Assessing the variation and drivers of cost in 1-level lumbar fusion: a time-driven activity-based costing analysis.

BACKGROUND CONTEXT: As value-based health care arrangements gain traction in spine care, understanding the true cost of care becomes critical. Historically, inaccurate cost proxies have been used, including negotiated reimbursement rates or list prices. However, time-driven activity-based costing (TDABC) allows for a more accurate cost assessment, including a better understanding of the primary drivers of cost in 1-level lumbar fusion. PURPOSE: To determine the variation of total hospital cost, differences in characteristics between high-cost and non-high-cost patients, and to identify the primary drivers of total hospital cost in a sample of patients undergoing 1-level lumbar fusion. STUDY DESIGN/SETTING: Retrospective, multicenter (one academic medical center, one community-based hospital), observational study. PATIENT SAMPLE: A total of 383 patients undergoing elective 1-level lumbar fusion for degenerative spine conditions between November 2, 2021 and December 2, 2022. OUTCOME MEASURES: Total hospital cost of care (normalized); preoperative, intraoperative, and postoperative cost of care (normalized); ratio of most to least expensive 1-level lumbar fusion. METHODS: Patients undergoing a 1-level lumbar fusion between November 2, 2021 and December 2, 2022 were identified at two hospitals (one quaternary referral academic medical center and one community-based hospital) within our health system. TDABC was used to calculate total hospital cost, which was also broken up into: pre-, intra-, and postoperative timeframes. Operating surgeon and patient characteristics were also collected and compared between high- and non-high-cost patients. The correlation of surgical time and cost was determined. Multivariable linear regression was used to determine factors associated with total hospital cost. RESULTS: The most expensive 1-level lumbar fusion was 6.8x more expensive than the least expensive 1-level lumbar fusion, with the intraoperative period accounting for 88% of total cost. On average. the implant cost accounted for 30% of the total, but across the patient sample, the implant cost accounted for a range of 6% to 44% of the total cost. High-cost patients were younger (55 years [SD: 13 years] vs.63 years [SD: 13 years], p=.0002), more likely to have commercial health insurance (24 out of 38 (63%) vs. 181 out of 345 (52%), p=.003). There was a poor correlation between time of surgery (i.e., incision to close) and total overall cost (ρ: .26, p<.0001). Increase age (RC: -0.003 [95% CI: -0.006 to -0.000007], p=.049) was associated with decreased cost. Surgery by certain surgeons was associated with decreased total cost when accounting for other factors (p<.05). CONCLUSIONS: A large variation exists in the total hospital cost for patients undergoing 1-level lumbar fusion, which is primarily driven by surgeon-level decisions and preferences (e.g., implant and technology use). Also, being a "fast" surgeon intraoperatively does not mean your total cost is meaningfully lower. As efforts continue to optimize patient value through ensuring appropriate clinical outcomes while also reducing cost, spine surgeons must use this knowledge to lead, or at least be active participants in, any discussions that could impact patient care.

Magnetic Resonance Imaging Is Inadequate to Assess Cervical Sagittal Alignment Parameters.

STUDY DESIGN: Retrospective radiographic study. OBJECTIVE: To evaluate cervical sagittal alignment measurement reliability and correlation between upright radiographs and magnetic resonance imaging (MRI). SUMMARY OF BACKGROUND DATA: Cervical sagittal alignment (CSA) helps determine the surgical technique employed to treat cervical spondylotic myelopathy. Traditionally, upright lateral radiographs are used to measure CSA, but obtaining adequate imaging can be challenging. Utilizing MRI to evaluate sagittal parameters has been explored; however, the impact of positional change on these parameters has not been determined. METHODS: One hundred seventeen adult patients were identified who underwent laminoplasty or laminectomy and fusion for cervical spondylotic myelopathy from 2017 to 2019. Two clinicians independently measured the C2-C7 sagittal angle, C2-C7 sagittal vertical axis (SVA), and the T1 tilt. Interobserver and intraobserver reliability were assessed by intraclass correlation coefficient. RESULTS: Intraobserver and interobserver reliabilities were highly correlated, with correlations greater than 0.85 across all permutations; intraclass correlation coefficients were highest with MRI measurements. The C2-C7 sagittal angle was highly correlated between x-ray and MRI at 0.76 with no significant difference ( P =0.46). There was a weaker correlation with regard to C2-C7 SVA (0.48) and T1 tilt (0.62) with significant differences observed in the mean values between the 2 modalities ( P <0.01). CONCLUSIONS: The C2-C7 sagittal angle is highly correlated and not significantly different between upright x-ray and supine MRIs. However, cervical SVA and T1 tilt change with patient position. Since MRI does not accurately reflect the CSA in the upright position, upright lateral radiographs should be obtained to assess global sagittal alignment when planning a posterior-based cervical procedure.

Surgical Intervention is Associated With Improvements in the ASIA Impairment Scale in Gunshot-induced Spinal Injuries of the Thoracic and Lumbar Spine.

