Background: Patient specific guides (PSG) have been reported to improve overall component alignment in total knee arthroplasty (TKA). With more surgeons likely to consider this method of TKA in the future, this study was performed to establish whether there is a learning curve with use of PSG in TKA.
Methods: Eighty-six consecutive PSG TKAs performed by one surgeon were retrospectively analyzed in two groups. The first 30 patients were compared to the second 56 patients with regards to their operative times and post-operative multi-planar alignments on computed tomography (CT) scan.
Results: Mean operative time was higher in the initial 30 cases compared to the second 56 cases (85 min vs. 78 min; p=0.001). No statistically significant differences were found in post-operative TKA alignment between the two groups.
Conclusions: This study suggests that there is a minimal learning curve with operative time associated with use of PSG in TKA. This study was unable to detect a significant learning curve with regards to restoration of mechanical knee alignment with the use of PSG in TKA.
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http://dx.doi.org/10.1016/j.knee.2015.03.002 | DOI Listing |
Brachytherapy
January 2025
Department of Radiation Oncology and Medical Physics, Advanced Centre for Treatment Research and Education in Cancer, Tata Memorial Centre, Homi Bhabha National Institute, Navi Mumbai, India. Electronic address:
Purpose: The quality of cervical cancer intracavitary brachytherapy (ICBT) depends on the training and experience of the radiation oncologist (RO). The present study was performed to establish primary learning curve for ICBT.
Materials And Methods: Forty-three skill parameters were identified for performing ICBT and were included for Brachytherapy Proficiency Assessment and Scoring System (Brachy-PASS) questionnaire.
J Voice
January 2025
Department of Surgery, UMONS Research Institute for Health Sciences and Technology, University of Mons (UMons), Mons, Belgium; Division of Laryngology and Bronchoesophagology, Department of Otolaryngology Head Neck Surgery, EpiCURA Hospital, Baudour, Belgium; Department of Otolaryngology-Head and Neck Surgery, Foch Hospital, School of Medicine, UFR Simone Veil, Université Versailles Saint-Quentin-en-Yvelines (Paris Saclay University), Paris, France; Department of Otolaryngology, Elsan Hospital, Paris, France. Electronic address:
Background: Voice analysis has emerged as a potential biomarker for mood state detection and monitoring in bipolar disorder (BD). The systematic review aimed to summarize the evidence for voice analysis applications in BD, examining (1) the predictive validity of voice quality outcomes for mood state detection, and (2) the correlation between voice parameters and clinical symptom scales.
Methods: A PubMed, Scopus, and Cochrane Library search was carried out by two investigators for publications investigating voice quality in BD according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statements.
J Psychiatr Res
January 2025
Department of Psychiatry, National Clinical Research Center for Mental Disorders, and National Center for Mental Disorders, The Second Xiangya Hospital of Central South University, Changsha, 410011, Hunan, China. Electronic address:
Background: Microstate characterization of electroencephalogram (EEG) is a data-driven approach to explore the functional changes and interrelationships of multiple brain networks on a millisecond scale. This study aimed to explore the pathological changes of whole-brain functional networks in patients with obsessive-compulsive disorders (OCD) through microstate analysis and further to explore its potential value as an auxiliary diagnostic index.
Methods: Forty-eight OCD patients (33 with more than moderate anxiety symptoms, 15 with mild anxiety symptoms) and 52 healthy controls (HCs) were recruited.
Neural Netw
December 2024
Department of Earth Science and Engineering, Imperial College London, Prince Consort Road, London SW7 2BP, UK; Centre for AI-Physics Modelling, Imperial-X, White City Campus, Imperial College London, W12 7SL, UK.
Machine learning (ML) has benefited from both software and hardware advancements, leading to increasing interest in capitalising on ML throughout academia and industry. There have been efforts in the scientific computing community to leverage this development via implementing conventional partial differential equation (PDE) solvers with machine learning packages, most of which rely on structured spatial discretisation and fast convolution algorithms. However, unstructured meshes are favoured in problems with complex geometries.
View Article and Find Full Text PDFPrenat Diagn
January 2025
Department of Artificial Intelligence, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur, Malaysia.
Objective: The first objective is to develop a nuchal thickness reference chart. The second objective is to compare rule-based algorithms and machine learning models in predicting small-for-gestational-age infants.
Method: This retrospective study involved singleton pregnancies at University Malaya Medical Centre, Malaysia, developed a nuchal thickness chart and evaluated its predictive value for small-for-gestational-age using Malaysian and Singapore cohorts.
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