Skip to main content

Advertisement

SpringerLink
Log in

Clinical predictive model of lumbar curve Cobb angle below selective fusion for thoracic adolescent idiopathic scoliosis: a longitudinal multicenter descriptive study

  • Original Article
  • Published:
European Journal of Orthopaedic Surgery & Traumatology Aims and scope Submit manuscript

Abstract

Purpose

To implement a clinically applicable, predictive model for the lumbar Cobb angle below a selective thoracic fusion in adolescent idiopathic scoliosis.

Methods

A series of 146 adolescents with Lenke 1 or 2 idiopathic scoliosis, surgically treated with posterior selective fusion, and minimum follow-up of 5 years (average 7) was analyzed. The cohort was divided in 2 groups: if lumbar Cobb angle at last follow-up was, respectively, ≥ or < 10°. A logistic regression-based prediction model (PredictMed) was implemented to identify variables associated with the group ≥ 10°. The guidelines of the TRIPOD statement were followed.

Results

Mean Cobb angle of thoracic main curve was 56° preoperatively and 25° at last follow-up. Mean lumbar Cobb angle was 33° (20; 59) preoperatively and 11° (0; 35) at last follow-up. 53 patients were in group ≥ 10°. The 2 groups had similar demographics, flexibility of both main and lumbar curves, and magnitude of the preoperative main curve, p > 0.1. From univariate analysis, mean magnitude of preoperative lumbar curves (35° vs. 30°), mean correction of main curve (65% vs. 58%), mean ratio of main curve/distal curve (1.9 vs. 1.6) and distribution of lumbar modifiers were statistically different between groups (p < 0.05).

PredictMed identified the following variables significantly associated with the group ≥ 10°: main curve % correction at last follow-up (p = 0.01) and distal curve angle (p = 0.04) with a prediction accuracy of 71%.

Conclusion

The main modifiable factor influencing uninstrumented lumbar curve was the correction of main curve. The clinical model PredictMed showed an accuracy of 71% in prediction of lumbar Cobb angle ≥ 10° at last follow-up.

Level of evidence IV

Longitudinal comparative study.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Eardley-Harris N, Munn Z et al (2015) The effectiveness of selective thoracic fusion for treating adolescent idiopathic scoliosis: a systematic review protocol. JBI Database Syst Rev Implement Rep 13:4–16. https://doi.org/10.11124/jbisrir-2015-2338

    Article  Google Scholar 

  2. Chang KW, Leng X, Zhao W et al (2011) Broader curve criteria for selective thoracic fusion. Spine (Phila Pa 1976) 36(20):1658–64. https://doi.org/10.1097/BRS.0b013e318215fa73

    Article  Google Scholar 

  3. Lenke LG, Edwards CC, Bridwell KH (2003) The Lenke classification of adolescent idiopathic scoliosis: how it organizes curve patterns as a template to perform selective fusions of the spine. Spine 28:S199-207

    Article  Google Scholar 

  4. Suk SI, Lee SM, Chung ER et al (2005) Selective thoracic fusion with segmental pedicle screw fixation in the treatment of thoracic idiopathic scoliosis: more than 5-year follow-up. Spine (Phila Pa 1976) 30:1602–9

    Article  Google Scholar 

  5. Zhang H, Richards BS, Sucato DJ et al (2018) The lumbar gap measurement in Lenke 1–4C curves. Spine Deform 6:241–249. https://doi.org/10.1016/j.jspd.2017.11.001

    Article  CAS  PubMed  Google Scholar 

  6. Boniello AJ, Hasan S, Yang S et al (2015) Selective versus nonselective thoracic fusion in Lenke 1C curves: a meta-analysis of baseline characteristics and postoperative outcomes. J Neurosurg Spine 23:721–730. https://doi.org/10.3171/2015.1.SPINE141020