STUDY DESIGN: Retrospective cohort study of patients from the National Spinal Cord Injury Statistical Center (NSCISC). OBJECTIVE: The aim was to compare the outcomes of patients with gunshot-induced spinal injuries (GSIs) treated operatively and nonoperatively. SUMMARY OF BACKGROUND DATA: The treatment of neurological deficits associated with gunshot wounds to the spine has been controversial. Treatment has varied widely, ranging from nonoperative to aggressive surgery. METHODS: Patient demographics, clinical information, and outcomes were extracted. Surgical intervention was defined as a "laminectomy, neural canal restoration, open reduction, spinal fusion, or internal fixation of the spine." The primary outcome was the American Spinal Injury Association (ASIA) Impairment Scale. Statistical comparisons of baseline demographics and neurological outcomes between operative and nonoperative cohorts were performed. RESULTS: In total, 961 patients with GSI and at least 1-year follow-up were identified from 1975 to 2015. The majority of patients were Black/African American (55.6%), male (89.7%), and 15-29 years old (73.8%). Of those treated surgically (19.7% of all patients), 34.2% had improvement in their ASIA Impairment Scale score at 1 year, compared with 20.6% treated nonoperatively. Overall, surgery was associated with a 2.0 [95% confidence interval (CI): 1.4-2.8] times greater likelihood of ASIA Impairment Scale improvement at 1 year. Specifically, benefit was seen in thoracic (odds ratio: 2.5; 95% CI: 1.4-4.6) and lumbar injuries (odds ratio: 1.7; 95% CI: 1.1-3.1), but not cervical injuries. CONCLUSIONS: While surgical indications are always determined on an individualized basis, in our review of GSIs, surgical intervention was associated with a greater likelihood of neurological recovery. Specifically, patients with thoracic and lumbar GSIs had a 2.5 and 1.7-times greater likelihood of improvement in their ASIA Impairment Scale score 1 year after injury, respectively, if they underwent surgical intervention.

Practice Variation Within a Single Institution in Management of Degenerative Spondylolisthesis.

STUDY DESIGN: This was a retrospective cohort study. OBJECTIVE: The objective of this study was to assess variation in care for degenerative spondylolisthesis (DS) among surgeons at the same institution, to establish diagnostic and therapeutic variables contributing to this variation, and to determine whether variation in care changed over time. SUMMARY OF BACKGROUND DATA: Like other degenerative spinal disorders, DS is prone to practice variation due to the wide array of treatment options. Focusing on a single institution can identify more individualized drivers of practice variation by omitting geographic variability of demographics and socioeconomic factors. MATERIALS AND METHODS: We collected number of office visits, imaging procedures, injections, electromyography (EMG), and surgical procedures within 1 year after diagnosis. Multivariable logistic regression was used to determine predictors of surgery. The coefficient of variation (CV) was calculated to compare the variation in practice over time. RESULTS: Patients had a mean 2.5 (±0.6) visits, 1.8 (±0.7) imaging procedures, and 0.16 (±0.09) injections in the first year after diagnosis. Thirty-six percent (1937/5091) of patients had physical therapy in the 3 months after diagnosis. CV was highest for EMG (95%) and lowest for office visits (22%). An additional spinal diagnosis [odds ratio (OR)=3.99, P <0.001], visiting a neurosurgery clinic (OR=1.81, P =0.016), and diagnosis post-2007 (OR=1.21, P =0.010) were independently associated with increased surgery rates. The CVs for all variables decreased after 2007, with the largest decrease seen for EMG (132% vs. 56%). CONCLUSIONS: While there is variation in the management of patients diagnosed with DS between surgeons of a single institution, this variation seems to have gone down in recent years. All practice variables showed diminished variation. The largest variation and subsequent decrease of variation was seen in the use of EMG. Despite the smaller amount of variation, the rate of surgery has gone up since 2007.

Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery.

BACKGROUND: Intraoperative vascular injury (VI) may be an unavoidable complication of anterior lumbar spine surgery; however, vascular injury has implications for quality and safety reporting as this intraoperative complication may result in serious bleeding, thrombosis, and postoperative stricture. PURPOSE: The purpose of this study was to (1) develop machine learning algorithms for preoperative prediction of VI and (2) develop natural language processing (NLP) algorithms for automated surveillance of intraoperative VI from free-text operative notes. PATIENT SAMPLE: Adult patients, 18 years or age or older, undergoing anterior lumbar spine surgery at two academic and three community medical centers were included in this analysis. OUTCOME MEASURES: The primary outcome was unintended VI during anterior lumbar spine surgery. METHODS: Manual review of free-text operative notes was used to identify patients who had unintended VI. The available population was split into training and testing cohorts. Five machine learning algorithms were developed for preoperative prediction of VI. An NLP algorithm was trained for automated detection of intraoperative VI from free-text operative notes. Performance of the NLP algorithm was compared to current procedural terminology and international classification of diseases codes. RESULTS: In all, 1035 patients underwent anterior lumbar spine surgery and the rate of intraoperative VI was 7.2% (n=75). Variables used for preoperative prediction of VI were age, male sex, body mass index, diabetes, L4-L5 exposure, and surgery for infection (discitis, osteomyelitis). The best performing machine learning algorithm achieved c-statistic of 0.73 for preoperative prediction of VI (https://sorg-apps.shinyapps.io/lumbar_vascular_injury/). For automated detection of intraoperative VI from free-text notes, the NLP algorithm achieved c-statistic of 0.92. The NLP algorithm identified 18 of the 21 patients (sensitivity 0.86) who had a VI whereas current procedural terminologyand international classification of diseases codes identified 6 of the 21 (sensitivity 0.29) patients. At this threshold, the NLP algorithm had a specificity of 0.93, negative predictive value of 0.99, positive predictive value of 0.51, and F1-score of 0.64. CONCLUSION: Relying on administrative procedural and diagnosis codes may underestimate the rate of unintended intraoperative VI in anterior lumbar spine surgery. External and prospective validation of the algorithms presented here may improve quality and safety reporting.

