Reducing scope 3 carbon emissions in gastrointestinal endoscopy: results of the prospective study of the 'Green Endoscopy Project Würzburg'.

OBJECTIVE: Carbon emissions generated by gastrointestinal endoscopy have been recognised as a critical issue. Scope 3 emissions are mainly caused by the manufacturing, packaging and transportation of purchased goods. However, to our knowledge, there are no prospective data on the efficacy of measurements aimed to reduce scope 3 emissions. DESIGN: The study was performed in a medium-sized academic endoscopy unit. Manufacturers of endoscopic consumables were requested to answer a questionnaire on fabrication, origin, packaging and transport. Based on these data, alternative products were purchased whenever possible. In addition, staff was instructed on how to avoid waste. Thereafter, the carbon footprint of each item purchased was calculated from February to May 2023 (intervention period), and scope 3 emissions were compared with the same period of the previous year (control period). RESULTS: 26 of 40 companies answered the questionnaire. 229 of 322 products were classified as unfavourable. A switch to alternative items was possible for 47/229 items (20.5%). 1666 endoscopies were performed during the intervention period compared with 1751 examinations during the control period (-4.1%). The number of instruments used decreased by 10.0% (3111 vs 3457). Using fewer and alternative products resulted in 11.5% less carbon emissions (7.09 vs 8.01 tons of carbon equivalent=tCO2 e). Separation of waste led to a reduction of 20.1% (26.55 vs 33.24 tCO2e). In total, carbon emissions could be reduced by 18.4%. CONCLUSION: Use of fewer instruments per procedure, recycling packaging material and switching to alternative products can reduce carbon emissions without impairing the endoscopic workflow.

Direct comparison of multiple computer-aided polyp detection systems.

BACKGROUND AND STUDY AIMS: Artificial intelligence (AI)-based systems for computer-aided detection (CADe) of polyps receive regular updates and occasionally offer customizable detection thresholds, both of which impact their performance, but little is known about these effects. This study aimed to compare the performance of different CADe systems on the same benchmark dataset. METHODS: 101 colonoscopy videos were used as benchmark. Each video frame with a visible polyp was manually annotated with bounding boxes, resulting in 129 705 polyp images. The videos were then analyzed by three different CADe systems, representing five conditions: two versions of GI Genius, Endo-AID with detection Types A and B, and EndoMind, a freely available system. Evaluation included an analysis of sensitivity and false-positive rate, among other metrics. RESULTS: Endo-AID detection Type A, the earlier version of GI Genius, and EndoMind detected all 93 polyps. Both the later version of GI Genius and Endo-AID Type B missed 1 polyp. The mean per-frame sensitivities were 50.63 % and 67.85 %, respectively, for the earlier and later versions of GI Genius, 65.60 % and 52.95 %, respectively, for Endo-AID Types A and B, and 60.22 % for EndoMind. CONCLUSIONS: This study compares the performance of different CADe systems, different updates, and different configuration modes. This might help clinicians to select the most appropriate system for their specific needs.

Closing the Gap: A Critical Examination of Adherence, Inconsistency, and Improvements in Colonoscopy Reporting Practices.

INTRODUCTION: Comprehensive and standardized colonoscopy reports are crucial in colorectal cancer prevention, monitoring, and research. This study investigates adherence to national and international guidelines by analyzing reporting practices among 21 endoscopists in 7 German centers, with a focus on polyp reporting. METHODS: We identified and assessed German, European, American, and World Health Organization-provided statements to identify key elements in colonoscopy reporting. Board-certified gastroenterologists rated the relevance of each element and estimated their reporting frequency. Adherence to the identified report elements was evaluated for 874 polyps from 351 colonoscopy reports ranging from March 2021 to March 2022. RESULTS: We identified numerous recommendations for colonoscopy reporting. We categorized the reasoning behind those recommendations into clinical relevance, justification, and quality control and research. Although all elements were considered relevant by the surveyed gastroenterologists, discrepancies were observed in the evaluated reports. Particularly diminutive polyps or attributes which are rarely abnormal (e.g., surface integrity) respectively rarely performed (e.g., injection) were sparsely documented. Furthermore, the white light morphology of polyps was inconsistently documented using either the Paris classification or free text. In summary, the analysis of 874 reported polyps revealed heterogeneous adherence to the recommendations, with reporting frequencies ranging from 3% to 89%. CONCLUSION: The inhomogeneous report practices may result from implicit reporting practices and recommendations with varying clinical relevance. Future recommendations should clearly differentiate between clinical relevance and research and quality control or explanatory purposes. Additionally, the role of computer-assisted documentation should be further evaluated to increase report frequencies of non-pathological findings and diminutive polyps.

