Lower Extremity Arterial Disease as a Predictor of Incident Atrial Fibrillation and Cardiovascular Events

ObjectiveTo evaluate the relationship between peripheral arterial disease (PAD) and incident atrial fibrillation (AF) and its clinical and pathophysiologic implications on ischemic stroke and all-cause mortality.Patients and MethodsWe identified all adult patients in the Mayo Clinic Health System without a previous diagnosis of AF undergoing ankle-brachial index (ABI) testing for any indication from January 1, 1996, to June 30, 2018. Retrospective extraction of ABI data and baseline echocardiographic data was performed. The primary outcome of interest was incident AF. The secondary outcomes of interest were incident ischemic stroke and all-cause mortality.ResultsA total of 33,734 patients were included in the study. After adjusting for demographic and comorbidity variables, compared with patients who had normal ABI (1.0 to 1.39), there was an increased risk of incident AF in patients with low ABI (<1.0) (adjusted hazard ratio, 1.14; 95% CI, 1.06 to 1.22) and elevated ABI (≥1.4) (adjusted hazard ratio, 1.18; 95% CI, 1.06 to 1.31). The risk was greater in patients with increasing severity of PAD. Patients with abnormal ABIs had an increased risk of ischemic stroke and all-cause mortality. We found that patients with PAD and incident AF have certain baseline echocardiographic abnormalities.ConclusionIn this large cohort of ambulatory patients undergoing ABI measurement, patients with PAD were at increased risk for incident AF, ischemic stroke, and mortality. In these high-risk patients with abnormal ABI, particularly severe PAD and cardiac structural abnormalities, routine monitoring for AF and management of cardiovascular risk factors may be warranted.     

Prognostic Value of Left Atrial Strain in Aortic Stenosis: A Competing Risk Analysis

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Right Heart Structure and Function in Lifelong Recreational Endurance Athletes with and without Paroxysmal Atrial Fibrillation

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Ratio between Vena Contracta Width and Tricuspid Annular Diameter: Prognostic Value in Secondary Tricuspid Regurgitation

STR = secondary tricuspid regurgitation; TA = tricuspid annulus; VC = vena contracta

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Longitudinal Anthropometric Measures and Risk of New-Onset Atrial Fibrillation Among Community-Dwelling Men and Women

ObjectiveTo assess the sex-specific evolution of various anthropometric measures and the association of their longitudinal trajectories with new-onset atrial fibrillation (AF).MethodsAmong 5266 men and 7218 women free of AF at baseline from the prospective population-based Rotterdam Study, each anthropometric measure was measured 1 to 5 times from 1989 to 2014. Anthropometric measures were standardized to obtain hazard ratios per 1 SD increase to enable comparison. Joint models were used to assess the longitudinal association between anthropometric measures and incident AF. Use of the joint models is a preferred method for simultaneous analyses of repeated measurements and survival data for conferring less biased estimates.ResultsMean (SD) age was 63.9 (8.9) years for men and 64.9 (9.8) years for women. Median follow-up time was 10.5 years. Longitudinal evolution of weight, height, waist circumference, hip circumference, and body mass index was associated with an increased risk of new-onset AF in both men and women. In joint models, larger height in men (hazard ratio [95% credible interval] per 1 SD, 1.27 [1.17 to 1.38]) and weight in women (1.24 [1.16 to 1.34]) showed the largest associations with AF. In joint models, waist to hip ratio was significantly associated with incident AF only in women (1.10 [1.03 to 1.18]).ConclusionConsidering the entire longitudinal trajectories in joint models, anthropometric measures were positively associated with an increased risk for new-onset AF among men and women in the general population. Increase in measure of central obesity showed a stronger association with increased risk of AF onset among women compared with men.     

