Machine learning–based identification and ranking of risk factors for lumbar paraspinal muscle atrophy - Scorecard - MDSpire

Machine learning–based identification and ranking of risk factors for lumbar paraspinal muscle atrophy

  • By

  • Lukas Schönnagel

  • Tom Folkerts

  • Ali Guven

  • Erika Chiapparelli

  • Jiaqi Zhu

  • Gaston Camino-Willhuber

  • Thomas Caffard

  • Artine Arzani

  • Paul Köhli

  • Marco D. Burkhard

  • Jennifer Shue

  • Andrew A. Sama

  • Federico P. Girardi

  • Frank P. Cammisa

  • Alexander P. Hughes

  • March 28, 2026

  • 0 min

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Clinical Scorecard: Utilizing Machine Learning to Identify and Prioritize Risk Factors for Atrophy of Lumbar Paraspinal Muscles

At a Glance

CategoryDetail
Condition
Key MechanismsImpairment of paraspinal muscles, particularly the multifidus, leads to increased intradiscal forces and lower back pain.
Target Population
Care Setting

Key Highlights

  • Machine learning models developed to predict severe paraspinal muscle atrophy, correlating MRI findings with clinical outcomes.
  • Factors influencing muscle atrophy include age, sex, BMI, and comorbidities, with specific emphasis on their clinical implications.

Guideline-Based Recommendations

Diagnosis

    Management

    • Consider demographic and radiologic factors in preoperative assessments, and implement targeted interventions based on identified risk factors.

    Monitoring & Follow-up

      Risks

        Patient & Prescribing Data

        Patients with degenerative spinal conditions undergoing surgery.

        Machine learning can enhance individual risk assessment for muscle atrophy.

        Clinical Best Practices

        • Incorporate comprehensive risk factor analysis in surgical planning, utilizing advanced imaging techniques like MRI for accurate assessment of paraspinal musculature.

        Related Resources & Content

        Original Source(s)

        Machine learning–based identification and ranking of risk factors for lumbar paraspinal muscle atrophy

        • by Lukas Schönnagel, Tom Folkerts, Ali Guven, Erika Chiapparelli, Jiaqi Zhu, Gaston Camino-Willhuber, Thomas Caffard, Artine Arzani, Paul Köhli, Marco D. Burkhard, Jennifer Shue, Andrew A. Sama, Federico P. Girardi, Frank P. Cammisa, Alexander P. Hughes

        • March 28, 2026

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