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Generative artificial intelligence (AI) describes technology that can create new content, including text, images and audio, based on patterns and structures learnt from existing data. Large language models (LLM) are types of generative AI models that are trained on vast amounts of online data and employ natural language processing, designed to mimic human language and communication. 

Since the release of ChatGPT 3.5 by OpenAI in November 2022, there has been a significant rise in interest in and development of LLM chatbot technology, which has become increasingly sophisticated. Now other companies, such as Google, have developed LLM AI technology integrated into search engines via plug-ins.

ChatGPT, and other AI chatbots, have not been designed for (or licensed to) provide medical information and advice. Despite ChatGPT usage policies dictating that medical and health advice without review by a qualified professional may significantly impair safety and wellbeing, the policy is not prohibitory. Therefore there’s increasing concern regarding the unregulated ‘off licence’ use by members of the public.

Some of you might be asking (or have forgotten) – what is this eFONA registry thing? Why? 

In short, emergency front-of-neck access is an unusual, emergency event about which we have limited information – what leads up to it, what happens during the event, what happens afterwards. Various studies, not least NAP4, have highlighted the need to understand more – so, the eFONA registry project was born.

Dear Editor

Drs Passi and Oliver state in their article that ‘in-vivo studies to quantify the reduction in serum progesterone concentration following sugammadex have not been performed…’. They are incorrect in this statement.

Devoy et al performed a prospective observational study comparing changes in serum oestrogen and progesterone in women undergoing surgery. 60 patients on hormonal contraception received sugammadex; 30 patients were not on hormonal contraception and did not receive sugammadex; 32 patients were not on hormonal contraception and did receive sugammadex. Blood samples pre, 15-minutes post, 240 min post sugammadex administration were taken to measure oestrogen and progesterone levels. 

Author: Dr Carolyn Johnston, Consultant Anaesthetist and Deputy Medical Director, St George’s Hospital; Chair of QI working group

During the early days of the COVID-19 pandemic, the UK government talked about their goal of delivering ‘shots in arms’ as the ultimate goal of the vaccine efforts. This wasn’t an exercise in expanding scientific knowledge or customising production, but the aim was clearly stated as being to deliver those advances to citizens in order to prevent them from becoming patients.

A large number of lives were saved by rapid development and national deployment of the new vaccines: the success of the vaccine programme is a reminder to us all how knowledge without application will not improve care.

The HSRC portfolio of projects creates a huge amount of knowledge that has the potential to improve care for our patients, but this knowledge remains potential unless we implement the recommendations of the various reports and use the rich datasets created to inform us of the most pressing areas for improvement in our clinical pathways.