Incidence and Risk of Various Types of Arterial Thromboembolism in Patients With Cancer

ObjectiveTo describe the temporal association and identify risk factors between cancer diagnosis and various types of arterial thromboembolism (ATE).Patients and MethodsWe inquired an aggregated electronic health record database (Explorys, IBM Corp., Armonk, New York) and identified patients with cancer from January 1999 to October 2019, with various types of ATE, including myocardial infarction, acute ischemic stroke, acute limb ischemia, acute mesenteric ischemia, acute renal infarction, and retinal artery occlusion. We investigated the temporal relationship between cancer diagnosis and ATE events by examining the incidence ratio (IR) of ATE before and after diagnosis of cancer.ResultsWe identified 305,384 patients with cancer and ATE. The 30-day interval IR of total ATE was elevated shortly before and after cancer diagnosis, which was consistent among different ATE and cancer types. The incidence was highest within a 330-day window (90 days before and 240 days after cancer diagnosis), and IR peaked at 13.9 (95% confidence interval [CI], 13.6 to 14.2) in the first 30 days following diagnosis of cancer. Compared with patients with cancer who never developed ATE, patients with ATE had more cardiovascular risk factors at baseline. Patients with brain cancer, lung cancer, colorectal cancer, and pancreatic cancer had the highest risk of developing ATE, whereas ATE type was anatomically associated with cancer type.ConclusionIn this observational study of an aggregated US patient population, those with newly diagnosed cancer had increased risk of ATE events. This risk was most elevated in a 330-day window around cancer diagnosis and was consistent across different types of ATE and cancer.     

Clinical Characteristics and Outcomes of Patients With Primary Plasma Cell Leukemia in the Era of Novel Agent Therapy

ObjectiveTo evaluate the clinical outcomes of patients with primary plasma cell leukemia (pPCL) defined by 5% or greater clonal circulating plasma cells on peripheral blood smear and treated with novel agent induction therapies.Patients and MethodsA cohort of 68 patients with pPCL diagnosed at the Mayo Clinic in Rochester, Minnesota, from January 1, 2000, to December 31, 2019, and treated with novel agent induction therapies was evaluated.ResultsThe median follow-up was 46 (95% CI, 41 to 90) months. The median bone marrow plasma cell content was 85% (range, 10% to 100%) and median clonal circulaitng plasma cell percentage on the peripheral blood smear was 26% (range, 5% to 93%). There was a preponderance of t(11;14) primary cytogenetic abnormality in this cohort. The median time to next therapy (TTNT) and overall survival (OS) for all patients with pPCL patients in this cohort was 13 (95% CI, 9 to 17) and 23 (95% CI, 19 to 38) months, respectively. However, when stratified by cytogenetic risk, the median TTNT and OS were 16 and 51 months for standard risk vs 9 and 19 months for high risk (P=.01 for OS).ConclusionPrimary plasma cell leukemia remains an aggressive disease with poor prognosis despite novel agent–based therapies. Some patients have better than expected survival and this phenomenon may be influenced by the absence of high-risk cytogenetics. Newer treatment regimens are needed to improve the prognosis of this devastating disease.     

Artificial Intelligence Application in Graves Disease: Atrial Fibrillation,Heart Failure and Menstrual Changes

ObjectiveTo study the utility of artificial intelligence (AI)–enabled electrocardiograms (ECGs) in patients with Graves disease (GD) in identifying patients at high risk of atrial fibrillation (AF) and heart failure with reduced ejection fraction (HFrEF), and to study whether AI-ECG can reflect hormonal changes and the resulting menstrual changes in GD.Patients and MethodsPatients diagnosed with GD between January 1, 2009, and December 31, 2019, were included. We considered AF diagnosed at 30 days or fewer before or any time after GD and de novo HFrEF not explained by ischemia, valve disorder, or other cardiomyopathy at/after GD diagnosis. Electrocardiograms at/after index condition were excluded. A subset analysis included females younger than 45 years of age to study the association between ECG-derived female probability and menstrual changes (shorter, lighter, or newly irregular cycles).ResultsAmong 430 patients (mean age, 50±17 years; 337 (78.4%) female), independent risk factors for AF included ECG probability of AF (hazard ratio [HR], 1.5; 95% CI, 1.2 to 1.6 per 10%; P<.001), older age (HR, 1.05; 95% CI, 1.03 to 1.07 per year; P<.001), and overt hyperthyroidism (HR, 3.9; 95% CI, 1.2 to 12.7; P=.03). The C-statistic was 0.85 for the combined model. Among 495 patients (mean age, 52±17 years; 374 (75.6%) female), independent risk factors for HFrEF were ECG probability of low ejection fraction (HR, 1.4; 95% CI, 1.1 to 1.6 per 10%; P=.001) and presence of AF (HR, 8.3; 95% CI, 2.2 to 30.9; P=.002), and a C-statistic of 0.89 for the combined model. Lastly, of 72 females younger than 45 years, 30 had menstrual changes at time of GD and had a significantly lower AI ECG–derived female probability [median 77.3; (IQR 57.9 to 94.4)% vs. median 97.7 (IQR 92.4 to 99.5)%, P<.001].ConclusionAI-enabled ECG identifies patients at risk for GD-related AF and HFrEF and was associated with menstrual changes in women with GD.     

An Electronic Health Record–Compatible Model to Predict Personalized Treatment Effects From the Diabetes Prevention Program: A Cross-Evidence Synthesis Approach Using Clinical Trial and Real-World Data

ObjectiveTo develop an electronic health record (EHR)-based risk tool that provides point-of-care estimates of diabetes risk to support targeting interventions to patients most likely to benefit.Patients and MethodsA risk prediction model was developed and validated in a large observational database of patients with an index visit date between January 1, 2012, and December 31, 2016, with treatment effect estimates from risk-based reanalysis of clinical trial data. The risk model development cohort included 1.1 million patients with prediabetes from the OptumLabs Data Warehouse (OLDW); the validation cohort included a distinct sample of 1.1 million patients in OLDW. The randomly assigned clinical trial cohort included 3081 people from the Diabetes Prevention Program (DPP) study.ResultsEleven variables reliably obtainable from the EHR were used to predict diabetes risk. This model validated well in the OLDW (C statistic = 0.76; observed 3-year diabetes rate was 1.8% (95% confidence interval [CI], 1.7 to 1.9) in the lowest-risk quarter and 19.6% (19.4 to 19.8) in the highest-risk quarter). In the DPP, the hazard ratio (HR) for lifestyle modification was constant across all levels of risk (HR, 0.43; 95% CI, 0.35 to 0.53), whereas the HR for metformin was highly risk dependent (HR, 1.1; 95% CI, 0.61 to 2.0 in the lowest-risk quarter vs HR, 0.45; 95% CI, 0.35 to 0.59 in the highest-risk quarter). Fifty-three percent of the benefits of population-wide dissemination of the DPP lifestyle modification and 73% of the benefits of population-wide metformin therapy can be obtained by targeting the highest-risk quarter of patients.ConclusionThe Tufts–Predictive Analytics and Comparative Effectiveness DPP Risk model is an EHR-compatible tool that might support targeted diabetes prevention to more efficiently realize the benefits of the DPP interventions.     

Kidney Microstructural Features at the Time of Donation Predict Long-term Risk of Chronic Kidney Disease in Living Kidney Donors

ObjectiveTo determine whether microstructural features on a kidney biopsy specimen obtained during kidney transplant surgery predict long-term risk of chronic kidney disease in the donor.Patients and MethodsWe studied kidney donors from May 1, 1999, through December 31, 2018, with a follow-up survey for the results of recent blood pressure and kidney function tests (estimated glomerular filtration rate [eGFR] and proteinuria). If not recently available, blood pressure and eGFRs were requested from a local clinic. Microstructural features on kidney biopsy at the time of donation were assessed as predictors of hypertension and kidney function after adjusting for years of follow-up, baseline age, sex, and clinical predictors.ResultsThere were 807 donors surveyed a mean 10.5 years after donation. An eGFR less than 45 mL/min/1.73 m² in 6.4% (43/673) of donors was predicted by larger glomerular volume per standard deviation (odds ratio [OR], 1.48; 95% CI, 1.08 to 2.04) and nephron number below the age-specific 5th percentile (OR, 3.38; 95% CI, 1.31 to 8.72). An eGFR less than 60 mL/min/1.73 m² in 42.5% (286/673) of donors was not predicted by any microstructural feature. Residual eGFR (postdonation/predonation eGFR) was predicted by nephron number below the age-specific 5th percentile (difference, ?6.07%; 95% CI, ?10.24% to ?1.89%). Self-reported proteinuria in 5.1% (40/786) of donors was predicted by larger glomerular volume (OR, 1.42; 95% CI, 1.08 to 1.86). Incident hypertension in 18.8% (119/633) of donors was not predicted by any microstructural features.ConclusionLow nephron number for age and larger glomeruli are important microstructural predictors for long-term risk of chronic kidney disease after living kidney donation.