Purpose: The goal of this retrospective study was to perform a CT imaging assessment of thoracic pedicles to provide a representative understanding of pedicle morphology for pedicle-based fixation systems commonly used in orthopedics, trauma and neurosurgery. This study aimed to better understand the morphology of the spine and give spine surgeons a better understanding of thoracic spine anatomy. Methods: In this study, we retrospectively measured the thoracic spine pedicles of a total of 16 males and 16 females, totaling in 768 individual pedicles. For the measurements, we used standardized planes in computed tomography imaging with a maximum slice thickness of 1 mm. Results: In brief, we identified significant differences in various measurements of male and female pedicle morphology. The medial cortical wall of the pedicles was significantly thicker than the lateral wall, and, in both sexes, the thoracic vertebral body number four was the vertebra with the least amount of cortical bone in the pedicle. Conclusions: Surgeons performing operations involving pedicle screw placement should be aware of the sex-specific differences in thoracic spine pedicle morphology noted in this research.

Background: Periprosthetic joint infection (PJI) is one of the most serious complications following total joint arthroplasty. The debridement, antibiotics, irrigation, and implant retention (DAIR) procedure is commonly employed to treat acute, early-stage infections, but its success is highly variable, influenced by factors such as pathogen virulence and antibiotic susceptibility profiles. This study aimed to evaluate the impact of pathogens responsible for these infections on the outcome of DAIR. Methods: This retrospective, single-center study analyzed the microbiological profiles of 116 patients (66 hips and 50 knees) treated for acute periprosthetic joint infections (PJIs) with DAIR between 2018 and 2022. Acute PJI was defined as a duration of symptom less than three weeks, according to the criteria established by the Tsukayama and Izakovicova classification. Preoperative joint aspirations, intraoperatively collected tissue samples, and sonication of the exchanged mobile parts were analyzed for each case. We differentiated between monomicrobial PJI, polymicrobial PJI (defined as the identification of more than one microorganism from preoperative joint fluid aspiration or intraoperative samples), and difficult-to-treat (DTT) pathogens. Results: In this cohort, the following pathogen profiles were identified: culture-negative cases accounted for 11.1% of infections, while 64.2% were attributed to Gram-positive bacteria, 19.8% to Gram-negative bacteria, and 4.9% to fungal pathogens. Among the identified microorganisms, coagulase-negative staphylococci (CNS) were the most frequently detected, exhibiting a notable oxacillin resistance rate of 52.9% and rifampicin resistance rate of 28.7%. Additionally, no significant difference in revision-free implant survival was found between patients with DTT pathogens and/or polymicrobial PJI and those without such infections. Conclusions: This study highlights that pathogens in prosthetic joint infections (PJIs) do not solely determine outcomes, as patient-specific factors (comorbidities, implant type) may also play a key role. Regional variations in pathogens and antibiotic resistance patterns should guide empirical therapy. For instance, this study found a high reliance on vancomycin due to high oxacillin resistance in CNS, the most frequent causative pathogen.

Background: Periprosthetic joint infections (PJI) represent a serious complication following joint arthroplasty and require, in addition to surgical intervention, a targeted antibiotic therapy. The aim of this study was to compare microbiological recommendations for the antibiotic treatment of fictitious PJI patients generated by an artificial intelligence (AI) system with those of an interdisciplinary team (IT) consisting of microbiologists and orthopedic surgeons. The differences between the recommendations suggested by AI and the IT were analyzed with regard to the suggested agents and duration of antibiotic therapy. Methods: Based on meta-analyses, a cohort of 100 fictitious patients with acute early- and acute late-onset PJI was created, reflecting the typical demographic data, comorbidities and pathogen profiles of such a population. This information was input into the AI system ChatGPT (OpenAI, GPT-5 “Thinking mode” accessed via ChatGPT Plus, San Francisco, CA, USA) to generate corresponding recommendations. The objective was to use these profiles to obtain recommendations for definitive antibiotic therapy, including daily dosage, intravenous and oral treatment durations. Simultaneously, the same fictitious patient data were reviewed by the IT to produce their own recommendations. Results: The results revealed both concordances and discrepancies in the selection of antibiotics. Notably, in cases involving multidrug-resistant organisms and more complex clinical scenarios, the AI-generated recommendations were incongruent with those of the IT, with estimated percentage agreement ranging from 0–33%. In straightforward clinical scenarios with monomicrobial infections, AI reached an estimated percentage agreement of up to 57% (95%-CI [0.47–0.67]). Furthermore, AI consistently recommended 12 weeks of therapy duration vs. six weeks usually recommended by the IT. Conclusions: The study provides important insights into the potential and limitations of AI-assisted decision-making models in orthopedic infection treatments. Consultation of AI is universally accessible at all times of day, which may offer a significant advantage in the future for the treatment of PJI. This kind of application will be of particular interest for institutions without in-house microbiology services. However, from our perspective, the current level of incongruence between the AI-generated recommendations and those of an experienced interdisciplinary team remains too high for this approach to be clinically implemented at this time. Furthermore, AI lacks transparency regarding the sources it uses to inform about its decision-making and therapeutic recommendations, currently carries no legal weight and clinical implementation is severely hindered by restrictive privacy laws regarding health care data.

