The extent and depth of routine health care data
are growing at an ever-increasing rate, forming huge repositories
of information. These repositories can answer a vast array of questions.
However, an understanding of the purpose of the dataset used and
the quality of the data collected are paramount to determine the
reliability of the result obtained. This Editorial describes the importance of adherence to sound
methodological principles in the reporting and publication of research
using ‘big’ data, with a suggested reporting framework for future Cite this article:
Cite this article:
Cite this article:
Cite this article:
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:
Cite this article:
Research into COVID-19 has been rapid in response to the dynamic global situation, which has resulted in heterogeneity of methodology and the communication of information. Adherence to reporting standards would improve the quality of evidence presented in future studies, and may ensure that findings could be interpreted in the context of the wider literature. The COVID-19 pandemic remains a dynamic situation, requiring continued assessment of the disease incidence and monitoring for the emergence of viral variants and their transmissibility, virulence, and susceptibility to vaccine-induced immunity. More work is needed to assess the long-term impact of COVID-19 infection on patients who sustain a hip fracture. The International Multicentre Project Auditing COVID-19 in Trauma & Orthopaedics (IMPACT) formed the largest multicentre collaborative audit conducted in orthopaedics in order to provide an emergency response to a global pandemic, but this was in the context of many vital established audit services being disrupted at an early stage, and it is crucial that these resources are protected during future health crises. Rapid data-sharing between regions should be developed, with wider adoption of the revised 2022 Fragility Fracture Network Minimum Common Data Set for Hip Fracture Audit, and a pragmatic approach to information governance processes in order to facilitate cooperation and meta-audit. This editorial aims to: 1) identify issues related to COVID-19 that require further research; 2) suggest reporting standards for studies of COVID-19 and other communicable diseases; 3) consider the requirement of new risk scores for hip fracture patients; and 4) present the lessons learned from IMPACT in order to inform future collaborative studies. Cite this article:
