Chirurgie (Heidelberg, Germany)最新文献

Overweight and obesity are among the leading causes of degenerative musculoskeletal disorders. As a consequence, the proportion of obese patients undergoing knee or hip joint arthroplasty or spinal surgery has significantly increased. In these interventions obese patients are at a higher risk for perioperative complications, including thromboembolic events, wound healing disorders, periprosthetic infections, implant failure and the need for revision surgery. A body mass index (BMI) >40 kg/m² is considered a contraindication for many elective orthopedic procedures. Bariatric surgery can lead to rapid and sustained weight loss; however, the metabolic changes induced by these procedures can affect the absorption and bioavailability of nutrients and medications. At the same time, the altered metabolic state following bariatric surgery is associated with an increased risk of perioperative complications during orthopedic interventions. Furthermore, the efficacy of medications, such as analgesics, antimicrobial agents and oral anticoagulants can be significantly altered by metabolic and bariatric procedures. This article provides an overview of the specific considerations for orthopedic procedures following metabolic and bariatric surgery.

Background: Artificial intelligence (AI) is increasingly being used in surgery; however, the validation of such systems is often methodologically insufficient.

Objective: Which validation issues arise in surgical AI and what requirements can be derived for clinically meaningful validation strategies?

Methods: Metric-related pitfalls reported in the literature were analyzed, combined with insights from the interdisciplinary consensus process "metrics reloaded" and its ongoing extension to surgical applications.

Results: Recurring weaknesses are observed at the levels of data, metrics and reporting. The lack of consideration of temporal structures and aggregation in video data is particularly critical.

Discussion: A structured, clinically grounded validation is essential for the safe use of surgical AI. The metrics reloaded procedure is currently being adapted to address surgery-specific requirements.

The treatment of giant hemangiomas of the caudate lobe remains a major challenge due to the complex anatomy and the proximity of the caudate lobe to important vascular structures. Recent progress in the field of artificial intelligence (AI) has introduced new paradigms for the preoperative planning, intraoperative navigation and postoperative care. This overview demonstrates how AI-guided technologies can improve the surgical precision, minimize complications and ultimately improve the results for patients who undergo a resection of giant hemangiomas in the caudate lobe.

The biliodigestive anastomosis represents a core element of hepatopancreatobiliary surgery. It requires a precise surgical technique and detailed knowledge of biliary anatomy and vascular supply. A tension-free suture, sufficient perfusion of the anastomosed structures and an exact mucosa-to-mucosa adaptation using delicate absorbable suture material are decisive for a successful construction. Hepaticojejunostomy has become established as the gold standard for a biliodigestive anastomosis. Currently available studies show no significant differences in morbidity between open and minimally invasive techniques, whereby the latter is becoming increasingly more important. There was also no difference in the clinical results with respect to the suture technique (interrupted vs. continuous suture); however, the continuous suture technique is associated with a shortening of the placement time and a reduction in costs. Complications after biliodigestive anastomosis, such as insufficiency and stenosis, are clinically relevant and substantially influence the morbidity and mortality; however, many of these complications can nowadays be effectively treated by interventional procedures.

Background: Despite intensive research the clinical implementation of artificial intelligence (AI) in surgery remains limited. In addition to infrastructural and regulatory barriers, this is due to the isolated processing of individual data sources (e.g. video), although the true potential of surgical AI lies in the integration of multimodal data.

Objective: What added value does AI-driven analysis of multimodal data offer in surgery, and how can it realistically be integrated into clinical practice?

Method: This review is based on first results on multimodal data acquisition and processing at University Hospital Cologne as well as a targeted literature search.

Results: The integration of different data sources shows great potential; however, lack of infrastructure and regulation hinders the implementation.

Discussion: In addition to technological development, clear legal frameworks are required to enable the clinical integration of innovative AI systems.

Background: Bureaucratic tasks in everyday surgical clinical practice are time-consuming. Due to the increasing shortage of skilled workers and the growing need for care, it is necessary to relieve surgeons of administrative tasks.

Objective: The analysis aims to make the nature and extent of administrative tasks transparent in order to derive options for action.

Material and methods: Data were collected as a survey using a digital questionnaire with 29 questions.

Results: 1632 BDC members participated in the survey with a response rate of 19%. The survey results illustrate that surgeons manage a particularly high workload and 82% of full-time employees reported working an average of 49-79 h per week. The proportion of bureaucratic tasks proved to be high, with 3-4 h per day according to 67% of full-time employees. While 94% of full-time employees stated that around 1-3 h of bureaucratic work should be delegated daily but only 42% are authorized to delegate bureaucratic tasks. Redundant documentation arises primarily from the need for duplicate documentation of identical data, audits by the medical service as well as quality audits. 88% of respondents rated the benefit of information technology in reducing the documentation burden as relatively low or minimal.

Discussion: The results fit into the context of other recent surveys on the burden of bureaucracy.

Conclusion: To improve the situation, legislators, partners in joint self-government and hospital management have a duty to reduce documentation requirements, optimize processes and improve opportunities for electronic data exchange.