Predicting long-term outcomes of kidney transplantation in the era of artificial intelligence.

The ability to accurately predict long-term kidney transplant survival can assist nephrologists in making therapeutic decisions. However, predicting kidney transplantation (KT) outcomes is challenging due to the complexity of the factors involved. Artificial intelligence (AI) has become an increasingly important tool in the prediction of medical outcomes.

Toward generalizing the use of artificial intelligence in nephrology and kidney transplantation.

With its robust ability to integrate and learn from large sets of clinical data, artificial intelligence (AI) can now play a role in diagnosis, clinical decision making, and personalized medicine. It is probably the natural progression of traditional statistical techniques. Currently, there are many unmet needs in nephrology and, more particularly, in the kidney transplantation (KT) field.

Personal protective equipment (PPE) disposal during COVID-19: An emerging source of microplastic and microfiber pollution in the environment.

Waste generated by healthcare facilities during the COVID-19 pandemic has become a new source of pollution, particularly with the widespread use of single-use personal protective equipment (PPE). Releasing microplastics (MPs) and microfibers (MFs) from discarded PPE becomes an emerging threat to environmental sustainability. MPs/MFs have recently been reported in a variety of aquatic and terrestrial ecosystems, including water, deep-sea sediments, air, and soil.

End-stage renal disease at dialysis initiation: Epidemiology and mortality risks during the first year of hemodialysis.

Chronic kidney disease (CKD) treated by hemodialysis (HD) is a worldwide major public health problem. Its incidence is getting higher and higher, leading to an alarming social and economic impact. The survival of these patients is significantly low, especially during the first year of treatment.