Study of capsule endoscopy delivery at scale through enhanced artificial intelligence-enabled analysis (the CESCAIL study).

AIM: Lower gastrointestinal (GI) diagnostics have been facing relentless capacity constraints for many years, even before the COVID-19 era. Restrictions from the COVID pandemic have resulted in a significant backlog in lower GI diagnostics. Given recent developments in deep neural networks (DNNs) and the application of artificial intelligence (AI) in endoscopy, automating capsule video analysis is now within reach. Comparable to the efficiency and accuracy of AI applications in small bowel capsule endoscopy, AI in colon capsule analysis will also improve the efficiency of video reading and address the relentless demand on lower GI services. The aim of the CESCAIL study is to determine the feasibility, accuracy and productivity of AI-enabled analysis tools (AiSPEED) for polyp detection compared with the 'gold standard': a conventional care pathway with clinician analysis. METHOD: This multi-centre, diagnostic accuracy study aims to recruit 674 participants retrospectively and prospectively from centres conducting colon capsule endoscopy (CCE) as part of their standard care pathway. After the study participants have undergone CCE, the colon capsule videos will be uploaded onto two different pathways: AI-enabled video analysis and the gold standard conventional clinician analysis pathway. The reports generated from both pathways will be compared for accuracy (sensitivity and specificity). The reading time can only be compared in the prospective cohort. In addition to validating the AI tool, this study will also provide observational data concerning its use to assess the pathway execution in real-world performance. RESULTS: The study is currently recruiting participants at multiple centres within the United Kingdom and is at the stage of collecting data. CONCLUSION: This standard diagnostic accuracy study carries no additional risk to patients as it does not affect the standard care pathway, and hence patient care remains unaffected.

Clinicians' Guide to Artificial Intelligence in Colon Capsule Endoscopy-Technology Made Simple.

Artificial intelligence (AI) applications have become widely popular across the healthcare ecosystem. Colon capsule endoscopy (CCE) was adopted in the NHS England pilot project following the recent COVID pandemic's impact. It demonstrated its capability to relieve the national backlog in endoscopy. As a result, AI-assisted colon capsule video analysis has become gastroenterology's most active research area. However, with rapid AI advances, mastering these complex machine learning concepts remains challenging for healthcare professionals. This forms a barrier for clinicians to take on this new technology and embrace the new era of big data. This paper aims to bridge the knowledge gap between the current CCE system and the future, fully integrated AI system. The primary focus is on simplifying the technical terms and concepts in machine learning. This will hopefully address the general "fear of the unknown in AI" by helping healthcare professionals understand the basic principle of machine learning in capsule endoscopy and apply this knowledge in their future interactions and adaptation to AI technology. It also summarises the evidence of AI in CCE and its impact on diagnostic pathways. Finally, it discusses the unintended consequences of using AI, ethical challenges, potential flaws, and bias within clinical settings.

Prospective, randomised, parallel-group, open-label study to evaluate the effectiveness and safety of IMU-838, in combination with oseltamivir, in adults with COVID-19: the IONIC trial protocol.

BACKGROUND: Globally, there is a scarcity of effective treatments for SARS-CoV-2 infections (causing COVID-19). Repurposing existing medications may offer the best hope for treating patients with COVID-19 to curb the pandemic. IMU-838 is a dihydroorotate dehydrogenase inhibitor, which is an effective mechanism for antiviral effects against respiratory viruses. When used synergistically with oseltamivir, therapeutic effects have been observed against influenza and SARS-CoV-2 in rodents. The IMU-838 and Oseltamivir in the Treatment of COVID-19 (IONIC) trial is a randomised controlled trial that will investigate whether time to clinical improvement in patients with COVID-19 is improved following a 14-day course of IMU-838+oseltamivir versus oseltamivir alone. METHODS: IONIC trial is an open-label study in which participants will be randomised 1:1 in two parallel arms: the intervention arm (IMU-838+oseltamivir) and the control arm (oseltamivir only). The primary outcome is time to clinical improvement; defined as the time from randomisation to a two-point improvement on WHO ordinal scale; discharge from hospital, or death (whichever occurs first). The study is sponsored by the University Hospitals Coventry and Warwickshire NHS Trust and funded by LifeArc. DISCUSSION: The IONIC protocol describes an overarching trial design to provide reliable evidence on the effectiveness of IMU-838 (vidofludimus calcium) when delivered in combination with an antiviral therapy (oseltamivir) (IONIC intervention) for confirmed or suspected COVID-19 infection in adult patients receiving usual standard of care. ETHICS AND DISSEMINATION: This study has been independently reviewed and approved by Wales Research Ethics Committee. In addition, required regulatory approvals were received from Medicines and Healthcare products Regulatory Agency. TRIAL REGISTRATION NUMBER: EudraCT 2020-001805-21, ISRCTN53038326, NCT04516915.

C-reactive protein and albumin association with mortality of hospitalised SARS-CoV-2 patients: A tertiary hospital experience.

OBJECTIVE: The objective was to study hospitalised COVID-19 patients' mortality and intensive care unit (ICU) admission with covariates of interest (age, gender, ethnicity, clinical presentation, comorbidities and admission laboratory findings). METHODS: Logistic regression analyses were performed for patients admitted to University Hospital, University Hospitals Coventry and Warwickshire NHS Trust, between 24 January 2020 - 13 April 2020. RESULTS: There were 321 patients hospitalised. Median age was 73 years and 189 (59%) were male. Ethnicity was divided between Caucasian (77%), and black, Asian, and minority ethnic (BAME) groups (23%). Commonest symptoms were dyspnoea (62.9%), fever (59.1%) and cough (56%). Gastrointestinal symptoms amounted to 11.8%.Forty-four patients (13.7%) received ICU care. ICU male to female ratio was 3:1 (p=0.027; odds ratio (OR) 2.3; 95% confidence interval (CI) 1.1-4.9), BAME (p=0.008; OR 2.5; 95% CI 1.3-4.9), age >65 years (p=0.026; OR 0.28; 95% CI 0.09-0.93), heart disease (p=0.009; OR 0.2; 95% CI 0.1-0.6) and elevated C-reactive protein (CRP; p<0.001; OR 1.004; 95% CI 1.002-1.008) were associated with ICU admission.One-hundred and four patients (32.4%) died. Age >65 years (p=0.011; OR 5; 95% CI 1.6-21.9), neutrophils (p=0.047), neutrophil:lymphocyte ratio (NLR; p=0.028), CRP (p<0.001) and albumin (p=0.002) were associated with mortality. When analysis adjusted for age, CRP (p<0.001; OR 1.006; 95% CI 1.004-1.008) and albumin (p=0.005; OR 0.94; 95% CI 0.90-0.98) remained associated with mortality. CONCLUSIONS: COVID-19 has high mortality. BAME and male patients were associated with ICU admission. High CRP and low albumin (after correcting for age) were associated with mortality.