Identification and Use of Frailty Indicators from Text to Examine Associations with Clinical Outcomes Among Patients with Heart Failure.

Frailty is an important health outcomes indicator and valuable for guiding healthcare decisions in older adults, but is rarely collected in a quantitative, systematic fashion in routine healthcare. Using a cohort of 12,000 Veterans with heart failure, we investigated the feasibility of topic modeling to identify frailty topics in clinical notes. Topics were generated through unsupervised learning and then manually reviewed by an expert. A total of 53 frailty topics were identified from 100,000 notes. We further examined associations of frailty with age-, sex-, and Charlson Comorbidity Index-adjusted 1-year hospitalizations and mortality (composite outcome) using logistic regression. Frailty (≤ 4 topics versu

Cost-effectiveness of genotype-guided and dual antiplatelet therapies in acute coronary syndrome.

BackgroundThe choice of antiplatelet therapy after acute coronary syndrome (ACS) is complicated: Ticagrelor and prasugrel are novel alternatives to clopidogrel, patients with some genotypes may not respond to clopidogrel, and low-cost generic formulations of clopidogrel are available.ObjectiveTo determine the most cost-effective strategy for dual antiplatelet therapy after percutaneous coronary intervention for ACS.DesignDecision-analytic model.Data sourcesPublished literature, Medicare claims, and life tables.Target populationPatients having percutaneous coronary intervention for ACS.Time horizonLifetime.PerspectiveSocietal.InterventionFive strategies were examined: generic clopidogrel, prasugrel, ticagrelor, and genotyping for polymorphisms of CYP2C19 with carriers of loss-of-function alleles receiving either ticagrelor (genotyping with ticagrelor) or prasugrel (genotyping with prasugrel) and noncarriers receiving clopidogrel.Outcome measuresDirect medical costs, quality-adjusted life years(QALYs), and incremental cost-effectiveness ratios (ICERs).Results of base-case analysisThe clopidogrel strategy produced$179 301 in costs and 9.428 QALYs. Genotyping with prasugrel was superior to prasugrel alone, with an ICER of$35 800 per QALY relative to clopidogrel. Genotyping with ticagrelor was more effective than genotyping with prasugrel ($30 200 per QALY relative to clopidogrel). Ticagrelor was the most effective strategy($52 600 per QALY relative to genotyping with ticagrelor).Results of sensitivity analysisStronger associations between genotype and thrombotic outcomes rendered ticagrelor substantially less cost-effective ($104 800 per QALY). Genotyping with prasugrel was the preferred therapy among patients who could not tolerate ticagrelor.LimitationNo randomized trials have directly compared genotyping strategies or prasugrel with ticagrelor.ConclusionGenotype-guided personalization may improve the cost-effectiveness of prasugrel and ticagrelor after percutaneous coronary intervention for ACS, but ticagrelor for all patients may bean economically reasonable alternative in some settings

Education, income, and incident heart failure in post-menopausal women: the Women\u27s Health Initiative Hormone Therapy Trials

OBJECTIVES: The purpose of this study is to estimate the effect of education and income on incident heart failure (HF) hospitalization among post-menopausal women. BACKGROUND: Investigations of socioeconomic status have focused on outcomes after HF diagnosis, not associations with incident HF. We used data from the Women\u27s Health Initiative Hormone Trials to examine the association between socioeconomic status levels and incident HF hospitalization. METHODS: We included 26,160 healthy, post-menopausal women. Education and income were self-reported. Analysis of variance, chi-square tests, and proportional hazards models were used for statistical analysis, with adjustment for demographics, comorbid conditions, behavioral factors, and hormone and dietary modification assignments. RESULTS: Women with household incomes $50,000 a year (16.7/10,000 person-years; p \u3c 0.01). Women with less than a high school education had higher HF hospitalization incidence (51.2/10,000 person-years) than college graduates and above (25.5/10,000 person-years; p \u3c 0.01). In multivariable analyses, women with the lowest income levels had 56% higher risk (hazard ratio: 1.56, 95% confidence interval: 1.19 to 2.04) than the highest income women; women with the least amount of education had 21% higher risk for incident HF hospitalization (hazard ratio: 1.21, 95% confidence interval: 0.90 to 1.62) than the most educated women. CONCLUSIONS: Lower income is associated with an increased incidence of HF hospitalization among healthy, post-menopausal women, whereas multivariable adjustment attenuated the association of education with incident HF. Elsevier Inc. All rights reserved

Shedding Light on the Black Box: Explaining Deep Neural Network Prediction of Clinical Outcomes.

