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Von Mises stress peak (VMSP) and laryngomalacia severity score (LSS) are extremely useful in the selection of treatment for laryngomalacia

  • Laryngology
  • Published:
European Archives of Oto-Rhino-Laryngology Aims and scope Submit manuscript

Abstract

Objective

To analyze the judgment efficiency of a computer stress model and severity score in severity evaluation and treatment plan selection of laryngomalacia patients.

Methods

Twenty-two children (12 cases in the operation group and 10 cases in the follow-up group) with moderate to severe laryngomalacia were assessed by laryngomalacia severity score (LSS) which included visual analogue scale (VAS) and clinical score. A computer stress model of the laryngeal cavity was constructed for all children, with the von Mises stress peak (VMSP) of the model used as another quantitative evaluation method. The ROC curves of two quantitative evaluation methods, the LSS and the VMSP, were analyzed respectively, according to the clinical guideline which is regarded as the gold standard for judging whether surgery is needed. The diagnostic efficiency indexes such as sensitivity, specificity, and accuracy were calculated. The area under ROC curves (AUC) of the two methods were compared by a DeLong model. Spearman correlation analysis and Kappa test were used to test the correlation and consistency of the two quantitative evaluation methods. The independent sample t test was used to compare the difference of LSS and VMSP between operation group and follow-up group.

Results

The sensitivity, specificity, and accuracy of LSS in judging whether laryngomalacia was operated or not were 83.33%, 80.00% and 81.82%, respectively, and the area under ROC curve (AUC) was 0.825 (p < 0.05). The sensitivity, specificity, and accuracy of the computer stress model for laryngomalacia were 58.33%, 90.00% and 72.73%, respectively, and the AUC was 0.796 (p < 0.05). The spearman correlation coefficient between LSS and VMSP was 0.833, p < 0.001, which is statistically significant. LSS (t = 3.251, p = 0.004) and VMSP (t = 2.435, p = 0.024) of the two groups were statistically different.

Conclusion

VMSP and LSS have high diagnostic efficacy in the quantitative evaluation of the severity of laryngomalacia and the selection of treatment plan. The consistency of the two quantitative evaluation methods is good, which has practical value for the evaluation of the severity of laryngomalacia and has guiding significance for surgery.

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Data availability

All data are available from the corresponding author upon reasonable request.

References

  1. Chen W, Yang C, Liu S et al (2014) Curative effect study of pulsed dye laser in the treatment of 43 patients with hand infantile hemangioma. Eur J Dermatol 24:76–79

    Article  CAS  PubMed  Google Scholar 

  2. Landry AM, Thompson DM (2012) Laryngomalacia: disease presentation, spectrum, and management. Int J Pediatr 2012:753526. https://doi.org/10.1155/2012/753526

    Article  PubMed  PubMed Central  Google Scholar 

  3. Liu XJ, Li XY (2019) Research progress in the pathogenesis of laryngomalacia and related diseases. Int J Otolaryngol Head Neck Surg 43(5):260–263

    Google Scholar 

  4. Brauer JA, Geronemus RG (2013) Laser treatment in the management of infantile hemangiomas and capillary vascular malformations. Tech Vasc Interv Radiol 16:51–54

    Article  PubMed  Google Scholar 

  5. Bentz BG, Hughes CA, Ludemann JP et al (2000) Masses of the salivary gland region in children. Arch Otolaryngol Head Neck Surg 126:1435–1439

    Article  CAS  PubMed  Google Scholar 

  6. Thorne MC, Garetz SL (2016) Laryngomalacia: review and summary of current clinical practice in 2015. Paediatr Respir Rev 17:3–8

    PubMed  Google Scholar 

  7. Van Der Heijden M, Dikkers FG, Halmos GB (2016) Treatment outcome of supraglottoplasty vs. wait-and-see policy in patients with laryngomalacia. Eur Arch Otorhinolaryngol 273:1507–1513

    Article  PubMed  PubMed Central  Google Scholar 

  8. Xu HM, Chen JL, Pu SL et al (2020) Three-dimensional finite element modeling for evaluation of laryngomalacia severity in infants and children. J Int Med Res 48(6):1–12

    Article  CAS  Google Scholar 

  9. Xu HM, Pu SL, Jiang YG, Li XY, Dong P (2018) Establishment and preliminary application of a laryngomalacia larynx three-dimension model. Lin Chung Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 32(12):891–894

    CAS  Google Scholar 

  10. China Maternal and Child health association Minimally Invasive Chapter Pediatric ORL Group (2020) Clinical practice guidelines for the diagnosis and management of laryngomalacia in children. Lin Chung Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 34(11):961–965

