Improvement of anticoagulant treatment using a dynamic decision support algorithm: A Danish Cohort study

Introduction

Warfarin is the most widely prescribed vitamin K antagonist and in the United States and Europe more than 10 million people are currently in long-term oral anticoagulant treatment. This study aims to retrospectively validate a dynamic statistical model providing dosage suggestions to patients in warfarin treatment.

Materials and methods

The model was validated on a cohort of 553 patients with a mean TTR of 83%. Patients in the cohort were self-monitoring and managed by a highly specialised anticoagulation clinic. The predictive model essentially consists of three parts handling INR history, warfarin dosage and biological noise, which allows for prediction of future INR values and optimal warfarin dose to stay on INR target. Further, the model is based on parameters initially being set to population values and gradually individualised during monitoring of patients.

Primary outcome

Time in therapeutic range was used as surrogate quality measure of the treatment, and model-suggested dosage of warfarin was used to assess the accuracy of the model performance.

Results

The accuracy of the model predictions measured as median absolute error was 0.53 mg/day (interquartile range from 0.25 to 1.0). The model performance was evaluated by the difference between observed and predicted warfarin intake in the preceding week of an INR measurement. In more than 70% of the cases where INR measurements were outside the therapeutic range, the model suggested a more reasonable dose than the observed intake.

Conclusion

Applying the proposed dosing algorithm can potentially further increase the time in INR target range beyond 83%.     

The development of a dynamic,six-axis spine simulator

Background contextAlthough a great deal of research has been completed to characterize the stiffness of spinal specimens, there remains a limited understanding of the spine in 6 df and there is a lack of data from dynamic testing in six axes.PurposeThis study details the development and validation of a dynamic six-axis spine simulator.Study designBiomechanical study.MethodsA synthetic spinal specimen was used for the purpose of tuning the simulator, completing positional accuracy tests, and measuring frequency response under physiological conditions. The spine simulator was used to complete stiffness matrix tests of an L3–L4 lumbar porcine functional spinal unit. Five testing frequencies were used, ranging from quasistatic (0.00575 Hz) to dynamic (0.5 Hz). Tests were performed without an axial preload and with an axial preload of 500 N.ResultsThe validation tests demonstrated that the simulator is capable of producing accurate positioning under loading at frequencies up to 0.5 Hz using both sine and triangle waveforms. The porcine stiffness matrix tests demonstrated that the stiffness matrix is not symmetrical about the principal stiffness diagonal. It was also shown that while an increase in test frequency generally increased the principal stiffness terms, axial preload had a much greater effect.ConclusionsThe spine simulator is capable of characterizing the dynamic biomechanics of the spine in six axes and provides a means to better understand the complex behavior of the spine under physiological conditions.     

Robotic Trans‐Abdominal Transplant Nephrectomy for a Failed Renal Allograft

Minimally invasive surgery for removal of a failed renal allograft has not previously been reported. Herein, we report the first robotic trans‐abdominal transplant nephrectomy (TN). A 34‐year‐old male with Alport's syndrome lost function of his deceased donor allograft after 12 years and presented with fever, pain over his allograft and hematuria. The operation was performed intra‐abdominally using the Da Vinci Robotic Surgical System with four trocars. The total operative time was 235 min and the estimated blood loss was less than 25 cm³. There were no peri‐operative complications observed and the patient was discharged to home less than 24 h postoperatively. The utilization of robotic technology facilitated the successful performance of a minimally invasive, trans‐abdominal TN.