Comparison between endovascular and surgical treatment of spinal dural arteriovenous fistulas: a single-center cohort and systematic review.

OBJECTIVE: With recent advancements in minimally invasive techniques, endovascular embolization has gained popularity as a first-line treatment option for spinal dural arteriovenous fistulas (sDAVFs). The authors present their institution's case series of sDAVFs treated endovascularly and surgically, and they performed a systemic review to assess the outcomes of both modalities of treatment. METHODS: The authors conducted a retrospective observational study of 24 consecutive patients with sDAVFs treated between 2013 and 2023. The primary outcome was the rate of occlusion, which was compared between the surgically and endovascularly treated sDAVFs. They also conducted a systemic review of all the literature comparing outcomes of endovascular and surgical treatment of sDAVFs. RESULTS: A total of 24 patients with 24 sDAVFs were studied. The mean patient age was 63.8 ± 15.5 years, and the majority of patients were male (n = 19, 79.2%). Of the 24 patients, 8 (33.3%) received endovascular treatment, 15 (62.5%) received surgical treatment, and 1 (4.2%) patient received both. Complete occlusion at first follow-up was higher in the surgical cohort but did not achieve statistical significance (66.7% vs 25%, p = 0.52). Recurrence was higher in the endovascular cohort (37.5% vs 13.3%, p = 0.3), while the rate of postprocedural complications was higher in the surgical cohort (13.3% vs 0%, p = 0.52); however, neither of these differences was statistically significant. CONCLUSIONS: Endovascular embolization in the management of sDAVFs is an alternative treatment to surgery, whose long-term efficacy is still under investigation. These findings suggest overall comparable outcomes between endovascular and open surgical treatment of sDAVFs. Future studies are needed to determine the role of endovascular embolization in the overall management of sDAVFs.

Causes and Predictors of 30-Day Readmission in Patients With Stroke Undergoing Mechanical Thrombectomy: A Large Single-Center Experience.

BACKGROUND AND OBJECTIVES: The 30-day readmission rate has emerged as a metric of quality care and is associated with increased health care expenditure. We aim to identify the rate and causes of 30-day readmission after mechanical thrombectomy and provide the risk factors of readmission to highlight high-risk patients who may require closer care. METHODS: This is a retrospective study from a prospectively maintained database of 703 patients presenting for mechanical thrombectomy between 2017 and 2023. All patients who presented with a stroke and underwent a mechanical thrombectomy were included in this study. Patients who were deceased on discharge were excluded from this study. RESULTS: Our study comprised 703 patients, mostly female (n = 402, 57.2%) with a mean age of 70.2 years ±15.4. The most common causes of readmission were cerebrovascular events (stroke [n = 21, 36.2%], intracranial hemorrhage [n = 9, 15.5%], and transient ischemic attack [n = 1, 1.7%]).Other causes of readmission included cardiovascular events (cardiac arrest [n = 4, 6.9%] and bradycardia [n = 1, 1.7%]), infection (wound infection postcraniectomy [n = 3, 5.2%], and pneumonia [n = 1, 1.7%]). On multivariate analysis, independent predictors of 30-day readmission were history of smoking (odds ratio [OR]: 2.2, 95% CI: 1.1-4.2) P = .01), distal embolization (OR: 3.2, 95% CI: 1.1-8.7, P = .03), decompressive hemicraniectomy (OR: 9.3, 95% CI: 3.2-27.6, P < .01), and intracranial stent placement (OR: 4.6, 95% CI: 2.4-8.7) P < .01). CONCLUSION: In our study, the rate of 30-day readmission was 8.3%, and the most common cause of readmission was recurrent strokes. We identified a history of smoking, distal embolization, decompressive hemicraniectomy, and intracranial stenting as independent predictors of 30-day readmission in patients with stroke undergoing mechanical thrombectomy.

What Factors Predict the Development of Neurologic Deficits Following Resection of Intramedullary Spinal Cord Tumors: A Multi-Center Study.

