Matthew Phelan

Management and outcomes in patients with moderate or severe functional mitral regurgitation and severe left ventricular dysfunction

AIMS The management and outcomes of patients with functional moderate/severe mitral regurgitation and severe left ventricular (LV) systolic dysfunction are not well defined. We sought to determine the characteristics, management strategies, and outcomes of patients with moderate or severe mitral regurgitation (MR) and LV systolic dysfunction. METHODS AND RESULTS For the period 1995-2010, the Duke Echocardiography Laboratory and Duke Databank for Cardiovascular Diseases databases were merged to identify patients with moderate or severe functional MR and severe LV dysfunction (defined as LV ejection fraction ≤ 30% or LV end-systolic diameter > 55 mm). We examined treatment effects in two ways. (i) A multivariable Cox proportional hazards model was used to assess the independent relationship of different treatment strategies and long-term event (death, LV assist device, or transplant)-free survival among those with and without coronary artery disease (CAD). (ii) To examine the association of mitral valve (MV) surgery with outcomes, we divided the entire cohort into two groups, those who underwent MV surgery and those who did not; we used inverse probability weighted (IPW) propensity adjustment to account for non-random treatment assignment. Among 1441 patients with moderate (70%) or severe (30%) MR, a significant history of hypertension (59%), diabetes (28%), symptomatic heart failure (83%), and CAD (52%) was observed. Past revascularization in 26% was noted. At 1 year, 1094 (75%) patients were treated medically. Percutaneous coronary intervention was performed in 114 patients, coronary artery bypass graft (CABG) surgery in 82, CABG and MV surgery in 96, and MV surgery alone in 55 patients. Among patients with CAD, compared with medical therapy alone, the treatment strategies of CABG surgery [hazard ratio (HR) 0.56, 95% confidence interval (CI) 0.42-0.76] and CABG with MV surgery (HR 0.58, 95% CI 0.44-0.78) were associated with long-term, event-free survival benefit. Percutaneous intervention treatment produced a borderline result (HR 0.78, 95% CI 0.61-1.00). However, the relationship with isolated MV surgery did not achieve statistical significance (HR 0.64, 95% CI 0.33-1.27, P = 0.202). Among those with CAD, following IPW adjustment, MV surgery was associated with a significant event-free survival benefit compared with patients without MV surgery (HR 0.71, 95% CI 0.52-0.95). In the entire cohort, following IPW adjustment, the use of MV surgery was associated with higher event-free survival (HR 0.69, 95% CI 0.53-0.88). CONCLUSION In patients with moderate or severe MR and severe LV dysfunction, mortality was substantial, and among those selected for surgery, MV surgery, though performed in a small number of patients, was independently associated with higher event-free survival.

Assessing electronic health record phenotypes against gold-standard diagnostic criteria for diabetes mellitus.

Objective: We assessed the sensitivity and specificity of 8 electronic health record (EHR)-based phenotypes for diabetes mellitus against gold-standard American Diabetes Association (ADA) diagnostic criteria via chart review by clinical experts. Materials and Methods: We identified EHR-based diabetes phenotype definitions that were developed for various purposes by a variety of users, including academic medical centers, Medicare, the New York City Health Department, and pharmacy benefit managers. We applied these definitions to a sample of 173 503 patients with records in the Duke Health System Enterprise Data Warehouse and at least 1 visit over a 5-year period (2007–2011). Of these patients, 22 679 (13%) met the criteria of 1 or more of the selected diabetes phenotype definitions. A statistically balanced sample of these patients was selected for chart review by clinical experts to determine the presence or absence of type 2 diabetes in the sample. Results: The sensitivity (62–94%) and specificity (95–99%) of EHR-based type 2 diabetes phenotypes (compared with the gold standard ADA criteria via chart review) varied depending on the component criteria and timing of observations and measurements. Discussion and Conclusions: Researchers using EHR-based phenotype definitions should clearly specify the characteristics that comprise the definition, variations of ADA criteria, and how different phenotype definitions and components impact the patient populations retrieved and the intended application. Careful attention to phenotype definitions is critical if the promise of leveraging EHR data to improve individual and population health is to be fulfilled.

Influence of QRS infarct score and QRS duration prior to transcatheter aortic valve replacement on follow-up left ventricular end systolic volume in patients with new persistent left bundle branch block

BACKGROUND New-onset left bundle branch block (LBBB) is a known complication during Transcatheter Aortic Valve Replacement (TAVR). This study evaluated the influence of pre-TAVR cardiac conditions on left ventricular functions in patients with new persistent LBBB post-TAVR. METHODS Only 11 patients qualified for this study because of the strict inclusion criteria. Pre-TAVR electrocardiograms were evaluated for Selvester QRS infarct score and QRS duration, and left ventricular end-systolic volume (LVESV) was used as outcome variable. RESULTS There was a trend towards a positive correlation between QRS score and LVESV of r=0.59 (p=0.058), while there was no relationship between QRS duration and LVESV (r=-0.18 [p=0.59]). CONCLUSION This study showed that patients with new LBBB and higher pre-TAVR QRS infarct score may have worse post-TAVR left ventricular function, however, pre-TAVR QRS duration has no such predictive value. Because of the small sample size these results should be interpreted with caution and assessed in a larger study population.