Assisted documentation as a new focus for artificial intelligence in endoscopy: the precedent of reliable withdrawal time and image reporting.

BACKGROUND : Reliable documentation is essential for maintaining quality standards in endoscopy; however, in clinical practice, report quality varies. We developed an artificial intelligence (AI)-based prototype for the measurement of withdrawal and intervention times, and automatic photodocumentation. METHOD: A multiclass deep learning algorithm distinguishing different endoscopic image content was trained with 10 557 images (1300 examinations, nine centers, four processors). Consecutively, the algorithm was used to calculate withdrawal time (AI prediction) and extract relevant images. Validation was performed on 100 colonoscopy videos (five centers). The reported and AI-predicted withdrawal times were compared with video-based measurement; photodocumentation was compared for documented polypectomies. RESULTS: Video-based measurement in 100 colonoscopies revealed a median absolute difference of 2.0 minutes between the measured and reported withdrawal times, compared with 0.4 minutes for AI predictions. The original photodocumentation represented the cecum in 88 examinations compared with 98/100 examinations for the AI-generated documentation. For 39/104 polypectomies, the examiners' photographs included the instrument, compared with 68 for the AI images. Lastly, we demonstrated real-time capability (10 colonoscopies). CONCLUSION : Our AI system calculates withdrawal time, provides an image report, and is real-time ready. After further validation, the system may improve standardized reporting, while decreasing the workload created by routine documentation.

Artificial intelligence-based polyp size measurement in gastrointestinal endoscopy using the auxiliary waterjet as a reference.

BACKGROUND: Measurement of colorectal polyp size during endoscopy is mainly performed visually. In this work, we propose a novel polyp size measurement system (Poseidon) based on artificial intelligence (AI) using the auxiliary waterjet as a measurement reference. METHODS: Visual estimation, biopsy forceps-based estimation, and Poseidon were compared using a computed tomography colonography-based silicone model with 28 polyps of defined sizes. Four experienced gastroenterologists estimated polyp sizes visually and with biopsy forceps. Furthermore, the gastroenterologists recorded images of each polyp with the waterjet in proximity for the application of Poseidon. Additionally, Poseidon's measurements of 29 colorectal polyps during routine clinical practice were compared with visual estimates. RESULTS: In the silicone model, visual estimation had the largest median percentage error of 25.1 % (95 %CI 19.1 %-30.4 %), followed by biopsy forceps-based estimation: median 20.0 % (95 %CI 14.4 %-25.6 %). Poseidon gave a significantly lower median percentage error of 7.4 % (95 %CI 5.0 %-9.4 %) compared with other methods. During routine colonoscopies, Poseidon presented a significantly lower median percentage error (7.7 %, 95 %CI 6.1 %-9.3 %) than visual estimation (22.1 %, 95 %CI 15.1 %-26.9 %). CONCLUSION: In this work, we present a novel AI-based method for measuring colorectal polyp size with significantly higher accuracy than other common sizing methods.

Quality of life in benign colorectal disease-a review of the assessment with the Gastrointestinal Quality of Life Index (GIQLI).

BACKGROUND AND PURPOSE: The Gastrointestinal Quality of Life Index (GIQLI) is an instrument for the assessment of quality of life (QOL) in diseases of the upper and lower GI tract, which is validated in several languages around the world. The purpose of this literature review is the assessment of the GIQLI in patients with benign colorectal diseases. Reports on GIQLI data are collected from several institutions, countries, and different cultures which allows for comparisons, which are lacking in literature. METHODS: The GIQL Index uses 36 items around 5 dimensions (gastrointestinal symptoms (19 items), emotional dimension (5 items), physical dimension (7 items), social dimension (4 items), and therapeutic influences (1 item). The literature search was performed on the GIQLI and colorectal disease, using reports in PubMed. Data are presented descriptively as GIQL Index points as well as a reduction from 100% maximum possible index points (max 144 index points = highest quality of life). RESULTS: The GIQLI was found in 122 reports concerning benign colorectal diseases, of which 27 were finally selected for detailed analysis. From these 27 studies, information on 5664 patients (4046 female versus 1178 male) was recorded and summarized. The median age was 52 years (range 29-74.7). The median GIQLI of all studies concerning benign colorectal disease was 88 index points (range 56.2-113). Benign colorectal disease causes a severe reduction in QOL for patients down to 61% of the maximum. CONCLUSIONS: Benign colorectal diseases cause substantial reductions in the patient's QOL, well documented by GIQLI, which allows a comparison QOL with other published cohorts.

