Factors Associated With Nonattendance for Osteoporosis Evaluation Following Fragility Fracture.

This study assessed patient demographic factors associated with nonattendance for osteoporosis evaluation after being referred to our Bone Health Clinic (BHC), a hospital-based outpatient Fracture Liaison Service (FLS), for a fragility fracture. 507 patients sustaining a fragility fracture were referred to the BHC over a 39-month period. Retrospective chart review was conducted to capture osteoporosis evaluation attendance rates and demographic factors (age, gender, race, area deprivation index, insurance type, and fracture type).

Reasons for multiple biologic and targeted synthetic DMARD switching and characteristics of treatment refractory rheumatoid arthritis.

Objective: Switching biologic and targeted synthetic DMARD (b/tsDMARD) medications occurs commonly in RA patients, however data are limited on the reasons for these changes. The objective of the study was to identify and categorize reasons for b/tsDMARD switching and investigate characteristics associated with treatment refractory RA.

Methods: In a multi-hospital RA electronic health record (EHR) cohort, we identified RA patients prescribed ≥1 b/tsDMARD between 2001 and 2017.

High rates of vitamin D insufficiency among patients presenting for total knee arthroplasty.

Widely varying prevalence of vitamin D deficiency has been reported in patients presenting for total knee arthroplasty (TKA). The primary aim of this study was to determine vitamin D levels in TKA patients and to compare to patients already routinely evaluated for vitamin D levels, patients with fragility fractures of the distal radius (DRF). There is significant overlap between patients presenting for TKA and with DRF, both in terms of medical comorbidities and overall health status, making these populations suitable comparative cohorts.

Identifying shared genetic architecture between rheumatoid arthritis and other conditions: a phenome-wide association study with genetic risk scores.

Background: Rheumatoid arthritis (RA) shares genetic variants with other autoimmune conditions, but existing studies test the association between RA variants with a pre-defined set of phenotypes. The objective of this study was to perform a large-scale, systemic screen to determine phenotypes that share genetic architecture with RA to inform our understanding of shared pathways.

Methods: In the UK Biobank (UKB), we constructed RA genetic risk scores (GRS) incorporating human leukocyte antigen (HLA) and non-HLA risk alleles.

Impact of an Outpatient Fracture Liaison Service on Osteoporosis Evaluation Among Patients With Upper Extremity Fragility Fracture.

Background: The purpose of this study was to assess the impact of implementation of an outpatient fracture liaison service (FLS) on completion rates of dual-energy x-ray absorptiometry (DXA) and screening labs including 25-OH vitamin D and parathyroid hormone (PTH) in patients with upper extremity (UE) fragility fractures.

Methods: At our institution, 367 patients were treated in 2014-2015 for UE fragility fractures of the distal radius and proximal humerus before implementation of our outpatient FLS and 395 patients in 2017-2018 after implementation. Retrospective chart review was conducted to identify completed DXA scans within 2 years of fracture treatment and completed 25-OH vitamin D and PTH labs within 1 year of fracture treatment.

Temporal Trends in Clinical Evidence of 5-Year Survival Within Electronic Health Records Among Patients With Early-Stage Colon Cancer Managed With Laparoscopy-Assisted Colectomy vs Open Colectomy.

Importance: Temporal shifts in clinical knowledge and practice need to be adjusted for in treatment outcome assessment in clinical evidence.

Objective: To use electronic health record (EHR) data to (1) assess the temporal trends in treatment decisions and patient outcomes and (2) emulate a randomized clinical trial (RCT) using EHR data with proper adjustment for temporal trends.

Design, Setting, And Participants: The Clinical Outcomes of Surgical Therapy (COST) Study Group Trial assessing overall survival of patients with stages I to III early-stage colon cancer was chosen as the target trial.

Future Fracture Risk in Upper Extremity Fracture and Non-Fracture Patients.

Background: Upper extremity (UE) fragility fractures are common and strong predictors of subsequent fractures. To investigate the relative importance of an UE fragility fracture in determining future fracture risk, we conducted a cross-sectional study to compare future fracture risk between patients presenting for osteoporosis evaluation after an UE fragility fracture and a similarly aged cohort of patients without an UE fracture.

Methods: In all, 129 UE fracture patients seen in our bone health clinic (BHC) and 114 non-fracture UE fracture patients seen in an UE clinic completed clinic intake surveys assessing for fracture risk factors.

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.

Leveraging electronic health records data to predict multiple sclerosis disease activity.

Objective: No relapse risk prediction tool is currently available to guide treatment selection for multiple sclerosis (MS). Leveraging electronic health record (EHR) data readily available at the point of care, we developed a clinical tool for predicting MS relapse risk.

Methods: Using data from a clinic-based research registry and linked EHR system between 2006 and 2016, we developed models predicting relapse events from the registry in a training set (n = 1435) and tested the model performance in an independent validation set of MS patients (n = 186).