Anemia is a common hematological disorder that affects 12% of the community-dwelling population, 40% of hospitalized patients, and 47% of nursing home residents. Our understanding of the impact of inflammation on iron metabolism and erythropoiesis is still lacking. In older adults, anemia can be divided into nutritional deficiency anemia, bleeding anemia, and unexplained anemia. The last type of anemia might be caused by reduced erythropoietin (EPO) activity, progressive EPO resistance of bone marrow erythroid progenitors, and the chronic subclinical pro-inflammatory state. Overall, one-third of older patients with anemia demonstrate a nutritional deficiency, one-third have a chronic subclinical pro-inflammatory state and chronic kidney disease, and one-third suffer from anemia of unknown etiology. Understanding anemia’s pathophysiology in people aged 65 and over is crucial because it contributes to frailty, falls, cognitive decline, decreased functional ability, and higher mortality risk. Inflammation produces adverse effects on the cells of the hematological system. These effects include iron deficiency (hypoferremia), reduced EPO production, and the elevated phagocytosis of erythrocytes by hepatic and splenic macrophages. Additionally, inflammation causes enhanced eryptosis due to oxidative stress in the circulation. Identifying mechanisms behind age-related inflammation is essential for a better understanding and preventing anemia in older adults.

In November 2022, OpenAI released a chatbot named ChatGPT, a product capable of processing natural language to create human-like conversational dialogue. It has generated a lot of interest, including from the scientific community and the medical science community. Recent publications have shown that ChatGPT can correctly answer questions from medical exams such as the United States Medical Licensing Examination and other specialty exams. To date, there have been no studies in which ChatGPT has been tested on specialty questions in the field of nephrology anywhere in the world. Using the ChatGPT-3.5 and -4.0 algorithms in this comparative cross-sectional study, we analysed 1560 single-answer questions from the national specialty exam in nephrology from 2017 to 2023 that were available in the Polish Medical Examination Center's question database along with answer keys. Of the 1556 questions posed to ChatGPT-4.0, correct answers were obtained with an accuracy of 69.84%, compared with ChatGPT-3.5 (45.70%, P = .0001) and with the top results of medical doctors (85.73%, P = .0001). Of the 13 tests, ChatGPT-4.0 exceeded the required ≥60% pass rate in 11 tests passed, and scored higher than the average of the human exam results. ChatGPT-3.5 was not spectacularly successful in nephrology exams. The ChatGPT-4.0 algorithm was able to pass most of the analysed nephrology specialty exams. New generations of ChatGPT achieve similar results to humans. The best results of humans are better than those of ChatGPT-4.0.