Skip to main content

Advertisement

Log in

Development and validation of a nomogram for predicting the prognosis in children with spinal cord injuries

  • Original Article
  • Published:
European Spine Journal Aims and scope Submit manuscript

Abstract

Aims

This research aims to construct and verify an accurate nomogram for forecasting the 3-, 5-, and 7-year outcomes in pediatric patients afflicted with spinal cord injury (SCI).

Methods

Pediatric patients with SCI from multiple hospitals in China, diagnosed between Jan 2005 and Jan 2020, were incorporated into this research. Half of these patients were arbitrarily chosen for training sets, and the other half were designated for external validation sets. The Cox hazard model was employed to pinpoint potential prognosis determinants related to the American Spinal Injury Association (ASIA) and Functional Independence Assessment (FIM) index. These determinants were then employed to formulate the prognostic nomogram. Subsequently, the bootstrap technique was applied to validate the derived model internally.

Results

In total, 224 children with SCI were considered for the final evaluation, having a median monitoring duration of 68.0 months. The predictive nomogram showcased superior differentiation capabilities, yielding a refined C-index of 0.924 (95% CI: 0.883–0.965) for the training cohort and a C-index of 0.863 (95% CI: 0.735–0.933) for the external verification group. Additionally, when applying the aforementioned model to prognostic predictions as classified by the FIM, it demonstrated a high predictive value with a C-index of 0.908 (95% CI: 0.863–0.953). Moreover, the calibration diagrams indicated a consistent match between the projected and genuine ASIA outcomes across both sets.

Conclusion

The crafted and verified prognostic nomogram emerges as a dependable instrument to foresee the 3-, 5-, and 7-year ASIA and FIM outcomes for children suffering from SCI.

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

Access this article

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

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  1. Eli I, Lerner DP, Ghogawala Z (2021) Acute traumatic spinal cord injury. Neurol Clin 39(2):471–488. https://doi.org/10.1016/j.ncl.2021.02.004

    Article  PubMed  Google Scholar 

  2. Chay W, Kirshblum S (2020) Predicting outcomes after spinal cord injury. Phys Med Rehabil Clin N Am 31(3):331–343. https://doi.org/10.1016/j.pmr.2020.03.003

    Article  PubMed  Google Scholar 

  3. Attal N (2021) Spinal cord injury pain. Rev Neurol (Paris) 177(5):606–612. https://doi.org/10.1016/j.neurol.2020.07.003

    Article  CAS  PubMed  Google Scholar 

  4. Alcántar-Garibay OV, Incontri-Abraham D, Ibarra A (2022) Spinal cord injury-induced cognitive impairment: a narrative review. Neural Regen Res 17(12):2649–2654. https://doi.org/10.4103/1673-5374.339475

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Robertson K, Ashworth F (2022) Spinal cord injury and pregnancy. Obstet Med 15(2):99–103. https://doi.org/10.1177/1753495X211011918

    Article  PubMed  Google Scholar 

  6. Tan JS, Hu S, Guo TT, Hua L, Wang XJ (2022) Text mining-based drug discovery for connective tissue disease-associated pulmonary arterial hypertension. Front Pharmacol 18(13):743210. https://doi.org/10.3389/fphar.2022.743210

    Article  CAS  Google Scholar 

  7. Cunha NSC, Malvea A, Sadat S, Ibrahim GM, Fehlings MG (2023) Pediatric spinal cord injury: a review. Children (Basel) 10(9):1456. https://doi.org/10.3390/children10091456

    Article  PubMed  Google Scholar 

  8. Sharif S, Jazaib Ali MY (2020) Outcome prediction in spinal cord injury: myth or reality. World Neurosurg 140:574–590. https://doi.org/10.1016/j.wneu.2020.05.043

    Article  PubMed  Google Scholar 

  9. Choi EH, Gattas S, Brown NJ, Hong JD, Limbo JN, Chan AY, Oh MY (2021) Epidural electrical stimulation for spinal cord injury. Neural Regen Res 16(12):2367–2375. https://doi.org/10.4103/1673-5374.313017

    Article  PubMed  PubMed Central  Google Scholar 

  10. Furlan JC, Sakakibara BM, Miller WC, Krassioukov AV (2013) Global incidence and prevalence of traumatic spinal cord injury. Can J Neurol Sci 40(4):456–464

    Article  PubMed  Google Scholar 

  11. Ding W, Hu S, Wang P, Kang H, Peng R, Dong Y, Li F (2022) Spinal cord injury: the global incidence, prevalence, and disability from the global burden of disease study 2019. Spine (Phila Pa 1976) 47(21):1532–1540

    Article  PubMed  Google Scholar 

  12. Strøm V, Månum G, Arora M, Joseph C, Kyriakides A, Le Fort M, Osterthun R, Perrouin-Verbe B, Postma K, Middleton J (2022) Physical health conditions in persons with spinal cord injury across 21 countries worldwide. J Rehabil Med 54:jrm00302

