The limitations and benefits of patient-reported outcome measures, in defining the merits of arthroplasty surgery, are discussed.

Cite this article: Bone Joint J 2015;97-B:578–81.

The OpenAI chatbot ChatGPT is an artificial intelligence (AI) application that uses state-of-the-art language processing AI. It can perform a vast number of tasks, from writing poetry and explaining complex quantum mechanics, to translating language and writing research articles with a human-like understanding and legitimacy. Since its initial release to the public in November 2022, ChatGPT has garnered considerable attention due to its ability to mimic the patterns of human language, and it has attracted billion-dollar investments from Microsoft and PricewaterhouseCoopers. The scope of ChatGPT and other large language models appears infinite, but there are several important limitations. This editorial provides an introduction to the basic functionality of ChatGPT and other large language models, their current applications and limitations, and the associated implications for clinical practice and research.

Cite this article: Bone Joint J 2023;105-B(6):587–589.

The effective capture of outcome measures in the healthcare setting can be traced back to Florence Nightingale’s investigation of the in-patient mortality of soldiers wounded in the Crimean war in the 1850s. Only relatively recently has the formalised collection of outcomes data into Registries been recognised as valuable in itself. With the advent of surgeon league tables and a move towards value based health care, individuals are being driven to collect, store and interpret data. Following the success of the National Joint Registry, the British Association of Spine Surgeons instituted the British Spine Registry. Since its launch in 2012, over 650 users representing the whole surgical team have registered and during this time, more than 27 000 patients have been entered onto the database. There has been significant publicity regarding the collection of outcome measures after surgery, including patient-reported scores. Over 12 000 forms have been directly entered by patients themselves, with many more entered by the surgical teams. Questions abound: who should have access to the data produced by the Registry and how should they use it? How should the results be reported and in what forum?. Cite this article: Bone Joint J 2015;97-B:871–4

The Bone & Joint Journal provides the latest evidence to guide the clinical practice of orthopaedic surgeons. The benefits of one intervention compared with another are presented using outcome measures; some may be specific to a limb or joint and some are more general health-related quality of life measures. Readers will be familiar with many of these outcome measures and will be able to judge the relative benefits of different interventions when measured using the same outcome tool; for example, different treatments for pain in the knee measured using a particular knee score. But, how should readers compare outcomes between different clinical areas using different outcome measures? This article explores the use of standardised effect sizes.

Cite this article: Bone Joint J 2014;96-B:853–4.

We explore the limitations of complete reliance on evidence-based medicine which can be diminished by confounding issues and sampling bias. Other strategies which may be reasonably invoked are discussed.

Cite this article: Bone Joint J 2014; 96-B:997–9.