European guidelines. Hypothesis: Utilization of primary prevention implantable cardioverter defibrillators (ICD) is higher in the US. Methods: We examined rates of primary prevention ICD implantation in 5,063 HCM patients in the international SHaRe registry from 2000 - 2020 (NUS=2,390; Nnon-US=2,673). Using multiple logistic regression we compared probability of ICD implantation for US vs non-US sites adjusting for standard SCD risk factors (Figure 1A). Interaction tests were performed to identify risk factors differentially associated with ICD implantation in US vs non-US sites after 2014 when the European Society of Cardiology (ESC) risk score was introduced. Results: The odds of ICD implantation were 3-fold higher in US sites [ORUS/non-US=3.11 (2.54 -3.81)] (Figure 1A). Odds remained similar after adjustment for ESC risk score [OR =3.17 (2.57 -3.91)]. Implantation rates were higher in the US throughout the study period with a notable drop in rates in both US and non-US sites after 2014 and a reduction in the magnitude of the difference in ICD utilization between US and non-US sites (ORUS/non-US (<2014) =4.20 (3.05-5.78) vs. ORUS/non-US (≥2014)=2.55 (1.89-3.44); pinteraction<0.001) (Figure 1B). Non-sustained ventricular tachycardia was a stronger predictor of ICD implantation in US sites [ORUS=4.9 (3.4-7.0) vs ORnon-US= 2.1 (1.2-3.6); pinteraction=0.005], whereas, left atrial diameter (> 40 mm) was a stronger predictor in non-US sites [ORNon-US=2.9 (2.1-4.0) vs ORUS=1.3 (1-1.6); pinteraction <0.001]. Conclusions: ICD utilization rates vary globally. In this study, primary prevention ICD utilization rates were 3-fold higher in the US despite adjustment for standard SCD risk factors. Further studies are needed to evaluate outcomes of these practice differences.

scholarly journals 3025 Individual Anesthesia Provider Performance Assessment

2019 ◽  
Vol 3 (s1) ◽  
pp. 147-147
Author(s):  
Stephan Maman ◽  
Michael Andreae
Keyword(s):  
Risk Factors ◽  
Graphical Representation ◽  
Regression Line ◽  
Healthcare Delivery ◽  
Individual Performance ◽  
Risk Category ◽  
Provider Performance ◽  
Antiemetic Prophylaxis ◽  
Increased Risk ◽  
Individual Provider

OBJECTIVES/SPECIFIC AIMS: We developed a multilevel hierarchical statistical model which describes the association of prophylactic interventions to patient PONV risk, and provides an intuitive summary for anesthesiologists to understand how well they are adhering to PONV guidelines. METHODS/STUDY POPULATION: Accepted PONV risk factors as well as preventative interventions to reduce the PONV risk, (e.g. total intravenous anesthesia or pharmacological prophylaxis) are retrieved from the electronic medical record (EMR). Risk is regressed against interventions. Fig 1, Panel A visualizes adherence for an individual provider by plotting anesthesia cases, with PONV risk in the x-axis and the number of interventions in the y-axis. Fig 1, Panel B shows a “Jitterplot”, jittering individual cases, which would otherwise plot onto the same coordinates (Panel A). The distribution of the number of interventions in each risk category is better summarized in Fig 1 Panel C by overlaying a violin plot onto the “Jitterplot”. Finally, a fitted regression line provides a summary measure for the individual provider’s risk-adjusted utilization of PONV prophylaxis in Fig 1, Panel D. The model can control for confounders and interactions, such as patient or procedure characteristics, such as supervision by attending physicians, institutional culture, and surgical procedure. RESULTS/ANTICIPATED RESULTS: Fig. 2, Panel A demonstrates good adherence. The provider responded to increased risk with additional interventions leading to a steep regression line. Less discriminate administration of prophylaxis is shown in Fig 2, Panel B. The graphical representation of our proposed measure of individual provider performance is intuitive, allowing us to compare adherence of two distinct groups of providers (light lines) and institutional averages (dark lines) as shown in Fig 2, Panel C. Controlling for known risk factors and potential confounders renders the assessment irrepudiable. The rigorous statistical approach allows for multi-level modeling and comparative effectiveness research, realistically evaluating process changes and interventions like CDS in the hierarchical structure of contemporary healthcare delivery. DISCUSSION/SIGNIFICANCE OF IMPACT: The strength of our novel measure of individual provider performance is its generalizability to other care settings, as well as the intuitive graphical representation of risk-adjusted individual performance. However, accuracy, precision and validity, sensitivity to system perturbations (like the implementation of CDS), and acceptance among providers remain to be evaluated. Fig 1. Risk-Adjusted Utilization of Antiemetic Prophylaxis Fig 2. Comparing Performance between Provider Groups

Epidemiology, risk and outcomes of venous thromboembolism in cancer

2012 ◽  
Vol 32 (02) ◽  
pp. 115-125 ◽  
Author(s):  
L. Russo ◽  
A. Falanga
Keyword(s):  
Risk Factors ◽  
Venous Thromboembolism ◽  
Brain Cancer ◽  
Prediction Models ◽  
Disease Stage ◽  
Individual Factors ◽  
Scientific Societies ◽  
Risk Prediction Models ◽  
Patients With Cancer ◽  
Increased Risk

SummaryCancer is associated with a fourfold increased risk of venous thromboembolism (VTE). The risk of VTE varies according to the type of malignancy (i. e. pancreatic cancer, brain cancer, lymphoma) and its disease stage and individual factors (i. e. sex, race, age, previous VTE history, immobilization, obesity). Preventing cancer-associated VTE is important because it represents a significant cause of morbidity and mortality. In order to identify cancer patient at particularly high risk, who need thromboprophylaxis, risk prediction models have become available and are under validation. These models include clinical risk factors, but also begin to incorporate biological markers. The major American and European scientific societies have issued their recommendations to guide the management of VTE in patients with cancer.In this review the principal aspects of epidemiology, risk factors and outcome of cancer-associated VTE are summarized.

scholarly journals Novel Cardiovascular Risk Factors in Patients with Diabetic Kidney Disease

2021 ◽  
Vol 22 (20) ◽  
pp. 11196
Author(s):  
Christodoula Kourtidou ◽  
Maria Stangou ◽  
Smaragdi Marinaki ◽  
Konstantinos Tziomalos
Keyword(s):  
Risk Factors ◽  
Cardiovascular Risk ◽  
Kidney Disease ◽  
Risk Stratification ◽  
Cardiovascular Risk Factors ◽  
Cardiovascular Events ◽  
Diabetic Kidney Disease ◽  
Fibroblast Growth Factor 23 ◽  
Diabetic Kidney ◽  
Increased Risk

Patients with diabetic kidney disease (DKD) are at very high risk for cardiovascular events. Only part of this increased risk can be attributed to the presence of diabetes mellitus (DM) and to other DM-related comorbidities, including hypertension and obesity. The identification of novel risk factors that underpin the association between DKD and cardiovascular disease (CVD) is essential for risk stratification, for individualization of treatment and for identification of novel treatment targets.In the present review, we summarize the current knowledge regarding the role of emerging cardiovascular risk markers in patients with DKD. Among these biomarkers, fibroblast growth factor-23 and copeptin were studied more extensively and consistently predicted cardiovascular events in this population. Therefore, it might be useful to incorporate them in risk stratification strategies in patients with DKD to identify those who would possibly benefit from more aggressive management of cardiovascular risk factors.

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