Shifting Determinants of Mortality Risk After Orthotopic Heart Transplantation Identified by Machine Learning
Kinga Bianka Koritsánszky, Rita Szentgróti, Ádám Szijártó, Márton Tokodi, Alexandra Vereb, Andrea Kőszegi, Balázs Sax, Attila Kovács, Béla Merkely, Andrea Székely, Ioannis Paraskevaidis · 2025
Read Shifting Determinants of Mortality Risk After Orthotopic Heart Transplantation Identified by Machine Learning by Kinga Bianka Koritsánszky, Rita Szentgróti, Ádám Szijártó, Márton Tokodi, Alexandra Vereb, Andrea Kőszegi, Balázs Sax, Attila Kovács, Béla Merkely, Andrea Székely, Ioannis Paraskevaidis (2025) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-12734402.txt.
Description
What kills a heart transplant patient in the first month is not what kills them in the first year. Kinga Koritsánszky and co-authors trained random forest models on 581 recipients and pried them open with explanation tools. Judged on pre-surgery data alone, the models were modest; fed the post-surgery course, they became sharp.
Early deaths were foreshadowed by acute stress: failing liver signals, inflammation, unstable circulation. Later deaths leaned on kidney function, metabolic reserve, and frailty. The shifting cast of predictors suggests follow-up should change its watchlist as the months pass, rather than guarding against one fixed profile of risk.
Catalog record
| CREATOR | Kinga Bianka Koritsánszky, Rita Szentgróti, Ádám Szijártó, Márton Tokodi, Alexandra Vereb, Andrea Kőszegi, Balázs Sax, Attila Kovács, Béla Merkely, Andrea Székely, Ioannis Paraskevaidis |
|---|---|
| YEAR | 2025 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 41 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |