Endoscopic vacuum therapy for in- and outpatient treatment of colorectal defects

Background. Evidence for endoscopic vacuum therapy (EVT) for colorectal defects is still based on small patient series from various institutions, employing different treatment algorithms and methods. As EVT was invented at our institution 20 years ago, the aim was to report the efficacy and safety of EVT for colorectal defects as well as to analyze factors associated with efficacy, therapy duration, and outpatient treatment. Methods. Cohort study with analysis of prospectively collected data of patients receiving EVT for colorectal defects at a tertiary referral center in Germany (n=281). Results. The majority of patients had malignant disease (83%) and an American Society of Anesthesiologists classification of III/IV (81%). Most frequent indications for EVT were anastomotic leakage after sigmoid or rectal resection (67%) followed by rectal stump leakage (20%). EVT was successful in 256 out of 281 patients (91%). EVT following multi-visceral resection (P = 0.037) and recent surgical revision after primary surgery (P = 0.009) were risk factors for EVT failure. EVT-associated adverse events occurred in 27 patients (10%). Median treatment duration was 25 days. Previous chemo-radiation (P = 0.006) was associated with a significant longer duration of EVT. Outpatient treatment was conducted in 49% of patients with a median hospital stay reduction of 15 days and 98% treatment success. Younger patient age (P = 0.044) was associated with the possibility of outpatient treatment. Restoration of intestinal continuity was achieved in 60% of patients where technically possible with a 12-month rate of 52%. Conclusions. In patients with colorectal defects, EVT appears to be a safe and effective, minimally invasive option for in- and outpatient treatment

Future-ai:International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

FUTURE-AI: International consensus guideline for trustworthy and deployable artificial intelligence in healthcare

Despite major advances in artificial intelligence (AI) for medicine and healthcare, the deployment and adoption of AI technologies remain limited in real-world clinical practice. In recent years, concerns have been raised about the technical, clinical, ethical and legal risks associated with medical AI. To increase real world adoption, it is essential that medical AI tools are trusted and accepted by patients, clinicians, health organisations and authorities. This work describes the FUTURE-AI guideline as the first international consensus framework for guiding the development and deployment of trustworthy AI tools in healthcare. The FUTURE-AI consortium was founded in 2021 and currently comprises 118 inter-disciplinary experts from 51 countries representing all continents, including AI scientists, clinicians, ethicists, and social scientists. Over a two-year period, the consortium defined guiding principles and best practices for trustworthy AI through an iterative process comprising an in-depth literature review, a modified Delphi survey, and online consensus meetings. The FUTURE-AI framework was established based on 6 guiding principles for trustworthy AI in healthcare, i.e. Fairness, Universality, Traceability, Usability, Robustness and Explainability. Through consensus, a set of 28 best practices were defined, addressing technical, clinical, legal and socio-ethical dimensions. The recommendations cover the entire lifecycle of medical AI, from design, development and validation to regulation, deployment, and monitoring. FUTURE-AI is a risk-informed, assumption-free guideline which provides a structured approach for constructing medical AI tools that will be trusted, deployed and adopted in real-world practice. Researchers are encouraged to take the recommendations into account in proof-of-concept stages to facilitate future translation towards clinical practice of medical AI

In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR

A plethora of databases exist online that can assist in in silico chemical or drug safety assessment. However, a systematic review and grouping of databases, based on purpose and information content, consolidated in a single source has been lacking. To resolve this issue, this review provides a comprehensive listing of the key in silico data resources relevant to: chemical identity and properties, drug action, toxicology (including nano-material toxicity), exposure, omics, pathways, Absorption, Distribution, Metabolism and Elimination (ADME) properties, clinical trials, pharmacovigilance, patents-related databases, biological (genes, enzymes, proteins, other macromolecules etc.) databases, protein-protein interactions (PPIs), environmental exposure related, and finally databases relating to animal alternatives in support of 3Rs policies. More than nine hundred databases were identified and reviewed against criteria relating to accessibility, data coverage, interoperability or application programming interface (API), appropriate identifiers, types of in vitro-in vivo -clinical data recorded and suitability for modelling, read-across or similarity searching. This review also specifically addresses the need for solutions for mapping and integration of databases into a common platform for better translatability of preclinical data to clinical data

Endoscopic vacuum therapy for the treatment of colorectal leaks - a systematic review and meta-analysis

