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Objective: To identify the impact of osteoporosis (OS) on postoperative outcomes in Medicare patients undergoing ASD surgery. Background: Patients with OP and advanced age experience higher than average rates of ASD. However, poor bone density could undermine the durability of a deformity correction. Methods: We queried the MarketScan Medicare Supplemental database to identify patients Medicare patients who underwent ASD surgery from 2007 to 2016. Results: A total of 2564 patients met the inclusion criteria of this study, of whom n = 971 (61.0%) were diagnosed with osteoporosis. Patients with OP had a similar 90-day postoperative complication rates (OP: 54.6% vs. non-OP: 49.2%, p = 0.0076, not significant after multivariate regression correction). This was primarily driven by posthemorrhagic anemia (37.6% in OP, vs. 33.1% in non-OP). Rates of revision surgery were similar at 90 days (non-OP 15.0%, OP 16.8%), but by 2 years, OP patients had a significantly higher reoperation rate (30.4% vs. 22.9%, p < 0.0001). In multivariate regression analysis, OP increased odds for revision surgery at 1 year (OR 1.4) and 2 years (OR 1.5) following surgery (all p < 0.05). OP was also an independent predictor of readmission at all time points (90 days, OR 1.3, p < 0.005). Conclusion: Medicare patients with OP had elevated rates of complications, reoperations, and outpatient costs after undergoing primary ASD surgery. [ABSTRACT FROM AUTHOR]

To compare complications, readmissions, revisions, and payments between navigated and conventional pedicle screw fixation for treatment of spine deformity. The Thomson Reuters MarketScan national longitudinal database was used to identify patients undergoing osteotomy, posterior instrumentation, and fusion for treatment of spinal deformity with or without image-guided navigation between 2007-2016. Conventional and navigated groups were propensity-matched (1:1) to normalize differences between demographics, comorbidities, and surgical characteristics. Clinical outcomes and charges were compared between matched groups using bivariate analyses. A total of 4,604 patients were identified as having undergone deformity correction, of which 286 (6.2%) were navigated. Propensity-matching resulted in a total of 572 well-matched patients for subsequent analyses, of which half were navigated. Rate of mechanical instrumentation-related complications was found to be significantly lower for navigated procedures (p = 0.0371). Navigation was also associated with lower rates of 90-day unplanned readmissions (p = 0.0295), as well as 30- and 90-day postoperative revisions (30-day: p = 0.0304, 90-day: p = 0.0059). Hospital, physician, and total payments favored the conventional group for initial admission (p = 0.0481, 0.0001, 0.0019, respectively); however, when taking into account costs of readmissions, hospital payments became insignificantly different between the two groups. Procedures involving image-guided navigation resulted in decreased instrumentation-related complications, unplanned readmissions, and postoperative revisions, highlighting its potential utility for the treatment of spine deformity. Future advances in navigation technologies and methodologies can continue to improve clinical outcomes, decrease costs, and facilitate widespread adoption of navigation for deformity correction. [ABSTRACT FROM AUTHOR]

We assessed whether the insurance type reflects a patient's quality of care after an anterior discectomy and fusion (ACDF) procedure by comparing differences in the postoperative complications, readmission rates, reoperation rates, lengths of hospital stay, and cost of treatment between patients with Medicare versus private insurance. Propensity score matching was used to match patient cohorts insured by Medicare and private insurance in the MarketScan Commercial Claims and Encounters Database (2007–2016). Age, sex, year of operation, geographic region, comorbidities, and operative factors were used to match cohorts of patients who had undergone an ACDF procedure. A total of 110,911 patients met the inclusion criteria. Of these patients, 97,543 patients (87.9%) were privately insured and 13,368 patients (12.1%) were insured by Medicare. The propensity score matching algorithm matched 7026 privately insured patients to 7026 Medicare patients. After matching, no significant differences were found in the 90-day postoperative complication rates, lengths of stay, or reoperation rates between the Medicare and privately insured cohorts. The Medicare group had had lower postoperative readmission rates for all time points: 30 days (1.8% vs. 4.6%; P < 0.001), 60 days (2.5% vs. 6.3%; P < 0.001), and 90 days (4.2% vs. 7.7%; P < 0.001). The median payment to physicians was significantly lower for the Medicare group ($3885 vs. $5601; P < 0.001). In the present study, propensity score matched patients covered by Medicare and private insurance who had undergone an ACDF procedure had had similar treatment outcomes. [ABSTRACT FROM AUTHOR]

