A multicenter prospective randomized controlled trial evaluating the usefulness of a real-time colonoscopy diagnostic support system
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Neoplasms
PROVIDER: 112417 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
Similar Datasets
Project description:The goal of this substudy is to investigate the accuracy of a computer-aided polyp characterization (CADx) system. The main question[s] it aims to answer are:
• How high is the specificity of the AI system when characterizing colorectal polyps
Participants will receive a standard colonoscopy, assisted by the artificial intelligence (AI) assisted system GI Genius.
Researchers will compare the AI system´s characterization with the histopathology to see how accurate the system is.
| 10350 | ecrin-mdr-crc
Project description:Interventions: AI-first group:AI-assisted colonoscopy is performed first, followed by standard colonoscopy;SC-first group:standard colonoscopy is performed first, followed by AI-assisted colonoscopy
Primary outcome(s): adenoma miss rate
Study Design: Cross-over
| 47631 | ecrin-mdr-crc
Project description:RationaleTuberculosis case-detection rates are below internationally established targets in high-burden countries. Real-time monitoring and evaluation of adherence to widely endorsed standards of tuberculosis care might facilitate improved case finding.ObjectivesTo monitor and evaluate the quality of tuberculosis case-detection and management services in a low-income country with a high incidence of tuberculosis.MethodsWe prospectively evaluated tuberculosis diagnostic services at five primary health-care facilities in Uganda for 1 year, after introducing a real-time, electronic performance-monitoring system. We collected data on every clinical encounter, and measured quality using indicators derived from the International Standards of Tuberculosis Care.Measurements and main resultsIn 2009, there were 62,909 adult primary-care visits. During the first quarter of 2009, clinicians referred only 21% of patients with cough greater than or equal to 2 weeks for sputum smear microscopy and only 71% of patients with a positive sputum examination for tuberculosis treatment. These proportions increased to 53% and 84%, respectively, in the fourth quarter of 2009. The cumulative probability that a smear-positive patient with cough greater than or equal to 2 weeks would be appropriately evaluated and referred for treatment rose from 11% to 34% (P = 0.005). The quarterly number of tuberculosis cases identified and prescribed treatment also increased four-fold, from 5 to 21.ConclusionsPoor adherence to internationally accepted standards of tuberculosis care improved after introduction of real-time performance monitoring and was associated with increased tuberculosis case detection. Real-time monitoring and evaluation can strengthen health systems in low-income countries and facilitate operational research on the effectiveness and sustainability of interventions to improve tuberculosis case detection.
| S-EPMC3175538 | biostudies-literature
Project description:Colorectal cancer (CRC) is a leading cause of cancer-related morbidity and mortality worldwide, with rates of CRC predicted to increase. Colonoscopy is currently the gold standard of screening for CRC. Artificial intelligence (AI) is seen as a solution to bridge this gap in adenoma detection, which is a quality indicator in colonoscopy. AI systems utilize deep neural networks to enable computer-aided detection (CADe) and computer-aided classification (CADx). CADe is concerned with the detection of polyps during colonoscopy, which in turn is postulated to help decrease the adenoma miss-rate.
In contrast, CADx deals with the interpretation of polyp appearance during colonoscopy to determine the predicted histology. Prediction of polyp histology is crucial in helping Clinicians decide on a "resect and discard" or "diagnose and leave strategy". It is also useful for the Clinician to be aware of the predicted histology of a colorectal polyp in determining the appropriate method of resection in terms of safety and efficacy. While CADe has been studied extensively in randomized controlled trials, there is a lack of prospective data validating the use of CADx in a clinical setting to predict polyp histology.
The investigators plan to conduct a prospective, multi-centre clinical trial to validate the accuracy of CADx support for prediction of polyp histology in real-time colonoscopy.
| 2388863 | ecrin-mdr-crc
Project description:This is a prospective, multicenter, randomized Trial to assess the safety and efficacy of the Olympus Endoscopy Computer-Aided Detection (CADe) system, OIP-1, in the detection of colorectal neoplasia’s during real-time colonoscopy. The aim of this system is to improve physician performance in the detection of potential mucosal abnormalities during colonoscopy performed for primary Colorectal Cancer screening or postpolypectomy surveillance.
| 66341 | ecrin-mdr-crc
Project description:A differential time to positivity (DTP) of ? 120 min is useful for diagnosing catheter-related bacteremia, but data on diagnosing catheter-related candidemia (CRC) in this way are limited. We wished to evaluate the usefulness of the DTP for diagnosing CRC. All adult patients who had the same Candida species isolated from blood cultures drawn simultaneously from a central venous catheter (CVC) and a peripheral vein were included at a tertiary care hospital over an 18-month period. A total of 105 patients with candidemia who had positive simultaneous CVC and peripheral vein blood cultures were included in our study. Sixty-one patients (58%) had CRC (47 definite and 14 probable), and 38 (36%) had candidemia from another source (non-CRC). The remaining 6 patients (6%) with indeterminate candidemia were excluded from the final analysis. The overall sensitivity and specificity of a DTP of ? 120 min for diagnosing CRC were 85% (95% confidence interval [CI], 74% to 93%) and 82% (95% CI, 66% to 92%), respectively, and for neutropenic patients, they were 75% (95% CI, 19% to 99%) and 100% (95% CI, 75% to 100%), respectively. For Candida glabrata infections, the optimal DTP cutoff was ? 6 h, with a sensitivity of 63% (95% CI, 35% to 85%) and a specificity of 75% (95% CI, 35% to 97%). In summary, DTP is useful for diagnosing CRC, and a DTP of ? 120 min appears to be the optimal cutoff except for CRC caused by C. glabrata. For neutropenic patients, DTP may be useful as an adjunct test to rule in CRC and to decide whether a catheter should be removed.