Laminoplasty-an underutilized procedure for cervical spondylotic myelopathy.

BACKGROUND CONTENT: Cervical laminoplasty (LP) and laminectomy and fusion (LF) are commonly used surgical techniques for cervical spondylotic myelopathy (CSM). Several recent studies have demonstrated superior perioperative metrics and decreased overall costs with LP, yet LF is performed far more often in the United States. PURPOSE: To determine the percentage of patients with CSM who are radiographically candidates for LP. STUDY DESIGN: Retrospective comparative cohort study. PATIENT SAMPLE: Patients >18 years old who underwent LF or LP for CSM at 2 large academic institutions from 2017 to 2019. OUTCOME MEASURES: Candidacy for LP based on radiographic criteria. METHODS: Radiographs were assessed by 2 spine surgeons not involved in the care of the patients to determine the C2-C7 Cobb angle and the presence and extent of cervical instability. Patients with kyphosis >13°, > 3.5 mm of listhesis on static imaging, or > 2.5 mm of motion on flexion-extension or standing-supine films were not considered candidates for LP. Intraclass coefficient (ICC) was calculated to assess the interobserver reliability of angular measurements and the presence of instability. The percentage of patients for whom LP was contraindicated was calculated. RESULTS: One hundred eight patients underwent LF while 142 underwent LP. Of the 108 patients who underwent LF, 79.6% were radiographically deemed candidates for LP, as were all 142 patients who underwent LP. The ICC for C2-C7 alignment was 0.90; there was 97% agreement with respect to the presence of instability. CONCLUSIONS: In 250 patients with CSM, 228 (91.2%) were radiographically candidates for LP. These data suggest that LP may be an underutilized procedure for the treatment for CSM.

Surgeon-level variance in achieving clinical improvement after lumbar decompression: the importance of adequate risk adjustment.

BACKGROUND CONTEXT: Patient-Reported Outcome Measurement Information System (PROMIS) scores are increasingly utilized in clinical care. However, it is unclear if PROMIS can discriminate surgeon performance on an individual level. PURPOSE: The purpose of this study was to examine surgeon-level variance in rates of achieving minimal clinically important difference (MCID) after lumbar decompression. PATIENT SAMPLE: This is a prospective, observational cohort study performed across a healthcare enterprise (two academic medical centers and three community centers). Patients 18 years or older undergoing one- to two-level primary decompression for lumbar disc herniation (LDH) or lumbar spinal stenosis (LSS) were included. OUTCOME MEASURES: The primary outcome was achievement of MCID, using a distribution-based method, on paired PROMIS physical function scores. METHODS: Descriptive statistics were generated to examine the baseline characteristics of the study cohort. Bivariate analyses were used to examine the impact of surgeon-level variance on rates of MCID. Multivariable analyses were used to examine the risk-adjusted impact of surgeon-level variance on rates of MCID. RESULTS: Overall, 636 patients treated by nine surgeons were included. The median patient age was 58 [interquartile range (IQR): 46-70] and 62.3% (n=396) were female. Among all patients, 56.9% (n=362) underwent surgery for LDH. The overall rate of achieving MCID was 75.8% (n=482). Of the surgeons, the median years in practice were 12 (range 4-31) and 55.6% (n=5) were in academic practice settings. On bivariate analysis, patients treated by one of the surgeons had lower rates of achieving MICD (odds ratio=0.37, 95% confidence interval: 0.15-0.91, p=.03). However, on multivariable analysis adjusting for operative indication (LDH vs. LSS), body mass index, number of comorbidities, percent unemployment in patient zip code, and preoperative PROMIS physical function scores, all surgeons were equally likely to obtain MCID. CONCLUSIONS: In this cohort, variance in PROMIS scores after primary lumbar decompression is influenced by patient-related factors and not by individual surgeon. Adequate risk adjustment is needed if ascertaining clinical improvement on an individual surgeon basis. LEVEL OF EVIDENCE: 2.

Development of prediction models for clinically meaningful improvement in PROMIS scores after lumbar decompression.