BACKGROUND: Intramedullary spinal cord tumors are challenging to resect, and their postoperative neurological outcomes are often difficult to predict, with few studies assessing this outcome. METHODS: We reviewed the medical records of all patients surgically treated for Intramedullary spinal cord tumors at our multisite tertiary care institution (Mayo Clinic Arizona, Mayo Clinic Florida, Mayo Clinic Rochester) between June 2002 and May 2020. Variables that were significant in the univariate analyses were included in a multivariate logistic regression. "MissForest" operating on the Random Forest algorithm, was used for data imputation, and K-prototype was used for data clustering. Heatmaps were added to show correlations between postoperative neurological deficit and all other included variables. Shapley Additive exPlanations were implemented to understand each feature's importance. RESULTS: Our query resulted in 315 patients, with 160 meeting the inclusion criteria. There were 53 patients with astrocytoma, 66 with ependymoma, and 41 with hemangioblastoma. The mean age (standard deviation) was 42.3 (17.5), and 48.1% of patients were women (n = 77/160). Multivariate analysis revealed that pathologic grade >3 (OR = 1.55; CI = [0.67, 3.58], P = 0.046 predicted a new neurological deficit. Random Forest algorithm (supervised machine learning) found age, use of neuromonitoring, histology of the tumor, performing a midline myelotomy, and tumor location to be the most important predictors of new postoperative neurological deficits. CONCLUSIONS: Tumor grade/histology, age, use of neuromonitoring, and myelotomy type appeared to be most predictive of postoperative neurological deficits. These results can be used to better inform patients of perioperative risk.

General Versus Nongeneral Anesthesia for Spinal Surgery: A Comparative National Analysis of Reimbursement Trends Over 10 Years.

BACKGROUND AND OBJECTIVES: Nongeneral anesthesia (non-GA) spine surgery is growing in popularity and has facilitated earlier postoperative recovery, reduced cost, and fewer complications compared with spine surgery under general anesthesia (GA). Changes in reimbursement policies have been demonstrated to correlate with clinical practice; however, they have yet to be studied for GA vs non-GA spine procedures. We aimed to investigate trends in physician reimbursement for GA vs non-GA spine surgery in the United States. METHODS: We queried the ACS-NSQIP for GA and non-GA (regional, epidural, spinal, and anesthesia care/intravenous sedation) spine surgeries during 2011-2020. Work relative value units per operative hour (wRVUs/h) were retrieved for decompression or stabilization of the cervical, thoracic, and lumbar spine. Propensity score matching (1:1) was performed using all baseline variables. RESULTS: We included 474 706 patients who underwent spine decompression or stabilization procedures. GA was used in 472 248 operations, whereas 2458 operations were non-GA. The proportion of non-GA spine operations significantly increased during the study period. Operative times ( P < .001) and length of stays ( P < .001) were shorter in non-GA when compared with GA procedures. Non-GA lumbar procedures had significantly higher wRVUs/h when compared with the same procedures performed under GA (decompression; P < .001 and stabilization; P = .039). However, the same could not be said about cervicothoracic procedures. Lumbar decompression surgeries using non-GA witnessed significant yearly increase in wRVUs/h ( P < .01) contrary to GA ( P = .72). Physician reimbursement remained stable for procedures of the cervical or thoracic spine regardless of the anesthesia. CONCLUSION: Non-GA lumbar decompressions and stabilizations are associated with higher and increasing reimbursement trends (wRVUs/h) compared with those under GA. Reimbursement for cervical and thoracic surgeries was equal regardless of the type of anesthesia and being relatively stable during the study period. The adoption of a non-GA technique relative to the GA increased significantly during the study period.

Surgical management of malignant melanotic nerve sheath tumors: an institutional experience and systematic review of the literature.

