Predicting Mechanical Failure Following Cervical Deformity Surgery: A Composite Score Integrating Age-Adjusted Cervical Alignment Targets.

STUDY DESIGN: Retrospective cohort study. OBJECTIVES: Investigate a composite score to evaluate the relationship between alignment proportionality and risk of distal junctional kyphosis (DJK). METHODS: 84 patients with minimum 1 year follow-up were included (age = 61.1 ± 10.3 years, 64.3% women). The Cervical Score was constructed using offsets from age-adjusted normative values for sagittal vertical axis (SVA), T1 Slope (TS), and TS minus cervical lordosis (CL). Individual points were assigned based on offset with age-adjusted alignment targets and summed to generate the Cervical Score. Rates of mechanical failure (DJK revision or severe DJK [DJK> 20° and ΔDJK> 10°]) were assessed overall and based on Cervical Score. Logistical regressions assessed associations between early radiographic alignment and 1-year failure rate. RESULTS: Mechanical failure rate was 21.4% (N = 18), 10.7% requiring revision. By multivariate logistical regression: 3-month T1S (OR: .935), TS-CL (OR:0.882), and SVA (OR:1.015) were independent predictors of 1-year failure (all P < .05). Cervical Score ranged (-6 to 6), 37.8% of patients between -1 and 1, and 50.0% with 2 or higher. DJK patients had significantly higher Cervical Score (4.1 ± 1.3 vs .6 ± 2.2, P < .001). Patients with a score ≥3 were significantly more likely to develop a failure (71.4%) with OR of 38.55 (95%CI [7.73; 192.26]) and Nagelkerke r2 .524 (P < .001). CONCLUSION: This study developed a composite alignment score predictive of mechanical failures in CD surgery. A score ≥3 at 3 months following surgery was associated with a marked increase in failure rate. The Cervical Score can be used to analyze sagittal alignment and help define realignment objectives to reduce mechanical failure.

Evolution of Proximal Junctional Kyphosis and Proximal Junctional Failure Rates Over 10 Years of Enrollment in a Prospective Multicenter Adult Spinal Deformity Database.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: The aim of this study was to investigate the evolution of proximal junctional kyphosis (PJK) rate over 10-year enrollment period within a prospective database. SUMMARY OF BACKGROUND DATA: PJK is a common complication following adult spinal deformity (ASD) surgery and has been intensively studied over the last decade. METHODS: Patients with instrumentation extended to the pelvis and minimum 2-year follow-up were included. To investigate evolution of PJK/proximal junctional failure (PJF) rate, a moving average of 321 patients was calculated across the enrollment period. Logistic regression was used to investigate the association between the date of surgery (DOS) and PJK and/or PJF. Comparison of PJK/PJF rates, demographics, and surgical strategies was performed between the first and second half of the cohort. RESULTS: A total of 641 patients met inclusion criteria (age: 64±10 years, 78.2% female, body mass index: 28.3±5.7). The overall rate of radiographic PJK at 2 years was 47.9%; 12.9% of the patients developed PJF, with 31.3% being revised within 2-year follow-up. Stratification by DOS produced two halves. Between these two periods, rate of PJK and PJF demonstrated nonsignificant decrease (50.3%-45.5%, P =0.22) and (15.0%-10.9%, P =0.12), respectively. Linear interpolation suggested a decrease of 1.2% PJK per year and 1.0% for PJF. Patients enrolled later in the study were older and more likely to be classified as pure sagittal deformity ( P <0.001). There was a significant reduction in the use of three-column osteotomies ( P <0.001), an increase in anterior longitudinal ligament release ( P <0.001), and an increase in the use of PJK prophylaxis (31.3% vs 55.1%). Logistical regression demonstrated no significant association between DOS and radiographic PJK ( P =0.19) or PJF ( P =0.39). CONCLUSION: Despite extensive research examining risk factors for PJK/PJF and increasing utilization of intraoperative PJK prophylaxis techniques, the rate of radiographic PJK and/or PJF did not significantly decrease across the 10-year enrollment period of this ASD database.

Surgical Planning for Adult Spinal Deformity: Anticipated Sagittal Alignment Corrections According to the Surgical Level.