    Google Scholar 

  11. Carter J, Rahbar R, Brigger M et al (2016) International Pediatric ORL Group (IPOG) laryngomalacia consensus recommendations. Int J Pediatr Otorhinolaryngol 86:256–261

    Article  PubMed  Google Scholar 

  12. Xu HM, Chen F, Zheng YY et al (2020) Efficacy and toxicities of low-temperature plasma radiofrequency ablation for the treatment of laryngomalacia in neonates and infants: a prospective randomized controlled trial. Ann Transl Med 8(21):1366

    Article  PubMed  PubMed Central  Google Scholar 

  13. Pu SL, Xu HM, Li XY (2018) Supraglottoplasty in neonates and infants: a radiofrequency ablation approach. Medicine (Baltimore) 97(7):e9850

    Article  PubMed  Google Scholar 

  14. Zhang Y, Shi T (2014) The research of laryngeal joints to reconstruction and modeling. Biomed Mater Eng 24:2627–2634

    PubMed  Google Scholar 

  15. Xu C, Brennick MJ, Dougherty L et al (2009) Modeling upper airway collapse by a finite element model with regional tissue properties. Med Eng Phys 31:1343–1348

    Article  PubMed  PubMed Central  Google Scholar 

  16. Li Q, Hu Y, Zhao H (2006) Application of infant double tube nasal continuous positive airway pressure system in treatment of preterm hyaline membrane disease and neonatal respiratory failure. J Clin Pediatr 24:887–889

    CAS  Google Scholar 

  17. Reinhard A, Sandu K (2014) Laryngomalacia: principal cause of stridor in infants and small children. Rev Med Suisse 10(444):1816–1819

    CAS  PubMed  Google Scholar 

  18. Clark CM, Kugler K, Carr MM (2018) Common causes of congenital stridor in infants. JAAPA 31(11):36–40

    Article  PubMed  Google Scholar 

  19. Alshumrani RA, Matt BH et al (2020) Correlation between the clinical severity of laryngomalacia and endoscopic findings. Saudi Med J 41(4):406–412

    Article  PubMed  PubMed Central  Google Scholar 

  20. Cialente F, Meucci D, Tropiano ML et al (2021) Changes in breathing patterns after surgery in severe laryngomalacia. Children (Basel) 8(12):1120

    PubMed  Google Scholar 

  21. Kilpatrick LA, Boyette JR, Hartzell LD et al (2014) Prospective quality of life assessment in congenital laryngomalacia. Int J Pediatr Otorhinolaryngol 78:583–587

    Article  PubMed  Google Scholar 

  22. Sivan Y, Ben-Ari J, Soferman R, DeRowe A (2006) Diagnosis of laryngomalacia by fiberoptic endoscopy: awake compared with anesthesia-aided technique. Chest 130(5):1412–1418

    Article  PubMed  Google Scholar 

  23. Weinstein JE, Lawlor CM, Eric LWu (2017) Utility of polysomnography in determination of laryngomalacia severity. Int J Pediatr Otorhinolaryngol 93:145–149

    Article  PubMed  Google Scholar 

  24. Thresher RW, Saito GE (1973) The stress analysis of human teeth. J Biomech 6(5):443–449

    Article  CAS  PubMed  Google Scholar 

  25. Kvit AA, Devine EE, Jiang JJ et al (2015) Characterizing liquid redistribution in a biphasic vibrating vocal fold using finite element analysis. J Voice 29(3):265–272

    Article  PubMed  PubMed Central  Google Scholar 

  26. Xu H, Kvit AA, Devine EE et al (2014) Voice outcome of modified frontolateral partial laryngectomy in excised canine larynges and finite element model. Otolaryngol Head Neck Surg 151(2):294–300

    Article  PubMed  Google Scholar 

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Funding

This work was supported by the Foundation for Cross Biomedical Engineering of Shanghai Jiao Tong University (no. YG2019QNB02), the Youth Program of Shanghai Municipal Health Bureau (no. 20194Y0165), and the Clinical Research Project of Shanghai Shenkang Hospital Development Center (no. 20873999).

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Correspondence to Xiaoyan Li.

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This research did not increase the patients’ risk or economic burden, the patients’ rights were fully protected, and the project design was conducted in line with scientific and ethical principles. The institutional review board approved this project.

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Chen, J., Xu, H. & Li, X. Von Mises stress peak (VMSP) and laryngomalacia severity score (LSS) are extremely useful in the selection of treatment for laryngomalacia. Eur Arch Otorhinolaryngol 280, 3287–3293 (2023). https://doi.org/10.1007/s00405-023-07866-5

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