BACKGROUND: The ability to preoperatively predict which patients will achieve a minimal clinically important difference (MCID) after lumbar spine decompression surgery can help determine the appropriateness and timing of surgery. Patient-Reported Outcome Measurement Information System (PROMIS) scores are an increasingly popular outcome instrument. PURPOSE: The purpose of this study was to develop algorithms predictive of achieving MCID after primary lumbar decompression surgery. PATIENT SAMPLE: This was a retrospective study at two academic medical centers and three community medical centers including adult patients 18 years or older undergoing one or two level posterior decompression for lumbar disc herniation or lumbar spinal stenosis between January 1, 2016 and April 1, 2019. OUTCOME MEASURES: The primary outcome, MCID, was defined using distribution-based methods as one half the standard deviation of postoperative patient-reported outcomes (PROMIS physical function, pain interference, pain intensity). METHODS: Five machine learning algorithms were developed to predict MCID on these surveys and assessed by discrimination, calibration, Brier score, and decision curve analysis. The final model was incorporated into an open access digital application. RESULTS: Overall, 906 patients completed at least one PROMs survey in the 90 days before surgery and at least one PROMs survey in the year after surgery. Attainment of MCID during the study period by PROMIS instrument was 74.3% for physical function, 75.8% for pain interference, and 79.2% for pain intensity. Factors identified for preoperative prediction of MCID attainment on these outcomes included preoperative PROs, percent unemployment in neighborhood of residence, comorbidities, body mass index, private insurance, preoperative opioid use, surgery for disc herniation, and federal poverty level in neighborhood of residence. The discrimination (c-statistic) of the final algorithms for these outcomes was 0.79 for physical function, 0.74 for pain interference, and 0.69 for pain intensity with good calibration. The open access digital application for these algorithms can be found here: https://sorg-apps.shinyapps.io/promis_pld_mcid/ CONCLUSION: Lower preoperative PROMIS scores, fewer comorbidities, and certain sociodemographic factors increase the likelihood of achieving MCID for PROMIS after lumbar spine decompression.

Laminoplasty versus laminectomy and fusion for cervical spondylotic myelopathy: a cost analysis.

BACKGROUND CONTEXT: Laminectomy with fusion (LF) and laminoplasty (LP) are commonly used to treat cervical spondylotic myelopathy (CSM). The decision regarding which procedure to perform is largely a matter of surgeon's preference, while financial implications are rarely considered. PURPOSE: We aimed to better understand the financial considerations of LF compared to LP in the treatment of CSM. STUDY DESIGN: Retrospective comparative study. PATIENT SAMPLE: Adult patients, 18 years of age or older, who had undergone LF or LP for CSM from 2017 to 2019 at 2 large academic centers were included. Patients who had undergone previous cervical spine surgery or procedures that extended above C2 or below T2 were excluded. OUTCOME MEASURES: The primary outcome was defined as the total cost of the procedure, which was calculated as the sum of the implant and non-implant supply costs. METHODS: Patient demographics, surgical parameters, including estimated blood loss and operative time, and length of stay were collected. Operating room material - both implant and non-implant - cost data was also obtained. Variables were analyzed individually as well as after adjustment based on the number of operative levels involved. Statistical analysis was performed using either Student t test with unequal variance or Wilcoxon rank sum test for continuous variables and chi-squared analysis for categorical variables. RESULTS: Two hundred fifty patients were identified who met inclusion criteria. There was no statistical difference in the mean age at time of surgery (p=.25), gender distribution (p=.33), or re-operation rate between the LF and LP groups (p=.39). Overall, operative time was similar between the LF (165.7 ± 61.9 min) and LP (173.8 ± 58.2 min) groups (p=.29), but the LP cohort had a shorter length of stay at 3.8 ± 2.7 days compared to the LF cohort at 4.8 ± 3.7 days. Implant costs in the LF group were significantly more at $6,204.94 ± $1426.41 compared to LP implant costs at $1994.39 ± $643.09. Mean total costs of LP were significantly less at $2,859.08 ± $784.19 compared to LF total costs of $6,983.16 ± $1,589.17. Furthermore, when adjusted for the number of operative levels, LP remained significantly less costly at $766.12 ± $213.64 per level while LF cost $1,789.05 ± $486.66 per operative level. Additional subgroup analysis limiting the cohorts to patients with either three or four involved vertebral levels demonstrated nearly identical cost savings with LP as compared to LF. CONCLUSIONS: This study demonstrates that LF is on average at least 2.4 times the total operative supply cost of LP and at least 2.3 times the operative supply cost of LP when adjusted for the number of operative levels. In patients deemed appropriate for either LP or LF, these data may be incorporated into decision-making for the treatment of CSM.

Can natural language processing provide accurate, automated reporting of wound infection requiring reoperation after lumbar discectomy?