STUDY DESIGN: Retrospective cohort study. OBJECTIVES: Establish simultaneous focal and regional corrective guidelines accounting for reciprocal global and pelvic compensation. METHODS: 433 ASD patients (mean age 62.9 yrs, 81.3% F) who underwent corrective realignment (minimum L1-pelvis) were included. Sagittal parameters, and segmental and regional Cobb angles were assessed pre and post-op. Virtual postoperative alignment was generated by combining post-op alignment of the fused spine with the pre-op alignment on the unfused thoracic kyphosis and the pre-op pelvic retroversion. Regression models were then generated to predict the relative impact of segmental (L4-L5) and regional (L1-L4) corrections on PT, SVA (virtual), and TPA. RESULTS: Baseline analysis revealed distal (L4-S1) lordosis of 33 ± 15°, flat proximal (L1-L4) lordosis (1.7 ± 17°), and segmental kyphosis from L2-L3 to T10-T11. Post-op, there was no mean change in distal lordosis (L5-S1 decreased by 2°, and L4-L5 increased by 2°), while the more proximal lordosis increased by 18 ± 16°. Regression formulas revealed that Δ10° in distal lordosis resulted in Δ10° in TPA, associated with Δ100 mm in SVA or Δ3° in PT; Δ10° in proximal lordosis yielded Δ5° in TPA associated with Δ50 mm in SVA; and finally Δ10° in thoraco-lumbar junction yielded Δ2.5° in TPA associated with Δ25 mm in SVA and no impact on PT correction. CONCLUSIONS: Overall impact of lumbar lordosis restoration is critically determined by location of correction. Distal correction leads to a greater impact on global alignment and pelvic retroversion. More specifically, it can be assumed that 1° L4-S1 lordosis correction produces 1° change in TPA / 10 mm change in SVA and 0.5° in PT.

Preoperative Hounsfield Units at the Planned Upper Instrumented Vertebrae May Predict Proximal Junctional Kyphosis in Adult Spinal Deformity.

STUDY DESIGN: Retrospective cohort study. OBJECTIVE: To investigate the association between Hounsfield units (HU) measured at the planned upper instrumented vertebra (UIV) and UIV+1 and proximal junctional kyphosis (PJK) in patients with adult spinal deformity (ASD). SUMMARY OF BACKGROUND DATA: PJK is a common complication following surgery for ASD and poor bone quality is noted to be one of the risk factors. HUs from standard computed tomography (CT) scans can be used for evaluating regional bone quality. METHODS: Sixty-three patients were included from a single institution. The demographic characteristics and radiographic parameters were recorded. Local vertebral HUs at the planned UIV and UIV+ 1 were measured using preoperative CT scans. The patients were divided into three groups: no PJK, non-bony PJK, and bony PJK. The risk factors between the three groups and the correlation between the mean HU and increase in the PJK angle were analyzed. RESULTS: The incidence of PJK was 36.5%. The mean HU was significantly lower in the bony PJK group (HU: 109.0) than in the no PJK group (HU: 168.7, P = 0.038), and the mean HU in the non-bony PJK group (HU: 141.7) was not different compared to the other two groups. There was a significant negative correlation between the mean HU values and the increase in the PJK angles (r = -0.475, P < 0.01). The cutoff value for the mean HU used to predict bony PJK was 120 and a HU value less than 120 was a significant risk factor for bony PJK (OR: 5.74, 95% CI [1.01-32.54], P = 0.04). CONCLUSIONS: We noted a significant inverse relationship between the mean HUs at the UIV and UIV+ 1 and increase in the PJK angles postoperatively. In ASD patients, the HUs may be used preoperatively to identify patients with a higher risk of bony PJK.Level of Evidence: 3.

Predictive Model for Selection of Upper Treated Vertebra Using a Machine Learning Approach.

OBJECTIVE: To train and validate an algorithm mimicking decision making of experienced surgeons regarding upper instrumented vertebra (UIV) selection in surgical correction of thoracolumbar adult spinal deformity. METHODS: A retrospective review was conducted of patients with adult spinal deformity who underwent fusion of at least the lumbar spine (UIV > L1 to pelvis) during 2013-2018. Demographic and radiographic data were collected. The sample was stratified into 3 groups: training (70%), validation (15%) and performance testing (15%). Using a deep learning algorithm, a neural network model was trained to select between upper thoracic (T1-T6) and lower thoracic (T7-T12) UIV. Parameters used in the deep learning algorithm included demographics, coronal and sagittal preoperative alignment, and postoperative pelvic incidence-lumbar lordosis mismatch. RESULTS: The study included 143 patients (mean age 63.3 ± 10.6 years, 81.8% women) with moderate to severe deformity (maximum Cobb angle: 43° ± 22°; T1 pelvic angle: 27° ± 14°; pelvic incidence-lumbar lordosis mismatch: 22° ± 21°). Patients underwent a significant change in lumbar alignment (Δpelvic incidence-lumbar lordosis mismatch: 21° ± 16°, P < 0.001); 35.0% had UIV in the upper thoracic region, and 65.0% had UIV in the lower thoracic region. At 1 year, revision rate was 11.9%, and rate of radiographic proximal junctional kyphosis was 29.4%. Neural network comprised 8 inputs, 10 hidden neurons, and 1 output (upper thoracic or lower thoracic). After training, results demonstrated an accuracy of 81.0%, precision of 87.5%, and recall of 87.5% on testing. CONCLUSIONS: An artificial neural network successfully mimicked 2 lead surgeons' decision making in the selection of UIV for adult spinal deformity correction. Future models integrating surgical outcomes should be developed.