This study compares postoperative pain scores and functional outcomes between liposomal bupivacaine peri-articular injection (LB-PAI) vs a single-shot adductor canal block (ACB) using bupivacaine HCl in patients undergoing primary total knee arthroplasty (TKA). This is a randomized controlled trial of 56 patients who were treated with TKA for arthritis. Patients were randomized to receive an intraoperative LB-PAI (n= 27) or preoperative ACB using bupivacaine HCl (n= 29). Both groups were otherwise given our institutional standard multimodal pain protocol. Data on Visual Analog Scale (VAS) pain scores, Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) scores, knee range of motion, postoperative ambulation distance, hospital length of stay, and opioid use were collected. The total cost of each intervention was compared at the conclusion of the study. Age, gender, or body mass index was similar between groups. Compared to the ACB group, the LB-PAI group trended to lower average VAS pain scores on postoperative days 0, 1, and 2 (average difference [95% confidence interval]=-0.5 [-0.7, 1.7],-1.0 [-0.1, 2.0],-0.2 [-0.8, 1.3]), and identical average VAS pain scores on postoperative days 4 and 7. These differences and all postoperative outcome measures were not statistically significant at any time point. A single 266-milligram vial of liposomal bupivacaine costs $351, and a single-shot ACB costs $893 at our institution. This randomized controlled trial shows similar postoperative pain control, functional outcomes, and opioid use between LB-PAI and a single-shot ACB in patients undergoing primary TKA. However, the single-shot ACB costs $542 more than the LB-PAI at our institution. This randomized controlled trial shows similar postoperative pain control, functional outcomes, and opioid use between LB-PAI and a single-shot ACB in patients undergoing primary TKA. However, the single-shot ACB costs $542 more than the LB-PAI at our institution. The aim was to test the hypothesis that during transfemoral implantation of a conical revision stem, the fixation of the stem at the distal tip leads to a low rate of periprosthetic fractures. Two hundred eighty-two stem revisions by a transfemoral approach in cases of Paprosky Type II and IIIA-defects (with a sufficient isthmus) were carried out and analyzed during and radiographically after the surgery for unintentional periprosthetic fractures below the osteotomy. In all cases, fixation was always achieved at the tip of the distal component in the isthmus of the femur. No periprosthetic fractures were observed. When the isthmus of the femur is intact, a transfemoral implantation of a tapered revision stem at the distal end reduces the risk of periprosthetic fractures by preventing bypassing the isthmus with the stem. Knowing the difference between the nominal diameter and the diameter at the distal start of the conical zone can help to create this fixation technique resulting in short revision stems. When the isthmus of the femur is intact, a transfemoral implantation of a tapered revision stem at the distal end reduces the risk of periprosthetic fractures by preventing bypassing the isthmus with the stem. Knowing the difference between the nominal diameter and the diameter at the distal start of the conical zone can help to create this fixation technique resulting in short revision stems. Predictive modeling promises to improve our understanding of what variables influence patient satisfaction after total knee arthroplasty (TKA). The purpose of this article was to systematically review the relevant literature using predictive models of clinical outcomes after TKA. The aim was to identify the predictor strategies used for systematic data collection with the highest likelihood of success in predicting clinical outcomes. A Preferred Reporting Items for Systematic Reviews and Meta-Analyses protocol systematic review was conducted using 3 databases (MEDLINE, EMBASE, and PubMed) to identify all clinical studies that had used predictive models or that assessed predictive features for outcomes after TKA between 1996 and 2020. The ROBINS-I tool was used to evaluate the quality of the studies and the risk of bias. A total of 75 studies were identified of which 48 met our inclusion criteria. Preoperative predictive factors strongly associated with postoperative clinical outcomes were knee pain, knee-specific Patient-Reported Outcome Measure (PROM) scores, and mental health scores. https://www.selleckchem.com/products/af353.html Demographic characteristics, pre-existing comorbidities, and knee alignment had an inconsistent association with outcomes. The outcome measures that correlated best with the predictive models were improvement of PROM scores, pain scores, and patient satisfaction. Several algorithms, based on PROM improvement, patient satisfaction, or pain after TKA, have been developed to improve decision-making regarding both indications for surgery and surgical strategy. Functional features such as preoperative pain and PROM scores were highly predictive for clinical outcomes after TKA. Some variables such as demographics data or knee alignment were less strongly correlated with TKA outcomes. Systematic review - Level III. Systematic review - Level III.Anthropogenic litter density and composition data were obtained by conducting aerial surveys on 44 beaches along the Saudi Arabian Coast of the Red Sea [1]. The aerial surveys were completed with commercial drones of the DJI Phantom suite flown at a 10 m altitude. The stills have a resolution of less than 0.5 cm pixels-1, hence, litter objects of few centimetres like bottle caps are easily detectable in the drone images. We here provide a subsample of the drone images acquired. To spare the time needed to visually count the litter objects in the thousands of drone images acquired, these were automatically screened using an object detection algorithm, specifically a Faster R-CNN, able to perform a binary classification in litter and non-litter and to categorize the objects in classes. The multi-class classification, however, is a challenging problem and, hence, it was conducted only on the 15 beaches that showed the highest performance after the binary classification. The performance of the algorithm was calculated by visually screening a subsample of images and it was used to correct the output of the Faster R-CNN.