    Article  PubMed  Google Scholar 

  13. Megía García A, Serrano-Muñoz D, Taylor J, Avendaño-Coy J, Gómez-Soriano J (2020) Transcutaneous spinal cord stimulation and motor rehabilitation in spinal cord injury: a systematic review. Neurorehabil Neural Repair 34(1):3–12. https://doi.org/10.1177/1545968319893298

    Article  PubMed  Google Scholar 

  14. Liu C, Liu Y, Ma B, Zhou M, Zhao X, Fu X, Kan S, Hu W, Zhu R (2022) Mitochondrial regulatory mechanisms in spinal cord injury: a narrative review. Medicine (Baltimore) 101(46):e31930. https://doi.org/10.1097/MD.0000000000031930

    Article  PubMed  Google Scholar 

  15. Atkins KD, Bickel CS (2021) Effects of functional electrical stimulation on muscle health after spinal cord injury. Curr Opin Pharmacol 60:226–231. https://doi.org/10.1016/j.coph.2021.07.025

    Article  CAS  PubMed  Google Scholar 

  16. Chen X, Li H (2022) Neuronal reprogramming in treating spinal cord injury. Neural Regen Res 17(7):1440–1445. https://doi.org/10.4103/1673-5374.330590

    Article  CAS  PubMed  Google Scholar 

  17. Janik K, Manire MA, Smith GM, Krynska B (2020) Spinal cord injury in myelomeningocele: prospects for therapy. Front Cell Neurosci 30(14):201. https://doi.org/10.3389/fncel.2020.00201

    Article  CAS  Google Scholar 

  18. Fogarty MJ, Sieck GC (2020) Spinal cord injury and diaphragm neuromotor control. Expert Rev Respir Med 14(5):453–464. https://doi.org/10.1080/17476348.2020.1732822

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Wang JZ, Yang M, Meng M, Li ZH (2023) Clinical characteristics and treatment of spinal cord injury in children and adolescents. Chin J Traumatol 26(1):8–13

    Article  PubMed  Google Scholar 

  20. Li C, Xiong W, Wan B, Kong G, Wang S, Wang Y, Fan J (2022) Role of peripheral immune cells in spinal cord injury. Cell Mol Life Sci 80(1):2. https://doi.org/10.1007/s00018-022-04644-0

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Kirshblum S, Snider B, Rupp R, Read MS, International Standards Committee of ASIA and ISCoS (2020) Updates of the international standards for neurologic classification of spinal cord injury: 2015 and 2019. Phys Med Rehabil Clin N Am 31(3):319–330. https://doi.org/10.1016/j.pmr.2020.03.005

    Article  PubMed  Google Scholar 

  22. Zheng Y, Mao YR, Yuan TF, Xu DS, Cheng LM (2020) Multimodal treatment for spinal cord injury: a sword of neuroregeneration upon neuromodulation. Neural Regen Res 15(8):1437–1450. https://doi.org/10.4103/1673-5374.274332

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. van Middendorp JJ, Goss B, Urquhart S, Atresh S, Williams RP, Schuetz M (2011) Diagnosis and prognosis of traumatic spinal cord injury. Global Spine J 1(1):1–8. https://doi.org/10.1055/s-0031-1296049

    Article  PubMed  PubMed Central  Google Scholar 

  24. Khachatryan Z, Haunschild J, von Aspern K, Borger MA, Etz CD (2022) Ischemic spinal cord injury-experimental evidence and evolution of protective measures. Ann Thorac Surg 113(5):1692–1702. https://doi.org/10.1016/j.athoracsur.2020.12.028

    Article  PubMed  Google Scholar 

  25. Hachem LD, Fehlings MG (2021) Pathophysiology of spinal cord injury. Neurosurg Clin N Am 32(3):305–313. https://doi.org/10.1016/j.nec.2021.03.002

    Article  PubMed  Google Scholar 

  26. Yan X, He Y, Jia M, Yang J, Huang K, Zhang P, Lai J, Chen M, Fan S, Li S, Fan Z, Teng H (2023) Development of a dynamic nomogram for predicting the probability of satisfactory recovery after 6 months for cervical traumatic spinal cord injury. Orthop Surg 15(4):1008–1020. https://doi.org/10.1111/os.13679

    Article  PubMed  PubMed Central  Google Scholar 

  27. Chaoran Y, Zhang Y (2019) Development and validation of a prognostic nomogram for early-onset colon cancer. Biosci Rep 39(6):BSR20181781

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Zhiqun Zhang.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

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

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, B., Xu, L., Zheng, P. et al. Development and validation of a nomogram for predicting the prognosis in children with spinal cord injuries. Eur Spine J (2024). https://doi.org/10.1007/s00586-024-08208-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s00586-024-08208-7

Keywords

Navigation