Left ventricular global longitudinal strain in patients with heart failure with preserved ejection fraction: outcomes following an acute heart failure hospitalization

While abnormal resting LV GLS has been described in patients with chronic heart failure with preserved ejection fraction (HFpEF), its prognostic significance when measured during an acute heart failure hospitalization remains unclear. We assessed the association between left ventricular global longitudinal strain (LV GLS) and outcomes in patients hospitalized with acute HFpEF.

Illustrating Informed Presence Bias in Electronic Health Records Data: How Patient Interactions with a Health System Can Impact Inference

Electronic health record (EHR) data are becoming a primary resource for clinical research. Compared to traditional research data, such as those from clinical trials and epidemiologic cohorts, EHR data have a number of appealing characteristics. However, because they do not have mechanisms set in place to ensure that the appropriate data are collected, they also pose a number of analytic challenges. In this paper, we illustrate that how a patient interacts with a health system influences which data are recorded in the EHR. These interactions are typically informative, potentially resulting in bias. We term the overall set of induced biases informed presence. To illustrate this, we use examples from EHR based analyses. Specifically, we show that: 1) Where a patient receives services within a health facility can induce selection bias; 2) Which health system a patient chooses for an encounter can result in information bias; and 3) Referral encounters can create an admixture bias. While often times addressing these biases can be straightforward, it is important to understand how they are induced in any EHR based analysis.

Prevalence and Outcomes of Left‐Sided Valvular Heart Disease Associated With Chronic Kidney Disease

Background Chronic kidney disease (CKD) is an adverse prognostic marker for valve intervention patients; however, the prevalence and related outcomes of valvular heart disease in CKD patients is unknown. Methods and Results Included patients underwent echocardiography (1999–2013), had serum creatinine values within 6 months before index echocardiogram, and had no history of valve surgery. CKD was defined as diagnosis based on the International Classification of Diseases, Ninth Revision or an estimated glomerular filtration rate <60 mL/min per 1.73 m2. Qualitative assessment determined left heart stenotic and regurgitant valve lesions. Cox models assessed CKD and aortic stenosis (AS) interaction for subsequent mortality; analyses were repeated for mitral regurgitation (MR). Among 78 059 patients, 23 727 (30%) had CKD; of these, 1326 were on hemodialysis. CKD patients were older; female; had a higher prevalence of hypertension, hyperlipidemia, diabetes, history of coronary artery bypass grafting/percutaneous coronary intervention, atrial fibrillation, and heart failure ≥mild AS; and ≥mild MR (all P<0.001). Five‐year survival estimates of mild, moderate, and severe AS for CKD patients were 40%, 34%, and 42%, respectively, and 69%, 54%, and 67% for non‐CKD patients. Five‐year survival estimates of mild, moderate, and severe MR for CKD patients were 51%, 38%, and 37%, respectively, and 75%, 66%, and 65% for non‐CKD patients. Significant interaction occurred among CKD, AS/MR severity, and mortality in adjusted analyses; the CKD hazard ratio increased from 1.8 (non‐AS patients) to 2.0 (severe AS) and from 1.7 (non‐MR patients) to 2.6 (severe MR). Conclusions Prevalence of at least mild AS and MR is substantially higher and is associated with significantly lower survival among patients with versus without CKD. There is significant interaction among CKD, AS/MR severity, and mortality, with increasingly worse outcomes for CKD patients with increasing AS/MR severity.

Development and validation of an electronic medical record (EMR)-based computed phenotype of HIV-1 infection

