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Deciphering Geoenvironmental Determinants of Chronic Kidney Disease of Unknown Etiology: An Integrated Trace-Metal, Hydrological and Explainable Machine-Learning Framework for the Sri Lankan Dry Zone

Key takeaways

In Sri Lanka's dry zone, many farm workers get kidney disease with no known cause. Researchers combined water data, trace metal levels, and machine learning to find which environmental features line up with where the disease clusters. This shows a link between local water and soil conditions and disease patterns, not proof that any one metal causes it. It is a preprint and has not passed peer review.

Who did this work

Nalika R. Dayananda (Wickramarachchi University of Indigenous Medicine) · Janitha A. Liyanage (University of Kelaniya)

Source

Paper · OpenAlex, Kidney disease concept sweep (verified C2778653478) · 2026-09-08
https://doi.org/10.21203/rs.3.rs-10887936/v1