Preoperative antithrombotic therapy and risk of blood transfusion and mortality following hip fracture surgery: a Danish nationwide cohort study.

Hip fracture surgery is associated with high risk of bleeding and mortality. The patients often have cardiovascular comorbidity, which requires antithrombotic treatment. This study found that preoperative use of oral anticoagulants was not associated with transfusion or mortality following hip fracture surgery, whereas increased risk may exist for antiplatelet drugs. INTRODUCTION: Hip fracture surgery is associated with high bleeding risk and mortality; however, data on operative outcomes of hip fracture patients admitted while on antithrombotic therapy is sparse. We examined if preoperative antithrombotic treatment was associated with increased use of blood transfusion and 30-day mortality following hip fracture surgery. METHODS: Using data from the Danish Multidisciplinary Hip Fracture Registry, we identified 74,791 hip fracture surgery patients aged ≥ 65 years during 2005-2016. Exposure was treatment with non-vitamin K antagonist oral anticoagulant (NOAC), vitamin K antagonists (VKA), or antiplatelet drugs at admission for hip fracture. Outcome was blood transfusion within 7 days postsurgery and death within 30 days. RESULTS: A 45.3% of patients received blood transfusion and 10.6% died. Current NOAC use was associated with slightly increased risk of transfusion (adjusted relative risk (aRR) 1.07, 95% confidence interval (CI) 1.01-1.14), but similar mortality risk (adjusted hazard ratio (aHR) 0.88, 95% CI 0.75-1.03) compared with non-users. The pattern remained when restricting to patients with short surgical delay (< 24 h). VKA users did not have increased risk of transfusion or mortality. The risks of transfusion (aRR 1.15 95% CI 1.12-1.18) and 30-day mortality (aHR 1.18 95% CI 1.14-1.23) were increased among antiplatelet users compared with non-users. CONCLUSIONS: In an observational setting, neither preoperative NOAC nor VKA treatments were associated with increased risk of 30-day postoperative mortality among hip fracture patients. NOAC was associated with slightly increased risk of transfusion. Preoperative use of antiplatelet drugs was associated with increased risk of transfusion and mortality.

Helicobacter pylori infection is not associated with rheumatoid arthritis.

OBJECTIVE: Rheumatoid arthritis (RA) is an autoinflammatory disease caused by genetic susceptibility and environmental triggers, which include infectious agents. Helicobacter pylori, a bacterium that frequently colonizes the stomach, is associated with the development of certain autoinflammatory disorders. This study examined a possible association between H. pylori infection and RA. METHOD: This cohort study was performed in the Central Denmark Region. Patients were enrolled from primary healthcare centres after a urea breath test (UBT) for H. pylori and followed for a median of 8 years. Nationwide administrative registries provided information about the patients' diagnoses, country of birth, and gender. Comorbidity was determined using the Charlson Comorbidity Index. We compared the prevalence of RA via odds ratios (ORs) and incidences using Cox regression to calculate the hazard ratios (HRs) by comparing H. pylori-positive and H. pylori-negative individuals and adjusting for confounding variables. RESULTS: A total of 56 000 people diagnosed as H. pylori positive or negative had similar rates of comorbidity. No link was found between H. pylori and RA. There was no difference in RA prevalence until time of UBT [OR = 0.91, 95% confidence interval (CI) 0.70-1.19)] or incidence of new RA cases after UBT (HR = 0.80, 95% CI 0.56-1.13) between H. pylori-positive and -negative subjects. Validation via four other RA definitions provided similar results. CONCLUSION: This study found no association between H. pylori infection and RA. This result does not support the involvement of H. pylori in a gut-joint axis of importance for RA development.

Body mass index, risk of allogeneic red blood cell transfusion, and mortality in elderly patients undergoing hip fracture surgery.

UNLABELLED: Despite improvements in preoperative and postoperative treatment, hip fracture surgery may lead to blood transfusion. Little is known about the impact of body mass index on transfusion risk and subsequent mortality. Opposite overweight and obese patients, underweight patients had increased risk of transfusion and death within 1 year of surgery. INTRODUCTION: Despite improvements in preoperative and postoperative treatment of hip fracture patients, hip fracture surgery may lead to blood loss. We examined the risk of red blood cell transfusion (as an indirect measure of blood loss) and subsequent mortality by body mass index level in patients aged 65 and over undergoing hip fracture surgery. METHODS: This is a population-based cohort study using medical databases. We included all patients who underwent surgery for hip fracture during 2005-2013. We calculated the cumulative risk of red blood cell transfusion within 7 days of surgery treating death as a competing risk and, among transfused patients, short- (8-30 days postsurgery) and long-term mortality (31-365 days postsurgery). RESULTS: Among 56,420 patients, 47.7 % received at least one red blood cell transfusion within 7 days of surgery. In patients with normal weight, the risk was 48.8 % compared with 57.0 % in underweight patients (adjusted RR = 1.11; CI 1.08-1.15), 42.1 % in overweight patients (adjusted RR = 0.89; CI 0.86-0.91), and 42.2 % in obese patients (adjusted RR = 0.87; CI 0.84-0.91). Among transfused patients, adjusted HRs for short-term mortality were 1.52 (CI 1.34-1.71), 0.70 (CI 0.61-0.80), and 0.58 (CI 0.43-0.77) for underweight, overweight, and obese patients, respectively, compared with normal-weight patients. The corresponding adjusted HRs for long-term mortality were 1.45 (CI 1.33-1.57), 0.80 (CI 0.74-0.86), and 0.58 (CI 0.50-0.69). Similar association between BMI and mortality was observed also among non-transfused patients. CONCLUSIONS: Underweight patients had a higher risk of red blood cell transfusion and death in the first year of surgery than normal-weight patients, even when controlling for age and comorbidity. Opposite findings were seen for overweight and obese patients.

