Introduction
The optimal duration of postoperative antibiotic treatment in orthopedic spinal infections is unknown. We report the 3rd interim analysis of the prospective randomized trial (SASI), emphasizing on material-related infections (ITT population between the study time points End-of-Treatment and Test-of-Cure).

Methods
A 1:1 randomization allocated adult spine patients with a residual infected implant into a short (6 weeks) or long (12 weeks) postoperative, systemic and targeted, antibiotic group. The major outcomes are "clinical failure" (reoperation for wound problems, new infections and/or uninfected mechanical reasons) and "microbiological recurrence" (infection relapse with the same pathogen(s) after therapy).

Results
In the database, we compare 81 infection episodes with 6 weeks’ therapy against 85 cases treated with 12-weeks of antibiotics. Overall, 11% in the short treatment arm revealed a “clinical failure” in the short and 14% in the long arm (9/83 vs. 12/85; Pearson-χ2-test; p=0.52). The corresponding numbers for “microbiological recurrence” were 2/83 (2%) vs. 1/85 (1%), p=0.55, respectively. The median number of surgical debridement was 1 in both arms (Wilcoxon-ranksum-test; p=0.28). Among 51 serious adverse events (SAE), there was a non-significant tendency in disfavor of the 12-weeks treatment arm (22/83 vs. 29/85 SAE, odds ratio 0.7; 95%CI 0.3-1,4; p=0.28). The formal non-inferiority for “micro-biologically-identical-recurrence” situated within a 5%-margin (2.1% percentage points [90%CI 2.2% to 4.6%]), that of “clinical failure” at a 10%-margin (5.2%, 90%CI 11% to 5%).

Conclusion
Equally at the 3rd interim analysis, a six-week antibiotic treatment remains noninferior to 12 weeks in residual implant-related spine infections after debridement. The SASI trial continue in terms of a long-term follow-ups targeting the scheduled per protocol analyses with a slightly higher sample size.

Introduction
Effective perioperative pain management and early mobilization after surgery are crucial to optimize recovery. The aim of this study was to determine the effect of the PEricapsular Nerve Group (PENG) block on postoperative (1) patient-reported pain, (2) total consumption of morphine and (3) length of stay (LOS) after primary anterior total hip arthroplasty (THA).

Methods
IRB-approved, single-center, multidisciplinary, prospective, randomized, double-blind controlled trial of patients undergoing primary anterior THA for osteoarthritis between June 2022 and April 2023. Preoperatively, patients were randomly assigned to either the study group (35 patients) or the control group (29 patients). Both groups underwent an ultrasound-guided injection of a 20 mL solution, the study group received 0.5% ropivacaine and the control group 0.9% NaCl. Each patient, anesthesiologist and surgeon were blinded to the solution injected. Four patients who required postoperative weight-bearing restrictions or whose documentation was incomplete were excluded from the study, resulting in a total of 60 patients (60 hips). The demographics of the two groups did not significantly differ. Overall the study population was 38% female, mean age was 64 ± 12 (34 to 84) years and mean body-mass-index was 27 ± 4 (19 to 38) kg/m2. We assessed (1) postoperative pain at 1h, 6h, 12h and 24h postoperatively via the Visual Analogue Scale (VAS) ranging from 0 (no pain) to 10 (maximal pain), (2) total morphine consumption in Morphine Equivalent Dose (MED) during the first 24 hours after surgery and (3) the LOS in days. Analysis were done using the Mann-Whitney test. The significance level was set at α < .05.

Results
VAS, at any of the four time points, did not differ significantly between the two groups (all P > .05). The lower 24-hour morphine consumption in the study group was not statistically significant (P = .110). The study group had a significantly shorter LOS than the control group (2.8 ± 1 [2 – 5] days vs 3.9 ± 1.5 [2 – 7] days, P = .003). No femoral motor nerve block or injection site infection were observed in either group.

Conclusion
In this prospective randomized controlled trial, the PENG block showed no significant difference in terms of postoperative reported VAS, a trend towards lower morphine consumption, though this did not reach statistical significance, and a statistically significant decrease in LOS after primary anterior THA when compared to a placebo.

Introduction: Reverse total shoulder arthroplasty (RTSA) offers satisfactory mid-term outcomes for a variety of pathologies but there is limited long-term follow up data. This study reports long-term clinical and radiographic outcomes, and predictive factors for outcome following RTSA implantation.

Methods: A prospective database of primary RTSAs performed at a single, tertiary referral center was analyzed at a minimum of ten years postoperative. Clinical outcomes included absolute and relative Constant-Murley score (CSa and CSr), Subjective Shoulder Value (SSV), range of motion, pain, complication rate and reintervention rate. Radiographic measurement included critical shoulder angle (CSA), lateralization and distalization shoulder angles (DSA, LSA), reverse shoulder angle (RSA), acromiohumeral distance (ACHD), center of rotation, glenoid height, analysis of notching, radiolucent lines, heterotopic ossification, and tuberosity resorption.

Results: 135 RTSAs (133 patients) were available for analysis at a mean follow-up of 10.9 ± 1.6 years. The mean age was 69 ± 8 years with 76 female shoulders (76 patients, 56%). Satisfactory results were achieved at long-term follow-up for CSa (64 ± 16), CSr (79% ± 18%), SSV (79% ± 21%), CS pain (14 ± 3) as well as flexion (117° ± 26°) and abduction (125° ± 35°). There was no deterioration in CSa, CSr and SSV, abduction and internal rotation over time. However, flexion and external rotation deteriorated while pain improved. Scapular notching, heterotopic ossification and radiolucent lines progressed during the study period. Analysis of predictive factors revealed younger age (p=0.040), notching grade II (p=0.048), tuberosity resorption (p=0.015), glenoid radiolucent lines (p=0.015) as predictive for impaired outcome. The complication rate was 28% with a reintervention rate of 11%.

Conclusion: RTSA can provide satisfactory long-term results without significant deterioration over time for most of the clinical parameters. Negative clinical outcome predictors were younger age, grade II notching, tuberosity resorption and radiolucent lines around the glenoid.

Introduction: Screw loosening following posterior spinal fusion surgery is a prevalent phenomenon, potentially leading to severe complications. A recent study conducted by our group has successfully demonstrated the feasibility of using patient-specific finite element (FE) modeling to predict screw loosening. However, the current modeling techniques demand significant manual effort and computational resources, limiting their practicality for routine clinical application. In response, we have innovated a framework designed to markedly diminish both the computational demands and manual intervention. This study evaluates the practicality of this automated framework and its effectiveness in predicting screws at risk of loosening during the medium-term postoperative period.
Methods: We retrospectively included 27 patients (96 pedicle screws) who underwent lumbar posterior spinal fusion surgery at our facility, consented to the use of their data for research, and had pre- and postoperative CT scans, with revision surgery within 27 months. Patient-specific FE models were generated by integrating bone segmentation and mechanical property estimates from preoperative CT scans with the configuration of surgical instrumentation (including screw types and placements) from postoperative CT scans. The external loading conditions were derived from the sagittal alignment and the body weight of each patient. Data from the surgical report of the revision procedure provided the basis for determining screw loosening. The framework's accuracy in identifying at-risk screws was gauged using the receiver operator characteristics (ROC) area under the curve (AUC).
Results: The automated modeling framework showcased robust performance across both initial and revision surgeries, regardless of the fused segments’ number or locations, demonstrating a high capability (Sensitivity: 56%, Specificity: 96%, ROC AUC: 0.740) in predicting the risk of screw loosening. Notably, beyond the initial steps of volumetric segmentation and data input, the process required no manual labor. Furthermore, simulations were completed in less than 5 minutes on an Intel Xeon (i9-7980) processor.
Conclusion: Our study introduces an important step towards utilizing automated biomechanical modeling to enhance outcomes in posterior spinal fusion surgeries.

