Pilot Study of an e-Cohort to Monitor Adverse Event for Patient with Hip Prostheses from Clinical Data Warehouse.

Hip arthroplasty represents a large proportion of orthopaedic activity, constantly increasing. Automating monitoring from clinical data warehouses is an opportunity to dynamically monitor devices and patient outcomes allowing improve clinical practices. Our objective was to assess quantitative and qualitative concordance between claim data and device supply data in order to create an e-cohort of patients undergoing a hip replacement.

Role of real-world digital data for orthopedic implant automated surveillance: a systematic review.

Introduction: Data collection automation through the reuse of real-world digital data from clinical data warehouses (CDW) could represent a great opportunity to improve medical device monitoring. For instance, this approach is starting to be used for the design of automated decision support systems for joint replacement monitoring. However, a number of obstacles remains, such as data quality and interoperability through the use of common and regularly updated terminologies, and the use of a Unique Device Identifier (UDI).

Comparison of Knowledge Databases to Be Used in Automated Monitoring of Orthopedic Medical Devices.

Surveillance and traceability of medical devices (MD) is a challenge in health care systems. In the perspective of reusing EHR data to automate the monitoring of medical devices, we carried out a comparison of the main MD knowledge bases (MD-KDB) currently available in France. Four MD-KDBs (ANSM, Gudid, Exhausmed and CIOdm) were compared quantitatively and through an example of a shoulder prosthesis.

Prescreening in Oncology Using Data Sciences: The PreScIOUS Study.

The development of precision medicine in oncology to define profiles of patients who could benefit from specific and relevant anti-cancer therapies is essential. An increasing number of specific eligibility criteria are necessary to be eligible to targeted therapies. This study aimed to develop an automated algorithm based on natural language processing to detect patients and tumor characteristics to reduce the time-consuming prescreening for trial inclusions.

[ANCA-vasculitis with renal impairment treated by intravenous versus oral cyclophosphamide: Multicentric analysis of relapse free survival (VaReCyS)].

Introduction: ANCA-vasculitis are associated with high morbidity and mortality. Large use of cyclophosphamide as induction immunosuppressive therapy is limited by its side effects. All recent literature trends in decreasing cumulative dose while optimizing maintenance therapy.

Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine learning algorithms (Gradient Boosting, Random Forest, and Neural Network) for predicting the risk of all-cause, 30-day hospital readmission using data from the clinical data warehouse of Rennes and from other sources. The dataset included hospital stays based on the criteria of the French national methodology for the 30-day readmission rate (i.

Degradation mechanism of tributyl phosphate by UV/HO treatment and parameters optimization towards the design of a pilot reactor.

While activated sludge treatment is currently the preferred process for the removal of tributyl phosphate (TBP) at the mg.L level, it is well known that this recalcitrant molecule is incompletely degraded, stimulating research into alternative approaches, such as advanced oxidation. The aim of this study was to characterize the degradation mechanism of TBP during ultraviolet/HO treatment using P NMR, ionic chromatography and total organic carbon analysis.