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To characterize the volume dependence of both facilities and surgeons on postoperative complications after lumbar fusion and characterize the role of socioeconomic status.Adults who underwent lumbar fusion from 2011 to 2015 were identified using International Classification of Diseases, Ninth Revision, Clinical Modification diagnostic codes for lumbar disc degeneration or spondylolisthesis and procedure codes for lumbar fusion in the New York Statewide Planning and Research Cooperative System database. Complications were compared across surgeon and facility volumes using multivariable Cox proportional hazards regression, controlling for patient demographic and clinical factors. Surgeon and facility volumes were compared between the lowest and highest 20%.Of the 26,211 patients identified with a lumbar fusion, 16,377 patients were treated at a high-volume or low-volume facility or by a high-volume or low-volume surgeon. Low-volume facilities had higher 3-month and 12-month rates of readmission, pneumonia, and cellulitis; lower 1-month, 3-month, and 12-month rates of deep vein thrombosis; and lower 1-month rates of wound complications. Low-volume surgeons had higher 1-month, 3-month, and 12-month rates of readmission, acute renal failure, surgical site infection, and wound complications; high 1-month and 3-month rates of urinary tract infection and pulmonary embolism; and a lower 12-month rate of revision. Patients who were treated by low-volume surgeons and had complications were more concentrated to ZIP codes with high social deprivation.Both high-volume facilities and high-volume surgeons show lower rates of complications and readmission. There are significant socioeconomic disparities regarding which patients can access high-volume surgeons.

Three-column osteotomy (3-CO) is a powerful tool for spinal deformity correction but has been associated with substantial risk and surgical invasiveness. It is incompletely understood how frailty might affect patients undergoing 3-CO.The PearlDiver database was used to examine spinal deformity patients with a diagnosis of frailty who had undergone 3-CO. Frail and nonfrail patients were matched, and the revision surgery rates, complications, and hospitalization costs were calculated. Logistic regression was used to account for possible confounding variables. Of the 2871 included patients, 1460 had had frailty and 1411 had had no frailty.The frail patients were older, had had more comorbidities (P0.001), and were more likely to have undergone posterior interbody fusion (P0.05), without differences in the anterior interbody fusion rates. No differences were found in the reoperation rates for ≤5 years. At 30 days, the frail patients were more likely to have experienced acute kidney injury (P = 0.018), bowel/bladder dysfunction (P = 0.014), cardiac complications (P = 0.006), and pneumonia (P = 0.039). At 2 years, the frail patients were also more likely to have experienced bowel/bladder dysfunction (P = 0.028), cardiac complications (P 0.001), deep vein thrombosis (P = 0.027), and sepsis (P = 0.033). The cost for the procedures was also higher for the frail patients than for the nonfrail patients ($24,544.79 vs. $21,565.63; P = 0.043).We found that frail patients undergoing 3-CO were more likely to experience certain medical complications and had had higher associated costs but similar reoperation rates compared with nonfrail patients. Careful patient selection and surgical strategy modification might alter the risks of medical and surgical complications after 3-CO for frail patients.

Background Readmission after spine surgery is costly and a relatively common occurrence. Previous research identified several risk factors for readmission; however, the conclusions remain equivocal. Machine learning algorithms offer a unique perspective in analysis of risk factors for readmission and can help predict the likelihood of this occurrence. This study evaluated a neural network (NN), a supervised machine learning technique, to determine whether it could predict readmission after 3 lumbar fusion procedures. Methods The American College of Surgeons National Surgical Quality Improvement Program database was queried between 2009 and 2018. Patients who had undergone anterior, lateral, and/or posterior lumbar fusion were included in the study. The Python scikit Learn package was used to run the NN algorithm. A multivariate regression was performed to determine risk factors for readmission. Results There were 63,533 patients analyzed (12,915 anterior lumbar interbody fusion, 27,212 posterior lumbar interbody fusion, and 23,406 posterior spinal fusion cases). The NN algorithm was able to successfully predict 30-day readmission for 94.6% of anterior lumbar interbody fusion, 94.0% of posterior lumbar interbody fusion, and 92.6% of posterior spinal fusion cases with area under the curve values of 0.64–0.65. Multivariate regression indicated that age >65 years and American Society of Anesthesiologists class >II were linked to increased risk for readmission for all 3 procedures. Conclusions The accurate metrics presented indicate the capability for NN algorithms to predict readmission after lumbar arthrodesis. Moreover, the results of this study serve as a catalyst for further research into the utility of machine learning in spine surgery.

Objective To evaluate the relationship between chiropractic spinal manipulation and medical malpractice using a legal database. Methods The legal database VerdictSearch was queried using the terms “chiropractor” OR “spinal manipulation” under the classification of “Medical Malpractice” between 1988 and 2018. Cases with chiropractors as defendants were identified. Relevant medicolegal characteristics were obtained, including legal outcome (plaintiff/defense verdict, settlement), payment amount, nature of plaintiff claim, and type and location of alleged injury. Results Forty-eight cases involving chiropractic management in the United States were reported. Of these, 93.8% (n = 45) featured allegations involving spinal manipulation. The defense (practitioner) was victorious in 70.8% (n = 34) of cases, with a plaintiff (patient) victory in 20.8% (n = 10) (mean payment $658,487 ± $697,045) and settlement in 8.3% (n = 4) (mean payment $596,667 ± $402,534). Overaggressive manipulation was the most frequent allegation (33.3%; 16 cases). A majority of cases alleged neurological injury of the spine as the reason for litigation (66.7%, 32 cases) with 87.5% (28/32) requiring surgery. C5-C6 disc herniation was the most frequently alleged injury (32.4%, 11/34, 83.3% requiring surgery) followed by C6-C7 herniation (26.5%, 9/34, 88.9% requiring surgery). Claims also alleged 7 cases of stroke (14.6%) and 2 rib fractures (4.2%) from manipulation therapy. Conclusions Litigation claims following chiropractic care predominately alleged neurological injury with consequent surgical management. Plaintiffs primarily alleged overaggressive treatment, though a majority of trials ended in defensive verdicts. Ongoing analysis of malpractice provides a unique lens through which to view this complicated topic.

