Perez-Vega, Carlos

BACKGROUND AND OBJECTIVES: Rising US healthcare costs and the COVID-19 pandemic put increased pressure on hospitals to reduce patient length of stay (LOS) while maintaining high-quality care. We aimed to determine if implementing a pathway for same-day discharge after elective neuroendovascular procedures to a monitored hotel setting is safe, feasible, and cost-effective. METHODS: We evaluated patient outcomes after elective neuroendovascular procedures and same-day discharge to an on-campus Care Hotel. The study enrolled patients aged ≥18 years from October 1, 2020, to February 28, 2023. Exclusion criteria comprised major comorbidities, additional care necessitating hospitalization, absence of a caregiver, insurer-mandated hospitalization, or patient refusal of the Care Hotel model. Primary outcomes were readmission rate or prolonged LOS, new ischemic or hemorrhagic complications rate, and death rate from vascular causes within 6 months. Secondary outcomes included adverse events and deaths related to causes other than vascular complications within 6 months and changes in modified Rankin Scale score by 1 or more points at last follow-up. Healthcare cost savings associated with same-day discharge were analyzed using a control group. RESULTS: The study included 42 patients discharged to the Care Hotel and 84 controls. The average age was 61 years in the Care Hotel group and 64 years in the control group, and aneurysm treatment was the most frequent neuroendovascular procedure (83.3% and 79.8%, respectively). The readmission and extended LOS rates were 4.8% for the Care Hotel group. The rate of new ischemic or hemorrhagic complications was 4.8%. Cost analysis estimated savings of $7730.12 per procedure. CONCLUSION: This study suggests that the Care Hotel model is a safe, feasible, and cost-effective option for carefully selected patients undergoing elective neuroendovascular interventions. Adherence to discharge readiness criteria and meticulous patient selection are critical to minimizing complications and readmissions.

Abstract Confounding results of engineered mesenchymal stem cells (MSCs) used as cellular vehicles has plagued technologies whereby success or failure of novel approaches may be dismissed or inaccurately ascribed solely to the biotechnology platform rather than suitability of the human donor. Polymeric materials were screened for non‐viral engineering of MSCs from multiple human donors to deliver bone morphogenic protein‐4 (BMP4), a protein previously investigated in clinical trials for glioblastoma (GBM) to combat a subpopulation of highly invasive and tumorigenic clones. A “smart technology” that target the migratory and stem‐like nature of GBM will require: (1) a cellular vehicle (MSC) which can scavenge and target residual cells left behind after surgical debulking and deliver; (2) anti‐glioma cargo (BMP4). Multiple MSC donors are safely engineered, though varied in susceptibility to accept BMP4 due to intrinsic characteristics revealed by their molecular signatures. Efficiency is compared via secretion, downstream signaling, differentiation, and anti‐proliferative properties across all donors. In a clinically relevant resection and recurrence model of patient‐derived human GBM, we demonstrate that nanoengineered MSCs are not “donor agnostic” and efficacy is influenced by the inherent suitability of the MSC to the cargo. Therefore, donor profiles hold greater influence in determining downstream outcomes than the technical capabilities of the engineering technology.