Background Electronic medical record (EMR) computed algorithms allow investigators to screen thousands of patient records to identify specific disease cases. No computed algorithms have been developed to detect all cases of human immunodeficiency virus (HIV) infection using administrative, laboratory, and clinical documentation data outside of the Veterans Health Administration. We developed novel EMR-based algorithms for HIV detection and validated them in a cohort of subjects in the Duke University Health System (DUHS). Methods We created 2 novel algorithms to identify HIV-infected subjects. Algorithm 1 used laboratory studies and medications to identify HIV-infected subjects, whereas Algorithm 2 used International Classification of Diseases, Ninth Revision (ICD-9) codes, medications, and laboratory testing. We applied the algorithms to a well-characterized cohort of patients and validated both against the gold standard of physician chart review. We determined sensitivity, specificity, and prevalence of HIV between 2007 and 2011 in patients seen at DUHS. Results A total of 172 271 patients were detected with complete data; 1063 patients met algorithm criteria for HIV infection. In all, 970 individuals were identified by both algorithms, 78 by Algorithm 1 alone, and 15 by Algorithm 2 alone. The sensitivity and specificity of each algorithm were 78% and 99%, respectively, for Algorithm 1 and 77% and 100% for Algorithm 2. The estimated prevalence of HIV infection at DUHS between 2007 and 2011 was 0.6%. Conclusions EMR-based phenotypes of HIV infection are capable of detecting cases of HIV-infected adults with good sensitivity and specificity. These algorithms have the potential to be adapted to other EMR systems, allowing for the creation of cohorts of patients across EMR systems.

Value of Neighborhood Socioeconomic Status in Predicting Risk of Outcomes in Studies That Use Electronic Health Record Data

Importance Data from electronic health records (EHRs) are increasingly used for risk prediction. However, EHRs do not reliably collect sociodemographic and neighborhood information, which has been shown to be associated with health. The added contribution of neighborhood socioeconomic status (nSES) in predicting health events is unknown and may help inform population-level risk reduction strategies. Objective To quantify the association of nSES with adverse outcomes and the value of nSES in predicting the risk of adverse outcomes in EHR-based risk models. Design, Setting, and Participants Cohort study in which data from 90 097 patients 18 years or older in the Duke University Health System and Lincoln Community Health Center EHR from January 1, 2009, to December 31, 2015, with at least 1 health care encounter and residence in Durham County, North Carolina, in the year prior to the index date were linked with census tract data to quantify the association between nSES and the risk of adverse outcomes. Machine learning methods were used to develop risk models and determine how adding nSES to EHR data affects risk prediction. Neighborhood socioeconomic status was defined using the Agency for Healthcare Research and Quality SES index, a weighted measure of multiple indicators of neighborhood deprivation. Main Outcomes and Measures Outcomes included use of health care services (emergency department and inpatient and outpatient encounters) and hospitalizations due to accidents, asthma, influenza, myocardial infarction, and stroke. Results Among the 90 097 patients in the training set of the study (57 507 women and 32 590 men; mean [SD] age, 47.2 [17.7] years) and the 122 812 patients in the testing set of the study (75 517 women and 47 295 men; mean [SD] age, 46.2 [17.9] years), those living in neighborhoods with lower nSES had a shorter time to use of emergency department services and inpatient encounters, as well as a shorter time to hospitalizations due to accidents, asthma, influenza, myocardial infarction, and stroke. The predictive value of nSES varied by outcome of interest (C statistic ranged from 0.50 to 0.63). When added to EHR variables, nSES did not improve predictive performance for any health outcome. Conclusions and Relevance Social determinants of health, including nSES, are associated with the health of a patient. However, the results of this study suggest that information on nSES may not contribute much more to risk prediction above and beyond what is already provided by EHR data. Although this result does not mean that integrating social determinants of health into the EHR has no benefit, researchers may be able to use EHR data alone for population risk assessment.

Long-term outcomes of mitral regurgitation by type and severity

Background: We aimed to determine the association of MR severity and type with all‐cause death in a large, real‐world, clinical setting. Methods: We reviewed full echocardiography studies at Duke Echocardiography Laboratory (01/01/1995–12/31/2010), classifying MR based on valve morphology, presence of coronary artery disease, and left ventricular size and function. Survival was compared among patients stratified by MR type and baseline severity. Results: Of 93,007 qualifying patients, 32,137 (34.6%) had ≥mild MR. A total of 8094 (8.7%) had moderate/severe MR, which was primary myxomatous (14.1%), primary non‐myxomatous (6.2%), secondary non‐ischemic (17.0%), and secondary ischemic (49.4%). At 10 years, patients with primary myxomatous MR or MR due to indeterminate cause had survival rates of >60%; primary non‐myxomatous, secondary ischemic, and non‐ischemic MR had survival rates <50%. While mild (HR 1.06, 95% CI 1.03–1.09), moderate (HR 1.31, 95% CI 1.27–1.37), and severe (HR 1.55, 95% CI 1.46–1.65) MR were independently associated with all‐cause death, the relationship of increasing MR severity with mortality varied across MR types (P ≤ .001 for interaction); the highest risk associated with worsening severity was seen in primary myxomatous MR followed by secondary ischemic MR and primary non‐myxomatous MR. Conclusions: Although MR severity is independently associated with increased all‐cause death risk for most forms of MR, the absolute mortality rates associated with worse MR severity are much higher for primary myxomatous, non‐myxomatous, and secondary ischemic MR. The findings from this study support carefully defining MR by type and severity.