FUSE-ML: development and external validation of a clinical prediction model for mid-term outcomes after lumbar spinal fusion for degenerative disease.

Publication

FUSE-ML: development and external validation of a clinical prediction model for mid-term outcomes after lumbar spinal fusion for degenerative disease.

Journal Paper/Review - Feb 21, 2022

Staartjes Victor E, Stumpo Vittorio, Ricciardi Luca, Maldaner Nicolai, Eversdijk Hubert A J, Vieli Moira, Ciobanu-Caraus Olga, Raco Antonino, Miscusi Massimo, Perna Andrea, Proietti Luca, Lofrese Giorgio, Dughiero Michele, Cultrera Francesco, Nicassio Nicola, An Seong Bae, Ha Yoon, Amelot Aymeric, Alcobendas Irene, Viñuela-Prieto Jose M, Gandía-González Maria L, Girod Pierre-Pascal, Lener Sara, Kögl Nikolaus, Abramovic Anto, Safa Nico Akhavan, Laux Christoph J, Farshad Mazda, O'Riordan Dave, Loibl Markus, Mannion Anne F, Scerrati Alba, Molliqaj Granit, Tessitore Enrico, Schröder Marc L, Vandertop W Peter, Stienen Martin N, Regli Luca, Serra Carlo

Citation

Staartjes V, Stumpo V, Ricciardi L, Maldaner N, Eversdijk H, Vieli M, Ciobanu-Caraus O, Raco A, Miscusi M, Perna A, Proietti L, Lofrese G, Dughiero M, Cultrera F, Nicassio N, An S, Ha Y, Amelot A, Alcobendas I, Viñuela-Prieto J, Gandía-González M, Girod P, Lener S, Kögl N, Abramovic A, Safa N, Laux C, Farshad M, O'Riordan D, Loibl M, Mannion A, Scerrati A, Molliqaj G, Tessitore E, Schröder M, Vandertop W, Stienen M, Regli L, Serra C. FUSE-ML: development and external validation of a clinical prediction model for mid-term outcomes after lumbar spinal fusion for degenerative disease. Eur Spine J 2022; 31:2629-2638.

Type

Journal Paper/Review (English)

Journal

Eur Spine J 2022; 31

Publication Date

Feb 21, 2022

Issn Electronic

1432-0932

Pages

2629-2638

Brief description/objective

Indications and outcomes in lumbar spinal fusion for degenerative disease are notoriously heterogenous. Selected subsets of patients show remarkable benefit. However, their objective identification is often difficult. Decision-making may be improved with reliable prediction of long-term outcomes for each individual patient, improving patient selection and avoiding ineffective procedures.