OBJECTIVE Chordomas are rare tumors of the skull base and spine believed to arise from the vestiges of the embryonic notochord. These tumors are locally aggressive and frequently recur following resection and adjuvant radiotherapy. Proton therapy has been introduced as a tissue-sparing option because of the higher level of precision that proton-beam techniques offer compared with traditional photon radiotherapy. This study aimed to compare recurrence in patients with chordomas receiving proton versus photon radiotherapy following resection by applying tree-based machine learning models. METHODS The clinical records of all patients treated with resection followed by adjuvant proton or photon radiotherapy for chordoma at Mayo Clinic were reviewed. Patient demographics, type of surgery and radiotherapy, tumor recurrence, and other variables were extracted. Decision tree classifiers were trained and tested to predict long-term recurrence based on unseen data using an 80/20 split. RESULTS Fifty-three patients with a mean ± SD age of 55.2 ± 13.4 years receiving surgery and adjuvant proton or photon therapy to treat chordoma were identified; most patients were male. Gross-total resection was achieved in 54.7% of cases. Proton therapy was the most common adjuvant radiotherapy (84.9%), followed by conventional or external-beam radiation therapy (9.4%) and stereotactic radiosurgery (5.7%). Patients receiving proton therapy exhibited a 40% likelihood of having recurrence, significantly lower than the 88% likelihood observed in those treated with nonproton therapy. This was confirmed on logistic regression analysis adjusted for extent of tumor resection and tumor location, which revealed that proton adjuvant radiotherapy was associated with a decreased risk of recurrence (OR 0.1, 95% CI 0.01–0.71; p = 0.047) compared with photon therapy. The decision tree algorithm predicted recurrence with an accuracy of 90% (95% CI 55.5%–99.8%), with the lowest risk of recurrence observed in patients receiving gross-total resection with adjuvant proton therapy (23%). CONCLUSIONS Following resection, adjuvant proton therapy was associated with a lower risk of chordoma recurrence compared with photon therapy. The described machine learning models were able to predict tumor progression based on the extent of tumor resection and adjuvant radiotherapy modality used.

OBJECTIVE Chordomas are slow-growing tumors derived from notochord remnants. Despite margin-negative excision and postoperative radiation therapy, spinal chordomas (SCs) often progress. The potential of immunohistochemical (IHC) markers, such as epithelial membrane antigen (EMA), combined with machine learning algorithms to predict long-term (≥ 12 months) postoperative tumor progression, has been understudied. The authors aimed to identify IHC markers using trained tree-based algorithms to predict long-term (≥ 12 months) postoperative tumor progression. METHODS The authors reviewed the records of patients who underwent resection of SCs between January 2017 and June 2021 across the Mayo Clinic enterprise. Demographics, type of treatment, histopathology, and other relevant clinical factors were abstracted from each patient’s record. Low tumor progression was defined as more than a 94.3-mm3 decrease in the tumor size at the latest radiographic follow-up. Decision trees and random forest classifiers were trained and tested to predict the long-term volumetric progression after an 80/20 data split. RESULTS Sixty-two patients diagnosed with and surgically treated for SC were identified, of whom 31 were found to have a more advanced tumor progression based on the tumor volume change cutoff of 94.3 mm3. The mean age was 54.3 ± 13.8 years, and most patients were male (62.9%) and White (98.4%). The most common treatment modality was subtotal resection with radiation therapy (35.5%), with proton beam therapy being the most common (71%). Most SCs were sacrococcygeal (41.9%), followed by cervical (32.3%). EMA-positive SCs had a postoperative progression risk of 67%. Pancytokeratin-positive SCs had a progression rate of 67%; however, patients with S100 protein–positive SCs had a 54% risk of progression. The accuracy of this model in predicting the progression of unseen test data was 66%. Pancytokeratin (mean minimal depth = 1.57), EMA (mean minimal depth = 1.58), cytokeratin A1/A3 (mean minimal depth = 1.59), and S100 protein (mean minimal depth = 1.6) predicted the long-term volumetric progression. Multiway variable importance plots show the relative importance of the top 10 variables based on three measures of varying significance and their predictive role. CONCLUSIONS These IHC variables with tree-based machine learning tools successfully demonstrate a high capacity to identify a patient’s tumor progression pattern with an accuracy of 66%. Pancytokeratin, EMA, cytokeratin A1/A3, and S100 protein were the IHC drivers of a low tumor progression. This shows the power of machine learning algorithms in analyzing and predicting outcomes of rare conditions in a small sample size.