BACKGROUND: Surgical site infections are a major driver of morbidity and increased costs in the postoperative period after spine surgery. Current tools for surveillance of these adverse events rely on prospective clinical tracking, manual retrospective chart review, or administrative procedural and diagnosis codes. PURPOSE: The purpose of this study was to develop natural language processing (NLP) algorithms for automated reporting of postoperative wound infection requiring reoperation after lumbar discectomy. PATIENT SAMPLE: Adult patients undergoing discectomy at two academic and three community medical centers between January 1, 2000 and July 31, 2019 for lumbar disc herniation. OUTCOME MEASURES: Reoperation for wound infection within 90 days after surgery METHODS: Free-text notes of patients who underwent surgery from January 1, 2000 to December 31, 2015 were used for algorithm training. Free-text notes of patients who underwent surgery after January 1, 2016 were used for algorithm testing. Manual chart review was used to label which patients had reoperation for wound infection. An extreme gradient-boosting NLP algorithm was developed to detect reoperation for postoperative wound infection. RESULTS: Overall, 5,860 patients were included in this study and 62 (1.1%) had a reoperation for wound infection. In patients who underwent surgery after January 1, 2016 (n=1,377), the NLP algorithm detected 15 of the 16 patients (sensitivity=0.94) who had reoperation for infection. In comparison, current procedural terminology and international classification of disease codes detected 12 of these 16 patients (sensitivity=0.75). At a threshold of 0.05, the NLP algorithm had positive predictive value of 0.83 and F1-score of 0.88. CONCLUSION: Temporal validation of the algorithm developed in this study demonstrates a proof-of-concept application of NLP for automated reporting of adverse events after spine surgery. Adapting this methodology for other procedures and outcomes in spine and orthopedics has the potential to dramatically improve and automatize quality and safety reporting.

Predicting prolonged opioid prescriptions in opioid-naïve lumbar spine surgery patients.

IMPORTANCE: Preoperative determination of the potential for postoperative opioid dependence in previously naïve patients undergoing elective spine surgery may facilitate targeted interventions. OBJECTIVE: The purpose of this study was to develop supervised machine learning algorithms for preoperative prediction of prolonged opioid prescription use in opioid-naïve patients following lumbar spine surgery. DESIGN: Retrospective review of clinical registry data. Variables considered for prediction included demographics, insurance status, preoperative medications, surgical factors, laboratory values, comorbidities, and neighborhood characteristics. Five supervised machine learning algorithms were developed and assessed by discrimination, calibration, Brier score, and decision curve analysis. SETTING: One healthcare entity (two academic medical centers, three community hospitals), 2000 to 2018. PARTICIPANTS: Opioid-naïve patients undergoing decompression and/or fusion for lumbar disk herniation, stenosis, and spondylolisthesis. MAIN OUTCOME: Sustained prescription opioid use exceeding 90 days after surgery. RESULTS: Overall, of 8,435 patients included, 359 (4.3%) were found to have prolonged postoperative opioid prescriptions. The elastic-net penalized logistic regression achieved the best performance in the independent testing set not used for algorithm development with c-statistic=0.70, calibration intercept=0.06, calibration slope=1.02, and Brier score=0.039. The five most important factors for prolonged opioid prescriptions were use of instrumented spinal fusion, preoperative benzodiazepine use, preoperative antidepressant use, preoperative gabapentin use, and uninsured status. Individual patient-level explanations were provided for the algorithm predictions and the algorithms were incorporated into an open access digital application available here: https://sorg-apps.shinyapps.io/lumbaropioidnaive/. CONCLUSION AND RELEVANCE: The clinician decision aid developed in this study may be helpful to preoperatively risk-stratify opioid-naïve patients undergoing lumbar spine surgery. The tool demonstrates moderate discriminative capacity for identifying those at greatest risk of prolonged prescription opioid use. External validation is required to further support the potential utility of this tool in practice.

Natural language processing for automated detection of incidental durotomy.

BACKGROUND: Incidental durotomy is a common intraoperative complication during spine surgery with potential implications for postoperative recovery, patient-reported outcomes, length of stay, and costs. To our knowledge, there are no processes available for automated surveillance of incidental durotomy. PURPOSE: The purpose of this study was to develop natural language processing (NLP) algorithms for automated detection of incidental durotomies in free-text operative notes of patients undergoing lumbar spine surgery. PATIENT SAMPLE: Adult patients 18 years or older undergoing lumbar spine surgery between January 1, 2000 and June 31, 2018 at two academic and three community medical centers. OUTCOME MEASURES: The primary outcome was defined as intraoperative durotomy recorded in free-text operative notes. METHODS: An 80:20 stratified split was undertaken to create training and testing populations. An extreme gradient-boosting NLP algorithm was developed to detect incidental durotomy. Discrimination was assessed via area under receiver-operating curve (AUC-ROC), precision-recall curve, and Brier score. Performance of this algorithm was compared with current procedural terminology (CPT) and international classification of diseases (ICD) codes for durotomy. RESULTS: Overall, 1,000 patients were included in the study and 93 (9.3%) had a recorded incidental durotomy in the free-text operative report. In the independent testing set (n=200) not used for model development, the NLP algorithm achieved AUC-ROC of 0.99 for detection of durotomy. In comparison, the CPT/ICD codes had AUC-ROC of 0.64. In the testing set, the NLP algorithm detected 16 of 18 patients with incidental durotomy (sensitivity 0.89) whereas the CPT and ICD codes detected 5 of 18 (sensitivity 0.28). At a threshold of 0.05, the NLP algorithm had specificity of 0.99, positive predictive value of 0.89, and negative predictive value of 0.99. CONCLUSIONS: Internal validation of the NLP algorithm developed in this study indicates promising results for future NLP applications in spine surgery. Pending external validation, the NLP algorithm developed in this study may be used by entities including national spine registries or hospital quality and safety departments to automate tracking of incidental durotomies.