Study Design: Retrospective cohort.Objective: Due to anterior cervical discectomy and fusion (ACDF) popularity, it is important to predict postoperative complications, unfavorable 90-day readmissions, and two-year reoperations to improve surgical decision-making, prognostication, and planning.Summary Of Background Data: Machine learning has been applied to predict postoperative complications for ACDF; however, studies were limited by sample size and model type. These studies achieved ≤0.70 area under the curve (AUC). Further approaches, not limited to ACDF, focused on specific complication types and resulted in AUC between 0.70 and 0.76.Materials and Methods: The IBM MarketScan Commercial Claims and Encounters Database and Medicare Supplement were queried from 2007 to 2016 to identify adult patients who underwent an ACDF procedure (N=176,816). Traditional machine learning algorithms, logistic regression, and support vector machines, were compared with deep neural networks to predict: 90-day postoperative complications, 90-day readmission, and two-year reoperation. We further generated random deep learning model architectures and trained them on the 90-day complication task to approximate an upper bound. Last, using deep learning, we investigated the importance of each input variable for the prediction of 90-day postoperative complications in ACDF.Results: For the prediction of 90-day complication, 90-day readmission, and two-year reoperation, the deep neural network-based models achieved AUC of 0.832, 0.713, and 0.671. Logistic regression achieved AUCs of 0.820, 0.712, and 0.671. Support vector machine approaches were significantly lower. The upper bound of deep learning performance was approximated as 0.832. Myelopathy, age, human immunodeficiency virus, previous myocardial infarctions, obesity, and documentary weakness were found to be the strongest variable to predict 90-day postoperative complications.Conclusions: The deep neural network may be used to predict complications for clinical applications after multicenter validation. The results suggest limited added knowledge exists in interactions between the input variables used for this task. Future work should identify novel variables to increase predictive power. [ABSTRACT FROM AUTHOR]

Candidates for anterior cervical discectomy and fusion (ACDF) have a higher rate of opioid use than does the public, but studies on preoperative opioid use have not been conducted. We aimed to understand how preoperative opioid use affects post-ACDF outcomes. The MarketScan Database was queried from 2007 to 2015 to identify adult patients who underwent an ACDF. Patients were classified into separate cohorts based on the number of separate opioid prescriptions in the year before their ACDF. Ninety-day postoperative complications, postoperative readmission, reoperation, and total inpatient costs were compared between opioid strata. Propensity score-matched patient cohorts were calculated to balance comorbidities across groups. Of 81,671 ACDF patients, 31,312 (38.3%) were nonusers, 30,302 (37.1%) were mild users, and 20,057 (24.6%) were chronic users. Chronic opioid users had a higher comorbidity burden, on average, than patients with less frequent opioid use (P < 0.001). Chronic opioid users had higher rates of postoperative complications (9.1%) than mild opioid users (6.0%) and nonusers (5.3%) (P < 0.001) and higher rates of readmission and reoperation. After balancing opioid nonusers versus chronic opioid users along with demographic characteristics, preoperative comorbidity, and operative characteristics, postoperative complications remained elevated for chronic opioid users relative to opioid nonusers (8.6% vs. 5.7%; P < 0.001), as did rates of readmission and reoperation. Chronic opioid users had more comorbidities than opioid nonusers and mild opioid users, longer hospitalizations, and higher rates of postoperative complication, readmission, and reoperation. After balancing patients across covariates, the outcome differences persisted, suggesting a durable association between preoperative opioid use and negative postoperative outcomes. [ABSTRACT FROM AUTHOR]