    Article  PubMed  Google Scholar 

  7. Enercan M, Kahraman S, Cobanoglu M et al (2015) Selective thoracic fusion provides similar health-related quality of life but can cause more lumbar disc and facet joint degeneration: a comparison of adolescent idiopathic scoliosis patients with normal population 10 years after surgery. Spine Deform 3:469–475. https://doi.org/10.1016/j.jspd.2015.07.001

    Article  PubMed  Google Scholar 

  8. Lonstein JE (2018) Selective thoracic fusion for adolescent idiopathic scoliosis: long-term radiographic and functional outcomes. Spine Deform 6:669–675. https://doi.org/10.1016/j.jspd.2018.04.008

    Article  PubMed  Google Scholar 

  9. Liljenqvist U, Halm H, Bullmann V (2013) Spontaneous lumbar curve correction in selective anterior instrumentation and fusion of idiopathic thoracic scoliosis of Lenke type C. Eur Spine J 22(Suppl 2):S138–S148. https://doi.org/10.1007/s00586-012-2299-7

    Article  PubMed  Google Scholar 

  10. Yong MR, Izatt MT, Adam CJ et al (2012) Secondary curve behavior in Lenke type 1C adolescent idiopathic scoliosis after thoracoscopic selective anterior thoracic fusion. Spine (Phila Pa 1976) 37:1965–74. https://doi.org/10.1097/BRS.0b013e3182583421

    Article  Google Scholar 

  11. Ishikawa M, Cao K, Pang L et al (2015) Postoperative behavior of thoracolumbar/lumbar curve and coronal balance after posterior thoracic fusion for Lenke 1C and 2C AIS. J Orthop Sci 20:31–37. https://doi.org/10.1007/s00776-014-0655-7

    Article  PubMed  Google Scholar 

  12. Edwards CC, Lenke LG, Peelle M et al (2004) Selective thoracic fusion for adolescent idiopathic scoliosis with C modifier lumbar curves: 2- to 16-year radiographic and clinical results. Spine (Phila Pa 1976) 29:536–46

    Article  Google Scholar 

  13. Clément JL, Solla F, Tran A et al (2017) Five-year outcomes of the first distal uninstrumented vertebra after posterior fusion for adolescent idiopathic scoliosis Lenke 1 or 2. Orthop Traumatol Surg Res 103:727–731. https://doi.org/10.1016/j.otsr.2017.04.006

    Article  PubMed  Google Scholar 

  14. Friedman J, Hastie T, Tibshirani R (2010) Regularization paths for generalized linear models via coordinate descent. J Stat Softw 33(1):1–22

    Article  Google Scholar 

  15. Oh E, Wook Seo S, Cheol Yoon Y, Kim DK, Kwon S, Yoon S (2017) Prediction of pathologic femoral fractures in patients with lung cancer using machine learning algorithms: comparison of computed tomography-based radiological features with clinical features versus without clinical features. J Orthop Surg (Hong Kong) 25(2):2309499017716243. https://doi.org/10.1177/2309499017716243

    Article  Google Scholar 

  16. Mossotto E, Ashton JJ, Coelho T, Beattie RM, Mac Arthur D, Ennis S (2017) Classification of paediatric inflammatory bowel disease using machine learning. Sci Rep 7:2427. https://doi.org/10.1038/s41598-017-02606-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bertoncelli CM, Altamura P, Vieira ER, Iyengar SS, Solla F, Bertoncelli D (2020) PredictMed: a logistic regression-based model to predict health conditions in cerebral palsy. Health Inform J 20:1460458219898568. https://doi.org/10.1177/1460458219898568

    Article  Google Scholar 

  18. Bertoncelli CM, Solla F, Loughenbury PR et al (2017) Risk factors for developing scoliosis in cerebral palsy: a cross-sectional descriptive study. J Child Neurol 32:657–662. https://doi.org/10.1177/0883073817701047

    Article  PubMed  Google Scholar 

  19. Bertoncelli CM, Bertoncelli D, Elbaum L et al (2018) Validation of a clinical prediction model for the development of neuromuscular scoliosis: a multinational study. Pediatr Neurol 79:14–20. https://doi.org/10.1016/j.pediatrneurol.2017.10.019