Normal intervertebral segment rotation of the subaxial cervical spine: An in vivo study of dynamic neck motions.

BACKGROUND: Accurate knowledge of the intervertebral center of rotation (COR) and its corresponding range of motion (ROM) can help understand development of cervical pathology and guide surgical treatment. METHODS: Ten asymptomatic subjects were imaged using MRI and dual fluoroscopic imaging techniques during dynamic extension-flexion-extension (EFE) and axial left-right-left (LRL) rotation. The intervertebral segment CORs and ROMs were measured from C34 to C67, as the correlations between two variables were analyzed as well. RESULTS: During the EFE motion, the CORs were located at 32.4 ± 20.6%, -2.4 ± 11.7%, 21.8 ± 12.5% and 32.3 ± 25.5% posteriorly, and the corresponding ROMs were 13.8 ± 4.3°, 15.1 ± 5.1°, 14.4 ± 7.0° and 9.2 ± 4.3° from C34 to C67. The ROM of C67 was significantly smaller than other segments. The ROMs were not shown to significantly correlate to COR locations (r = -0.243, p = 0.132). During the LRL rotation cycle, the average CORs were at 85.6 ± 18.2%, 32.3 ± 25.3%, 15.7 ± 12.3% and 82.4 ± 31.3% posteriorly, and the corresponding ROMs were 3.5 ± 1.7°, 6.9 ± 3.8°, 9.6 ± 4.1° and 2.6 ± 2.5° from C34 to C67. The ROMs of C34 and C67 was significantly smaller than those of C45 and C56. A more posterior COR was associated with a less ROM during the neck rotation (r = -0.583, p < 0.001). The ROMs during EFE were significantly larger than those during LRL in each intervertebral level. CONCLUSION: The CORs and ROMs of the subaxial cervical intervertebral segments were segment level- and neck motion-dependent during the in-vivo neck motions. THE TRANSLATIONAL POTENTIAL OF THIS ARTICLE: Our study indicates that the subaxial cervical intervertebral CORs and ROMs were segment level- and neck motion-dependent. This may help to improve the artificial disc design as well as surgical technique by which the neck functional motion is restored following the cervical arthroplasty.

Discharge Disposition After Anterior Cervical Discectomy and Fusion.

OBJECTIVE: Age and comorbidity burden of patients going anterior cervical discectomy and fusion (ACDF) have increased significantly over the past 2 decades, resulting in increased expenditures. Non-home discharge after ACDF contributes to increased direct and indirect costs of postoperative care. The purpose of this study was to identify independent prognostic factors for discharge disposition in patients undergoing ACDF. METHODS: A retrospective review was conducted at 5 medical centers to identify patients undergoing ACDF for degenerative conditions. The primary outcome was non-home discharge. Additional outcomes considered included discharge to rehabilitation and home discharge with services. Bivariate and multivariable analyses were used to identify independent prognostic factors for non-home discharge. RESULTS: Of 2070 patients undergoing ACDF, 114 (5.5%) had non-home discharge and 63 (3.0%) had discharge to inpatient rehabilitation. Factors independently associated with non-home discharge included older age, marital status, Medicare insurance, Medicaid insurance, previous spine surgery, myelopathy, preoperative comorbidities (hemiplegia/paraplegia, congestive heart failure, cerebrovascular accident), anemia, and leukocytosis. C-statistic for the overall model was 0.85. Results were relatively similar for patients younger than the age of 65 years as well as for discharge to inpatient rehabilitation and discharge home with services. CONCLUSIONS: Numerous sociodemographic and clinical characteristics influence the risk of non-home discharge and discharge to inpatient rehabilitation in patients undergoing ACDF. Policy makers and payers should consider these factors when determining appropriate preoperative adjustment for risk-based reimbursements.

Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation.

BACKGROUND CONTEXT: Spine surgery has been identified as a risk factor for prolonged postoperative opioid use. Preoperative prediction of opioid use could improve risk stratification, shared decision-making, and patient counseling before surgery. PURPOSE: The primary purpose of this study was to develop algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation. STUDY DESIGN/SETTING: Retrospective, case-control study at five medical centers. PATIENT SAMPLE: Chart review was conducted for patients undergoing surgery for lumbar disc herniation between January 1, 2000 and March 1, 2018. OUTCOME MEASURES: The primary outcome of interest was sustained opioid prescription after surgery to at least 90 to 180 days postoperatively. METHODS: Five models (elastic-net penalized logistic regression, random forest, stochastic gradient boosting, neural network, and support vector machine) were developed to predict prolonged opioid prescription. Explanations of predictions were provided globally (averaged across all patients) and locally (for individual patients). RESULTS: Overall, 5,413 patients were identified, with sustained postoperative opioid prescription of 416 (7.7%) at 90 to 180 days after surgery. The elastic-net penalized logistic regression model had the best discrimination (c-statistic 0.81) and good calibration and overall performance; the three most important predictors were: instrumentation, duration of preoperative opioid prescription, and comorbidity of depression. The final models were incorporated into an open access web application able to provide predictions as well as patient-specific explanations of the results generated by the algorithms. The application can be found here: https://sorg-apps.shinyapps.io/lumbardiscopioid/ CONCLUSION: Preoperative prediction of prolonged postoperative opioid prescription can help identify candidates for increased surveillance after surgery. Patient-centered explanations of predictions can enhance both shared decision-making and quality of care.

