Salvage Algorithm for Deep Surgical Site Infections after HTO with Unstable Bone Situation Using a Hexapod System - Primary Results.

Abstract

The incidence of deep surgical site infections following high tibial osteotomy (HTO) ranges between 0.4 to 4.7%. It is a severe complication with a high risk for poor clinical outcome. The aim of this study was to proof that a salvage algorithm for infected HTO with unstable bone situation leads to an infection-free status and bone union of the osteotomy and that correct limb alignment can be restored with good knee function.The study included seven patients with peri-implant infections following HTO. Infections occurred 83±58.9 days (range: 24-191) after HTO. All patients underwent the "RESTORE" algorithm: patients received (1) REmoval of the HTO hardware and extensive debridement; (2) the osteotomy was STabilized with a hexapod external fixator (Taylor Spatial Frame, TSF); (3) the osteotomy gap was Opened; and (4) the alignment was REconstructed using the TSF, aiming for the intended limb alignment of the initial HTO. Patient-reported outcomes were assessed 22-36 months after removal of the TSF.After 24 weeks (range: 11-35), an infection-free status and bone healing were achieved. In all cases, the limb was saved, and the previously targeted mechanical axis of the lower limb was restored. All patients reached full extension of the knee joint and at least 110° of flexion. For KOOS: Symptoms 67.86±18.1, Pain 73.41±16.58, ADL 78.99±21.32, Sports 52.14±25.96, and QoL 41.96±24.66. OKS 35.71±8.8, SF-12 Physical Health 38.89±10.3, and SF-12 Mental Health 46.86±13.76.The "RESTORE" algorithm is a safe and effective salvage procedure. The concept allows for saving the limb and obtaining the previously planned limb alignment. Patient-reported outcome measures showed slightly lowered values than healthy samples, but substantially better values than patients awaiting HTO. Due to the possibility of initial full weight-bearing, the risk of higher morbidity caused by immobilization is minimized.