Factors Affecting the Absorption of Subcutaneously Administered Insulin: Effect on Variability.

Variability in the effect of subcutaneously administered insulin represents a major challenge in insulin therapy where precise dosing is required in order to achieve targeted glucose levels. Since this variability is largely influenced by the absorption of insulin, a deeper understanding of the factors affecting the absorption of insulin from the subcutaneous tissue is necessary in order to improve glycaemic control and the long-term prognosis in people with diabetes. These factors can be related to either the insulin preparation, the injection site/patient, or the injection technique. This review highlights the factors affecting insulin absorption with special attention on the physiological factors at the injection site. In addition, it also provides a detailed description of the insulin absorption process and the various modifications to this process that have been utilized by the different insulin preparations available.

PharmML in Action: an Interoperable Language for Modeling and Simulation.

PharmML is an XML-based exchange format created with a focus on nonlinear mixed-effect (NLME) models used in pharmacometrics, but providing a very general framework that also allows describing mathematical and statistical models such as single-subject or nonlinear and multivariate regression models. This tutorial provides an overview of the structure of this language, brief suggestions on how to work with it, and use cases demonstrating its power and flexibility.

The Effects of a GLP-1 Analog on Glucose Homeostasis in Type 2 Diabetes Mellitus Quantified by an Integrated Glucose Insulin Model.

In recent years, several glucagon-like peptide-1 (GLP-1)-based therapies for the treatment of type 2 diabetes mellitus (T2DM) have been developed. The aim of this work was to extend the semimechanistic integrated glucose-insulin model to include the effects of a GLP-1 analog on glucose homeostasis in T2DM patients. Data from two trials comparing the effect of steady-state liraglutide vs. placebo on the responses of postprandial glucose and insulin in T2DM patients were used for model development. The effect of liraglutide was incorporated in the model by including a stimulatory effect on insulin secretion. Furthermore, for one of the trials an inhibitory effect on glucose absorption was included to account for a delay in gastric emptying. As other GLP-1 receptor agonists have similar modes of action, it is believed that the model can also be used to describe the effect of other receptor agonists on glucose homeostasis.

Pharmacometrics Markup Language (PharmML): Opening New Perspectives for Model Exchange in Drug Development.

The lack of a common exchange format for mathematical models in pharmacometrics has been a long-standing problem. Such a format has the potential to increase productivity and analysis quality, simplify the handling of complex workflows, ensure reproducibility of research, and facilitate the reuse of existing model resources. Pharmacometrics Markup Language (PharmML), currently under development by the Drug Disease Model Resources (DDMoRe) consortium, is intended to become an exchange standard in pharmacometrics by providing means to encode models, trial designs, and modeling steps.

Methods for Predicting Diabetes Phase III Efficacy Outcome From Early Data: Superior Performance Obtained Using Longitudinal Approaches.

The link between glucose and HbA1c at steady state has previously been described using steady-state or longitudinal relationships. We evaluated five published methods for prediction of HbA1c after 26/28 weeks using data from four clinical trials. Methods (1) and (2): steady-state regression of HbA1c on fasting plasma glucose and mean plasma glucose, respectively, (3) an indirect response model of fasting plasma glucose effects on HbA1c, (4) model of glycosylation of red blood cells, and (5) coupled indirect response model for mean plasma glucose and HbA1c. Absolute mean prediction errors were 0.61, 0.38, 0.55, 0.37, and 0.15% points, respectively, for Methods 1 through 5. This indicates that predictions improved by using mean plasma glucose instead of fasting plasma glucose, by inclusion of longitudinal glucose data and further by inclusion of longitudinal HbA1c data until 12 weeks. For prediction of trial outcome, the longitudinal models based on mean plasma glucose (Methods 4 and 5) had substantially better performance compared with the other methods.

Longitudinal Modeling of the Relationship Between Mean Plasma Glucose and HbA1c Following Antidiabetic Treatments.

Late-phase clinical trials within diabetes generally have a duration of 12-24 weeks, where 12 weeks may be too short to reach steady-state glycated hemoglobin (HbA1c). The main determinant for HbA1c is blood glucose, which reaches steady state much sooner. In spite of this, few publications have used individual data to assess the time course of both glucose and HbA1c, for predicting HbA1c. In this paper, we present an approach for predicting HbA1c at end-of-trial (24-28 weeks) using glucose and HbA1c measurements up to 12 weeks. The approach was evaluated using data from 4 trials covering 12 treatment arms (oral antidiabetic drug, glucagon-like peptide-1, and insulin treatment) with measurements at 24-28 weeks to evaluate predictions vs. observations. HbA1c percentage was predicted for each arm at end-of-trial with a mean prediction error of 0.14% [0.01;0.24]. Furthermore, end points in terms of HbA1c reductions relative to comparator were accurately predicted. The proposed model provides a good basis to optimize late-stage clinical development within diabetes.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e82; doi:10.1038/psp.2013.58; advance online publication 30 October 2013.