Sagittal spinal parameters after en bloc resection of mobile spine tumors.

BACKGROUND CONTEXT: En bloc resection and reconstruction (EBR) in patients with spinal malignancy aims to achieve local disease control. This is an invasive procedure with significant alterations of the physiological anatomy and subsequently, the spino-pelvic alignment. Sagittal spinal parameters are useful measurements to objectively identify disproportionate alignment on a radiograph. In the field of spinal deformities, there is increasing evidence for a relationship between sagittal alignment and patient reported outcomes. PURPOSE: To determine sagittal spino-pelvic alignment after EBR in patients with spinal malignancies and the effect of these parameters on surgical and patient reported outcomes. STUDY DESIGN: A retrospective case series. METHODS: We included 35 patients who underwent EBR for spinal malignancies between 2000 and 2018. Radiographic measurements were performed using semi-automatic software; the parameters included were pelvic incidence (PI), sacral slope, pelvic tilt (PT), global tilt and lumbar lordosis. We calculated PI-based Global Alignment and Proportion (GAP) scores and prospective patient reported outcome scores Patient-Reported Outcome Measurement Information System-Physical Function (PROMIS-PF) were used. RESULTS: Twenty-one (60%) patients filled out the PROMIS-PF score at a median of 16 months (Interquartile Range (IQR) 4-108) after surgery with a median score of 39 (IQR 32-42), the median GAP score was 7 (IQR 5-9). Bivariate analysis showed no statistically significant relationship between GAP score and instrumentation failure or need for revision surgery. Multivariable analysis of GAP score and PROMIS-PF score corrected for local disease recurrence showed a statistically significant correlation coefficient of -1.721 (p=.026; 95%CI=-3.216, -0.226). CONCLUSION: In this cohort, all patients had a moderate or severe disproportioned spinal alignment after EBR and reconstruction surgery. The degree of sagittal spino-pelvic misalignment after EBR for spinal malignancies seems to be associated with patient reported health status in terms of PROMIS-PF scores. Further research with a larger patient cohort and standardized imaging and follow-up protocols is necessary in order to accurately use sagittal alignment as a predictive value for instrumentation failure and revision surgery.

Development of a machine learning algorithm predicting discharge placement after surgery for spondylolisthesis.

PURPOSE: We aimed to develop a machine learning algorithm that can accurately predict discharge placement in patients undergoing elective surgery for degenerative spondylolisthesis. METHODS: The National Surgical Quality Improvement Program (NSQIP) database was used to select patients that underwent surgical treatment for degenerative spondylolisthesis between 2009 and 2016. Our primary outcome measure was non-home discharge which was defined as any discharge not to home for which we grouped together all non-home discharge destinations including rehabilitation facility, skilled nursing facility, and unskilled nursing facility. We used Akaike information criterion to select the most appropriate model based on the outcomes of the stepwise backward logistic regression. Four machine learning algorithms were developed to predict discharge placement and were assessed by discrimination, calibration, and overall performance. RESULTS: Nine thousand three hundred and thirty-eight patients were included. Median age was 63 (interquartile range [IQR] 54-71), and 63% (n = 5,887) were female. The non-home discharge rate was 18.6%. Our models included age, sex, diabetes, elective surgery, BMI, procedure, number of levels, ASA class, preoperative white blood cell count, and preoperative creatinine. The Bayes point machine was considered the best model based on discrimination (AUC = 0.753), calibration (slope = 1.111; intercept = - 0.002), and overall model performance (Brier score = 0.132). CONCLUSION: This study has shown that it is possible to create a predictive machine learning algorithm with both good accuracy and calibration to predict discharge placement. Using our methodology, this type of model can be developed for many other conditions and (elective) treatments. These slides can be retrieved under Electronic Supplementary Material.

Machine learning for prediction of sustained opioid prescription after anterior cervical discectomy and fusion.

