The implantation of a total knee arthroplasty (TKA) is a milestone in a resident's surgical training. Studies demonstrate higher loosening rates after TKA by inexperienced surgeons. Alignment outliers should be avoided to achieve a long implant survival. Therefore, our study questioned whether residents implant knee prostheses using computer navigation as accurately as experienced consultants. The data for 662 consecutive TKAs were analyzed retrospectively. The operations were performed by 4 consultants (n=555) and 5 residents under supervision by a consultant (n=107). Cutting errors were recorded from the navigation data. The postoperative mechanical axis and operation time were recorded. Operation time was significantly prolonged if residents performed the operation vs consultants (139 vs 122 minutes, respectively). The analysis of cutting errors within each surgeon's first 20 navigated operations resulted in no significant difference between residents and consultants. During the subsequent operations, a trend toward a more accurate placement of the prosthesis was detected for consultants. The rate of outliers with a mechanical axis deviation >2° was low and did not significantly differ between residents and consultants (3.7% vs 2.3%, respectively). Our study shows that residents implant their first TKA using computer navigation as accurately as experienced consultants. However, the residents' operations take longer and therefore incur additional costs for the teaching clinic.
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http://dx.doi.org/10.3928/01477447-20110124-05 | DOI Listing |
Zhong Nan Da Xue Xue Bao Yi Xue Ban
August 2024
Center of Clinical Pharmacology, Third Xiangya Hospital, Central South University, Changsha 410013.
Objectives: Software for pharmacological modeling and statistical analysis is essential for drug development and individualized treatment modeling. This study aims to develop a pharmacokinetic analysis cloud platform that leverages cloud-based benefits, offering a user-friendly interface with a smoother learning curve.
Methods: The platform was built using Rails as the framework, developed in Julia language, and employs PostgreSQL 14 database, Redis cache, and Sidekiq for asynchronous task management.
Phys Life Rev
January 2025
Institute of Intelligent Systems and Robotics, CNRS, Sorbonne University, Paris, France.
The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges. This paper introduces a composite, multilevel, and multidimensional model of consciousness as a heuristic framework to guide research in this field. Consciousness is treated as a complex phenomenon, with distinct constituents and dimensions that can be operationalized for study and for evaluating their replication.
View Article and Find Full Text PDFJ Med Syst
January 2025
Computer Science Institute, DISIT, University of Eastern Piedmont, Alessandria, Italy.
In traditional medical education, learners are mostly trained to diagnose and treat patients through supervised practice. Artificial Intelligence and simulation techniques can complement such an educational practice. In this paper, we present GLARE-Edu, an innovative system in which AI knowledge-based methodologies and simulation are exploited to train learners "how to act" on patients based on the evidence-based best practices provided by clinical practice guidelines.
View Article and Find Full Text PDFAlzheimers Dement
December 2024
Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center at San Antonio, San Antonio, TX, USA.
Background: The hippocampus and its subfields in the human brain play a pivotal role in forming new memories and spatial navigation. The automated assessment of the hippocampus and its subfields are useful tools for the early diagnosis of Alzheimer's disease and other neurodegenerative diseases such as primary age-related tauopathy, Lewy body dementia, limbic-predominant age-related TDP-43 encephalopathy (LATE), and frontotemporal lobar Dementia. Postmortem brain magnetic resonance imaging plays a crucial role in neuroscience and clinical research, providing valuable insights into the structural and pathological features of the brain after death.
View Article and Find Full Text PDFBackground: Digital cognitive tools offer novel ways to detect early cognitive changes associated with preclinical Alzheimer's disease (AD). A digital version of the maze test (dMaze) was recently developed using a digital pen (12 ms temporal precision) to uniquely capture the process of test completion, reflecting the thinking effort, potentially more sensitive to early cognitive deficits in preclinical AD. The sensitivity of these novel digital maze test variables-Wall Penetration Count and Speed Standard Deviation (Speed SD)-to detect early amyloid-β burden was evaluated, hypothesizing that greater amyloid accumulation would be associated with greater variability of speed, and more wall penetration errors while completing the task, reflecting a greater thinking effort.
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