In this surgical video, the authors present a successful minimally invasive (MIS) lateral retroperitoneal transpsoas approach for resection of an L4 nerve root schwannoma. They describe the surgical approach in detail, with special emphasis on patient positioning for an orthogonal view, as well as technical nuances throughout the procedure. Using a sequential tubular retractor, they performed a microscopic dissection of the lesion. The tumor was debulked and the tumor capsule was disconnected from the surrounding tissue. During dissection, direct stimulation identified a functional nerve root that was carefully dissected from the tumor capsule. The tumor was then removed en bloc. The video can be found here: https://stream.cadmore.media/r10.3171/2022.3.FOCVID2220

AbstractDrug‐resistant epilepsy (DRE) is characterized by recurrent seizures despite appropriate treatment with antiseizure medication (ASM). Due to their regenerative and immunomodulatory potential, therapies with biologics such as mesenchymal stem cells (MSCs) offer a potential therapeutic benefit for structural causes of epilepsy, such as hippocampal sclerosis. In this article, we report a systematic review of the literature evaluating the preclinical and clinical studies of MSCs for DRE. Medline, Ovid EMBASE, Scopus, and the Cochrane Databases were searched electronically from their dates of inception to November 2021 using the following keywords: ((“mesenchymal”) AND (“stem cell”)) AND ((“epilepsy”) OR (“convulsion”) OR (“seizures”)). This review followed Preferred Reporting Items for Systemic Reviews and Meta‐Analyses (PRISMA) guidelines. The initial query identified 488 studies representing 323 unique manuscripts. After application of selection criteria, 15 studies were included in this systematic review; 11 were preclinical studies and 4 were clinical studies. All preclinical studies were performed in rodents and all clinical studies were phase 1 trials. Thus far, therapy with MSCs appears to be safe for use in humans, as no severe adverse events related directly to the therapy were reported. Furthermore, MSC therapy appears to provide a statistically significant clinical benefit by reducing the seizure burden of patients, reducing the electrophysiological biomarkers of epilepsy, and improving their comorbidities, such as depression and anxiety. In addition, animal studies reveal that the therapy exerts its effect by reducing aberrant mossy fiber sprouting (reduce excitatory pathways) and increasing γ‐aminobutyric acid (GABA)ergic interneurons (increase inhibitory pathways). Both preclinical and clinical studies have shown MSC therapy to be safe and preliminary effective, thus warranting further studies to investigate its therapeutic potential.

OBJECTIVE Multiple meningiomas (MMs) occur in as many as 18% of patients with meningioma, and data on progression-free survival (PFS) are scarce. The objective of this study was to explore the influence of the number of lesions and clinical characteristics on PFS in patients with WHO grade I meningiomas. METHODS The authors retrospectively reviewed the records of all adults diagnosed with a meningioma at their three main sites from January 2009 to May 2020. Progression was considered the time from diagnosis until radiographic growth of the originally resected meningioma. A secondary analysis was performed to evaluate the time of diagnosis until the time to second intervention (TTSI). Univariable and multivariable analyses were conducted to assess whether the number of lesions or any associated variables (age, sex, race, radiation treatment, tumor location, and extent of resection) had a significant impact on PFS and TTSI. RESULTS Eight hundred thirty-eight patients were included. Use of a log-rank test to evaluate PFS and TTSI between a single and multiple lesions showed a significantly shorter progression for MM (p < 0.001 and p < 0.001, respectively). Multivariable Cox regression analysis showed significantly inferior PFS on MM compared to a single lesion (hazard ratio [HR] 2.262, 95% confidence interval [CI] 1.392–3.677, p = 0.001) and a significantly inferior TTSI for patients with MM when compared to patients with a single meningioma (HR 2.377, 95% CI 1.617–3.494, p = 0.001). By testing the number of meningiomas as a continuous variable, PFS was significantly inferior for each additional meningioma (HR 1.350, 95% CI 1.074–1.698, p = 0.010) and TTSI was significantly inferior as well (HR 1.428, 95% CI 1.189–1.716, p < 0.001). African American patients had an inferior PFS when compared to non-Hispanic White patients (HR 3.472, 95% CI 1.083–11.129, p = 0.036). CONCLUSIONS The PFS of meningiomas appears to be influenced by the number of lesions present. Patients with MM also appear to be more prone to undergoing a second intervention for progressive disease. Hence, a closer follow-up may be warranted in patients who present with multiple lesions. These results show a decreased PFS for each additional lesion present, as well as a shorter PFS for MM compared to a single lesion. When assessing associated risk factors, African American patients showed an inferior PFS, whereas older age and adjuvant therapy with radiation showed an improved PFS.