BACKGROUND CONTEXT: The severity of the opioid epidemic has increased scrutiny of opioid prescribing practices. Spine surgery is a high-risk episode for sustained postoperative opioid prescription. PURPOSE: To develop machine learning algorithms for preoperative prediction of sustained opioid prescription after anterior cervical discectomy and fusion (ACDF). STUDY DESIGN/SETTING: Retrospective, case-control study at two academic medical centers and three community hospitals. PATIENT SAMPLE: Electronic health records were queried for adult patients undergoing ACDF for degenerative disorders between January 1, 2000 and March 1, 2018. OUTCOME MEASURES: Sustained postoperative opioid prescription was defined as uninterrupted filing of prescription opioid extending to at least 90-180 days after surgery. METHODS: Five machine learning models were developed to predict postoperative opioid prescription and assessed for overall performance. RESULTS: Of 2,737 patients undergoing ACDF, 270 (9.9%) demonstrated sustained opioid prescription. Variables identified for prediction of sustained opioid prescription were male sex, multilevel surgery, myelopathy, tobacco use, insurance status (Medicaid, Medicare), duration of preoperative opioid use, and medications (antidepressants, benzodiazepines, beta-2-agonist, angiotensin-converting enzyme-inhibitors, gabapentin). The stochastic gradient boosting algorithm achieved the best performance with c-statistic=0.81 and good calibration. Global explanations of the model demonstrated that preoperative opioid duration, antidepressant use, tobacco use, and Medicaid insurance were the most important predictors of sustained postoperative opioid prescription. CONCLUSIONS: One-tenth of patients undergoing ACDF demonstrated sustained opioid prescription following surgery. Machine learning algorithms could be used to preoperatively stratify risk these patients, possibly enabling early intervention to reduce the potential for long-term opioid use in this population.

Computer-Assisted Navigation for Real Time Planning of Pedicle Subtraction Osteotomy in Cervico-Thoracic Deformity Correction.

BACKGROUND: Pedicle subtraction osteotomy (PSO) at the cervicothoracic junction (CTJ) is a powerful technique to correct severe kyphosis and sagittal malalignment. Reported techniques have demonstrated the safety and efficacy of the PSO, however limited visualization of surrounding tissues increases the potential for complications with this advanced technique. OBJECTIVE: To describe the application of computed tomographic (CT)-based image guidance to the planning and execution of PSO at the CTJ. METHODS: Intraoperative registration and verification of anatomic landmarks are performed with the intraoperative O-arm CT across the CTJ. With the navigation probe, the targeted pedicle is identified and the intended trajectories are rehearsed and saved on the navigational computer. As the PSO is performed, the navigation probe is used to check the depth, accuracy, and trajectory through each side. The extent of soft tissue dissection around the lateral aspect of the vertebral body through which the PSO is performed is also verified in real time. This technique was performed in 12 consecutive patients from 2013-2016. An IRB approved, retrospective analysis was performed from a prospective spinal deformity outcomes database. Patient consent is not required for publication as this report does not describe a specific case but rather a surgical technique used in practice. RESULTS: There were no vascular, esophageal, or soft tissue injuries in 12 consecutive patients. There were no cases of paralysis. Two patients developed hand weakness days after surgery. Intraoperative O-arm CT performed after closure of the osteotomy confirmed the accuracy of the osteotomy planning with no breach of the anterior cortical wall of the osteotomized vertebral body. CONCLUSION: CT-guided navigation allows for 3-dimensional visualization of the CTJ and minimizes complications associated with inadequate surgical visualization of vascular and deep organ structures.

Practice Variation Among Surgeons Treating Lumbar Spinal Stenosis in a Single Institution.

STUDY DESIGN: A retrospective study. OBJECTIVE: The aim of this study was to examine practice variation in the treatment of lumbar spinal stenosis and identify targets for reducing variation. SUMMARY OF BACKGROUND DATA: Lumbar spinal stenosis is a degenerative condition susceptible to practice variation. Reducing variation aims to improve quality, increase safety, and lower costs. Establishing differences in surgeons' practices from a single institution can help identify personalized variation. METHODS: We identified adult patients first diagnosed with lumbar spinal stenosis between 2003 and 2015 in three hospitals of the same institution with ICD-9 codes.We extracted number of office visits, imaging procedures, injections, electromyographies (EMGs), and surgery within the first year after diagnosis; physical therapy within the first 3 months after diagnosis. Multivariable logistic regression was used to identify factors associated with surgery. The coefficient of variation (CV) was calculated to compare the variation in practice. RESULTS: The 10,858 patients we included had an average of 2.5 visits (±1.9), 1.5 imaging procedures (±2.0), 0.03 EMGs (±0.22), and 0.16 injections (±0.53); 36% had at least one surgical procedure and 32% had physical therapy as part of their care. The CV was smallest for number of visits (19%) and largest for EMG (140%).Male sex [odds ratio (OR): 1.23, P < 0.001], seeing an additional surgeon (OR: 2.82, P < 0.001), and having an additional spine diagnosis (OR: 3.71, P < 0.001) were independently associated with surgery. Visiting an orthopedic clinic (OR: 0.46, P < 0.001) was independently associated with less surgical interventions than visiting a neurosurgical clinic. CONCLUSION: There is widespread variation in the entire spectrum of diagnosis and therapy for lumbar spinal stenosis among surgeons in the same institution. Male gender, seeing an additional surgeon, having an additional spine diagnosis, and visiting a neurosurgery clinic were independently associated with increased surgical intervention. The main target we identified for decreasing variability was the use of diagnostic EMG. LEVEL OF EVIDENCE: 3.