Age-stratified comorbid and pharmacologic analysis of patients with glioblastoma.

Background: Increased age is a strong and unfavorable prognostic factor for patients with glioblastoma (GBM). However, the relationships between stratified patient age, comorbidities, and medications have yet to be explored in GBM patient survival analyses. Objective: To evaluate co-morbid conditions, tumor-related symptoms, medication prescriptions, and subject age for patients with GBM and to establish potential targets for prospective studies. Methods: Electronic health records for 565 patients with IDHwt GBM were evaluated at a single center between January 1, 2000 and August 9, 2021 were retrospectively assessed. Data were stratified by MGMT promoter methylation status when available and were used to construct multivariable time-dependent cox models and intra-cohort hazards. Results: Younger (<65 years of age) but not older (≥65 years) GBM patients demonstrated a worse prognosis with movement related disabilities (P < 0.0001), gait/balance difficulty (P = 0.04) and weakness (P = 0.007), as well as psychiatric conditions, mental health disorders (P = 0.002) and anxiety (P = 0.001). In contrast, older but not younger GBM patients demonstrated a worse prognosis with epilepsy (P = 0.039). Both groups had worse survival with confusion/altered mental status (P = 0.023 vs < 0.000) and an improved survival with a Temozolomide prescription. Older but not younger GBM patients experienced an improved hazard with a prescription of ace-inhibitor medications (P = 0.048). Conclusion: Age-dependent novel associations between clinical symptoms and medications prescribed for co-morbid conditions were demonstrated in patients with GBM. The results of the current work support future mechanistic studies that investigate the negative relationship(s) between increased age, comorbidities, and drug therapies for differential clinical decision-making across the lifespan of patients with GBM.

Implementation of single-port robotic urologic surgery: experience at a large academic center.

The Single-Port (SP) robotic system is increasingly being implemented in the United States, allowing for several minimally invasive urologic procedures to be performed. The present study aims to describe our single-center experience since the adoption of the SP platform. We retrospectively collected and analyzed consecutive SP cases performed at a major teaching hospital in the Midwest (Rush University Medical Center) from December 2020 to December 2023. Demographic variables were collected. Surgical and pathological outcomes were analyzed in the overall cohort and for each type of procedure. The study timeframe was divided into two periods to assess the evolution of SP technical features over time. In total, 160 procedures were performed, with robot-assisted radical prostatectomy (RARP) being the most common (49.4%). Overall, 54.4% of the procedures were extraperitoneal, with a significantly higher adoption of this approach in the second half of the study period (30% vs 74.3%, p < 0.001). A "plus one" assistant port was adopted in 38.1% of cases, with a shift towards a "pure" single-port surgery in the most recent procedures (21.1% vs 76.7%, p < 0.001). The median LOS was 33.5 h (30-48), with a rate of any grade and CD ≥ 3 postoperative complications of 9.4% and 2.5%, respectively, and a 30-day readmission rate of 1.9%. SP robotic surgery can be safely and effectively implemented for various urologic procedures. With increasing experience, the SP platform allows shifting away from transperitoneal procedures, potentially minimizing postoperative pain, and shortening hospital stay and postoperative recovery.

Single-port vs multi-port robot-assisted partial nephrectomy: A single center propensity score-matched analysis.

INTRODUCTION AND OBJECTIVES: The aim of the study is to compare key outcomes of Single-Port (SP) and Multi-Port (MP) robot-assisted partial nephrectomy (RAPN). METHODS: A retrospective analysis was conducted on our prospectively collected database of patients who underwent SP-RAPN or MP-RAPN at our institution from January 2021 to August 2023. To adjust for potential baseline pre-operative confounders, a 1:1 propensity-score matching analysis (PSMa) was performed. The primary endpoint was to compare perioperative outcomes between the two groups. The secondary endpoint was to compare the achievement of the "Trifecta" outcome (defined as negative surgical margins, absence of high-grade complications and change in eGFR values (ΔeGFR) < 10% at 6 months follow-up) in the matched cohort. RESULTS: After PSMa, 30 SP cases were matched 1:1 to 30 MP cases. In the matched cohort, there were no significant differences between SP and MP approaches in operative time, estimated blood loss, ischemia time, transfusions rate, intraoperative complications, postoperative complications, and positive surgical margin rates. Patients who underwent SP-RAPN had a shorter median length of stay [25 (IQR:24.0-34.5) vs 34 (IQR:30.2-48.0) hours, p < 0.003]. The Trifecta outcome was achieved in 16 (57%) of SP patients and 17 (63%) of MP patients (p = 0.8). CONCLUSIONS: SP-RAPN can be safely implemented in a Center with an established MP-RAPN program. Despite being early in the SP-RAPN experience, key surgical outcomes are not compromised. While offering comparable perioperative and short-term functional outcomes, SP-RAPN can translate into faster recovery and shorter LOS, paving the way for outpatient robotic surgery.

Patterns of Antiseizure Medication Use Following Meningioma Resection: A Single-Institution Experience.

