Despite the globally ascertained success of Total Knee Arthroplasty (TKA) procedure, 20% of patients are still unsatisfied with the surgery results. The purpose of the study is to identify the functional and radiological outcomes of the computer-assisted (CAS) TKA compared to the conventional technique. The clinical databases and medical records of both clinical sites were retrospectively analyzed, and then according to study time-lapse, inclusion, and exclusion criteria, eligible patients were retrieved and included. A total of 42 patients that underwent to CAS TKA (NAVI) and 61 patients that underwent to Conventional TKA (CONV) were included. The NAVI group reported a statistically significant higher surgical time. A lower intraoperative blood loss was found in the computer-assisted group, though this difference was not statistically significant. Implant survival analysis at two years did not show differences between groups during the follow-up period. At two years, follow-up postoperative intergroup analysis showed no statistically significant difference between groups. According to the radiologic analysis, the NAVI group showed comparable outcomes to the conventional group. The present study showed that there was no clinical and radiological difference between CAS arthroplasty and conventional technique.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8347820PMC
http://dx.doi.org/10.3390/jcm10153352DOI Listing

Publication Analysis

Top Keywords

outcomes computer-assisted
8
total knee
8
knee arthroplasty
8
compared conventional
8
conventional tka
8
cas tka
8
conventional technique
8
patients underwent
8
navi group
8
conventional
5

Similar Publications

Effects and mechanisms of computerized cognitive training in Huntington's disease: protocol for a pilot study.

Neurodegener Dis Manag

January 2025

Turner Institute for Brain & Mental Health, School of Psychological Sciences, Faculty of Medicine, Nursing & Health Sciences, 18 Innovation Walk, Monash University, Clayton VIC 3800, Australia.

Huntington's disease (HD) causes progressive cognitive decline, with no available treatments. Computerized cognitive training (CCT) has shown efficacy in other populations, but its effects in HD are largely unknown. This pilot study will explore the effects and neural mechanisms of CCT in HD.

View Article and Find Full Text PDF

Effective BCDNet-based breast cancer classification model using hybrid deep learning with VGG16-based optimal feature extraction.

BMC Med Imaging

January 2025

Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal, Karnataka, 576104, India.

Problem: Breast cancer is a leading cause of death among women, and early detection is crucial for improving survival rates. The manual breast cancer diagnosis utilizes more time and is subjective. Also, the previous CAD models mostly depend on manmade visual details that are complex to generalize across ultrasound images utilizing distinct techniques.

View Article and Find Full Text PDF

Introduction: Numerous studies have characterised trajectories of asthma and allergy in children using machine learning, but with different techniques and mixed findings. The present work aimed to summarise the evidence and critically appraise the methodology.

Methods: 10 databases were searched.

View Article and Find Full Text PDF

Dynamic domain adaptive EEG emotion recognition based on multi-source selection.

Rev Sci Instrum

January 2025

School of Computer Science and Technology, Xi'an University of Posts and Telecommunications, Xi'an, Shaanxi 710121, China.

Emotion recognition based on electroencephalogram (EEG) has always been a research hotspot. However, due to significant individual variations in EEG signals, cross-subject emotion recognition based on EEG remains a challenging issue to address. In this article, we propose a dynamic domain-adaptive EEG emotion recognition method based on multi-source selection.

View Article and Find Full Text PDF

Post-stroke cognitive impairment is a common consequence of stroke, characterized by deficits in language, cognitive functioning, functional abilities. Innovative technological approaches, such as computerized cognitive retraining, offer promising strategies for mitigating the cognitive challenges. Despite their potential, the impact of these interventions on neuropsychological function and daily living capabilities has poor outcomes.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!