    Article  PubMed  Google Scholar 

  20. Maillot C, Ferrero E, Fort D et al (2015) Reproducibility and repeatability of a new computerized software for sagittal spinopelvic and scoliosis curvature radiologic measurements: keops(®). Eur Spine J 24:1574–1581. https://doi.org/10.1007/s00586-015-3817-1

    Article  CAS  PubMed  Google Scholar 

  21. Solla F, Clément JL, Doria C et al (2018) Adolescent idiopathic scoliosis exceeding 70°: a single center surgical experience. Minerva Ortop 69:69–77

    Google Scholar 

  22. Solla F, Tran A, Rampal V (2019) What level of evidence is provided by comparative retrospective studies? Orthop Traumatol Surg Res 105(4):789–790. https://doi.org/10.1016/j.otsr.2019.03.013 (Epub 2019 May 1)

    Article  PubMed  Google Scholar 

  23. Solla F, Tran A, Bertoncelli D et al (2018) Why a P-value is not enough. Clin Spine Surg 31:385–388. https://doi.org/10.1097/BSD.0000000000000695

    Article  PubMed  Google Scholar 

  24. Vapnik V, Vashist A (2009) A new learning paradigm: learning using privileged information. Neural Netw 22(5–6):544–57. https://doi.org/10.1016/j.neunet.2009.06.042 (Epub 2009 Jul 3)

    Article  PubMed  Google Scholar 

  25. Bertoncelli CM, Altamura P, Vieira ER, Bertoncelli D, Latalski M, Berthet S, Solla F (2020) Predictive model for gastrostomy placement in adolescents with developmental disabilities and cerebral palsy. Nutr Clin Pract 35(1):149–156. https://doi.org/10.1002/ncp.10309 (Epub 2019 May 27 PMID: 31134674)

    Article  PubMed  Google Scholar 

  26. Bertoncelli CM, Altamura P, Vieira ER, Bertoncelli D, Thummler S, Solla F (2019) Identifying factors associated with intellectual disabilities in teenagers with cerebral palsy using a predictive learning model. J Child Neurol 22:883073818822358. https://doi.org/10.1177/0883073818822358

    Article  Google Scholar 

  27. Bertoncelli CM, Altamura P, Vieira ER, Bertoncelli D, Solla F (2019) Using artificial intelligence to identify factors associated with autism spectrum disorder in adolescents with cerebral palsy. Neuropediatrics 50(3):178–187. https://doi.org/10.1055/s-0039-1685525

    Article  PubMed  Google Scholar 

  28. Collins GS, Reitsma JB, Altman DG et al (2014) Transparent reporting of a multivaria-ble prediction model for individual prognosis or diagnosis (TRIPOD): the TRIPOD statement. BMJ 350:g7594. https://doi.org/10.1136/bmj.g7594

    Article  Google Scholar 

  29. Koller H, Hitzl W, Marks MC, Newton PO (2019) Accurate prediction of spontaneous lumbar curve correction following posterior selective thoracic fusion in adolescent idiopathic scoliosis using logistic regression models and clinical rationale. Eur Spine J 28:1987–1997. https://doi.org/10.1007/s00586-019-06000-6

    Article  CAS  PubMed  Google Scholar 

  30. Louer C Jr, Yaszay B, Cross M et al (2019) Ten-year outcomes of selective fusions for adolescent idiopathic scoliosis. J Bone Jt Surg Am 101:761–770. https://doi.org/10.2106/JBJS.18.01013

    Article  Google Scholar 

  31. Scaramuzzo L, Giudici F, Bongetta D et al (2017) Thoraco-lumbar selective fusion in adolescent idiopathic scoliosis with Lenke C modifier curves: clinical and radiographic analysis at 10-year follow-up. Eur Spine J. https://doi.org/10.1007/s00586-017-5152-1

