Developing Clinical Risk Prediction Models for Worsening Heart Failure Events and Death by Left Ventricular Ejection Fraction.

Background There is a need to develop electronic health record-based predictive models for worsening heart failure (WHF) events across clinical settings and across the spectrum of left ventricular ejection fraction (LVEF). Methods and Results We studied adults with heart failure (HF) from 2011 to 2019 within an integrated health care delivery system. WHF encounters were ascertained using natural language processing and structured data. We conducted boosted decision tree ensemble models to predict 1-year hospitalizations, emergency department visits/observation stays, and outpatient encounters for WHF and all-cause death within each LVEF category: HF with reduced ejection fraction (EF) (LVEF <40%), HF with mildly reduced EF (LVEF 40%-49%), and HF with preserved EF (LVEF ≥50%). Model discrimination was evaluated using area under the curve and calibration using mean squared error. We identified 338 426 adults with HF: 61 045 (18.0%) had HF with reduced EF, 49 618 (14.7%) had HF with mildly reduced EF, and 227 763 (67.3%) had HF with preserved EF. The 1-year risks of any WHF event and death were, respectively, 22.3% and 13.0% for HF with reduced EF, 17.0% and 10.1% for HF with mildly reduced EF, and 16.3% and 10.3% for HF with preserved EF. The WHF model displayed an area under the curve of 0.76 and mean squared error of 0.13, whereas the model for death displayed an area under the curve of 0.83 and mean squared error of 0.076. Performance and predictors were similar across WHF encounter types and LVEF categories. Conclusions We developed risk prediction models for 1-year WHF events and death across the LVEF spectrum using structured and unstructured electronic health record data and observed no substantial differences in model performance or predictors except for death, despite differences in underlying HF cause.

Variation in Heart Failure Risk by HIV Severity and Sex in People With HIV Infection.

BACKGROUND: HIV is an independent risk factor for heart failure (HF). However, the association of HIV severity with incident HF and the potential interaction with sex are incompletely understood. SETTING: Integrated health care system. METHODS: We conducted a cohort study of people with HIV (PWH) and matched people without HIV (PWoH), all aged ≥ 21 years and with no previous HF. Poisson regression was used to compare incident HF by HIV status, with PWH stratified by severity of HIV infection [defined by recent (<6 months) CD4 count, nadir CD4 count, or recent HIV RNA level]. Models were adjusted for sociodemographic characteristics, substance use, and HF risk factors. Analyses were conducted for men and women combined, then by sex. RESULTS: The study included 38,868 PWH and 386,569 PWoH (mean baseline age = 41.0 ± 10.8 years; 88% men). Compared with PWoH, incident HF risk was higher among PWH with lower recent CD4 [200-499 cells/µL, adjusted rate ratio (aRR) = 1.82, 95% confidence interval (CI) = 1.50 to 2.21 and <200 cells/µL, aRR = 3.26 (2.47 to 4.30)] and a low nadir CD4 [<200 cells/µL, aRR = 1.56 (1.37 to 1.79)] but not among PWH with normal CD4 [≥500 cells/µL, aRR = 1.14 (0.90 to 1.44)]. Higher incident HF risk was observed among PWH at all HIV RNA levels, with greater HF risk at higher HIV RNA levels. The excess HF risk associated with low CD4 (recent or nadir) and high HIV RNA was stronger among women than men (P interactions=0.05, 0.08, and 0.01, respectively). CONCLUSIONS: Given the association of HIV severity with HF, optimizing HIV treatment and management may be important for HF prevention among PWH.

Analysis of Worsening Heart Failure Events in an Integrated Health Care System.

BACKGROUND: There is growing interest to disentangle worsening heart failure (WHF) from location of care and move away from hospitalization as a surrogate for acuity. OBJECTIVES: The purpose of this study was to describe the incidence of WHF events across the care continuum from ambulatory encounters to hospitalizations. METHODS: We studied calendar year cohorts of adults with diagnosed heart failure (HF) from 2010-2019 within a large, integrated health care delivery system. Electronic health record (EHR) data were accessed for outpatient encounters, emergency department (ED) visits/observation stays, and hospitalizations. WHF was defined as ≥1 symptom, ≥2 objective findings including ≥1 sign, and ≥1 change in HF-related therapy. Symptoms and signs were ascertained using natural language processing. RESULTS: We identified 103,138 eligible individuals with mean age 73.6 ± 13.7 years, 47.5% women, and mean left ventricular ejection fraction of 51.4% ± 13.7%. There were 1,136,750 unique encounters including 743,039 (65.4%) outpatient encounters, 224,670 (19.8%) ED visits/observation stays, and 169,041 (14.9%) hospitalizations. A total of 126,008 WHF episodes were identified, including 34,758 (27.6%) outpatient encounters, 28,301 (22.5%) ED visits/observation stays, and 62,949 (50.0%) hospitalizations. The annual incidence (events per 100 person-years) of WHF increased from 25 to 33 during the study period primarily caused by outpatient encounters (7 to 10) and ED visits/observation stays (4 to 7). The 30-day rate of hospitalizations for WHF ranged from 8.2% for outpatient encounters to 12.4% for hospitalizations. CONCLUSIONS: ED visits/observation stays and outpatient encounters account for approximately one-half of WHF events, are driving the underlying growth in HF morbidity, and portend a poor short-term prognosis.