Purpose: The full spectrum of diseases caused by S. infantarius remains poorly understood, particularly its role in musculoskeletal infections. Methods: A retrospective study was conducted from January 2008 to May 2024. Patients with bacterial infections and detection of S. infantarius in at least one tissue sample, fluid sample, or blood cultures were included. Follow-up controls in patients with musculoskeletal infection were performed. Results: S. infantarius could be identified in at least one sample (blood cultures, wound fluid, wound swab, bile, tissue or urine sample) of 72 patients. 33 were considered clinically relevant with symptomatic infections (63.4 ± 21.1 years; positive samples: 1.39 ± 0.86; total number of samples: 2.7 ± 1.76). Non-muskuloskeletal infections (n = 29; 61.1 ± 21.5 years; positive samples: 1.28 ± 0.59) included a variety of different infections (sepsis (n = 11), abdominal/gastrointestinal/urogenital infections (n = 16), soft tissue infections (n = 2)). Four patients with musculoskeletal S. infantarius infection (positive samples: 2.25 ± 1.89; diagnosis: acute PJI, spondylodiscitis, chronic PJI and postoperative spinal wound infection) required surgical and/or antimicrobial treatment. Follow-up after musculoskeletal infection varied between 10 and 60 months. Antibiotic susceptibility testing displayed a sensitivity to Penicillin in all isolates. No patient had a recurrent positive sample/infection with S. infantarius. Conclusions: This study describes musculoskeletal infections caused by S. infantarius, highlighting its possible relevance as pathogen in orthopedic infections. The findings underscore the importance of recognizing and appropriately treating S. infantarius. In case of penicillin allergy, clindamycin shows to be an effective alternative treatment.

Background: Patients who have fallen from great height with suicidal intent present unique challenges, including delayed medical attention, injury patterns that are often difficult to detect, severe hypothermia, and difficulties obtaining informed consent due to the patient’s mental state. Further delays to treatment can be caused by legal and logistical hurdles, such as coordinating with legal guardians or family members. These co-factors contribute to the high reported overall complication rates in these cases, which can reach up to 50%. This study aims to analyse injury patterns, inflammatory responses and complication rates in people who have jumped to their death, compared to those who have fallen unintentionally. It also aims to investigate the correlation between jump height and injury severity. Methods: This retrospective monocentric study analysed patient data such as age, gender, injuries, treatments and duration of hospitalisation. A total of 68 suicidal falls were included during the period from January 2014 to January 2024. Subsequently, 68 unintentional falls from a height of more than three meters were included from the same period as a control group, which was analysed alongside the suicidal falls. We analysed injuries sustained in clinical and radiological findings, as well as the inflammatory response and coagulation status of patients in blood gas analysis (BGA) and laboratory analysis of blood drawn in the first hours/days after trauma (C-reactive protein, white blood cell count, lactate, pH value, base excess, procalcitonin and prothrombin time). During hospitalisation, we analysed mortality rates, complication rates, transfusions performed, and intensive care unit/hospital stay for each group. Results: The group of suicidal jumps had an equal number of male and female patients (50% and 50%, respectively). In contrast, a predominance of male patients was observed in the subgroup of unintentional falls (76.5%, p = 0.002). Overall, suicidal falls resulted in a significantly more severe injury pattern. The average mean reported fall height was 9.61 m (± 6.42 m) in the suicidal group compared to 6.14 m (± 4.08 m) in the unintentional group. The injury severity score (ISS) was significantly higher in the suicidal group with 32.04 (± 23.43) compared to 17.37 (± 14.01) in the unintentional group ( p < 0.001). In accordance with this, higher complication rates (wound healing disorders and total number of complications) were observed in the suicidal group (52.5% vs. 29.9%, p = 0.011). A greater number of total surgeries were also required in this group (3.21 ± 4.27 vs. 1.69 ± 2.81, p = 0.016). Patients in the suicidal group had significantly worse measurable coagulation status (prothrombin time) upon admission (74.95 (± 21.89) vs. 89.09 (± 21.66), p < 0.001), resulting in a significantly higher requirement for transfusions of erythrocyte concentrates (4.07 (± 9.39) vs. 0.97 (± 2.29), p < 0.001). Interestingly, comparable trends in ISS, injury patterns, complication rates and coagulation status were observed in a subgroup analysis, even after adjusting the cohorts for fall height (8.41 ± 4.38 m vs. 8.52 ± 3.80 m; p = 0.495). Conclusion: Patients who had attempted suicide by jumping suffered more severe injuries and had a significantly higher ISS than those in the group who had fallen unintentionally. This remained true even when fall height was considered. Suicidal patients exhibited a higher complication rate ( p = 0.011), increased overall transfusion requirements, impaired coagulation status upon admission and a greater number of operations (including repeat operations) compared to the unintentional fall cohort. Our data suggest that these patients require more resources and are more challenging to treat. We therefore recommend that they be treated in level 1 trauma centres with interdisciplinary intensive care capacities.