Background
Multiple 2D MRI studies indicate that the size of the labrum adjusts in response to altered joint loading. In patients with hip dysplasia, it tends to increase as a compensatory mechanism for inadequate acetabular coverage.
Purpose
Using a deep learning based approach for automatic 3D segmentation of MRI we asked: What are the differences in labrum contribution to joint contact surface among different hip deformities and which radiographic parameters influence labral contribution to joint contact surface?
Study design Retrospective Cross-Sectional Study
Materials and Methods
This retrospective study was approved by the local ethics committee with waiver for informed consent. 98 patients (100 hips) with symptomatic hip deformities undergoing direct hip MR arthrography (3T) between January 2020-October 2021 were consecutively selected (mean age = 309; 64% female). Standard imaging protocol included multiplanar PD-w TSE images and an axial-oblique 3D T1 MP2RAGE sequence. According to acetabular morphology, hips were divided into subgroups: dysplasia (lateral center-edge [LCE] angle < 23°), normal coverage (LCE 23-33°), overcoverage (LCE 33-39°), severe overcoverage (LCE > 39°) and retroversion (retroversion index>10% and all 3 retroversion signs positive). A previously validated deep learning approach for automatic segmentation and software for calculation of joint contact surface were used. Labral contribution to joint contact surface was defined as: labrum surface area/(labrum surface area+cartilage surface area). One-way ANOVA with Tukey’s correction for multiple comparison and linear regression analysis was performed.
Results
Mean labral contribution of joint contact surface of dysplastic hips was 265 (17–33)% and higher compared to all other hip deformities (p ranging from 0.001 to 0.036).
Linear regression analysis identified LCE angle ( = -0.002, p < 0.001) and femoral torsion (=0.001, p=0.008) as independent predictors for labral contribution to joint contact surface with a goodness of fit of R2=0.35.
Conclusion
Labral contribution to joint contact surface differs among hip deformities and is influenced by lateral acetabular coverage and femoral torsion. This study paves way for a more in-depth understanding of the underlying pathomechanism and a reliable 3D analysis of the hip joint which can be indicative for surgical decision making in patients with hip deformities.

INTRODUCTION
Accurate pedicle screw placement in spine surgery is essential due to the proximity of vital neural structures, indicating the utilization of surgical navigation. State-of-the-art navigation systems still rely on pre- or intraoperative imaging with ionizing radiation, leading to increased radiation exposure and surgery time. To overcome this shortcoming, we propose a novel PSP planning method capable of calculating the navigation information, such as entry points and trajectories of the screws, directly from intraoperative camera data and without ionizing radiation. This study's objective was to compare our approach's accuracy against gold standard methods.

METHODS
Our approach employs an optical depth camera (ZED mini, StereoLabs) to provide a 3D reconstruction of visible surfaces, in our case, a 3D surface of the exposed dorsal lumbar spine. A first AI module processes this data to identify the individual vertebrae levels and predict their full 3D shape, including invisible parts, as 3D models. Based on the predicted 3D model, an AI-powered planning component identifies the entry points of the screw and trajectory. For evaluation, an ex-vivo dataset of 10 specimens was used, consisting of the camera data from two perspectives and ground truth CT data. The CT data was segmented to establish gold standard screw trajectories, which were then compared to our method for accuracy evaluation.

RESULTS
The PSP planning method showed an average entry point error of 1.98 mm and an average trajectory error of 8.78 degrees. Clinical outcome evaluation using the Gertzbein and Robbins classification method yielded 98.50% clinically acceptable grades (A and B) and 1.50% unacceptable grades (C).

CONCLUSION
The accuracy of our approach matches state-of-the-art CT-based PSP planning methods without requiring registration, thereby reducing radiation exposure. The method is planned to be integrated into a robotic platform to serve as an intraoperative navigation technology.