Interplay Between Systemic Inflammation, Myocardial Injury, and Coronary Microvascular Dysfunction in Rheumatoid Arthritis: Results From the LiiRA Study.

BACKGROUND: Coronary microvascular dysfunction as measured by myocardial flow reserve (MFR) is associated with increased cardiovascular risk in rheumatoid arthritis (RA). The objective of this study was to determine the association between reducing inflammation with MFR and other measures of cardiovascular risk. METHODS AND RESULTS: Patients with RA with active disease about to initiate a tumor necrosis factor inhibitor were enrolled (NCT02714881). All subjects underwent a cardiac perfusion positron emission tomography scan to quantify MFR at baseline before tumor necrosis factor inhibitor initiation, and after tumor necrosis factor inhibitor initiation at 24 weeks. MFR <2.5 in the absence of obstructive coronary artery disease was defined as coronary microvascular dysfunction. Blood samples at baseline and 24 weeks were measured for inflammatory markers (eg, high-sensitivity C-reactive protein [hsCRP], interleukin-1b, and high-sensitivity cardiac troponin T [hs-cTnT]). The primary outcome was mean MFR before and after tumor necrosis factor inhibitor initiation, with Δhs-cTnT as the secondary outcome. Secondary and exploratory analyses included the correlation between ΔhsCRP and other inflammatory markers with MFR and hs-cTnT. We studied 66 subjects, 82% of which were women, mean RA duration 7.4 years. The median atherosclerotic cardiovascular disease risk was 2.5%; 47% had coronary microvascular dysfunction and 23% had detectable hs-cTnT. We observed no change in mean MFR before (2.65) and after treatment (2.64, P=0.6) or hs-cTnT. A correlation was observed between a reduction in hsCRP and interleukin-1b with a reduction in hs-cTnT. CONCLUSIONS: In this RA cohort with low prevalence of cardiovascular risk factors, nearly 50% of subjects had coronary microvascular dysfunction at baseline. A reduction in inflammation was not associated with improved MFR. However, a modest reduction in interleukin-1b and no other inflammatory pathways was correlated with a reduction in subclinical myocardial injury. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT02714881.

Psychological Evaluation of Patients With Cancer Presenting to the Emergency Department With Pain: Independent Predictors of Worse Pain Severity, Interference, and Higher Hourly Opioid Administration.

PURPOSE: Pain is a common complaint in patients with cancer presenting to the emergency department (ED). This prospective study evaluated whether biopsychosocial factors could help predict cancer patients with risk of higher pain severity, pain interference, and opioid consumption. METHODS: Patients with cancer presenting to the ED with a complaint of moderate-severe pain (≥ 4/10-numeric rating scale) completed validated self-report measures assessing sociodemographics, cancer-related treatments, pain severity and interference, medication use, and psychological symptoms (depression, anxiety, pain catastrophizing, and sleep disturbance). Opioids administered and subsequent hospitalization were abstracted. Univariable and multivariable regression analyses assessed factors associated with pain-related outcomes. RESULTS: Participants (n = 175) presented with a variety of cancer types, with 76% having metastatic disease and 42% reporting current outpatient opioid use. Higher pain catastrophizing, lower depressive symptoms, lower income, outpatient opioid use, and historical chronic pain were independently associated with worse pain (P ≤ .05). Higher pain catastrophizing, anxiety, sleep disturbance, outpatient opioid use, and education were independently associated with worse pain interference (P ≤ .05). The sole independent predictor of ED opioid administration was outpatient opioid use. Patients taking outpatient opioids were younger, had lower health literacy, worse pain catastrophizing, sleep disturbance, depression/anxiety, and greater rates of metastatic cancer and cancer-related surgery (P ≤ .05). CONCLUSION: Biopsychosocial factors, particularly pain catastrophizing, remained significantly associated with worse pain outcomes for patients with cancer in the ED even after controlling for demographic and clinical variables. Patient outpatient opioid use was independently associated with worse pain, interference, and greater opioid administration, identifying this as a marker for who may benefit most from adjuvant pharmacologic and behavioral interventions.

Improving the Efficiency of Clinical Trial Recruitment Using an Ensemble Machine Learning to Assist With Eligibility Screening.

OBJECTIVE: Efficiently identifying eligible patients is a crucial first step for a successful clinical trial. The objective of this study was to test whether an approach using electronic health record (EHR) data and an ensemble machine learning algorithm incorporating billing codes and data from clinical notes processed by natural language processing (NLP) can improve the efficiency of eligibility screening. METHODS: We studied patients screened for a clinical trial of rheumatoid arthritis (RA) with one or more International Classification of Diseases (ICD) code for RA and age greater than 35 years, from a tertiary care center and a community hospital. The following three groups of EHR features were considered for the algorithm: 1) structured features, 2) the counts of NLP concepts from notes, 3) health care utilization. All features were linked to dates. We applied random forest and logistic regression with least absolute shrinkage and selection operator penalty against the following two standard approaches: 1) one or more RA ICD code and no ICD codes related to exclusion criteria (ScreenRAICD1 +EX ) and 2) two or more RA ICD codes (ScreenRAICD2 ). To test the portability, we trained the algorithm at one institution and tested it at the other. RESULTS: In total, 3359 patients at Brigham and Women's Hospital (BWH) and 642 patients at Faulkner Hospital (FH) were studied, with 461 (13.7%) eligible patients at BWH and 84 (13.4%) at FH. The application of the algorithm reduced ineligible patients from chart review by 40.5% at the tertiary care center and by 57.0% at the community hospital. In contrast, ScreenRAICD2 reduced patients for chart review by 2.7% to 11.3%; ScreenRAICD1+EX reduced patients for chart review by 63% to 65% but excluded 22% to 27% of eligible patients. CONCLUSION: The ensemble machine learning algorithm incorporating billing codes and NLP data increased the efficiency of eligibility screening by reducing the number of patients requiring chart review while not excluding eligible patients. Moreover, this approach can be trained at one institution and applied at another for multicenter clinical trials.

Coronary Microvascular Dysfunction in Rheumatoid Arthritis Compared to Diabetes Mellitus and Association With All-Cause Mortality.

OBJECTIVE: Coronary microvascular dysfunction (CMD) is a predictor of cardiac death in diabetes mellitus (DM) independent of traditional cardiovascular (CV) risk factors. Rheumatoid arthritis (RA) is a chronic inflammatory condition, with excess CV risk compared to the general population, in which CMD is hypothesized to play a role; however, there are limited data on CMD in RA and any association with clinical outcomes. The objective of this study was to compare the prevalence of CMD in RA to that in DM and to test the association with all-cause mortality. METHODS: We performed a retrospective cohort study using data from a registry of all patients undergoing stress myocardial perfusion positron emission tomography as part of routine clinical care from 2006 to 2017. The inclusion criterion was a normal perfusion scan. Patients with RA or DM were classified using previously published approaches. Coronary flow reserve (CFR) was calculated for all patients in the registry and linked with mortality data. CMD was defined as CFR <2.0. RESULTS: We studied 73 patients with RA and 441 patients with DM. Among patients with a normal perfusion scan, the prevalence of CMD in RA was similar to that in DM (P = 0.2). CMD was associated with increased risk for all-cause mortality in RA (hazard ratio 2.4 [95% confidence interval 1.4-4.2]) as well as increased risk for cardiac-related death at rates similar to those in DM. CONCLUSION: These findings suggest an important role for CMD as a potential contributor to excess CV risk and mortality in RA, as previously observed in DM, as well as evidence for a mechanistic link between inflammation and cardiovascular disease.