BACKGROUND During the last two decades, vacuum-assisted wound therapy has been successfully transferred to an endoscopic treatment approach of various upper and lower gastrointestinal leaks called endoscopic vacuum therapy (EVT). As mostly small case series are published in this field, the aim of our systematic review and meta-analysis was to evaluate the efficacy and safety of EVT in the treatment of colorectal leaks. METHODS A systematic search of MEDLINE/PubMed and Cochrane databases was performed using search terms related to EVT and colorectal defects (anastomotic leakage, rectal stump insufficiency) according to the PRISMA guidelines. Randomized controlled trials (RCTs), observational studies, and case series published by December 2020 were eligible for inclusion. A meta-analysis was conducted on the success of EVT, stoma reversal rate after EVT as well as procedure-related complications. Statistical interferences were based on pooled estimates from random effects models using DerSimonian-Laird estimator. RESULTS Only data from observational studies and case series were available. Twenty-four studies reporting on 690 patients with colorectal defects undergoing EVT were included. The mean rate of success was 81.4% (95% CI: 74.0%-87.1%). The proportion of diverted patients was 76.4% (95% CI: 64.9%-85.0%). The mean rate of ostomy reversal across the studies was 66.7% (95% CI: 58.0%-74.4%). Sixty-four patients were reported with EVT-associated complications, the weighted mean complication rate across the studies was 12.1% (95% CI: 9.7%-15.2%). CONCLUSIONS Current medical evidence on EVT in patients with colorectal leaks lacks high quality data from RCTs. Based on the data available, EVT can be seen as a feasible treatment option with manageable risks for selected patients with colorectal leaks

Erwartete Effekte der neuen Weiterbildungsordnung in der Allgemein- und Viszeralchirurgie

Introduction The new competency-based continuing education regulations for surgical training (WBO) came into effect in Bavaria in August 2022. Methods From May to July 2022, we conducted an anonymized online survey among Bavarian general and visceral surgeons and surgical residents (aiW). The aim was to survey expectations of the effects of the new WBO. Results The response rate was 35%. In total data could be collected from 80 persons, 36 aiW (45%), 30 specialists and senior physicians (37.5%) and 14 chief physicians (17.5%). The majority of respondents worked at a university hospital (38.8%) or a regular provider (35%). A strengthening of the competence to act through implementation of the new WBO is seen by 41.3% and 55.7% see independent operating under partial supervision by the instructor as a goal. Of the respondents 50% see the required case numbers as not achievable and 55.1% deny reaching them in the expected period of 6 years. About 60% do not expect to be able to train the same number of aiWs in the same amount of time. Almost 75% of the respondents state that from their point of view, a good continuing education with the achievement of a solid competence to act would not work without overtime hours. About 44% of the respondents expect that a full surgical training would continue to be possible at their institution. Conclusion Both among the instructors and among the trainees there is a tendency to fear that realistic training, in particular the achievement of the guideline figures, will no longer be possible in the usual further training time. This necessitates the consistent implementation of structured continuing education with a high degree of transparency in training

Tumour-Derived Cell Lines and Their Potential for Therapy Prediction in Patients with Metastatic Colorectal Cancer

The prognosis of metastatic colorectal cancer (CRC) remains poor. Patients and physicians are in need of individual therapies and precise response predictions. We investigated the predictive capacity of primary tumour material for treatment response of metastases. Mutational landscapes of primary tumours and corresponding metastases of 10 CRC patients were compared. Cell line characteristics and chemosensitivity were investigated pairwise for primary and metastatic tumours of four patients. PDX models of one patient were treated in vivo for proof of concept. Driver mutations did not differ between primaries and metastases, while the latter accumulated additional mutations. In vitro chemosensitivity testing revealed no differences for responses to 5-FU and oxaliplatin between primary and metastatic cell lines. However, irinotecan response differed significantly: the majority of metastases-derived cell lines was less sensitive to irinotecan than their matching primary counterpart. Therapy recommendations based on these findings were compared to clinical treatment response and mostly in line with the predicted outcome. Therefore, primary tumour cell models seem to be a good tool for drug response testing and conclusion drawing for later metastases. With further data from tumour-derived cell models, such predictions could improve clinical treatment decisions, both recommending likely effective therapeutic options while excluding ineffective treatments