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Which sagittal plane assessment method is most predictive of complications after adult spinal deformity surgery?

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Abstract

Purpose

Different methods of sagittal alignment assessment compete for predicting adverse events after adult spinal deformity (ASD) surgery. We wanted to study which method provides greater benefit.

Methods

Retrospective study of 391 patients operated for ASD, with > 6 instrumented levels, fused to the pelvis, and 2 years of follow-up. Three alignment methods were analyzed 6-week postoperatively: (1) Roussouly mismatch; (2) GAP score/GAP categories; (3) T4-L1-Hip axis. Binary logistic regression generated models that best predict the following adverse events: mechanical complications (MC): in general and isolated (PJK, PJF, rod breakage); reinterventions (in general and after MC); and readmissions. ROC/AUC analysis was also implemented. In a second regression round, we added different variables that were selected on univariate analysis—demographic, surgical, and radiographic—to complete the models.

Results

The best predictor parameters in most models were T4-L1PA mismatch and GAP score; we could not prove a predictive ability of the Roussouly mismatch. The T4-L1PA mismatch best predicted general MC, PJK, PJK + PJF, and readmission, while the GAP score best predicted PJF and reinterventions (for MC and for any complication). However, the variance explained by these models was limited (Nagelkerke's R2 = 0.031–0.113), with odds ratios ranging from 1.070 to 1.456. ROC curves plotted an AUC between 0.57 and 0.70. Introducing additional variables (demographic, surgical, and radiographic) improved prediction in all the models (Nagelkerke's R2 = 0.082–0.329) and allowed predicting rod breakage.

Conclusion

The T4-L1-Hip axis and GAP score show potential in predicting adverse events, surpassing the Roussouly method. Despite partial efficacy in complication anticipation, recognizing postoperative sagittal alignment as a key modifiable risk factor, the crucial need arises to integrate diverse variables, both modifiable and non-modifiable, for enhanced predictive accuracy.

Level of evidence

Level IV.

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Data availability

All data were from a multicenter European database.

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Acknowledgements

This study was presented at the GEER meeting 2023.

Funding

A DePuy Synthes Spine and Medtronic research grants were received in partial support of this work. The device(s)/drug(s) is/are FDA approved or approved by the corresponding national agency for this indication. No benefits in any form have been or will be received from a commercial party related directly or indirectly to the subject of this manuscript.

Author information

Authors and Affiliations

  1. Spine Unit, Department of Orthopedic Surgery, Hospital Universitario La Paz, Paseo de la Castellana 261, 28046, Madrid, Spain

    Javier Pizones, Lucía Moreno-Manzanaro & Francisco Javier Sánchez Perez-Grueso

  2. University of Texas, San Antonio, TX, USA

    Jeffrey Hills

  3. Rady Children Hospital San Diego, University of California, San Diego, CA, USA

    Michael Kelly

  4. Department of Orthopedics and Traumatology, Acibadem Mehmet Ali Aydinlar University, Istanbul, Turkey

    Caglar Yilgor & Ahmet Alanay

  5. Department of Orthopedics, Schulthess Klinik, Zurich, Switzerland

    Frank Kleinstück

  6. Spine Surgery Unit, Pellegrin University Hospital, Bordeaux, France

    Ibrahim Obeid

  7. Spine Surgery Unit, Hospital Universitario Vall d’Hebron, Barcelona, Spain

    Ferran Pellisé

Authors
  1. Javier Pizones
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Consortia

ESSG European Spine Study Group

Contributions

All authors have done the following: Substantial contributions to the conception and design of the work, acquisition, analysis, or interpretation of data. Drafting the work and revising it critically for important intellectual content. Final approval of the version to be published. And all authors agree to be accountable for the author’s own contributions and for ensuring that questions related to the accuracy or integrity of any part of the work, even ones in which the author was not personally involved, are appropriately investigated, resolved, and documented in the literature.

Corresponding author

Correspondence to Javier Pizones.

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Conflict of interest

Javier Pizones, Jeffrey Hills, Lucía Moreno-Manzanaro, and Francisco Javier Sánchez Perez-Grueso have nothing to disclose. Michael Kelly received honorarium from Wolters Kluwer. Caglar Yilgor is a Consultant for Medtronic. Frank Kleinstück did teaching and speaking for DePuy Synthes. Ibrahim Obeid received grants from DePuy synthes and did consulting for DePuy synthes, Medtronic, Clariance, Spineart, Alphatec. Ahmet Alanay received grants from Medtronic, DePuy Synthes is a Consultant for Globus medical and ZimVie. Ferran Pellisé is a Consultant for Medtronic and Depuy Synthes.

Institutional review board

Ethical approval was obtained before patient enrollment and data collection protocols. The procedures used in this study adhere to the tenets of the Declaration of Helsinki.

Informed consent

All the participating patients gave prior informed consent to their inclusion in this study. Patients signed informed consent regarding publishing their data and photographs.

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Pizones, J., Hills, J., Kelly, M. et al. Which sagittal plane assessment method is most predictive of complications after adult spinal deformity surgery?. Spine Deform (2024). https://doi.org/10.1007/s43390-024-00864-5

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