The quality and readability of patient information provided by ChatGPT: can AI reliably explain common ENT operations?

PURPOSE: Access to high-quality and comprehensible patient information is crucial. However, information provided by increasingly prevalent Artificial Intelligence tools has not been thoroughly investigated. This study assesses the quality and readability of information from ChatGPT regarding three index ENT operations: tonsillectomy, adenoidectomy, and grommets. METHODS: We asked ChatGPT standard and simplified questions. Readability was calculated using Flesch-Kincaid Reading Ease Score (FRES), Flesch-Kincaid Grade Level (FKGL), Gunning Fog Index (GFI) and Simple Measure of Gobbledygook (SMOG) scores. We assessed quality using the DISCERN instrument and compared these with ENT UK patient leaflets. RESULTS: ChatGPT readability was poor, with mean FRES of 38.9 and 55.1 pre- and post-simplification, respectively. Simplified information from ChatGPT was 43.6% more readable (FRES) but scored 11.6% lower for quality. ENT UK patient information readability and quality was consistently higher. CONCLUSIONS: ChatGPT can simplify information at the expense of quality, resulting in shorter answers with important omissions. Limitations in knowledge and insight curb its reliability for healthcare information. Patients should use reputable sources from professional organisations alongside clear communication with their clinicians for well-informed consent and making decisions.

DNA Methylation and Non-Coding RNAs during Tissue-Injury Associated Pain.

While about half of the population experience persistent pain associated with tissue damages during their lifetime, current symptom-based approaches often fail to reduce such pain to a satisfactory level. To provide better patient care, mechanism-based analgesic approaches must be developed, which necessitates a comprehensive understanding of the nociceptive mechanism leading to tissue injury-associated persistent pain. Epigenetic events leading the altered transcription in the nervous system are pivotal in the maintenance of pain in tissue injury. However, the mechanisms through which those events contribute to the persistence of pain are not fully understood. This review provides a summary and critical evaluation of two epigenetic mechanisms, DNA methylation and non-coding RNA expression, on transcriptional modulation in nociceptive pathways during the development of tissue injury-associated pain. We assess the pre-clinical data and their translational implication and evaluate the potential of controlling DNA methylation and non-coding RNA expression as novel analgesic approaches and/or biomarkers of persistent pain.