There has been extensive research into methods of increasing academic departmental scholarly activity (DSA) through targeted interventions. Residency programmes are responsible for ensuring sufficient scholarly opportunities for residents. We sought to discover the outcomes of an intensive research initiative (IRI) on DSA in our department in a short-time interval. IRI was implemented, consisting of multiple interventions, to rapidly produce an increase in DSA through resident/medical student faculty engagement. We compare pre-IRI (8 years) and post-IRI (2 years) research products (RP), defined as the sum of oral presentations and publications, to evaluate the IRI. The study was performed in 2020. The IRI resulted in an exponential increase in DSA with an annual RP increase of 350% from 2017 (3 RP) to 2018 (14 RP), with another 92% from 2018 (14 RP) to 2019 (27 RP). RP/year exponentially increased from 2.1/year to 10.5/year for residents and 0.5/year to 10/year for medical students, resulting in a 400% and 1900% increase in RP/year, respectively. The common methods in literature to increase DSA included instituting protected research time (23.8%) and research curriculum (21.5%). We share our department's increase in DSA over a short 2-year period after implementing our IRI. Our goal in reporting our experience is to provide an example for departments that need to rapidly increase their DSA. By reporting the shortest time interval to achieve exponential DSA growth, we hope this example can support programmes in petitioning hospitals and medical colleges for academic support resources.
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http://dx.doi.org/10.1136/postgradmedj-2020-139133 | DOI Listing |
Transplant Proc
January 2025
Immunology Department, Immunopathology Group, Marqués de Valdecilla University Hospital-IDIVAL, Santander, Spain. Electronic address:
Background: Antibody-mediated rejection (ABMR) has become one of the leading causes of chronic lung graft dysfunction. However, in lung transplantation, this entity is sometimes difficult and controversial to diagnose. It is mainly caused by the appearance of donor-specific anti-human leukocyte antigen (HLA) antibodies (DSA), although there are situations with C4d deposits in biopsy in the absence of circulating DSA.
View Article and Find Full Text PDFTranspl Int
January 2025
Department of Nephrology, University Hospital Zurich, Zurich, Switzerland.
J Shoulder Elbow Surg
December 2024
Department of Trauma Surgery and Orthopedics - Medical University of Vienna, AKH Wien, Vienna, Austria. Electronic address:
Background: While outcomes following reverse shoulder arthroplasty (rTSA) have often been gauged through radiological assessments focusing on prosthesis position, there is increasing recognition of patient-reported outcomes, particularly satisfaction, as indicators of surgical success. The objective of this study was to correlate radiological findings with clinical outcomes, patient satisfaction, and health-related quality of life (HRQoL).
Materials And Methods: A retrospective evaluation was conducted on patients following rTSA at a minimum of two years postoperatively.
Front Transplant
December 2024
Duke Transplant Center, Duke University School of Medicine, Durham, NC, United States.
Objective: Cardiac Allograft Vasculopathy (CAV), a process of vascular damage accelerated by antibody-mediated rejection (AMR), is one of the leading causes of cardiac transplant failure. Proteasome inhibitors (PIs) are utilized to treat AMR, however PI-associated toxicity limits their therapeutic utility. Novel immunoproteasome inhibitors (IPIs) have higher specificity for immune cells and have not been investigated for AMR in cardiac transplant patients.
View Article and Find Full Text PDFWater Res
December 2024
Centre for Water System, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK. Electronic address:
Machine learning has been increasingly used to solve management problems of water distribution networks (WDNs). A critical research gap, however, remains in the effective incorporation of WDN hydraulic characteristics in machine learning. Here we present a new water distribution network embedding (WDNE) method that transforms the hydraulic relationships of WDN topology into a vector form to be best suited for machine learning algorithms.
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