Machine learning-based prediction of perioperative complications in spine surgery: a large-scale model…

AI / informaticsEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society· Jul 2026

Machine learning-based prediction of perioperative complications in spine surgery: a large-scale model development and validation study.

Andrea Campagner, Francesco Langella, Pablo Bellosta-López … Pedro Berjano

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Prediction Models & Risk ScoresAI / informaticsPrognosisQ1IF 3.2

Random forest model predicted perioperative spine surgery complications with 0.87 AUC.

Machine learning-based prediction of perioperative complications in spine surgery: a large-scale model development and validation study.

Andrea Campagner … Pedro Berjano

European spine journal · Jul 2026

Background

Spinal surgery carries substantial perioperative risks.

Purpose

To develop and validate machine learning models for predicting perioperative complications in spine surgery, and assess fairness across patient subgroups.

Methods

We conducted a retrospective cohort study of 5,060 adult patients from the SpineReg registry (2015-2023), each with 160 preoperative demographic, clinical, imaging, and patient-reported outcome features.

n = 5,060 adult

Results

0.87

correctly separated higher from lower risk patients most of the time

n = 5,060 adult

More results

Random forest maintained robust performance across demographic and surgical subgroups.

Key predictors of increased complication risk included sagittal imbalance, and multilevel surgery, whereas degenerative pathology and monosegmental fusion were protective.

More results

Sensitivity declined for rare complications but exceeded 75% for most categories.

“

Conclusion · 1 of 2

Random forest-based models can accurately and equitably predict perioperative complications in diverse spine surgery contexts, supporting personalized counseling, targeted monitoring, and optimized resource allocation.

Conclusion · 2 of 2

Integration into clinical decision support systems may enhance surgical safety and efficiency.

Machine learning-based prediction of perioperative complications in spine surgery: a large-scale model development and validation study.

Machine learning-based prediction of perioperative complications in spine surgery: a large-scale model development and validation study.

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