Object: Minimally invasive surgery (MIS) is an alternative to open deformity surgery for the treatment of patients with adult spinal deformity. However, at this time MIS techniques are not as versatile as open deformity techniques, and MIS techniques have been reported to result in suboptimal sagittal plane correction or pseudarthrosis when used for severe deformities. The minimally invasive spinal deformity surgery (MISDEF) algorithm was created to provide a framework for rational decision making for surgeons who are considering MIS versus open spine surgery.
Methods: A team of experienced spinal deformity surgeons developed the MISDEF algorithm that incorporates a patient's preoperative radiographic parameters and leads to one of 3 general plans ranging from MIS direct or indirect decompression to open deformity surgery with osteotomies. The authors surveyed fellowship-trained spine surgeons experienced with spinal deformity surgery to validate the algorithm using a set of 20 cases to establish interobserver reliability. They then resurveyed the same surgeons 2 months later with the same cases presented in a different sequence to establish intraobserver reliability. Responses were collected and tabulated. Fleiss' analysis was performed using MATLAB software.
Results: Over a 3-month period, 11 surgeons completed the surveys. Responses for MISDEF algorithm case review demonstrated an interobserver kappa of 0.58 for the first round of surveys and an interobserver kappa of 0.69 for the second round of surveys, consistent with substantial agreement. In at least 10 cases there was perfect agreement between the reviewing surgeons. The mean intraobserver kappa for the 2 surveys was 0.86 ± 0.15 (± SD) and ranged from 0.62 to 1.
Conclusions: The use of the MISDEF algorithm provides consistent and straightforward guidance for surgeons who are considering either an MIS or an open approach for the treatment of patients with adult spinal deformity. The MISDEF algorithm was found to have substantial inter- and intraobserver agreement. Although further studies are needed, the application of this algorithm could provide a platform for surgeons to achieve the desired goals of surgery.