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NCT05161130: FUSE-ML

Predicting Outcomes After Lumbar Fusion for Degenerative Disease

Completed Last updated 10 January 2022
What this trial tests

trial testing Lumbar Spinal Fusion in Low Back Pain in 1,115 participants. Completed in 1 November 2021.

Timeline
1 January 2021
Primary endpoint
1 November 2021
1 November 2021

Quick facts

Lead sponsorBergman Clinics
StatusCompleted
Study typeOBSERVATIONAL
Enrollment1,115
Start date1 January 2021
Primary completion1 November 2021
Estimated completion1 November 2021
Sites4 locations across Austria, Netherlands, France

Drugs / interventions tested

Conditions studied

Sponsor

Bergman Clinics

Who can join

18 and older, any sex, with Low Back Pain or Disk Herniated Lumbar. Patients with the condition only — healthy volunteers not accepted.

Sponsor's own description

The aim of the FUSE-ML study is to develop and externally validate a robust ML-based prediction tool based on multicenter data from a range of international centers that will provide individualized risk-benefit profiles tailored to each patient undergoing lumbar spinal fusion for degenerative disease. Data will be collected by a range of international centers.

Publications & conference data

1 peer-reviewed publication reference this trial (live from Europe PMC):

  1. Artificial Intelligence in Neurosurgery: A State-of-the-Art Review from Past to Future.
    Tangsrivimol JA, Schonfeld E, Zhang M, Veeravagu A, et al · · 2023 · cited 43× · PMID 37510174 · DOI 10.3390/diagnostics13142429

Verify or expand the search:

Other recruiting trials for Low Back Pain

Currently open trials in the same condition.

Other Bergman Clinics trials

Trials by the same sponsor.

Verify against primary sources

Data sources for this page

Drug Landscape aggregates and links these public records for informational use only. Always verify against the primary source before clinical or regulatory decisions. Canonical URL: https://druglandscape.com/trial/NCT05161130.

Primary sources · FDA · ClinicalTrials.gov · EMA · SEC EDGAR · ChEMBL · Wikidata · full sourcing