Search

Objective: Metastatic spinal tumors represent a rare but concerning complication of primary thyroid carcinoma. We identified demographics, metastatic features, outcomes, and treatment strategies for these tumors in our institutional cohort. Materials and Methods: We retrospectively reviewed patients surgically treated for spinal metastases of primary thyroid carcinoma. Demographics, tumor characteristics, and treatment modalities were collected. The functional outcomes were quantified using Nurik, Modified Rankin, and Karnofsky Scores. Results: Twelve patients were identified who underwent 17 surgeries for resection of spinal metastases. The primary thyroid tumor pathologies included papillary (4/12), follicular (6/12), and Hurthle cell (2/12) subtypes. The average number of spinal metastases was 2.5. Of the primary tumor subtypes, follicular tumors averaged 2.8 metastases at the highest and Hurthle cell tumors averaged 2.0 spinal metastases at the lowest. Five patients (41.7%) underwent preoperative embolization for their spinal metastases. Seven patients (58.3%) received postoperative radiation. There was no significant difference in progression-free survival between patients receiving surgery with adjuvant radiation and surgery alone (P = 0.0773). Five patients (41.7%) experienced postoperative complications. Two patients (16.7%) succumbed to disease progression and two patients (16.7%) experienced tumor recurrence following resection. Postsurgical mean Nurik scores decreased 0.54 points, mean Modified Rankin scores decreased 0.48 points, and mean Karnofsky scores increased 4.8 points. Conclusion: Surgery presents as an important treatment modality in the management of spinal metastases from thyroid cancer. Further work is needed to understand the predictive factors for survival and outcomes following treatment.

Introduction: Atlas fractures often accompany traumatic dens fractures, but existing literature on the management of simultaneous atlantoaxial fractures is limited. Methods: We examined all patients with traumatic dens fractures at our institution between 2008 and 2018. We used multivariable logistic regression and ordinal logistic regression to identify factors independently associated with presentation with a simultaneous atlas fracture, as well myelopathy severity, fracture nonunion, and selection for surgery. Results: Two hundred and eighty-two patients with traumatic dens fractures without subaxial fractures were identified, including 65 (22.8%) with simultaneous atlas fractures. The distribution of injury mechanisms differed between groups (χ2 P = 0.0360). On multivariable logistic regression, dens nonunion was positively associated with type II fractures (odds ratio [OR] = 2.00, P = 0.038) and negatively associated with having surgery (OR = 0.52, P = 0.049), but not with having a C1 fracture (P = 0.3673). Worse myelopathy severity on presentation was associated with having a severe injury severity score (OR = 102.3, P < 0.001) and older age (OR = 1.28, P = 0.002), but not with having an atlas fracture (P = 0.2446). Having a simultaneous atlas fracture was associated with older age (OR = 1.29, P = 0.024) and dens fracture angulation (OR = 2.62, P = 0.004). Among patients who underwent surgery, C1/C2 posterior fusion was the most common procedure, and having a simultaneous atlas fracture was associated with selection for occipitocervical fusion (OCF) (OR = 14.35, P = 0.010). Conclusions: Among patients with traumatic dens, patients who have simultaneous atlas fractures are a distinct subpopulation with respect to age, mechanism of injury, fracture morphology, and management. Traumatic dens fractures with simultaneous atlas fractures are independently associated with selection for OCF rather than posterior cervical fusion alone.

Objective: Venous thromboembolic event (VTE) after spine surgery is a rare but potentially devastating complication. With the advent of machine learning, an opportunity exists for more accurate prediction of such events to aid in prevention and treatment. Methods: Seven models were screened using 108 database variables and 62 preoperative variables. These models included deep neural network (DNN), DNN with synthetic minority oversampling technique (SMOTE), logistic regression, ridge regression, lasso regression, simple linear regression, and gradient boosting classifier. Relevant metrics were compared between each model. The top four models were selected based on area under the receiver operator curve; these models included DNN with SMOTE, linear regression, lasso regression, and ridge regression. Separate random sampling of each model was performed 1000 additional independent times using a randomly generated training/testing distribution. Variable weights and magnitudes were analyzed after sampling. Results: Using all patient-related variables, DNN using SMOTE was the top-performing model in predicting postoperative VTE after spinal surgery (area under the curve [AUC] =0.904), followed by lasso regression (AUC = 0.894), ridge regression (AUC = 0.873), and linear regression (AUC = 0.864). When analyzing a subset of only preoperative variables, the top-performing models were lasso regression (AUC = 0.865) and DNN with SMOTE (AUC = 0.864), both of which outperform any currently published models. Main model contributions relied heavily on variables associated with history of thromboembolic events, length of surgical/anesthetic time, and use of postoperative chemoprophylaxis. Conclusions: The current study provides promise toward machine learning methods geared toward predicting postoperative complications after spine surgery. Further study is needed in order to best quantify and model real-world risk for such events.

Background: Patients with simultaneous fractures of the atlas and dens have traditionally been managed according to the dens fracture's morphology, but data supporting this practice are limited. Methods: We retrospectively examined all patients with traumatic atlas fractures at our institution between 2008 and 2016. We used multivariable regression and propensity score matching to compare the presentation, management, and outcomes of patients with isolated atlas fractures to patients with simultaneous atlas-dens fractures. Results: Ninety-nine patients were identified. Patients with isolated atlas fractures were younger (61 ± 22 vs. 77 ± 14, P = 0.0003), had lower median Charlson Comorbidity Index (3 vs. 5, P = 0.0005), had better presenting Nurick myelopathy scores (0 vs. 3, P < 0.0001), and had different mechanisms of injury (P = 0.0011). Multivariable regression showed that having a simultaneous atlas-dens fracture was independently associated with older age (odds ratio [OR] =1.59 [1.22, 2.07], P = 0.001), worse presenting myelopathy (OR = 3.10 [2.04, 4.16], P < 0.001), and selection for surgery (OR = 4.91 [1.10, 21.97], P = 0.037). Propensity score matching yielded balanced populations (Rubin's B = 23.3, Rubin's R = 1.96) and showed that the risk of atlas fracture nonunion was no different among isolated atlas fractures compared to simultaneous atlas-dens fractures (P = 0.304). Age was the only variable independently associated with atlas fracture nonunion (OR = 2.39 [1.15, 5.00], P = 0.020), having a simultaneous atlas-dens fracture was not significant (P = 0.2829). Conclusions: Among patients with atlas fractures, simultaneous fractures of the dens occur in older patients and confer an increased risk of myelopathy and requiring surgical stabilization. Controlling for confounders, the risk of atlas fracture nonunion is equivalent for isolated atlas fractures versus simultaneous atlas-dens fractures.

Background: Social media use is increasingly common among academic neurosurgery departments, but its relationship with academic metrics remains underexamined. Methods: We examine the relationship between American academic neurosurgery departments’ number of followers on Twitter, Instagram, and Facebook and the following academic metrics: Doximity Residency rankings, US News & World Report rankings (USNWR) of their affiliated medical schools, and the amount of NIH funding of those schools. Results: Few departments had disproportionate number of followers. A greater proportion of programs had Twitter accounts (88.9%) than had Instagram (72.2%) or Facebook (51.9%) accounts (p=0.0001). Programs identified as ''Influencers'' had more departmental NIH funding (p=0.044), more institutional NIH funding (p=0.035), better Doximity residency rankings (p=0.044), and better affiliated medical school rankings (p=0.002). Number of Twitter followers had the strongest correlation with academic metrics, yet only modest correlations were identified to departmental NIH funding (R=0.496, p=0.0001), institutional NIH funding (R=0.387, p=0.0072), Doximity residency rank (R=0.411, p=0.0020), and affiliated medical school ranking (R=0.545,p

Background: The coronavirus (COVID-19) pandemic has caused unprecedented suspensions of neurosurgical elective surgeries, a large proportion of which involve spine procedures. The goal of this study is to report granular data on the impact of early COVID-19 pandemic operating room restrictions upon neurosurgical case volume in academic institutions, with attention to its secondary impact upon neurosurgery resident training. This is the first multicenter quantitative study examining these early effects upon neurosurgery residents caseloads. Methods: A retrospective review of neurosurgical caseloads among seven residency programs between March 2019 and April 2020 was conducted. Cases were grouped by ACGME Neurosurgery Case Categories, subspecialty, and urgency (elective vs. emergent). Residents caseloads were stratified into junior (PGY1-3) and senior (PGY4-7) levels. Descriptive statistics are reported for individual programs and pooled across institutions. Results: When pooling across programs, the 2019 monthly mean (SD) case volume was 214 (123) cases compared to 217 (129) in January 2020, 210 (115) in February 2020, 157 (81), in March 2020 and 82 (39) cases April 2020. There was a 60% reduction in caseload between April 2019 (207 [101]) and April 2020 (82 [39]). Adult spine cases were impacted the most in the pooled analysis, with a 66% decrease in the mean number of cases between March 2020 and April 2020. Both junior and senior residents experienced a similar steady decrease in caseloads, with the largest decreases occurring between March and April 2020 (48% downtrend). Conclusions: Results from our multicenter study reveal considerable decreases in caseloads in the neurosurgical specialty with elective adult spine cases experiencing the most severe decline. Both junior and senior neurosurgical residents experienced dramatic decreases in case volumes during this period. With the steep decline in elective spine cases, it is possible that fellowship directors may see a disproportionate increase in spine fellowships in the coming years. In the face of the emerging Delta and Omicron variants, programs should pay attention toward identifying institution-specific deficiencies and developing plans to mitigate the negative educational effects secondary to such caseloads reduction.