A Natural Language Processing-Based Approach for Identifying Hospitalizations for Worsening Heart Failure Within an Integrated Health Care Delivery System.

Importance: The current understanding of epidemiological mechanisms and temporal trends in hospitalizations for worsening heart failure (WHF) is based on claims and national reporting databases. However, these data sources are inherently limited by the accuracy and completeness of diagnostic coding and/or voluntary reporting. Objective: To assess the overall burden of and temporal trends in the rate of hospitalizations for WHF. Design, Setting, and Participants: This cohort study, performed from January 1, 2010, to December 31, 2019, used electronic health record (EHR) data from a large integrated health care delivery system. Exposures: Calendar year trends. Main Outcomes and Measures: Hospitalizations for WHF (ie, excluding observation stays) were defined as 1 symptom or more, 2 objective findings or more including 1 sign or more, and 2 doses or more of intravenous loop diuretics and/or new hemodialysis or continuous kidney replacement therapy. Symptoms and signs were identified using natural language processing (NLP) algorithms applied to EHR data. Results: The study population was composed of 118 002 eligible patients experiencing 287 992 unique hospitalizations (mean [SD] age, 75.6 [13.1] years; 147 203 [51.1%] male; 1655 [0.6%] American Indian or Alaska Native, 28 451 [9.9%] Asian or Pacific Islander, 34 903 [12.1%] Black, 23 452 [8.1%] multiracial, 175 840 [61.1%] White, and 23 691 [8.2%] unknown), including 65 357 with a principal discharge diagnosis and 222 635 with a secondary discharge diagnosis of HF. The study population included 59 868 patients (20.8%) with HF with a reduced ejection fraction (HFrEF) (<40%), 33 361 (11.6%) with HF with a midrange EF (HFmrEF) (40%-49%), 142 347 (49.4%) with HF with a preserved EF (HFpEF) (≥50%), and 52 416 (18.2%) with unknown EF. A total of 58 042 admissions (88.8%) with a primary discharge diagnosis of HF and 62 764 admissions (28.2%) with a secondary discharge diagnosis of HF met the prespecified diagnostic criteria for WHF. Overall, hospitalizations for WHF identified on NLP-based algorithms increased from 5.2 to 7.6 per 100 hospitalizations per year during the study period. Subgroup analyses found an increase in hospitalizations for WHF based on NLP from 1.5 to 1.9 per 100 hospitalizations for HFrEF, from 0.6 to 1.0 per 100 hospitalizations for HFmrEF, and from 2.6 to 3.9 per 100 hospitalizations for HFpEF. Conclusions and Relevance: The findings of this cohort study suggest that the burden of hospitalizations for WHF may be more than double that previously estimated using only principal discharge diagnosis. There has been a gradual increase in the rate of hospitalizations for WHF with a more noticeable increase observed for HFpEF.

Human immunodeficiency virus infection and risks of morbidity and death in adults with incident heart failure.

Aims: Human immunodeficiency virus (HIV) increases the risk of heart failure (HF), but whether it influences subsequent morbidity and mortality remains unclear. Methods and results: We investigated the risks of hospitalization for HF, HF-related emergency department (ED) visits, and all-cause death in an observational cohort of incident HF patients with and without HIV using data from three large US integrated healthcare delivery systems. We estimated incidence rates and adjusted hazard ratios (aHRs) by HIV status at the time of HF diagnosis for subsequent outcomes. We identified 448 persons living with HIV (PLWH) and 3429 without HIV who developed HF from a frequency-matched source cohort of 38 868 PLWH and 386 586 without HIV. Mean age was 59.5 ± 11.3 years with 9.8% women and 31.8% Black, 13.1% Hispanic, and 2.2% Asian/Pacific Islander. Compared with persons without HIV, PLWH had similar adjusted rates of HF hospitalization [aHR 1.01, 95% confidence interval (CI): 0.81-1.26] and of HF-related ED visits [aHR 1.22 (95% CI: 0.99-1.50)], but higher adjusted rates of all-cause death [aHR 1.31 (95% CI: 1.08-1.58)]. Adjusted rates of HF-related morbidity and all-cause death were directionally consistent across a wide range of CD4 counts but most pronounced in the subset with a baseline CD4 count <200 or 200-499 cells/µL. Conclusion: In a large, diverse cohort of adults with incident HF receiving care within integrated healthcare delivery systems, PLWH were at an independently higher risk of all-cause death but not HF hospitalizations or HF-related ED visits. Future studies investigating modifiable HIV-specific risk factors may facilitate more personalized care to optimize outcomes for PLWH and HF.