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Algorithm-Guided Treatment of Ulna Impaction Syndrome: A 10-Year Follow-Up Study of Ulna Shortening Osteotomy and Wafer Procedure.

Irene Mesas ArandaElisabeth Maria Haas-LützenbergerSara ImamRiccardo E GiuntaElias Volkmer
Published in: Journal of clinical medicine (2024)
Background : Ulnar impaction syndrome (UIS) is a common degenerative wrist condition which results from positive ulnar variance, leading to an overload on the ulnar carpus. Ulnar shortening osteotomy (USO) and the arthroscopic wafer procedure (AWP) are established therapies for UIS if conservative management fails. This study assessed an algorithm-guided treatment of UIS over a period of 10 years. Methods: This prospective observational study compared the outcome of 54 patients who underwent either USO or AWP for UIS based on a predefined treatment algorithm. The mean follow-up period was 10 years. Primary outcome parameters were the visual analogue scale (VAS) for pain and the Disabilities of the Arm, Shoulder, and Hand questionnaire (DASH), whereas secondary outcome parameters were grip and pinch strength and range of motion. Results: The median preoperative ulnar variance was 2.6 mm in the USO group and 2.0 mm in the AWP group. The postoperative average ulnar variance was 0 mm in both groups. The preoperative pain at rest was 3.4 in the USO group and 2.3 in the AWP group. One year after surgery, there was a significant reduction to VAS 0.7 and 0.2, respectively. These results persisted to the 10-year follow-up (VAS 0.9 and 0.2). The pain in motion also decreased significantly in the first year (from 6.8 and 6.7 to 2.2 and 2.1), as well as after 10 years (2.4 and 1.0). The preoperative DASH score averaged 31.3 in the USO group and 35.8 in the AWP group. At the 10-year follow-up, the DASH of both groups decreased significantly to 4.35 in the AWP group compared to 12.7 in the USO group. Conclusions : Our data show that, when using our algorithm, both USO and AWP, two common operative treatment options of UIS, reliably reduce pain and significantly reduce the DASH score over at least a period of ten years. The results after 10 years differ from short-term results in so far as after one year, the USO group showed to some degree similar outcome parameters compared to AWP, whereas at the 10-year follow-up, AWP reached slightly better primary outcome parameters. The algorithm presented, thus, produced excellent short- and long-term outcomes. Our findings and the applied algorithm can assist in decision-making and patient education.
Keyphrases
  • machine learning
  • chronic pain
  • deep learning
  • patients undergoing
  • pain management
  • healthcare
  • neuropathic pain
  • mass spectrometry
  • minimally invasive
  • chronic kidney disease
  • high resolution
  • high speed
  • rotator cuff