Automated classification of polyps using deep learning architectures and few-shot learning.

BACKGROUND: Colorectal cancer is a leading cause of cancer-related deaths worldwide. The best method to prevent CRC is a colonoscopy. However, not all colon polyps have the risk of becoming cancerous. Therefore, polyps are classified using different classification systems. After the classification, further treatment and procedures are based on the classification of the polyp. Nevertheless, classification is not easy. Therefore, we suggest two novel automated classifications system assisting gastroenterologists in classifying polyps based on the NICE and Paris classification. METHODS: We build two classification systems. One is classifying polyps based on their shape (Paris). The other classifies polyps based on their texture and surface patterns (NICE). A two-step process for the Paris classification is introduced: First, detecting and cropping the polyp on the image, and secondly, classifying the polyp based on the cropped area with a transformer network. For the NICE classification, we design a few-shot learning algorithm based on the Deep Metric Learning approach. The algorithm creates an embedding space for polyps, which allows classification from a few examples to account for the data scarcity of NICE annotated images in our database. RESULTS: For the Paris classification, we achieve an accuracy of 89.35 %, surpassing all papers in the literature and establishing a new state-of-the-art and baseline accuracy for other publications on a public data set. For the NICE classification, we achieve a competitive accuracy of 81.13 % and demonstrate thereby the viability of the few-shot learning paradigm in polyp classification in data-scarce environments. Additionally, we show different ablations of the algorithms. Finally, we further elaborate on the explainability of the system by showing heat maps of the neural network explaining neural activations. CONCLUSION: Overall we introduce two polyp classification systems to assist gastroenterologists. We achieve state-of-the-art performance in the Paris classification and demonstrate the viability of the few-shot learning paradigm in the NICE classification, addressing the prevalent data scarcity issues faced in medical machine learning.

New Concept of External and Independent Next-to-the-Scope Intraluminal Grasping Device (EINTS).

Background: Interventional endoscopic procedures require complex manipulations and precise maneuvering of end-effectors. One focus in research on improved endoscopic instrument function was based on surgical experience to gain additional traction. The idea has emerged using assisting instruments by applying external tools next-to-the endoscope to follow surgical concepts. The aim of this study is the assessment of flexible endoscopic grasping instruments regarding their function and working-radius introducing the concept of an intraluminal "next-to the-scope" endoscopic grasper. Methods: In this study endoscopic graspers are evaluated (1:through-the-scope-grasper, TTSG; 2:additional-working-channel-system AWC-S;3:external-independent-next-to-the-scope-grasper EINTS-G) regarding their working-radius, grasping abilities, maneuverability and the ability to expose tissue with varying angulation. Results: The working radius of the tools attached or within the endoscope (TTS-G and AWC-S) benefit from the steering abilities of the scope reaching 180-210 degrees in retroflexion; EINTS-G is limited to 110-degrees. The robust EINTS-grasper has the advantage of stronger grip for grasping and pulling force, which enables manipulation of larger objects. The independent maneuverability during ESD-dissection provides better tissue-exposure by changing the traction-angulation. Conclusion: The working radius of tools attached to the endoscope benefit from scope- steering. The EINTS-grasper has the advantage of stronger grasping force and pulling within the GI-tract and independent maneuverability enables improved tissue-exposure. WC200.

New concept for colonoscopy including side optics and artificial intelligence.

