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Bone & Joint Research
Vol. 13, Issue 2 | Pages 66 - 82
5 Feb 2024
Zhao D Zeng L Liang G Luo M Pan J Dou Y Lin F Huang H Yang W Liu J

Aims

This study aimed to explore the biological and clinical importance of dysregulated key genes in osteoarthritis (OA) patients at the cartilage level to find potential biomarkers and targets for diagnosing and treating OA.

Methods

Six sets of gene expression profiles were obtained from the Gene Expression Omnibus database. Differential expression analysis, weighted gene coexpression network analysis (WGCNA), and multiple machine-learning algorithms were used to screen crucial genes in osteoarthritic cartilage, and genome enrichment and functional annotation analyses were used to decipher the related categories of gene function. Single-sample gene set enrichment analysis was performed to analyze immune cell infiltration. Correlation analysis was used to explore the relationship among the hub genes and immune cells, as well as markers related to articular cartilage degradation and bone mineralization.


The Bone & Joint Journal
Vol. 103-B, Issue 8 | Pages 1358 - 1366
2 Aug 2021
Wei C Quan T Wang KY Gu A Fassihi SC Kahlenberg CA Malahias M Liu J Thakkar S Gonzalez Della Valle A Sculco PK

Aims

This study used an artificial neural network (ANN) model to determine the most important pre- and perioperative variables to predict same-day discharge in patients undergoing total knee arthroplasty (TKA).

Methods

Data for this study were collected from the National Surgery Quality Improvement Program (NSQIP) database from the year 2018. Patients who received a primary, elective, unilateral TKA with a diagnosis of primary osteoarthritis were included. Demographic, preoperative, and intraoperative variables were analyzed. The ANN model was compared to a logistic regression model, which is a conventional machine-learning algorithm. Variables collected from 28,742 patients were analyzed based on their contribution to hospital length of stay.


The Bone & Joint Journal
Vol. 101-B, Issue 3 | Pages 340 - 347
1 Mar 2019
Elkassabany NM Cai LF Badiola I Kase B Liu J Hughes C Israelite CL Nelson CL

Aims

Adductor canal block (ACB) has emerged as an alternative to femoral nerve block (FNB) for analgesia after total knee arthroplasty (TKA). The optimal duration of maintenance of the ACB is still questionable. The purpose of this study was to compare the analgesic benefits and physiotherapy (PT) outcomes of single-shot ACB to two different regimens of infusion of the continuous ACB, 24-hour and 48-hour infusion.

Patients and Methods

This was a prospective, randomized, unblinded study. A total of 159 American Society of Anesthesiologists (ASA) physical status I to III patients scheduled for primary TKA were randomized to one of three study groups. Three patients did not complete the study, leaving 156 patients for final analysis. Group A (n = 53) was the single-shot group (16 female patients and 37 male patients with a mean age of 63.9 years (sd 9.6)), group B (n = 51) was the 24-hour infusion group (22 female patients and 29 male patients with a mean age of 66.5 years (sd 8.5)), and group C (n = 52) was the 48-hour infusion group (18 female patients and 34 male patients with a mean age of 62.2 years (sd 8.7)). Pain scores, opioid requirements, PT test results, and patient-reported outcome instruments were compared between the three groups.