OBJECTIVE: Malignant melanotic nerve sheath tumors are rare tumors characterized by neoplastic melanin-producing Schwann cells. In this study, the authors report their institution's experience in treating spinal and peripheral malignant melanotic nerve sheath tumors and compare their results with the literature. METHODS: Data were collected from 8 patients who underwent surgical treatment for malignant melanotic nerve sheath tumors between 1996 and 2023 at Mayo Clinic and 63 patients from the literature. Time-to-event analyses were performed for the combined group of 71 cases to evaluate the risk of recurrence, metastasis, and death based on tumor location and type of treatment received. Unpaired 2-sample t-tests and Fisher's exact tests were used to determine statistical significance between groups. RESULTS: Between 1996 and 2023, 8 patients with malignant melanotic nerve sheath tumors underwent surgery at the authors' institution, while 63 patients were identified in the literature. The authors' patients and those in the literature had the same mean age at diagnosis (43 years). At the authors' institution, 5 patients (63%) experienced metastasis, 6 patients (75%) experienced long-term recurrence, and 5 patients (62.5%) died. In the literature, most patients (60.3%) were males, with a peak incidence between the 4th and 5th decades of life. Nineteen patients (31.1%) were diagnosed with Carney complex. Nerve root tumors accounted for most presentations (n = 39, 61.9%). Moreover, 24 patients (38.1%) had intradural lesions, with 54.2% (n = 13) being intramedullary and 45.8% (n = 11) extramedullary. Most patients underwent gross-total resection (GTR) (n = 41, 66.1%), followed by subtotal resection (STR) (n = 12, 19.4%), STR with radiation therapy (9.7%), and GTR with radiation therapy (4.8%). Sixteen patients (27.6%) experienced metastasis, 23 (39.7%) experienced recurrence, and 13 (22%) died. Kaplan-Meier analyses showed no significant differences among treatment approaches in terms of recurrence-free, metastasis-free, and overall survival (p > 0.05). Similar results were obtained when looking at the differences with respect to intradural versus nerve root location of the tumor (p > 0.05). CONCLUSIONS: Malignant melanotic nerve sheath tumors are rare tumors with a high potential for malignancy. They carry a dismal prognosis, with a pooled local recurrence rate of 42%, distant metastasis rate of 27%, and mortality rate of 26%. The findings from this study suggest a trend favoring the use of GTR alone or STR with radiation therapy over STR alone. Mortality was similar regardless, which highlights the need for the development of effective treatment options to improve survival in patients with melanotic schwannomas.

Limitations in Evaluating Machine Learning Models for Imbalanced Binary Outcome Classification in Spine Surgery: A Systematic Review.

Clinical prediction models for spine surgery applications are on the rise, with an increasing reliance on machine learning (ML) and deep learning (DL). Many of the predicted outcomes are uncommon; therefore, to ensure the models' effectiveness in clinical practice it is crucial to properly evaluate them. This systematic review aims to identify and evaluate current research-based ML and DL models applied for spine surgery, specifically those predicting binary outcomes with a focus on their evaluation metrics. Overall, 60 papers were included, and the findings were reported according to the PRISMA guidelines. A total of 13 papers focused on lengths of stay (LOS), 12 on readmissions, 12 on non-home discharge, 6 on mortality, and 5 on reoperations. The target outcomes exhibited data imbalances ranging from 0.44% to 42.4%. A total of 59 papers reported the model's area under the receiver operating characteristic (AUROC), 28 mentioned accuracies, 33 provided sensitivity, 29 discussed specificity, 28 addressed positive predictive value (PPV), 24 included the negative predictive value (NPV), 25 indicated the Brier score with 10 providing a null model Brier, and 8 detailed the F1 score. Additionally, data visualization varied among the included papers. This review discusses the use of appropriate evaluation schemes in ML and identifies several common errors and potential bias sources in the literature. Embracing these recommendations as the field advances may facilitate the integration of reliable and effective ML models in clinical settings.

Immunohistochemical markers predicting recurrence following resection and radiotherapy in chordoma patients: insights from a multicenter study [RETRACTED].

OBJECTIVE: Chordomas are rare tumors that often recur regardless of surgery with negative margins and postoperative radiotherapy. The predictive accuracy of widely used immunohistochemical (IHC) markers in addressing the recurrence of skull base chordomas (SBCs) is yet to be determined. This study aimed to investigate IHC markers in the prediction of recurrence after SBC resection with adjuvant radiation therapy. METHODS: The authors reviewed the records of patients who had treatment for SBC between January 2017 and June 2021 across the Mayo Clinic in Minnesota, Florida, and Arizona. Exclusion criteria included patients who had no histopathology or recurrence as an outcome. Histopathological markers included cytokeratin A1/A3 only, epithelial membrane antigen (EMA), S100 protein, pan-cytokeratin, IN1, GATA3, CAM5.2, OSCAR, and chondroid. Information from patient records was abstracted, including treatment, clinical and radiological follow-up duration, demographics, and histopathological factors. Decision tree and random forest classifiers were trained and tested to predict the recurrence based on unseen data using an 80/20 split. RESULTS: A total of 38 patients with a diagnosis of SBC who underwent resection (gross-total resection: 42.1%; and subtotal resection: 57.9%) and radiation therapy were extracted from the medical records. The mean patient age was 48.2 (SD 19.6) years; most patients were male (n = 23; 60.5%) and White (n = 36; 94.7%). Pan-cytokeratin was associated with an increased risk of postoperative recurrence (OR 14.67, 95% CI 2.44-88.13; p = 0.00517) after resection and adjuvant radiotherapy. The decision tree analysis found pan-cytokeratin-positive tumors to have a 78% chance of being classified as a recurrence, with an accuracy of 75%. The distribution of minimal depth in the prediction of postoperative recurrence indicates that the most important variables were pan-cytokeratin, followed by cytokeratin A1/A3 and EMA. CONCLUSIONS: The authors' machine learning algorithm identified pan-cytokeratin as the largest contributor to recurrence among other IHC markers after SBC resection. Machine learning may facilitate the prediction of outcomes in rare tumors, such as chordomas.