BACKGROUND AND AIMS: Adenoma detection rate is the crucial parameter for colorectal cancer screening. Increasing the field of view with additional side optics has been reported to detect flat adenomas hidden behind folds. Furthermore, artificial intelligence (AI) has also recently been introduced to detect more adenomas. We therefore aimed to combine both technologies in a new prototypic colonoscopy concept. METHODS: A 3-dimensional-printed cap including 2 microcameras was attached to a conventional endoscope. The prototype was applied in 8 gene-targeted pigs with mutations in the adenomatous polyposis coli gene. The first 4 animals were used to train an AI system based on the images generated by microcameras. Thereafter, the conceptual prototype for detecting adenomas was tested in a further series of 4 pigs. RESULTS: Using our prototype, we detected, with side optics, adenomas that might have been missed conventionally. Furthermore, the newly developed AI could detect, mark, and present adenomas visualized with side optics outside of the conventional field of view. CONCLUSIONS: Combining AI with side optics might help detect adenomas that otherwise might have been missed.

The influence of computer-aided polyp detection systems on reaction time for polyp detection and eye gaze.

BACKGROUND: Multiple computer-aided systems for polyp detection (CADe) have been introduced into clinical practice, with an unclear effect on examiner behavior. This study aimed to measure the influence of a CADe system on reaction time, mucosa misinterpretation, and changes in visual gaze pattern. METHODS: Participants with variable levels of colonoscopy experience viewed video sequences (n = 29) while eye movement was tracked. Using a crossover design, videos were presented in two assessments, with and without CADe support. Reaction time for polyp detection and eye-tracking metrics were evaluated. RESULTS: 21 participants performed 1218 experiments. CADe was significantly faster in detecting polyps compared with participants (median 1.16 seconds [99 %CI 0.40-3.43] vs. 2.97 seconds [99 %CI 2.53-3.77], respectively). However, the reaction time of participants when using CADe (median 2.90 seconds [99 %CI 2.55-3.38]) was similar to that without CADe. CADe increased misinterpretation of normal mucosa and reduced the eye travel distance. CONCLUSIONS: Results confirm that CADe systems detect polyps faster than humans. However, use of CADe did not improve human reaction times. It increased misinterpretation of normal mucosa and decreased the eye travel distance. Possible consequences of these findings might be prolonged examination time and deskilling.

A video based benchmark data set (ENDOTEST) to evaluate computer-aided polyp detection systems.

BACKGROUND AND AIMS: Computer-aided polyp detection (CADe) may become a standard for polyp detection during colonoscopy. Several systems are already commercially available. We report on a video-based benchmark technique for the first preclinical assessment of such systems before comparative randomized trials are to be undertaken. Additionally, we compare a commercially available CADe system with our newly developed one. METHODS: ENDOTEST consisted in the combination of two datasets. The validation dataset contained 48 video-snippets with 22,856 manually annotated images of which 53.2% contained polyps. The performance dataset contained 10 full-length screening colonoscopies with 230,898 manually annotated images of which 15.8% contained a polyp. Assessment parameters were accuracy for polyp detection and time delay to first polyp detection after polyp appearance (FDT). Two CADe systems were assessed: a commercial CADe system (GI-Genius, Medtronic), and a self-developed new system (ENDOMIND). The latter being a convolutional neuronal network trained on 194,983 manually labeled images extracted from colonoscopy videos recorded in mainly six different gastroenterologic practices. RESULTS: On the ENDOTEST, both CADe systems detected all polyps in at least one image. The per-frame sensitivity and specificity in full colonoscopies was 48.1% and 93.7%, respectively for GI-Genius; and 54% and 92.7%, respectively for ENDOMIND. Median FDT of ENDOMIND with 217 ms (Inter-Quartile Range(IQR)8-1533) was significantly faster than GI-Genius with 1050 ms (IQR 358-2767, p = 0.003). CONCLUSIONS: Our benchmark ENDOTEST may be helpful for preclinical testing of new CADe devices. There seems to be a correlation between a shorter FDT with a higher sensitivity and a lower specificity for polyp detection.

Pilot study of a new freely available computer-aided polyp detection system in clinical practice.