| S-EPMC4097682 | biostudies-literature
Project description:Underwater sensor networks represent an important and promising field of research due to the large diversity of underwater ubiquitous applications that can be supported by these networks, e.g., systems that deliver tsunami and oil spill warnings, or monitor submarine ecosystems. Most of these monitoring and warning systems require real-time communication in wide area networks that have a low density of nodes. The underwater communication medium involved in these networks is very harsh and imposes strong restrictions to the communication process. In this scenario, the real-time transmission of information is done mainly using acoustic signals, since the network nodes are not physically close. The features of the communication scenario and the requirements of the communication process represent major challenges for designers of both, communication protocols and monitoring and warning systems. The lack of models to represent these networks is the main stumbling block for the proliferation of underwater ubiquitous systems. This paper presents a real-time communication model for underwater acoustic sensor networks (UW-ASN) that are designed to cover wide areas with a low density of nodes, using any-to-any communication. This model is analytic, considers two solution approaches for scheduling the real-time messages, and provides a time-constraint analysis for the network performance. Using this model, the designers of protocols and underwater ubiquitous systems can quickly prototype and evaluate their solutions in an evolving way, in order to determine the best solution to the problem being addressed. The suitability of the proposal is illustrated with a case study that shows the performance of a UW-ASN under several initial conditions. This is the first analytic model for representing real-time communication in this type of network, and therefore, it opens the door for the development of underwater ubiquitous systems for several application scenarios.
| S-EPMC5539683 | biostudies-other
Project description:Interventions: Group 1: colonoscopy with AI System
Primary outcome(s): The rate of correctly classified polyps detected by the AI system (accuracy).
The polyp classification is documented during the colonoscopy using the case report form(CRF).
Later the result is compared with histology(gold standard).
Study Design: Allocation: N/A: single arm study; Masking: Open (masking not used); Control: uncontrolled; Assignment: single; Study design purpose: prevention
| 2733414 | ecrin-mdr-crc
Project description:Primary outcome(s): Adenoma Detection Rate
| 2656527 | ecrin-mdr-crc
Project description:BackgroundUse of electronic clinical decision support (eCDS) has been recommended to improve implementation of clinical decision rules. Many eCDS tools, however, are designed and implemented without taking into account the context in which clinical work is performed. Implementation of the pediatric traumatic brain injury (TBI) clinical decision rule at one Level I pediatric emergency department includes an electronic questionnaire triggered when ordering a head computed tomography using computerized physician order entry (CPOE). Providers use this CPOE tool in less than 20% of trauma resuscitation cases. A human factors engineering approach could identify the implementation barriers that are limiting the use of this tool.ObjectivesThe objective was to design a pediatric TBI eCDS tool for trauma resuscitation using a human factors approach. The hypothesis was that clinical experts will rate a usability-enhanced eCDS tool better than the existing CPOE tool for user interface design and suitability for clinical use.MethodsThis mixed-methods study followed usability evaluation principles. Pediatric emergency physicians were surveyed to identify barriers to using the existing eCDS tool. Using standard trauma resuscitation protocols, a hierarchical task analysis of pediatric TBI evaluation was developed. Five clinical experts, all board-certified pediatric emergency medicine faculty members, then iteratively modified the hierarchical task analysis until reaching consensus. The software team developed a prototype eCDS display using the hierarchical task analysis. Three human factors engineers provided feedback on the prototype through a heuristic evaluation, and the software team refined the eCDS tool using a rapid prototyping process. The eCDS tool then underwent iterative usability evaluations by the five clinical experts using video review of 50 trauma resuscitation cases. A final eCDS tool was created based on their feedback, with content analysis of the evaluations performed to ensure all concerns were identified and addressed.ResultsAmong 26 EPs (76% response rate), the main barriers to using the existing tool were that the information displayed is redundant and does not fit clinical workflow. After the prototype eCDS tool was developed based on the trauma resuscitation hierarchical task analysis, the human factors engineers rated it to be better than the CPOE tool for nine of 10 standard user interface design heuristics on a three-point scale. The eCDS tool was also rated better for clinical use on the same scale, in 84% of 50 expert-video pairs, and was rated equivalent in the remainder. Clinical experts also rated barriers to use of the eCDS tool as being low.ConclusionsAn eCDS tool for diagnostic imaging designed using human factors engineering methods has improved perceived usability among pediatric emergency physicians.
| S-EPMC5338692 | biostudies-literature