Methodological considerations in the multicenter cohort study of partial-thickness supraspinatus tear repair by Audigé et al.


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Koluman A. C., ZİROĞLU N., BİLSEL İ. K.

Journal of Orthopaedic Surgery and Research, vol.21, no.1, 2026 (SCI-Expanded, Scopus)

  • Publication Type: Article / Letter
  • Volume: 21 Issue: 1
  • Publication Date: 2026
  • Doi Number: 10.1186/s13018-026-07124-4
  • Journal Name: Journal of Orthopaedic Surgery and Research
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, CINAHL, EMBASE, MEDLINE, Directory of Open Access Journals, Academic Search Ultimate (EBSCO), Biomedical Reference Collection: Corporate Edition (EBSCO), Health Research Premium Collection (ProQuest)
  • Keywords: Arthroscopic repair, Ellman classification, Multicenter cohort, Partial-thickness rotator cuff tear, Postoperative stiffness, Tear completion
  • Open Archive Collection: AVESIS Open Access Collection
  • Acibadem Mehmet Ali Aydinlar University Affiliated: Yes

Abstract

This correspondence comments on the multicenter cohort study by Audigé et al. (Journal of Orthopaedic Surgery and Research, 2026) reporting outcomes of arthroscopic repair for partial-thickness supraspinatus tears. We highlight four aspects of the study that, in our view, would benefit from further clarification or additional discussion: (1) limited information regarding the surgical indications for tear completion, which may complicate interpretation of treatment-selection effects; (2) the absence of a technique-specific analysis of adverse events, particularly postoperative stiffness; (3) the unreported methodology used for intraoperative Ellman grade determination, the primary classification variable and the only factor significantly associated with tear completion; and (4) the potential residual influence of differential concomitant acromioplasty across tear-location groups despite statistical adjustment. Addressing these issues would further strengthen the interpretation and clinical applicability of this otherwise valuable prospective multicenter dataset.