PURPOSE: Computer-aided polyp detection (CADe) systems for colonoscopy are already presented to increase adenoma detection rate (ADR) in randomized clinical trials. Those commercially available closed systems often do not allow for data collection and algorithm optimization, for example regarding the usage of different endoscopy processors. Here, we present the first clinical experiences of a, for research purposes publicly available, CADe system. METHODS: We developed an end-to-end data acquisition and polyp detection system named EndoMind. Examiners of four centers utilizing four different endoscopy processors used EndoMind during their clinical routine. Detected polyps, ADR, time to first detection of a polyp (TFD), and system usability were evaluated (NCT05006092). RESULTS: During 41 colonoscopies, EndoMind detected 29 of 29 adenomas in 66 of 66 polyps resulting in an ADR of 41.5%. Median TFD was 130 ms (95%-CI, 80-200 ms) while maintaining a median false positive rate of 2.2% (95%-CI, 1.7-2.8%). The four participating centers rated the system using the System Usability Scale with a median of 96.3 (95%-CI, 70-100). CONCLUSION: EndoMind's ability to acquire data, detect polyps in real-time, and high usability score indicate substantial practical value for research and clinical practice. Still, clinical benefit, measured by ADR, has to be determined in a prospective randomized controlled trial.

Fast machine learning annotation in the medical domain: a semi-automated video annotation tool for gastroenterologists.

BACKGROUND: Machine learning, especially deep learning, is becoming more and more relevant in research and development in the medical domain. For all the supervised deep learning applications, data is the most critical factor in securing successful implementation and sustaining the progress of the machine learning model. Especially gastroenterological data, which often involves endoscopic videos, are cumbersome to annotate. Domain experts are needed to interpret and annotate the videos. To support those domain experts, we generated a framework. With this framework, instead of annotating every frame in the video sequence, experts are just performing key annotations at the beginning and the end of sequences with pathologies, e.g., visible polyps. Subsequently, non-expert annotators supported by machine learning add the missing annotations for the frames in-between. METHODS: In our framework, an expert reviews the video and annotates a few video frames to verify the object's annotations for the non-expert. In a second step, a non-expert has visual confirmation of the given object and can annotate all following and preceding frames with AI assistance. After the expert has finished, relevant frames will be selected and passed on to an AI model. This information allows the AI model to detect and mark the desired object on all following and preceding frames with an annotation. Therefore, the non-expert can adjust and modify the AI predictions and export the results, which can then be used to train the AI model. RESULTS: Using this framework, we were able to reduce workload of domain experts on average by a factor of 20 on our data. This is primarily due to the structure of the framework, which is designed to minimize the workload of the domain expert. Pairing this framework with a state-of-the-art semi-automated AI model enhances the annotation speed further. Through a prospective study with 10 participants, we show that semi-automated annotation using our tool doubles the annotation speed of non-expert annotators compared to a well-known state-of-the-art annotation tool. CONCLUSION: In summary, we introduce a framework for fast expert annotation for gastroenterologists, which reduces the workload of the domain expert considerably while maintaining a very high annotation quality. The framework incorporates a semi-automated annotation system utilizing trained object detection models. The software and framework are open-source.

Frame-by-Frame Analysis of a Commercially Available Artificial Intelligence Polyp Detection System in Full-Length Colonoscopies.

INTRODUCTION: Computer-aided detection (CADe) helps increase colonoscopic polyp detection. However, little is known about other performance metrics like the number and duration of false-positive (FP) activations or how stable the detection of a polyp is. METHODS: 111 colonoscopy videos with total 1,793,371 frames were analyzed on a frame-by-frame basis using a commercially available CADe system (GI-Genius, Medtronic Inc.). Primary endpoint was the number and duration of FP activations per colonoscopy. Additionally, we analyzed other CADe performance parameters, including per-polyp sensitivity, per-frame sensitivity, and first detection time of a polyp. We additionally investigated whether a threshold for withholding CADe activations can be set to suppress short FP activations and how this threshold alters the CADe performance parameters. RESULTS: A mean of 101 ± 88 FPs per colonoscopy were found. Most of the FPs consisted of less than three frames with a maximal 66-ms duration. The CADe system detected all 118 polyps and achieved a mean per-frame sensitivity of 46.6 ± 26.6%, with the lowest value for flat polyps (37.6 ± 24.8%). Withholding CADe detections up to 6 frames length would reduce the number of FPs by 87.97% (p < 0.001) without a significant impact on CADe performance metrics. CONCLUSIONS: The CADe system works reliable but generates many FPs as a side effect. Since most FPs are very short, withholding short-term CADe activations could substantially reduce the number of FPs without impact on other performance metrics. Clinical practice would benefit from the implementation of customizable CADe thresholds.

Smartphone Application to Reinforce Education Increases High-Quality Preparation for Colorectal Cancer Screening Colonoscopies in a Randomized Trial.