INTRODUCTION: Deep neural network models are emerging as an important method in healthcare delivery, following the recent success in other domains such as image recognition. Due to the multiple non-linear inner transformations, deep neural networks are viewed by many as black boxes. For practical use, deep learning models require explanations that are intuitive to clinicians. METHODS: In this study, we developed a deep neural network model to predict outcomes following major cardiovascular procedures, using temporal image representation of past medical history as input. We created a novel explanation for the prediction of the model by defining impact scores that associate clinical observations with the outcome. For comparison, a logistic regression model was fitted to the same dataset. We compared the impact scores and log odds ratios by calculating three types of correlations, which provided a partial validation of the impact scores. RESULTS: The deep neural network model achieved an area under the receiver operating characteristics curve (AUC) of 0.787, compared to 0.746 for the logistic regression model. Moderate correlations were found between the impact scores and the log odds ratios. CONCLUSION: Impact scores generated by the explanation algorithm has the potential to shed light on the “black box” deep neural network model and could facilitate its adoption by clinicians

Development of a cardiac-centered frailty ontology

Abstract Background A Cardiac-centered Frailty Ontology can be an important foundation for using NLP to assess patient frailty. Frailty is an important consideration when making patient treatment decisions, particularly in older adults, those with a cardiac diagnosis, or when major surgery is a consideration. Clinicians often report patient’s frailty in progress notes and other documentation. Frailty is recorded in many different ways in patient records and many different validated frailty-measuring instruments are available, with little consistency across instruments. We specifically explored concepts relevant to decisions regarding cardiac interventions. We based our work on text found in a large corpus of clinical notes from the Department of Veterans Affairs (VA) national Electronic Health Record (EHR) database. Results The full ontology has 156 concepts, with 246 terms. It includes 86 concepts we expect to find in clinical documents, with 12 qualifier values. The remaining 58 concepts represent hierarchical groups (e.g., physical function findings). Our top-level class is clinical finding, which has children clinical history finding, instrument finding, and physical examination finding, reflecting the OGMS definition of clinical finding. Instrument finding is any score found for the existing frailty instruments. Within our ontology, we used SNOMED-CT concepts where possible. Some of the 86 concepts we expect to find in clinical documents are associated with the properties like ability interpretation. The concept ability to walk can either be able, assisted or unable. Each concept-property level pairing gets a different frailty score. Each scored concept received three scores: a frailty score, a relevance to cardiac decisions score, and a likelihood of resolving after the recommended intervention score. The ontology includes the relationship between scores from ten frailty instruments and frailty as assessed using ontology concepts. It also included rules for mapping ontology elements to instrument items for three common frailty assessment instruments. Ontology elements are used in two clinical NLP systems. Conclusions We developed and validated a Cardiac-centered Frailty Ontology, which is a machine-interoperable description of frailty that reflects all the areas that clinicians consider when deciding which cardiac intervention will best serve the patient as well as frailty indications generally relevant to medical decisions. The ontology owl file is available on Bioportal at http://bioportal.bioontology.org/ontologies/CCFO

Cost-effectiveness of genotype-guided and dual antiplatelet therapies in acute coronary syndrome.

BackgroundThe choice of antiplatelet therapy after acute coronary syndrome (ACS) is complicated: Ticagrelor and prasugrel are novel alternatives to clopidogrel, patients with some genotypes may not respond to clopidogrel, and low-cost generic formulations of clopidogrel are available.ObjectiveTo determine the most cost-effective strategy for dual antiplatelet therapy after percutaneous coronary intervention for ACS.DesignDecision-analytic model.Data sourcesPublished literature, Medicare claims, and life tables.Target populationPatients having percutaneous coronary intervention for ACS.Time horizonLifetime.PerspectiveSocietal.InterventionFive strategies were examined: generic clopidogrel, prasugrel, ticagrelor, and genotyping for polymorphisms of CYP2C19 with carriers of loss-of-function alleles receiving either ticagrelor (genotyping with ticagrelor) or prasugrel (genotyping with prasugrel) and noncarriers receiving clopidogrel.Outcome measuresDirect medical costs, quality-adjusted life years(QALYs), and incremental cost-effectiveness ratios (ICERs).Results of base-case analysisThe clopidogrel strategy produced$179 301 in costs and 9.428 QALYs. Genotyping with prasugrel was superior to prasugrel alone, with an ICER of$35 800 per QALY relative to clopidogrel. Genotyping with ticagrelor was more effective than genotyping with prasugrel ($30 200 per QALY relative to clopidogrel). Ticagrelor was the most effective strategy($52 600 per QALY relative to genotyping with ticagrelor).Results of sensitivity analysisStronger associations between genotype and thrombotic outcomes rendered ticagrelor substantially less cost-effective ($104 800 per QALY). Genotyping with prasugrel was the preferred therapy among patients who could not tolerate ticagrelor.LimitationNo randomized trials have directly compared genotyping strategies or prasugrel with ticagrelor.ConclusionGenotype-guided personalization may improve the cost-effectiveness of prasugrel and ticagrelor after percutaneous coronary intervention for ACS, but ticagrelor for all patients may bean economically reasonable alternative in some settings

Clinical Trial Participation and COVID-19: a Descriptive Analysis from the American Heart Association\u27s Get With The Guidelines Registry.

As COVID-19 cases begin to decrease in the USA, learning from the pandemic experience will provide insights regarding disparities of care delivery. We sought to determine if specific populations hospitalized with COVID-19 are equally likely to be enrolled in clinical trials. We examined patients hospitalized with COVID-19 at centers participating in the American Heart Association\u27s COVID-19 CVD Registry. The primary outcome was odds of enrollment in a clinical trial, according to sex, race, and ethnicity. Among 14,397 adults hospitalized with COVID-19, 9.5% (n = 1,377) were enrolled in a clinical trial. The proportion of enrolled patients was the lowest for Black patients (8%); in multivariable analysis, female and Black patients were less likely to be enrolled in a clinical trial related to COVID-19 compared to men and other racial groups, respectively. Determination of specific reasons for the disparities in trial participation related to COVID-19 in these populations should be further investigated