Clinical Experience with the PillCam Patency Capsule prior to Video Capsule Endoscopy: A Real-World Experience

Background. In patients with known or suspected risk factors for gastrointestinal stenosis, the PillCam patency capsule (PC) is given before a video capsule endoscopy (VCE) in order to minimize the risk of capsule retention (CR). CR is considered unlikely upon excretion of the PC within 30 hours, excretion in an undamaged state after 30 hours, or radiological projection to the colon. Methods. We performed a retrospective analysis of 38 patients with risk factors for CR, who received a PC from 02/2013 to 04/2015 at Klinikum Augsburg. Results. Sixteen of our 38 patients observed a natural excretion after a mean time of 34 hours past ingestion. However, only 8 patients observed excretion within 30 hours, as recommended by the company. In 20 patients passage of the PC into the colon was shown via RFID-scan or radiological imaging (after 33 and 45 hours, resp.). Only 2 patients showed a pathologic PC result. In consequence, 32 patients received the VCE; no CR was observed. Conclusion. Our data indicates that a VCE could safely be performed even if the PC excretion time is longer than 30 hours and the excreted PC was not screened for damage

Clinical Study Clinical Experience with the PillCam Patency Capsule prior to Video Capsule Endoscopy: A Real-World Experience

Background. In patients with known or suspected risk factors for gastrointestinal stenosis, the PillCam patency capsule (PC) is given before a video capsule endoscopy (VCE) in order to minimize the risk of capsule retention (CR). CR is considered unlikely upon excretion of the PC within 30 hours, excretion in an undamaged state after 30 hours, or radiological projection to the colon. Methods. We performed a retrospective analysis of 38 patients with risk factors for CR, who received a PC from 02/2013 to 04/2015 at Klinikum Augsburg. Results. Sixteen of our 38 patients observed a natural excretion after a mean time of 34 hours past ingestion. However, only 8 patients observed excretion within 30 hours, as recommended by the company. In 20 patients passage of the PC into the colon was shown via RFID-scan or radiological imaging (after 33 and 45 hours, resp.). Only 2 patients showed a pathologic PC result. In consequence, 32 patients received the VCE; no CR was observed. Conclusion. Our data indicates that a VCE could safely be performed even if the PC excretion time is longer than 30 hours and the excreted PC was not screened for damage

Detection Rate and Clinical Relevance of Ink Tattooing during Balloon-Assisted Enteroscopy

Background and Aims. Balloon-assisted enteroscopy (BAE) is a well-established tool in the diagnosis and therapy of small bowel diseases. Ink tattooing of the small bowel is used to mark pathologic lesions or the depth of small bowel insertion. The purpose of this study was to determine the safety, the detection rate, and the clinical relevance of ink tattooing during BAE. Methods. We performed a retrospective analysis of all 81 patients who received an ink tattooing during BAE between 2010 and 2015. Results. In all patients, ink tattooing was performed with no complications. 26 patients received a capsule endoscopy after BAE. The tattoo could be detected via capsule endoscopy in 19 of these 26 patients. The tattoo of the previous BAE could be detected via opposite BAE in 2 of 11 patients. In 9 patients, ink tattooing influenced the choice of approach for reenteroscopy. In 7 patients, the tattoo was used for intraoperative localization and in 3 patients for intraoperative localization as well as for reenteroscopy. The intraoperative detection rate of the tattoo was 100%. Conclusion. Ink tattooing of the small intestine is a safe endoscopic procedure to mark the depth of scope insertion or a pathologic lesion during balloon-assisted enteroscopy

Predictive preoperative clinical score for patients with liver-only oligometastatic colorectal cancer

BACKGROUND: Resection of liver metastases from colorectal cancer (CRC) in the oligometastatic stage improves survival and is a potentially curative treatment. Thus, predictive scores that reliably identify those patients who especially benefit from surgery are essential. PATIENTS AND METHODS: In this multicenter analysis, 512 patients had undergone surgery for liver metastases from CRC. We investigated distinct cancer-specific risk factors that are routinely available in clinical practice and developed a predictive preoperative score using a training cohort (TC), which was thereafter tested in a validation cohort (VC). RESULTS: Inflammatory response to the tumor, a right-sided primary tumor, multiple liver metastases, and node-positive primary tumor were significant adverse variables for overall survival (OS). Patients were stratified in five groups according to the cumulative score given by the presence of these risk factors. Median OS for patients without risk factors was 133.8 months [95% confidence interval (CI) 81.2-not reached (nr)] in the TC and was not reached in the VC. OS decreased significantly for each subsequent group with increasing number of risk factors. Median OS was significantly shorter (P < 0.0001) for patients presenting all four risk factors: 14.3 months (95% CI 10.5 months-nr) in the TC and 16.6 months (95% CI 14.6 months-nr) in the VC. CONCLUSIONS: Including easily obtainable variables, this preoperative score identifies oligometastatic CRC patients with prolonged survival rates that may be cured, and harbors potential to be implemented in daily clinical practice

Cost-effectiveness of artificial intelligence for screening colonoscopy: a modelling study

Background: Artificial intelligence (AI) tools increase detection of precancerous polyps during colonoscopy and might contribute to long-term colorectal cancer prevention. The aim of the study was to investigate the incremental effect of the implementation of AI detection tools in screening colonoscopy on colorectal cancer incidence and mortality, and the cost-effectiveness of such tools. Methods: We conducted Markov model microsimulation of using colonoscopy with and without AI for colorectal cancer screening for individuals at average risk (no personal or family history of colorectal cancer, adenomas, inflammatory bowel disease, or hereditary colorectal cancer syndrome). We ran the microsimulation in a hypothetical cohort of 100 000 individuals in the USA aged 50–100 years. The primary analysis investigated screening colonoscopy with versus without AI every 10 years starting at age 50 years and finishing at age 80 years, with follow-up until age 100 years, assuming 60% screening population uptake. In secondary analyses, we modelled once-in-life screening colonoscopy at age 65 years in adults aged 50–79 years at average risk for colorectal cancer. Post-polypectomy surveillance followed the simplified current guideline. Costs of AI tools and cost for downstream treatment of screening detected disease were estimated with 3% annual discount rates. The main outcome measures included the incremental effect of AI-assisted colonoscopy versus standard (no-AI) colonoscopy on colorectal cancer incidence and mortality, and cost-effectiveness of screening projected for the average risk screening US population. Findings: In the primary analyses, compared with no screening, the relative reduction of colorectal cancer incidence with screening colonoscopy without AI tools was 44·2% and with screening colonoscopy with AI tools was 48·9% (4·8% incremental gain). Compared with no screening, the relative reduction in colorectal cancer mortality with screening colonoscopy with no AI was 48·7% and with screening colonoscopy with AI was 52·3% (3·6% incremental gain). AI detection tools decreased the discounted costs per screened individual from $3400 to$3343 (a saving of $57 per individual). Results were similar in the secondary analyses modelling once-in-life colonoscopy. At the US population level, the implementation of AI detection during screening colonoscopy resulted in yearly additional prevention of 7194 colorectal cancer cases and 2089 related deaths, and a yearly saving of US$290 million. Interpretation: Our findings suggest that implementation of AI detection tools in screening colonoscopy is a cost-saving strategy to further prevent colorectal cancer incidence and mortality. Funding: European Commission and Japan Society of Promotion of Science