In this work, we developed and validated a computer method capable of robustly detecting drill breakthrough events and show the potential of deep learning-based acoustic sensing for surgical error prevention. Bone drilling is an essential part of orthopedic surgery and has a high risk of injuring vital structures when over-drilling into adjacent soft tissue. We acquired a dataset consisting of structure-borne audio recordings of drill breakthrough sequences with custom piezo contact microphones in an experimental setup using six human cadaveric hip specimens. In the following step, we developed a deep learning-based method for the automated detection of drill breakthrough events in a fast and accurate fashion. We evaluated the proposed network regarding breakthrough detection sensitivity and latency. The best performing variant yields a sensitivity of $$93.64 \pm 2.42$$ 93.64 ± 2.42 % for drill breakthrough detection in a total execution time of 139.29$${\hbox { ms}}$$ ms . The validation and performance evaluation of our solution demonstrates promising results for surgical error prevention by automated acoustic-based drill breakthrough detection in a realistic experiment while being multiple times faster than a surgeon’s reaction time. Furthermore, our proposed method represents an important step for the translation of acoustic-based breakthrough detection towards surgical use.

Abstract. Diabetic foot infection is a frequent complication in long-standing diabetes mellitus. For antimicrobial therapy of this infection, both the optimal duration and the route of administration are often based more on expert opinion than on published evidence. We reviewed the scientific literature, specifically seeking prospective trials, and aimed at addressing two clinical issues: (1) shortening the currently recommended antibiotic duration and (2) using oral (rather than parenteral) therapy, especially after the patient has undergone debridement and revascularization. We also reviewed some older key articles that are critical to our understanding of the treatment of these infections, particularly with respect to diabetic foot osteomyelitis. Our conclusion is that the maximum duration of antibiotic therapy for osteomyelitis should be no more than to 4–6 weeks and might even be shorter in selected cases. In the future, in addition to conducting randomized trials and propagating national and international guidance, we should also explore innovative strategies, such as intraosseous antibiotic agents and bacteriophages.

Background The skin commensal Cutibacterium avidum has been recognized as an emerging pathogen for periprosthetic joint infections (PJI). One currently assumes that the early occurring PJIs are a consequence of skin commensals contaminating the peri-implant tissue during surgery. We addressed whether standard skin antisepsis with povidone-iodine/alcohol before total hip arthroplasty (THA) is effective to eliminate colonizing bacteria with focus on C. avidum. Methods In a single-center, prospective study, we screened all patients for skin colonizing C. avidum in the groin before THA. Only in the patients positive for C. avidum, we preoperatively repeated skin swabs after the first and third skin antisepsis and antibiotic prophylaxis. We also obtained dermis biopsies for microbiology and fluorescence in situ hybridization (FISH). Results Fifty-one out of 60 patients (85%) were colonized on the skin with various bacteria, in particular with C. avidum in 12 out of 60. Skin antisepsis eliminated C. avidum in eight of ten (20%) colonized patients undergoing THA. Deeper skin (dermis) biopsies were all culture negative, but FISH detected single positive ribosome-rich C. avidum in one case near sweat glands. Conclusion Standard skin antisepsis was not effective to completely eliminate colonizing C. avidum on the skin in the groin of patients undergoing THA. Colonizing with C. avidum might pose an increased risk for PJI when considering a THA. Novel more effective antisepsis strategies are needed. Trial registration No clinical trial