Dataset Information

The Effect of Routine Video-recording on Colonoscopy Quality Indicators.

ABSTRACT: Routine video recording of the colonoscopy examination has been proposed as a simple and easy to implement method that could improve the quality of colonoscopy. The purpose of this study is to investigate whether implementation of routine video recording of screening colonoscopy withdrawal is effective as a means of supporting quality performance of colonoscopy. The study will be performed in 8 screening centers within the framework of a national colonoscopy screening program in Poland (the Polish Colonoscopy Screening Platform; PCSP). Individuals aged 55-64 years are eligible to participate in the PCSP. In the run-in period colonoscopy quality measures will be monitored through a dedicated joint database. Then eligible screening centres will be randomly assigned in a 1:1 ratio to the video recording group or the control group. Screening centres assigned to the video recording group will receive videorecorders and DVDs and will be asked to video record all screening colonoscopies (only withdrawal). Control group will be allowed to record colonoscopies on demand only. Then , the colonoscopy quality measures will again be monitored through a dedicated joint database. All the recorded DVDs will be reviewed to verify ceacal intubation and withdrawal time by the PCSP team.

DISEASE(S): Colorectal Cancer,Colorectal Neoplasms

PROVIDER: 2160210 | ecrin-mdr-crc |

REPOSITORIES: ECRIN MDR

ACCESS DATA

Similar Datasets

Project description:Colorectal cancer often arises from adenomatous polyps. Polyps can grow and progress to cancer, but may also remain static in size, regress, or resolve. Prediciting which progress to cancer and which remain benign is difficult. We developed a long-lived murine model of colorectal cancer with tumors that can be followed by colonoscopy. Our aim was to assess whether these tumors have similar growth patterns and histologic fates to human colorectal polyps to identify features to aid in risk stratification of colonic tumors. Long-lived Apcin/+ mice were treated with 4% dextran sodium sulfate to promote colonic tumorigenesis. Tumor growth patterns were characterized by serial colonoscopy, and pathology was determined. Serial biopsies of tumors were obtained for immunohistochemistry and gene expression profiling by microarray analysis with Affymetrix Whole Genome array. Tumors (n=424) grew, remained static, regressed, or resolved over time with different relative frequencies. Newly developed tumors demonstrated dynamic growth patterns with higher rates of growth and resolution, while more established tumors tended to remain static in size. Colonic tumors were hyperplastic lesions (3%), adenomas (73%), intramucosal carcinomas (20%), or adenocarcinomas (3%). Differentially expressed genes between adenomas and intramucosal carcinomas were identified. We did not identify differentially expressed genes between early and late biopsies from the same tumor. This novel murine model of intestinal tumorigenesis develops colonic tumors that can be monitored by serial colonoscopy, mirror growth patterns seen in human colorectal polyps, and progress to colorectal cancer. Further characterization of cellular and molecular features are needed to determine which features can be used to risk-stratify polyps for progress to colorectal cancer and potentially guide prevention strategies. F1 (SWR x C57BL/6) Apcin/+ mice who had been given two treatments of 4% dextran sodium sulfate in drinking water at weaning underwent colonoscopy around 80 days of age. Those with distal colonic tumors amenable to biopsy had two biopsies taken at that time. Tumors were monitored by colonoscopy every 14 days. Every 28 days, two additional biopsies were taken of each tumor. This protocol was repeated until mice were moribund. Six tumors were removed after sacrifice. The earliest and latest biopsies of each tumor were selected for RNA extraction and Affymetrix hybridization.

Project description:Endometriosis is associated with aberrant gene expression in the eutopic endometrium of women with disease. To determine if the development of endometriotic lesions directly impacts eutopic endometrial gene expression, we sequentially analyzed the eutopic endometrium across the time course of disease progression in a baboon model of induced disease. Endometriosis was induced in baboons by intraperitoneal inoculation of autologous menstrual endometrium. Eutopic endometria were collected at 9-11 days postovulation) in five time points: 1, 3, 6-7, 10-12, and 15-16 months after disease induction and compared with tissue from disease-free baboons. We used microarrays to identify differentially expressed genes between time points. Sequential analysis of the same animals during disease progression demonstrated an early disease insult and a transitory dominance of an estrogenic phenotype. However, as the disease progressed, a progesterone-resistant phenotype became evident. Endometriosis was experimentally induced in Papio anubis female baboons (n = 4) by intraperitoneal inoculation with menstrual endometrium on two consecutive menstrual cycles. Baboons with spontaneous endometriosis (n = 2) were also included in this study with an unknown duration of disease. Control endometrium was similarly harvested from animals (n = 4) with no previous surgeries and with no visible disease. The progression of disease was monitored in each animal by consecutive laparoscopies and video recording at 1 (n = 2), 3 (n = 4), 6-7 (n = 4), 10-12, (n = 4), and 15-16 (n = 3) months after inoculation during a window of 9-11 days postovulation. Eutopic endometrial tissues were harvested and were snap frozen in liquid nitrogen for RNA extraction. Additionally, menstrual endometrium was harvested on Days 1-2 of menses using a Unimar Pipelle (Cooper Surgical Inc., Shelton, CT) immediately prior to laparoscopy. Blood samples were collected daily from days 7 through 16 postmenstruation of menstrual cycles.

Dataset Information

The Effect of Routine Video-recording on Colonoscopy Quality Indicators.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets