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1.
PLoS One ; 19(7): e0304654, 2024.
Article in English | MEDLINE | ID: mdl-38980889

ABSTRACT

PURPOSE: This meta-analysis compared the efficacy and safety of Proximal Femoral Nail Antirotation (PFNA) and InterTan Nail in the treatment of intertrochanteric fractures. Given the high incidence of femoral intertrochanteric fractures in the elderly population and its impact on quality of life, choosing the most effective and safest surgical option is crucial. PFNA and InterTan are currently two commonly used techniques, but there is a lack of systematic evaluation comparing their safety and effectiveness. This study aims to fill this knowledge gap through Meta-analysis, providing clinicians with evidence-based treatment recommendations. MATERIALS AND METHODS: A computer search was used to search for published literature on PFNA and InterTan in the treatment of intertrochanteric fractures in PubMed (Medline), Web of Science, Embase, Cochrane Library (CENTRAL), Cinahl, CBM, and CNKI.A total of 853 related literatures were retrieved, and 15 literatures were finally included. Newcastle-Ottawa-Scale and Cochrane systematic review methodologies were used to assess the quality of the literature. Meta-analysis was performed using Review Manager 5.4 software, following data extraction. RESULTS: The comparison found that during the surgical treatment of intertrochanteric fractures, the operation time, fluoroscopy time, and blood loss in the PFNA group were significantly shorter than those in the InterTan group, and the difference was statistically significant. In terms of postoperative complication rates, the InterTan group had a significant advantage over the PFNA group. Shaft fracture, varus collapse, cut out, screw migration, and pain of hip and thigh were the most likely to occur in the PFNA group, and the differences were all statistically significant. In terms of postoperative efficacy, the results of the PFNA group and the InterTan group were comparable, and there was no significant differences. CONCLUSIONS: When selecting surgical techniques for the treatment of femoral intertrochanteric fractures, it is necessary to conduct individualized assessments based on the patient's overall health status, surgical tolerance, and post-operative recovery needs. For patients who cannot tolerate long-term surgery or are in poor physical condition, PFNA may be more appropriate. While for patients who can tolerate long-term surgery or have more complex conditions, InterTan may be more suitable.


Subject(s)
Bone Nails , Hip Fractures , Humans , Hip Fractures/surgery , Treatment Outcome , Fracture Fixation, Intramedullary/methods , Fracture Fixation, Intramedullary/instrumentation , Postoperative Complications/etiology , Postoperative Complications/epidemiology
2.
PLoS One ; 19(5): e0303506, 2024.
Article in English | MEDLINE | ID: mdl-38771826

ABSTRACT

OBJECTIVE: To elucidate potential molecular mechanisms differentiating osteoarthritis (OA) and rheumatoid arthritis (RA) through a bioinformatics analysis of differentially expressed genes (DEGs) in patient synovial cells, aiming to provide new insights for clinical treatment strategies. MATERIALS AND METHODS: Gene expression datasets GSE1919, GSE82107, and GSE77298 were downloaded from the Gene Expression Omnibus (GEO) database to serve as the training groups, with GSE55235 being used as the validation dataset. The OA and RA data from the GSE1919 dataset were merged with the standardized data from GSE82107 and GSE77298, followed by batch effect removal to obtain the merged datasets of differential expressed genes (DEGs) for OA and RA. Intersection analysis was conducted on the DEGs between the two conditions to identify commonly upregulated and downregulated DEGs. Enrichment analysis was then performed on these common co-expressed DEGs, and a protein-protein interaction (PPI) network was constructed to identify hub genes. These hub genes were further analyzed using the GENEMANIA online platform and subjected to enrichment analysis. Subsequent validation analysis was conducted using the GSE55235 dataset. RESULTS: The analysis of differentially expressed genes in the synovial cells from patients with Osteoarthritis (OA) and Rheumatoid Arthritis (RA), compared to a control group (individuals without OA or RA), revealed significant changes in gene expression patterns. Specifically, the genes APOD, FASN, and SCD were observed to have lower expression levels in the synovial cells of both OA and RA patients, indicating downregulation within the pathological context of these diseases. In contrast, the SDC1 gene was found to be upregulated, displaying higher expression levels in the synovial cells of OA and RA patients compared to normal controls.Additionally, a noteworthy observation was the downregulation of the transcription factor PPARG in the synovial cells of patients with OA and RA. The decrease in expression levels of PPARG further validates the alteration in lipid metabolism and inflammatory processes associated with the pathogenesis of OA and RA. These findings underscore the significance of these genes and the transcription factor not only as biomarkers for differential diagnosis between OA and RA but also as potential targets for therapeutic interventions aimed at modulating their expression to counteract disease progression. CONCLUSION: The outcomes of this investigation reveal the existence of potentially shared molecular mechanisms within Osteoarthritis (OA) and Rheumatoid Arthritis (RA). The identification of APOD, FASN, SDC1, TNFSF11 as key target genes, along with their downstream transcription factor PPARG, highlights common potential factors implicated in both diseases. A deeper examination and exploration of these findings could pave the way for new candidate targets and directions in therapeutic research aimed at treating both OA and RA. This study underscores the significance of leveraging bioinformatics approaches to unravel complex disease mechanisms, offering a promising avenue for the development of more effective and targeted treatments.


Subject(s)
Arthritis, Rheumatoid , Gene Expression Profiling , Osteoarthritis , Protein Interaction Maps , Synovial Membrane , Arthritis, Rheumatoid/genetics , Arthritis, Rheumatoid/metabolism , Arthritis, Rheumatoid/pathology , Humans , Osteoarthritis/genetics , Osteoarthritis/metabolism , Osteoarthritis/pathology , Protein Interaction Maps/genetics , Synovial Membrane/metabolism , Synovial Membrane/pathology , Computational Biology/methods , Gene Regulatory Networks , Gene Expression Regulation , Databases, Genetic
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