BACKGROUND & AIMS: Sufficient bowel preparation is crucial for successful screening and surveillance colonoscopy. However, rates of inadequate preparation are still high. We investigated the effects of reinforced patient education using a smartphone application software (APP) for colonoscopy preparation in participants in a CRC screening program. METHODS: We performed a prospective, endoscopist-blinded study of 500 patients undergoing split-dose bowel preparation for CRC screening or surveillance colonoscopies at multiple centers in Germany, from November 2017 through January 2019. Participants (n = 500) were given oral and written instructions during their initial appointment and then randomly assigned (1:1) to groups that received reinforced education starting 3 days before the colonoscopy (APP group) or no further education (controls). The primary outcome was quality of bowel preparation according to the Boston bowel preparation scale. Secondary outcomes included polyp and adenoma detection rates, compliance with low-fiber diet, split-dose laxative intake, perceived discomfort from the preparation procedure. RESULTS: The mean Boston bowel preparation scale score was significantly higher in the APP-group (7.6 ± 0.1) than in the control group (6.7 ± 0.1) (P < .0001). The percentage of patients with insufficient bowel preparation was significantly lower in the APP group (8%) than in the control group (17%) (P = .0023). The adenoma detection rate was significantly higher in the APP group (35% vs 27% in controls) (P = .0324). Use of the APP was accompanied by a lower level of non-compliance with correct laxative intake (P =.0080) and diet instructions (P = .0089). The APP group reported a lower level of discomfort during preparation (P < .0001). CONCLUSIONS: In a randomized trial, reinforcing patient education with a smartphone application optimized bowel preparation in the 3 days before colonoscopy, increasing bowel cleanliness, adenoma detection, and compliance in patients undergoing CRC screening or surveillance. ClinicalTrials.gov no: NCT03290157.

Etiology and Morphology Impact on the Clinical Course of Chronic Pancreatitis.

BACKGROUND: Symptoms caused by chronic pancreatitis (CP) are common but often elusive hampering therapeutic decisions. Though correlations of morphologic findings in imaging and clinical appearance remain vague. We aimed in investigating whether a distinct combination of clinical parameters can better define the extent of pancreatic insufficiency and disease burden. METHODS: Data from 350 CP patients were evaluated retrospectively from a single center data base following predefined criteria: (i) confirmed CP, (ii) endoscopic ultrasound (EUS) plus (iii) fecal elastase-1 testing, (iv) age ≥18 years, and (v) Cambridge Score ≥1 on EUS evaluation. RESULTS: In total, 182 patients (137 male, 45 female) fulfilled criteria. Median age was 52 years (range 19-88 years). Etiology distributed as follows: idiopathic 50%, alcohol 42.3%, autoimmune 7.7%. Totally, 56.6% of patients suffered from chronic pain that was significantly associated with male sex and younger age. Stool elastase-1 activity discriminated exocrine pancreatic function in Cambridge IV significantly better than in lower stages. Similarly, the endocrine function was significantly more reduced in Cambridge IV CP. Multinominal regression analysis revealed (i) presence of diabetes, (ii) presence of complications, and (iii) extent of Cambridge score as main determinants for exocrine impairment. CONCLUSION: A high disease burden is linked to extensive morphological alterations in EUS, while pain is more frequent in younger and male patients. The etiology of CP predicts the course of disease in terms of complications.

Improving the quality and acceptance of colonoscopy preparation by reinforced patient education with short message service: results from a randomized, multicenter study (PERICLES-II).

BACKGROUND AND AIMS: Sufficient bowel preparation is crucial for successful screening and surveillance colonoscopy. However, the rates of inadequate preparation are still high. We investigated the effects of reinforcing patient education and guidance by using the short message service (SMS). METHODS: In this prospective, endoscopist-blinded, multicenter study, standard instructions pertaining to split-dose preparation were provided in a verbal and written format to all patients during the initial appointment. Patients were randomly assigned (1:1) to a group that received reinforced education starting 4 days before the colonoscopy (SMS group) or to the control group which did not receive further education. The primary outcome was the percentage of insufficient preparation results (Boston Bowel Preparation Scale [BBPS] score <6). The secondary outcomes included quality of bowel preparation according to the BBPS, polyp and adenoma detection rates, and patients' perceived discomfort in the preparation procedure. RESULTS: The percentage of patients with insufficient bowel preparation was significantly lower in the SMS group (9%) than in the control group (19%) (P = .0013). The mean BBPS score was significantly higher in the SMS group (7.4 ± 0.1) than in the control group (6.5 ± 0.1) (P < .0001). Each colon segment had significantly higher BBPS scores in the SMS group. The adenoma detection rate and number of detected adenomas in the right segment of the colon were higher in the SMS group. SMS messages were accompanied by a lower level of discomfort during preparation (numeric rating scale) (5.2 SMS vs 5.8 controls) (P = .0042). CONCLUSIONS: Reinforced patient education by using SMS messages during the 4 days before colonoscopy increased bowel cleanliness, adenoma detection in the right segment of the colon, and reduced discomfort. (Clinical trial registration number: NCT02272036.).