Transverse Sinus Stenting for the Treatment of Idiopathic Intracranial Hypertension With a Pressure Gradient of 70 mm Hg: A Technical Note and Systematic Review.

BACKGROUND AND IMPORTANCE: Venous sinus stenosis is believed to play a role in the pathogenesis of idiopathic intracranial hypertension (IIH). Venous stenting has emerged as a promising treatment option for patients with IIH because of venous sinus stenosis refractory to medical management or unsuitable for shunt placement. In this technical note, we present a case of IIH with the highest recorded pressure gradient to date. CLINICAL PRESENTATION: This technical note presents the successful use of intracranial venous stenting in a patient with IIH because of severe venous sinus stenosis, leading to significant improvement in vision and reduction in intracranial pressure. A meticulous review of the literature revealed that our patient exhibited the highest recorded pressure gradient (70 mm Hg). This remarkable finding underscores the potential effectiveness of venous stenting as a viable treatment approach. The procedure involved the placement of a Zilver stent (Cook Medical) and balloon angioplasty after stenting of the right transverse sinus stenosis, resulting in a substantial decrease in pressure gradient. Following the procedure, another venous manometry showed no more gradient with a uniform pressure in the whole venous system at 18 mm Hg. CONCLUSION: To our knowledge, this case presents the highest pressure gradient reported in the literature and contributes to the growing evidence supporting venous stenting in patients with IIH and venous sinus stenosis.

Using machine learning to predict 30-day readmission and reoperation following resection of supratentorial high-grade gliomas: an ACS NSQIP study involving 9418 patients.

OBJECTIVE: High-grade gliomas (HGGs) are among the rarest yet most aggressive tumor types in neurosurgical practice. In the current literature, few studies have assessed the drivers of early outcomes following resection of these tumors and investigated their association with quality of care. The authors aimed to identify the clinical predictors for 30-day readmission and reoperation following HGG surgery using the American College of Surgeons (ACS) National Surgical Quality Improvement Project (NSQIP) database and sought to create web-based applications predicting each outcome. METHODS: Using the ACS NSQIP database, the authors conducted a retrospective, multicenter cohort analysis of patients who underwent resection of supratentorial HGGs between January 1, 2016, and December 31, 2020. Demographics and comorbidities were extracted. The primary outcomes were 30-day unplanned readmission and reoperation. A stratified 80:20 split of the available data was carried out. Supervised machine learning algorithms were trained to predict 30-day outcomes. RESULTS: A total of 9418 patients were included in our cohort. The observed rate of unplanned readmission within 30 days of surgery was 13.0% (n = 1221). In terms of predictors, weight, chronic steroid use, preoperative blood urea nitrogen level, and white blood cell count were associated with a higher risk of readmission. The observed rate of unplanned reoperation within 30 days of surgery was 5.2% (n = 489). In terms of predictors, increased weight, longer operative time, and more days between hospital admission and operation were associated with an increased risk of early reoperation. The random forest algorithm showed the highest predictive performance for early readmission (area under the curve [AUC] = 0.967), while the XGBoost algorithm showed the highest predictive performance for early reoperation (AUC = 0.985). Web-based tools for both outcomes were deployed (https://glioma-readmission.herokuapp.com/ and https://glioma-reoperation.herokuapp.com/). CONCLUSIONS: In this study, the authors provide the first nationwide analysis for short-term outcomes in patients undergoing resection of supratentorial HGGs. Multiple patient, hospital, and admission factors were associated with readmission and reoperation, confirmed by machine learning predicting patients' prognosis, leading to better planning preoperatively and subsequently improved personalized patient care.