Cauda equina syndrome (CES) is a potentially devastating spinal condition requiring prompt diagnosis and intervention. This study examines the relationship between timing of surgery and patient outcomes such as mortality and total complications, and longitudinal trends in timing of operative treatment over the years 2000-2014.This study considered patients in the Healthcare Cost and Utilization Project National Inpatient Sample Database between 2000 and 2014 who had both an International Classification of Disease, Ninth Edition, Clinical Modification code for CES (344.61) and an International Classification of Disease, Ninth Edition, Clinical Modification procedure code for either disc excision (8051) or spinal canal exploration and decompression (0309) in their inpatient record. Patients were separated into an early surgical intervention cohort versus a delayed intervention cohort, and associated outcomes were analyzed using linear regression. Trends in timing of surgery were examined for the years 2000-2014, and linear regression was used to assess degree of change over time.In total, 20,924 patients with CES met inclusion criteria. Following adjustment for demographic variables, the delayed-intervention group was associated with statistically significant increased inpatient mortality (odds ratio [OR] 9.60, P = 0.002), total complications (OR 1.41, P = 0.018), and non-routine discharge (OR 2.37, P0.0001). The proportion of patients receiving early intervention within 48 hours remained unchanged from 2000 to 2014 ranging from 80.2% (2000-2002) to 76.2% (2012-2014) (P = 0.190).This study represents the largest investigation to date examining CES and reveals the timing of surgical management for CES has not changed appreciably from 2000 to 2014 despite mounting evidence for early decompression. Patients receiving decompression within 0 or 1 day after admission are associated with improved inpatient outcomes, including lower complication and mortality rates.

Mortality following surgical resection of spinal tumors is a devastating outcome. Naïve Bayes machine learning algorithms may be leveraged in surgical planning to predict mortality. In this investigation, we use a Naïve Bayes classification algorithm to predict mortality following spinal tumor excision within 30 days of surgery.Patients who underwent laminectomies between 2006 and 2018 for excisions of intraspinal neoplasms were selected from the National Surgical Quality Initiative Program. Naïve Bayes classifier analysis was conducted in Python. The area under the receiver operating curve (AUC) was calculated to evaluate the classifier's ability to predict mortality within 30 days of surgery. Multivariable logistic regression analysis was performed in R to identify risk factors for 30-day postoperative mortality.In total, 2094 spine tumor surgery patients were included in the study. The 30-day mortality rate was 5.16%. The classifier yielded an AUC of 0.898, which exceeds the predictive capacity of the National Surgical Quality Initiative Program mortality probability calculator's AUC of 0.722 (P0.0001). The multivariable regression indicated that smoking history, chronic obstructive pulmonary disease, disseminated cancer, bleeding disorder history, dyspnea, and low albumin levels were strongly associated with 30-day mortality.The Naïve Bayes classifier may be used to predict 30-day mortality for patients undergoing spine tumor excisions, with an increasing degree of accuracy as the model better performs by learning continuously from the input patient data. Patient outcomes can be improved by identifying high-risk populations early using the algorithm and applying that data to inform preoperative decision making, as well as patient selection and education.

To evaluate the effect of a recent history of total hip arthroplasty (THA) on primary lumbar spine fusion (LSF) for concurrent hip and spine disease.A total of 98,242 patient records from the PearlDiver Database were evaluated and divided into 3 cohorts: 1) patients with a history of LSF alone, 2) patients with a history of LSF for newly diagnosed lumbar disease after having a remote THA2 years previously, and 3) patients with a history of LSF after having recent THA2 years before LSF who initially presented with concurrent hip and lumbar spine disease and underwent THA before LSF. Postoperative outcomes were assessed with multivariable logistic regression to determine the effect of THA on outcomes after LSF with respect to postoperative complications, LSF revision rates, and opioid use.Patients who had LSF after a recent THA had increased risk of deep venous thrombosis (adjusted odds ratio [aOR], 1.39; P = 0.0191), neurologic complications (aOR, 1.81; P = 0.0459), prolonged opioid use (aOR, 1.22; P = 0.0032), and revision LSF (12.8%; P = 0.0004 vs. 9.9%; OR, 1.41; P0.0001; hazard ratio, 1.69; P0.0001). Patients who underwent LSF after a remote history of THA had no significant difference in DVT (4.2% vs. 2.6%, aOR, 1.31; P = 0.2190), neurologic complications (1.0% vs. 0.5%, aOR, 2.02; P = 0.1220), revision surgery (9.6% vs. 9.9%, aOR, 1.06; P = 0.7197), or prolonged opioid use (36.5% vs. 24.4%, aOR, 1.17; P = 0.1120).Patients who undergo LSF with a history of THA may be at increased risk of postoperative complications, revision LSF, and prolonged opioid use if their THA was performed for concurrent hip-spine disease in the recent past (2 years).