DOI QR코드

DOI QR Code

What is the interobserver agreement of displaced humeral surgical neck fracture patterns?

  • Reinier W. A. Spek (Department of Orthopaedic Surgery, Flinders Medical Centre and Flinders University) ;
  • Laura J. Kim (Department of Trauma Surgery, University Medical Centre Groningen and University of Groningen)
  • Received : 2022.10.06
  • Accepted : 2022.10.06
  • Published : 2022.12.01

Abstract

Background: The Boileau classification distinguishes three surgical neck fracture patterns: types A, B, and C. However, the reproducibility of this classification on plain radiographs is unclear. Therefore, we questioned what the interobserver agreement and accuracy of displaced surgical neck fracture patterns is categorized according to the modified Boileau classification. Does the reliability to recognize these fracture patterns differ between orthopedic residents and attending surgeons? Methods: This interobserver study consisted of a randomly retrieved series of 30 plain radiographs representing clinical practice in a level 1 and a level 2 trauma center. Radiographs were included from patients (≥18 years) who sustained an isolated displaced surgical neck fracture if they were taken ≤1 week after initial injury. A ground truth was established by consensus among three senior orthopedic surgeons. All images were assessed by 17 orthopedic residents and 17 attending orthopedic trauma surgeons. Results: Agreement for the modified Boileau classification was fair (κ=0.37; 95% confidence interval [CI], 0.36-0.38) with an accuracy of 62% (95% CI, 57%-66%). Comparison of interobserver variability between residents and attending surgeons revealed a significant but clinically irrelevant difference in favor of attending surgeons (0.34 vs. 0.39, respectively, Δκ=0.05, 95% CI, 0.02-0.07). Conclusions: The modified Boileau classification yields a low interobserver agreement with an unsatisfactory accuracy in a panel of orthopedic residents and attending surgeons. This supports the hypothesis that surgical neck fractures are challenging to categorize and that this classification should not be used to determine prognosis if only plain radiographs are available.

Keywords

Acknowledgement

The traumaplatform 3D study collaborative: Henrik Aberg, Anushka Abeywickrama, Michel P. J. van den Bekerom, Wael Chiri, Samantha Damude, Marion M. Deken, Ron L. Diercks, Derek F. P. van Deurzen, Job N. Doornberg, Nathan Eardley-Harris, Anne T. Fokkema, Tom J. Gieroba, H. S. Femke Hagenmaier, Sharon Hendriks, Tanneke I. Herklots, Genevieve S. Hernandez, Lotje A. Hoogervorst, Frank F. A. IJpma, Ruurd L. Jaarsma, Bhavin Jadav, Paul C. Jutte, Bas Keizers, Simone F. Kleiss, Maarten C. Koper, Borg Leijtens, Hamid Lutfi, Shoumit Mukhopadhaya, Arthur van Noort, Pradeep M. Poonnoose, Tim Ramsey, Jai Rawat, Jack Richards, Mieke van Suijlichem, Hugo C. van der Veen, Klaus W. Wendt, Roy Zuidema. Representative trauma platform study Collaborative: Job N. Doornberg.

References

  1. Yoon RS, Dziadosz D, Porter DA, Frank MA, Smith WR, Liporace FA. A comprehensive update on current fixation options for two-part proximal humerus fractures: a biomechanical investigation. Injury 2014;45:510-4.
  2. Setaro N, Rotini M, Luciani P, Facco G, Gigante A. Surgical management of 2- or 3-part proximal humeral fractures: comparison of plate, nail and K-wires. Musculoskelet Surg 2022;106:163-7.
  3. Court-Brown CM, Garg A, McQueen MM. The epidemiology of proximal humeral fractures. Acta Orthop Scand 2001;72:365-71.
  4. Launonen AP, Sumrein BO, Reito A, et al. Operative versus non-operative treatment for 2-part proximal humerus fracture: a multicenter randomized controlled trial. PLoS Med 2019;16:e1002855.
  5. Handoll HH, Brorson S. Interventions for treating proximal humeral fractures in adults. Cochrane Database Syst Rev 2015;(11):CD000434.
  6. Neer CS 2nd. Displaced proximal humeral fractures. I. Classification and evaluation. J Bone Joint Surg Am 1970;52:1077-89.
  7. Meinberg EG, Agel J, Roberts CS, Karam MD, Kellam JF. Fracture and Dislocation Classification Compendium-2018. J Orthop Trauma 2018;32 Suppl 1:S1-170.
  8. Boileau P, d'Ollonne T, Bessiere C, et al. Displaced humeral surgical neck fractures: classification and results of third-generation percutaneous intramedullary nailing. J Shoulder Elbow Surg 2019;28:276-87.
  9. Foroohar A, Tosti R, Richmond JM, Gaughan JP, Ilyas AM. Classification and treatment of proximal humerus fractures: inter-observer reliability and agreement across imaging modalities and experience. J Orthop Surg Res 2011;6:38.
  10. Bruinsma WE, Guitton TG, Warner JJ, Ring D; Science of Variation Group. Interobserver reliability of classification and characterization of proximal humeral fractures: a comparison of two and three-dimensional CT. J Bone Joint Surg Am 2013;95:1600-4.
  11. Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform 2019;95:103208.
  12. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG. Research electronic data capture (REDCap): a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377-81.
  13. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics 1977;33:159-74.
  14. Iordens GI, Mahabier KC, Buisman FE, Schep NW, Muradin GS, Beenen LF, et al. The reliability and reproducibility of the Hertel classification for comminuted proximal humeral fractures compared with the Neer classification. J Orthop Sci 2016;21:596-602.
  15. Marongiu G, Leinardi L, Congia S, Frigau L, Mola F, Capone A. Reliability and reproducibility of the new AO/OTA 2018 classification system for proximal humeral fractures: a comparison of three different classification systems. J Orthop Traumatol 2020;21:4.
  16. Bernstein J, Adler LM, Blank JE, Dalsey RM, Williams GR, Iannotti JP. Evaluation of the Neer system of classification of proximal humeral fractures with computerized tomographic scans and plain radiographs. J Bone Joint Surg Am 1996;78:1371-5.
  17. Chung SW, Han SS, Lee JW, et al. Automated detection and classification of the proximal humerus fracture by using deep learning algorithm. Acta Orthop 2018;89:468-73.