Defining criteria for optimal lumbar curve correction following the selective thoracic fusion surgery in Lenke 1 adolescent idiopathic scoliosis: developing a decision tree

Eur J Orthop Surg Traumatol. 2020 Apr;30(3):513-522. doi: 10.1007/s00590-019-02596-z. Epub 2019 Nov 23.

Abstract

Objective: The aim of this study was to identify the range of optimal versus suboptimal rates of spontaneous lumbar Cobb correction (SLCC%) and the factors predicting such outcomes in a cohort of Lenke 1 adolescent idiopathic scoliosis (AIS) after posterior spinal fusion surgery.

Methods: Seventy-one consecutive Lenke1 B and C AIS patients with a fusion level to L1 and higher with two-year follow-up were included. Thoracic kyphosis (T1-T4 and T4-T12 TK), lumbar lordosis (L1-S1 LL), thoracic and lumbar Cobb angles, thoracic and lumbar apical vertebral rotations and translations (AVR and AVT), pelvic incidence, sacral slope, and sagittal and frontal balances were measured at preoperative, early postoperative, and two-year follow-up. The SLCC% was calculated between preoperative and two-year follow-up. A clustering analysis determined the subgroups of patients with significantly higher and lower (optimal versus suboptimal) rate of SLCC% in the cohort at two-year follow-up. The cutoff values of the preoperative and early postoperative radiographic parameters that significantly predicted the optimal and suboptimal SLCC% were determined using a decision tree.

Results: The averages of the optimal versus suboptimal range of SLCC% in the cohort were 72% [55%, 105%] versus 39% [- 7%, 42%]. Preoperative and early postoperative spinal parameters predicted the optimal versus suboptimal SLCC% with an accuracy of 82%, 95%CI [0.73-0.94]. Preoperative AVTLumbar < 10 mm was a predictor of optimal SLCC%. In patients with a preoperative AVTLumbar > 10 mm, early postoperative T4-T12 TK < 24° (but not less than 17°) accompanied by - 5° < AVRThoracic < 5° were the main predictors of optimal SLCC% in our cohort.

Conclusion: Quantitative clustering of the SLCC% into optimal and suboptimal groups allowed identifying the cutoff values of preoperative (AVTLumbar) and early postoperative (T4-T12 TK and AVRThoracic) spinal parameters that can predict the optimal range of SLCC% at two-year postoperative in our cohort of Lenke 1 AIS.

Level of evidence: IV.

Keywords: Adolescent idiopathic scoliosis; Decision trees; Machine learning; Spine; Surgical planning; Three-dimentional.

MeSH terms

  • Adolescent
  • Decision Trees*
  • Female
  • Humans
  • Lumbar Vertebrae / diagnostic imaging
  • Lumbar Vertebrae / pathology*
  • Lumbar Vertebrae / surgery
  • Male
  • Radiography
  • Scoliosis / diagnostic imaging
  • Scoliosis / pathology
  • Scoliosis / surgery*
  • Spinal Fusion / methods*
  • Thoracic Vertebrae / diagnostic imaging
  • Thoracic Vertebrae / surgery*
  • Treatment Outcome