Publications by authors named "P Burckhardt"

A rebound of osteoclast activity during the 2 years after a treatment or prevention of osteoporosis with denosumab (Dmab) leads to an increased risk of vertebral fractures (VFs). We attempted to identify the risk factors for these VF and to examine the protective role of bisphosphonates. For that, 22 specialists in Switzerland provided data of unselected patients, treated with denosumab for osteoporosis or breast cancer without metastases under aromatase inhibitors, who have received at least two injections of Dmab, with at least 1 year of follow-up after discontinuation.

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Risk-stratifying chronic disease patients in real time has the potential to facilitate targeted interventions and improve disease management and outcomes. We apply group-based multi-trajectory modeling to risk stratify patients with chronic kidney disease (CKD) and its major complications into distinct trajectories of disease development and predict acute kidney injury (AKI), a serious, under-diagnosed outcome of CKD that is both preventable and treatable with early detection. Utilizing Electronic Health Record data of 1,947 patients, we identify eight risk groups with distinct trajectories and profiles.

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Objective: To test whether daily high-dose vitamin D improves recovery after unilateral total knee replacement.

Methods: Data come from a 24-month randomised, double-blind clinical trial. Adults aged 60 and older undergoing unilateral joint replacement due to severe knee osteoarthritis were 6-8 weeks after surgery randomly assigned to receive daily high-dose (2000 IU) or standard-dose (800 IU) vitamin D.

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AMIA Annu Symp Proc

March 2019

The increased adoption of Electronic Health Record (EHR) systems offers new opportunities for clinical research. The Health Insurance Portability and Accountability Act (HIPAA) mandates that medical records need to be stripped of personal identifiers in order to be shared. One particular challenge is how to handle free-text medical records.

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An ever increasing number of people are affected by chronic kidney disease (CKD). A better understanding of the progression ofCKD and its complications is needed to address what is becoming a major burden for health-care systems worldwide. Utilizing a rich data set consisting of the Electronic Health Records (EHRs) of more than patients from a leading community nephrology practice in Western Pennsylvania, we applied group-based trajectory modeling (GBTM) in order to detect patient risk groups and uncover typical progressions of CKD and related comorbidities and complications.

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