Effect of race, sex, and socioeconomic factors on overall survival following the resection of intramedullary spinal cord tumors.

INTRODUCTION: Intramedullary spinal cord tumors (IMSCTs) account for 2-4% of all primary CNS tumors. Given their low prevalence and the intricacy of their diagnosis and management, it is critical to address the surrounding racial and socioeconomic factors that impact the care of patients with IMSCTs. This study aimed to investigate the association between race and socioeconomic factors with overall 5 year mortality following the resection of IMSCTs. METHODS: The study used the National Cancer Database to retrospectively analyze patients who underwent resection of IMSCTs from 2004 to 2017. Patients were divided into four cohorts by race/ethnicity, facility type, insurance, median income quartiles, and living area. The primary outcome of interest was 5 year survival, and secondary outcomes included postoperative length of stay and 30 day readmission. Descriptive and multivariable analyses were used to identify independent factors associated with mortality, with statistical significance assessed at a 2-sided p < 0.05. RESULTS: We evaluated the patient characteristics and outcomes for 8,028 patients who underwent surgical treatment for IMSCTs between 2004 and 2017. Most patients were white males (52.4%) with a mean age of 44 years where 7.17% of patients were Black, 7.6% were Hispanic, and 3% were Asian. Most were treated in an academic/research program (72.4%) and had private insurance (69.2%). Black patients had a higher odd of 5 year mortality (OR 1.4; 95% CI 1.1 to 1.77; p = 0.04) compared to white patients, while no significant differences in mortality were observed among other races. Factors associated with lower odds of mortality included being female (OR 0.89; 95% CI 0.78 to 1.02; p < 0.01), receiving treatment in an academic/research program (OR 0.51; 95% CI 0.33 to 0.79; p = 0.04), having private insurance (OR 0.65; 95% CI 0.45 to 0.93; p = 0.02), and having higher income quartiles (OR 0.77; 95% CI 0.62 to 0.96; p = 0.02). CONCLUSION: Our study sheds light on the healthcare disparities that exist in the surgical management of IMSCTs. Our findings indicate that race, sex, socioeconomic status, and treatment facility are independent predictors of 5 year mortality, with Black patients, males, those with lower socioeconomic status, and those treated at non-academic centers experiencing significantly higher mortality rates. These alarming disparities underscore the urgent need for policymakers and researchers to address the underlying factors contributing to these discrepancies and provide equal access to high-quality surgical care for patients with IMSCTs.

Deep Learning Approaches for Glioblastoma Prognosis in Resource-Limited Settings: A Study Using Basic Patient Demographic, Clinical, and Surgical Inputs.

BACKGROUND: Glioblastoma (GBM) is the most common brain tumor in the United States, with an annual incidence rate of 3.21 per 100,000. It is the most aggressive type of diffuse glioma and has a median survival of months after treatment. This study aims to assess the accuracy of different novel deep learning models trained on a set of simple clinical, demographic, and surgical variables to assist in clinical practice, even in areas with constrained health care infrastructure. METHODS: Our study included 37,095 patients with GBM from the SEER (Surveillance Epidemiology and End Results) database. All predictors were based on demographic, clinicopathologic, and treatment information of the cases. Our outcomes of interest were months of survival and vital status. Concordance index (C-index) and integrated Brier scores (IBS) were used to evaluate the performance of the models. RESULTS: The patient characteristics and the statistical analyses were consistent with the epidemiologic literature. The models C-index and IBS ranged from 0.6743 to 0.6918 and from 0.0934 to 0.1034, respectively. Probabilistic matrix factorization (0.6918), multitask logistic regression (0.6916), and logistic hazard (0.6916) had the highest C-index scores. The models with the lowest IBS were the probabilistic matrix factorization (0.0934), multitask logistic regression (0.0935), and logistic hazard (0.0936). These models had an accuracy (1-IBS) of 90.66%; 90.65%, and 90.64%, respectively. The deep learning algorithms were deployed on an interactive Web-based tool for practical use available via https://glioblastoma-survanalysis.herokuapp.com/. CONCLUSIONS: Novel deep learning algorithms can better predict GBM prognosis than do baseline methods and can lead to more personalized patient care regardless of extensive electronic health record availability.