Conectar
A non-contrast CT head scan (NCCTH) is the most common cross-sectional imaging investigation requested in the emergency department. Advances in computer vision have led to development of several artificial intelligence (AI) tools to detect abnormalities on NCCTH. These tools are intended to provide clinical decision support for clinicians, rather than stand-alone diagnostic devices. However, validation studies mostly compare AI performance against radiologists, and there is relative paucity of evidence on the impact of AI assistance on other healthcare staff who review NCCTH in their daily clinical practice.
A retrospective data set of 150 NCCTH will be compiled, to include 60 control cases and 90 cases with intracranial haemorrhage, hypodensities suggestive of infarct, midline shift, mass effect or skull fracture. The intracranial haemorrhage cases will be subclassified into extradural, subdural, subarachnoid, intraparenchymal and intraventricular. 30 readers will be recruited across four National Health Service (NHS) trusts including 10 general radiologists, 15 emergency medicine clinicians and 5 CT radiographers of varying experience. Readers will interpret each scan first without, then with, the assistance of the qER EU 2.0 AI tool, with an intervening 2-week washout period. Using a panel of neuroradiologists as ground truth, the stand-alone performance of qER will be assessed, and its impact on the readers’ performance will be analysed as change in accuracy (area under the curve), median review time per scan and self-reported diagnostic confidence. Subgroup analyses will be performed by reader professional group, reader seniority, pathological finding, and neuroradiologist-rated difficulty.
The study has been approved by the UK Healthcare Research Authority (IRAS 310995, approved 13 December 2022). The use of anonymised retrospective NCCTH has been authorised by Oxford University Hospitals. The results will be presented at relevant conferences and published in a peer-reviewed journal.
by Jaclyn Schess, Lydia Bennett-Li, Richard Velleman, Urvita Bhatia, Alexander Catalano, Abhijeet Jambhale, Abhijit Nadkarni
Globally, alcohol consumption causes significant societal harm and is a leading risk factor for death and disability in adults. In India, 3.7% of all deaths and 3.1% disability adjusted life years (DALYs) can be attributed to alcohol. In the context of rapid economic development and emphasized by the COVID-19 pandemic, India’s lack of a consolidated and comprehensive alcohol policy has posed significant challenges to addressing this harm. In this context, the aim of our review was to undertake a comprehensive mapping of the State and national policy environment surrounding alcohol and its use in India, based on an analysis of policy documents. We did this though a scoping review of academic and grey literature, which helped to iteratively identify the websites of 15 international organizations, 21 Indian non-governmental organizations, and eight Indian Federal governmental organizations as well as State/Union Territory government sites, to search for relevant policy documents. We identified 19 Federal policy documents and 36 State level policy documents within which we have identified the specific policy measures which address the 10 categories of the World Health Organization’s Global Action Plan to Reduce the Harmful Use of Alcohol. We found that there are major gaps in regulation of marketing and price controls, with much of this controlled by the States. In addition, regulation of availability of alcohol varies widely throughout the country, which is also a policy area controlled locally by States. Through the clear elucidation of the current policy environment surrounding alcohol in India, policy makers, researchers and advocates can create a clearer roadmap for future reform.
FreshRSS 