[Survey: Why did you become a gastroenterologist?] / Umfrage: Was hat Sie dazu bewogen, die Gastroenterologie als Fachgebiet auszuwählen?

INTRODUCTION: The specific support of medical students is indispensable in gastroenterology. The aim of this study was to identify factors that influenced members of the German Society of Gastroenterology, Digestive and Metabolic Diseases (DGVS) to choose their specialty. METHODS: Using an online survey all members of the DGVS were invited to assess the following factors: earliest time point of the decision to become a gastroenterologist, important role models and mentors, important course contents and teaching methods, the role of the doctoral thesis and other influencing aspects of the specialty gastroenterology. The evaluation included an additional subgroup analysis involving work experience (≤ 8, 9-29, ≥ 30 years) and working place (university hospital, community-based hospital, private practice). RESULTS: 1358 participants representing 24.2 % of the DGVS-members took part in the survey. Physicians with ≤ 8 years of work experience decided in 62.5 % during medical school to become a gastroenterologist compared to 37.1 % of the physicians with a work experience of ≥ 9 years (p < 0.001). Senior physicians were regarded as important role models and mentors by 40.8 % of the participants. Doctoral supervisors were regarded as important mentors that influenced the selection of the specialty by 42.8 % of the participants that completed their doctoral thesis in gastroenterology. Hands-on courses like sonography were regarded as important course contents by 42.2 % of the participants. Interventional medicine in particular endoscopy and the diversity of gastroenterology were rated as important in the selection process for the specialty. CONCLUSION: The decision to become a gastroenterologist is mainly made during medical school. The main influencing role models and mentors are senior physicians. Hands-on training in ultrasound and endoscopy were regarded as important course contents and teaching methods.

Chemotherapeutic agents eligible for prior dosing in pancreatic cancer patients requiring hemodialysis: a systematic review
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AIMS: New chemotherapeutic agents prolong survival of patients with pancreatic ductal adenocarcinoma (PDAC). Although their incidence is rising, patients with end-stage renal disease (ESRD) requiring hemodialysis (HD) are not included in the phase III trials evaluating the effects of these chemotherapies. Many experts recommend applying chemotherapy after HD using a reduced dose. Alternatively, the concept of prior dosing allows for the application of dialyzable chemotherapeutic drugs using a normal dose, with an HD followed shortly after to mimic normal renal function. In this work, we provide guidance for clinicians on how to use chemotherapy in patients with PDAC on HD and how to identify substances suitable for prior dosing. MATERIALS AND METHODS: We systematically searched PubMed, from inception to September 2016, for published studies describing patients with ESRD on HD who received chemotherapies commonly applied in PDAC, including gemcitabine, fluorouracil (5-FU), capecitabine, oxaliplatin, irinotecan, docetaxel, erlotinib, sunitinib, S-1, and afatinib. Applied dosages, described toxicities, application time relative to HD, and pharmacokinetic measurements of the drug and its metabolites were assessed. Quantitative analysis of the drug plasma concentrations, including half-life during and in between HD and fraction of the drug eliminated during HD, were assessed. RESULTS: We identified 56 studies describing 128 patients with ESRD undergoing HD during chemotherapeutic treatment. Quantitative pharmacokinetic analysis revealed that the following substances are dialyzable and thus suitable for application using the prior-dosing method: gemcitabine, 5-FU, oxaliplatin, irinotecan, and S-1. CONCLUSION: This work supports the application of dialyzable chemotherapeutic agents in patients with PDAC in standard dose when HD is performed shortly after the infusion.
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