The increasing frequency of total hip (THA) and knee arthroplasties (TKA) is marred by the rise in periprosthetic joint infections (PJIs) and surgical site infections (SSIs), with PJIs incurring costs over $1.62 billion as of 2020 and individual case management averaging $90,000. SSIs additionally burden the U.S. healthcare economy with billions in expenses annually. PJI prevalence in primary THA and TKA ranges from 0.5% to 2.4%, spiking to 20% in revisions and representing 25% of TKA revision causes. Projections estimate up to 270,000 annual PJI cases by 2030. Often caused by gram-positive bacteria, particularly methicillin-resistant staphylococci, these infections demand preventive measures. This review dissects PJI prevention across preoperative, intraoperative, and perioperative phases, aligning with evidence-based CDC and WHO guidelines. Preoperative measures include managing diabetes, obesity, tobacco use, Staphylococcus aureus screening and nasal decolonization, nutritional optimization, and management of inflammatory arthropathies. Intraoperatively, antibiotic prophylaxis, skin preparation, operative room environmental controls, surgical technique precision, and irrigation options are scrutinized. Perioperative concerns focus on anticoagulation, blood management, and infection risk mitigation. Integrating these strategies promotes a patient-centric care model, aiming to reduce PJI incidence, improve patient outcomes, and increase care cost-effectiveness in joint arthroplasty.

Purpose: The success of medial patellofemoral ligament (MPFL) reconstruction is closely linked to the precise positioning of the femoral tunnel. Intraoperative fluoroscopy is commonly utilized to identify the MPFL footprint. This study aimed to ascertain the most accurate fluoroscopic method among the five previously described methods used to determine the MPFL femoral footprint. Materials and methods: Using 44 well-preserved dry femur bones, the MPFL femoral insertion site was demarcated using anatomical bony landmarks, namely the center of the saddle sulcus between the medial epicondyle, adductor tubercle and gastrocnemius tubercle. Fluoroscopic true lateral knee images were acquired and measurements taken, referencing established methods by Schottle et al., Redfern et al., Wijdicks et al., Barnett et al., and Kaipel et al. The distance between anatomic and fluoroscopic MPFL footprints was then measured on digital fluoroscopic images. The accuracy of the locations was compared using a margin of error of 5 and 7 mm. Results: The Schottle method consistently emerged superior, showcasing the smallest mean distance (3.2 ± 1.2 mm) between the anatomic and radiographic MPFL footprints and a high in-point detection rate of 90.9% under 5 mm criteria. While the Redfern method displayed perfect accuracy (100%) within the 7 mm criteria, the Schottle method also performed 97.7% accuracy. Conclusions: For intraoperative identification of the MPFL footprint using fluoroscopy, the Schottle method is the most consistent and accurate among the assessed methods. Thus, its accuracy in detecting the MPFL footprint makes it recommended for MPFLR to ensure optimal outcomes. Level of evidence: Level IV, cadaveric study.

Background: This prospective study aimed to test the reliability and validity of hallux valgus angle (HVA) measurement on smartphone digital photographs compared with the standard radiographic evaluation.Methods: Twenty Seven female patients (45 feet) with forefoot deformity were evaluated with weight‐bearing anteroposterior foot radiographs and smartphone photographs. Radiographic hallux valgus angle (rHVA) was measured on digital radiographs. Two different photographic HVA measurement methods were used. In the first, the longitudinal axes of the first metatarsal and proximal phalanx were determined, and the angle between these axes was measured (pHVA), similar to the radiographic method. In the other method, the angle of the margo medialis pedis was measured on the photograph (pMMP). Two independent observers performed all measurements twice on two different occasions. Reliability analysis was performed using the interclass correlation coefficient. Agreement between the measurements was tested using Bland‐Altman analysis.Results: The repeated rHVA, pHVA and pMMP measurements showed excellent intra and inter‐observer reliability, with ICC values above 0.900. The mean rHVA, pHVA, and pMMP were statistically similar (p:0.929, 27.03°±8.7°, 27.11°±8.8° and 26.5°±9.0° respectively). The mean difference between the rHVA and pHVA was − 0.07°±5.1° (range, ‐‐9.67 to 9.56°), and the mean difference between the rHVA and pMMP was 0.53°±4.4° (range, ‐9.76° to 8.22°). There was a strong positive correlation between both photographic methods and radiographic measurements (rho = 0.809, p = 0.001 and rho = 0.872, p = 0.001). In the Bland Altman plot, the upper and lower LOAs (95%CI) ranged from − 10.11° to 9.93° for rHVA and pHVA, and from − 8.26° to 9.33° for rHVA and pMMP. Linear regression analysis showed a proportional bias for pHVA but not for the pMMP (p:0.010 versus p:0.633, respectively). The range of the mean difference (prediction interval) between the pMMP and rHVA was 17.59° and 20° for pHVA and rHVA. Simple linear regression showed that the rHVA was predicted by the following equation: rHVA = 4.73 + 0.84 × pMMP (r2 = 0.761, p < 0.001).Conclusions: Although measuring HVA through smartphone photographs is reliable, it is not a valid prediction method.Level of evidence: Level II, diagnostic assessment.