Alexander A. Theologis, Tamir Ailon, Justin K. Scheer, Justin S. Smith, Christopher I. Shaffrey, Shay Bess, Munish Gupta, Eric O. Klineberg, Khaled Kebaish, Frank Schwab, Virginie Lafage, Douglas Burton, Robert Hart, Christopher P. Ames, and The International Spine Study Group
The objective of this study was to isolate whether the effect of a baseline clinical history of depression on outcome is independent of associated physical disability and to evaluate which mental health screening tool has the most utility in determining 2-year clinical outcomes after adult spinal deformity (ASD) surgery.
Consecutively enrolled patients with ASD in a prospective, multicenter ASD database who underwent surgical intervention with a minimum 2-year follow-up were retrospectively reviewed. A subset of patients who completed the Distress and Risk Assessment Method (DRAM) was also analyzed. The effects of categorical baseline depression and DRAM classification on the Oswestry Disability Index (ODI), SF-36, and Scoliosis Research Society questionnaire (SRS-22r) were assessed using univariate and multivariate linear regression analyses. The probability of achieving ≥ 1 minimal clinically important difference (MCID) on the ODI based on the DRAM’s Modified Somatic Perceptions Questionnaire (MSPQ) score was estimated.
Of 267 patients, 66 (24.7%) had self-reported preoperative depression. Patients with baseline depression had significantly more preoperative back pain, greater BMI and Charlson Comorbidity Indices, higher ODIs, and lower SRS-22r and SF-36 Physical/Mental Component Summary (PCS/MCS) scores compared with those without self-reported baseline depression. They also had more severe regional and global sagittal malalignment. After adjusting for these differences, preoperative depression did not impact 2-year ODI, PCS/MCS, or SRS-22r totals (p > 0.05). Compared with those in the “normal” DRAM category, “distressed somatics” (n = 11) had higher ODI (+23.5 points), lower PCS (−10.9), SRS-22r activity (−0.9), and SRS-22r total (−0.8) scores (p ≤ 0.01), while “distressed depressives” (n = 25) had lower PCS (−8.4) and SRS-22r total (−0.5) scores (p < 0.05). After adjusting for important covariates, each additional point on the baseline MSPQ was associated with a 0.8-point increase in 2-year ODI (p = 0.03). The probability of improving by at least 1 MCID in 2-year ODI ranged from 77% to 21% for MSPQ scores 0–20, respectively.
A baseline clinical history of depression does not correlate with worse 2-year outcomes after ASD surgery after adjusting for baseline differences in comorbidities, health-related quality of life, and spinal deformity severity. Conversely, DRAM improved risk stratification of patient subgroups predisposed to achieving suboptimal surgical outcomes. The DRAM’s MSPQ was more predictive than MCS and SRS mental domain for 2-year outcomes and may be a valuable tool for surgical screening.
Justin K. Scheer, Justin S. Smith, Frank Schwab, Virginie Lafage, Christopher I. Shaffrey, Shay Bess, Alan H. Daniels, Robert A. Hart, Themistocles S. Protopsaltis, Gregory M. Mundis Jr., Daniel M. Sciubba, Tamir Ailon, Douglas C. Burton, Eric Klineberg, Christopher P. Ames, and The International Spine Study Group
The operative management of patients with adult spinal deformity (ASD) has a high complication rate and it remains unknown whether baseline patient characteristics and surgical variables can predict early complications (intraoperative and perioperative [within 6 weeks]). The development of an accurate preoperative predictive model can aid in patient counseling, shared decision making, and improved surgical planning. The purpose of this study was to develop a model based on baseline demographic, radiographic, and surgical factors that can predict if patients will sustain an intraoperative or perioperative major complication.
This study was a retrospective analysis of a prospective, multicenter ASD database. The inclusion criteria were age ≥ 18 years and the presence of ASD. In total, 45 variables were used in the initial training of the model including demographic data, comorbidities, modifiable surgical variables, baseline health-related quality of life, and coronal and sagittal radiographic parameters. Patients were grouped as either having at least 1 major intraoperative or perioperative complication (COMP group) or not (NOCOMP group). An ensemble of decision trees was constructed utilizing the C5.0 algorithm with 5 different bootstrapped models. Internal validation was accomplished via a 70/30 data split for training and testing each model, respectively. Overall accuracy, the area under the receiver operating characteristic (AUROC) curve, and predictor importance were calculated.
Five hundred fifty-seven patients were included: 409 (73.4%) in the NOCOMP group, and 148 (26.6%) in the COMP group. The overall model accuracy was 87.6% correct with an AUROC curve of 0.89 indicating a very good model fit. Twenty variables were determined to be the top predictors (importance ≥ 0.90 as determined by the model) and included (in decreasing importance): age, leg pain, Oswestry Disability Index, number of decompression levels, number of interbody fusion levels, Physical Component Summary of the SF-36, Scoliosis Research Society (SRS)–Schwab coronal curve type, Charlson Comorbidity Index, SRS activity, T-1 pelvic angle, American Society of Anesthesiologists grade, presence of osteoporosis, pelvic tilt, sagittal vertical axis, primary versus revision surgery, SRS pain, SRS total, use of bone morphogenetic protein, use of iliac crest graft, and pelvic incidence–lumbar lordosis mismatch.
A successful model (87% accuracy, 0.89 AUROC curve) was built predicting major intraoperative or perioperative complications following ASD surgery. This model can provide the foundation toward improved education and point-of-care decision making for patients undergoing ASD surgery.