    Article  PubMed  Google Scholar 

  32. Choudhry MN, Ahmad Z, Verma R (2016) Adolescent Idiopathic Scoliosis. Open Orthop J 30(10):143–54. https://doi.org/10.2174/1874325001610010143 (eCollection 2016)

    Article  Google Scholar 

  33. Feng J, Zhou J, Huang M et al (2018) Clinical and radiological outcomes of the multilevel ponte osteotomy with posterior selective segmental pedicle screw constructs to treat adolescent thoracic idiopathic scoliosis. J Orthop Surg Res 2018(13):305. https://doi.org/10.1186/s13018-018-1001-0

    Article  Google Scholar 

  34. Clements DH, Betz RR, Newton PO et al (2009) Correlation of scoliosis curve correction with the number and type of fixation anchors. Spine (Phila Pa 1976) 34:2147–50. https://doi.org/10.1097/BRS.0b013e3181adb35d

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Pediatric Orthopaedic Surgery Unit, Lenval University Children’s Hospital, Nice, France

    Federico Solla, Jean-Luc Clément & Carlo M. Bertoncelli

  2. Pediatric Orthopaedic Surgery Unit, University Hospital of Tours, Clocheville, France

    Walid Lakhal

  3. Pediatric Orthopaedic Surgery Unit, Institut Calot, Fondation Hopale, Berk, France

    Christian Morin

  4. Pediatric Orthopaedic Surgery Unit, University Hospital of Toulouse, Toulouse, France

    Jerome Sales de Gauzy

  5. Hôtel-Dieu de France, Beyrouth, Lebanon

    Gaby Kreichati

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

    Ibrahim Obeid

  7. Spine Surgery Unit, Saint Joseph hospital, Paris, France

    Stéphane Wolff

  8. Pediatric Orthopaedic Surgery Unit, University Hospital of Rouen, Rouen, France

    Joël Lechevallier

  9. Spine Surgery Unit, Trélazé, France

    Henry F. Parent

  10. Hal Marcus College of Science & Engineering, University of West Florida, Pensacola, USA

    Carlo M. Bertoncelli

Authors
  1. Federico Solla
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Walid Lakhal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Christian Morin
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jerome Sales de Gauzy
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Gaby Kreichati
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Ibrahim Obeid
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Stéphane Wolff
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Joël Lechevallier
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Henry F. Parent
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jean-Luc Clément
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Carlo M. Bertoncelli
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

FS: Conception or design of the work, Acquisition, analysis, or interpretation of data, Drafted the work, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. WL: Acquisition, analysis, or interpretation of data, Drafted the work, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. CM: Conception or design of the work, Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. JSdG: Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. GK: Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. IO: Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. SW: Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. JL: Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. HFP: Acquisition, analysis, or interpretation of data, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. JLC: Conception or design of the work, Acquisition, analysis, or interpretation of data, Drafted the work, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved, CMB: Conception or design of the work, Acquisition, analysis, or interpretation of data, Drafted the work, Revised it critically for important intellectual content, Approved the version to be published, Agree to be accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Corresponding author

Correspondence to Carlo M. Bertoncelli.

Ethics declarations

Conflict of interest

FS received financial support for attending symposia and congresses from Medicrea Int. and Euros. JLC is consultant for Medicrea Int. JSdG received financial support for attending symposia and congresses from Medtronic and Implanet. IO and WL received financial support for attending symposia and congresses from Medtronic and Spineart. JL, HP et SW received financial support for attending symposia and congresses from Medtronic. CMB, CM, GK: no conflicts.

Ethical approval

All procedures described in this work have been approved by the IRB of the leading center (Nice) with number 2017728v0, 14th September 2016; all patients and parents provided formal consent.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Solla, F., Lakhal, W., Morin, C. et al. Clinical predictive model of lumbar curve Cobb angle below selective fusion for thoracic adolescent idiopathic scoliosis: a longitudinal multicenter descriptive study. Eur J Orthop Surg Traumatol 32, 827–836 (2022). https://doi.org/10.1007/s00590-021-03054-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00590-021-03054-5

Keywords

Search

Navigation