A subset of patients with hypothyroidism are not satisfied with their current therapy or their physicians. Higher satisfaction with both treatment and physicians is reported by those patients on DTE. While the study design does not provide a mechanistic explanation for this observation, future studies should investigate whether preference for DTE is related to triiodothyronine levels or other unidentified causes.

Long-term exposure to oral anticoagulation is associated with an increased risk of vertebral and rib fractures. The mechanism by which this occurs is still unclear and needs further investigation.

Oral anticoagulants are putative risk factors for osteoporosis, but observational cross-sectional studies describing their effects on bone mineral density have reported conflicting results, prospective studies are not available, and randomized trials are not feasible. To determine the association between exposure to oral anticoagulants and changes in bone density, we systematically reviewed nine original cross-sectional studies on the effect of long-term exposure to any oral anticoagulant on bone density in adults. The effect size was assessed by standardized mean difference (SMD, exposed minus unexposed) and pooled by skeletal site; results are reported in standard deviation units. Bone density was significantly decreased among exposed subjects in the ultradistal radius (SMD, -0.39; 95% CI, -0.67 to -0.10) but not in the distal radius (SMD, -0.47; 95% CI, -0.97 to 0.04), lumbar spine (SMD, -0.27; 95% CI, -0.59 to 0.05), femoral neck (SMD, 0.03; 95% CI, -0.22 to 0.29) or femoral trochanter (SMD, -0.18; 95% CI, -0.48 to 0.11). The evidence should be considered with caution, but it is consistent with a negative association of oral anticoagulants with bone density in the ultradistal radius, although not in the spine or hip. This suggests that long-term oral anticoagulation might be associated with no more than a modest increase in osteoporotic fracture risk, but this should be verified in future longitudinal studies.

Disease progression models, statistical models that assess a patient's risk of diabetes progression, are popular tools in clinical practice for prevention and management of chronic conditions. Most, if not all, models currently in use are based on gold standard clinical trial data. The relatively small sample size available from clinical trial limits these models only considering the patient's state at the time of the assessment and ignoring the trajectory, the sequence of events, that led up to the state. Recent advances in the adoption of electronic health record (EHR) systems and the large sample size they contain have paved the way to build disease progression models that can take trajectories into account, leading to increasingly accurate and personalized assessment. To address these problems, we present a novel method to observe trajectories directly. We demonstrate the effectiveness of the proposed method by studying type 2 diabetes mellitus (T2DM) trajectories. Specifically, using EHR data for a large population-based cohort, we identified a typical trajectory that most people follow, which is a sequence of diseases from hyperlipidemia (HLD) to hypertension (HTN), impaired fasting glucose (IFG), and T2DM. In addition, we also show that patients who follow different trajectories can face significantly increased or decreased risk.