OBJECTIVE: To investigate antiseizure medication (ASM) practice behavior for patients who present with seizures before meningioma resection and to review postoperative ASM management. METHODS: A retrospective study was performed of 112 consecutive patients with meningiomas who underwent resection at a single institution between October 2016 and January 2020. Data were collected through detailed chart review. RESULTS: Of 112 patients, 35 (31%) had a preoperative seizure, and 43 (38%) were prescribed a preoperative ASM. At discharge, 96 patients (86%) were prescribed an ASM, most often 1000 mg daily of levetiracetam (64%, 61/96) and less often higher doses of levetiracetam or other ASMs. By the 6-month postoperative visit, 55 patients (49%) were taking at least 1 ASM, most commonly levetiracetam monotherapy (65%) at 500 mg twice daily (47%). This number further decreased to 45 (40%) patients by 1-year follow-up and 36 (32%) patients by last-known follow-up. By last follow-up (median 27.3 months; range 5.4-57.4 months), 24 patients (21%) had experienced a postoperative seizure, and 36 patients (32%) were never able to discontinue ASMs. Of patients remaining on levetiracetam monotherapy, only 36% remained on levetiracetam 500 mg twice daily. CONCLUSIONS: Approximately two thirds (68%) of patients who underwent surgical resection of meningioma were eventually able to completely discontinue their postoperative ASM regimen. However, nearly one third (32%) of patients required long-term ASM management. Levetiracetam monotherapy was the most common ASM prescribed during the postoperative period, and the proportion of patients requiring either higher doses of levetiracetam or alternative ASMs increased over time.

Discovery of novel cMET-targeting antibody Fab drug conjugates as potential treatment for solid tumors with highly expressed cMET.

BACKGROUND: Solid tumors are becoming prevalent affecting both old and young populations. Numerous solid tumors are associated with high cMET expression. The complexity of solid tumors combined with the highly interconnected nature of the cMET/HGF pathway with other cellular pathways make the pursuit of finding an effective treatment extremely challenging. The current standard of care for these malignancies is mostly small molecule-based chemotherapy. Antibody-based therapeutics as well as antibody drug conjugates are promising emerging classes against cMET-overexpressing solid tumors. RESEARCH DESIGN AND METHODS: In this study, we described the design, synthesis, in vitro and in vivo characterization of cMET-targeting Fab drug conjugates (FDCs) as an alternative therapeutic strategy. The format is comprised of a Fab conjugated to a potent cytotoxic drug via a cleavable linker employing lysine-based and cysteine-based conjugation chemistries. RESULTS: We found that the FDCs have potent anti-tumor efficacies in cancer cells with elevated overexpression of cMET. Moreover, they demonstrated a remarkable anti-tumor effect in a human gastric xenograft mouse model. CONCLUSIONS: The FDC format has the potential to overcome some of the challenges presented by the other classes of therapeutics. This study highlights the promise of antibody fragment-based drug conjugate formats for the treatment of solid tumors.

Long-term antiseizure medication use in patients after meningioma resection: identifying predictors for successful weaning and failures.

OBJECTIVE: To define risk factors for meningioma-related seizures and predictors of successful weaning of antiseizure medications following meningioma resection. METHODS: This is a retrospective study of 95 patients who underwent meningioma resection at a single institution. Primary outcome analyzed was ability to achieve seizure freedom without the use of anti-seizure medication at 6-months, 1-year, and last known follow up. Secondary outcome was postoperative seizure freedom. RESULTS: Preoperative seizures (OR: 11.63, 95% CI [3.64, 37.17], p < 0.0001), non-skull base tumor location (OR: 3.01, 95% CI [1.29, 7.02], p = 0.0128), and modified STAMPE score of 3-5 (OR: 5.42, 95% CI [2.18, 13.52], p = 0.0003) were associated with greater likelihood of remaining on antiseizure medication at 6-month follow up. Preoperative seizures (OR: 4.93, 95% CI: [2.00, 12.16 ], p = 0.0008), intratumoral calcifications (OR: 4.19, 95% CI: [1.61, 14.46], p = 0.0055), modified STAMPE score of 3-5 (OR: 5.42, CI [2.18, 13.52], p = 0.0003), and Ki67 greater than 7% (OR: 5.68, CI [1.61, 20.10], p = 0.0060) were significant risk factors for inability to discontinue ASMs by last follow up. Preoperative seizures (OR: 4.33, 95% CI [1.59, 11.85], p = 0.0050) and modified STAMPE score of 3-5 (OR: 6.09, 95% CI [2.16, 17.20], p = 0.0007) were significant risk factors for postoperative seizures. CONCLUSIONS: Preoperative seizures, modified STAMPE2 score of 3-5, non-skull base tumor location, intratumoral calcifications, and Ki67 > 7% were significant risk factors for inability to achieve seizure freedom without ASMs. In addition, the modified STAMPE2 score successfully predicted increased seizure risk following meningioma resection for patients with a score of 3 or higher.

Cross-Sectional Analysis of Neurosurgical Residency Websites During the Virtual Interview Cycle.

BACKGROUND: The loss of in-person interviews during the COVID-19 pandemic warrants an investigation into what information is provided to applicants through neurosurgery residency program websites (NRPWs). This study examines NRPWs across the United States and Canada to determine what details are provided to applicants through their respective websites. METHODS: Accreditation Council for Graduate Medical Education accredited neurologic surgery residency programs were identified through the American Association of Neurological Surgeons (AANS) website. NRPWs were searched for 48 criteria, including program overview, application requirements, and curriculum information. Small programs were defined as 1-2 residents per class, while large programs were classified as those with 3-4 residents per year. Content differences were analyzed between the top 20 and remaining programs per the Doximity Residency Navigator Rankings. RESULTS: The most prevalent information among 122 NRPWs was the neurosurgery residency overview (95%), names of faculty members (95%), and names of current residents (94%). Top-20 NRPWs were more likely to include post PGY-7 fellowships (90% vs. 61% P = 0.0108), operating room virtual reality experience (35% vs. 12% P = 0.0160), and faculty research (90% vs. 62% P = 0.0182) than the remainder of the programs. CONCLUSIONS: This study investigates NRPW content after the COVID-19 pandemic. We report broad variability in content provided by various neurosurgical training programs. Higher-ranked neurosurgery programs are more likely to include fellowship information, operating room virtual reality experience, and faculty research than lower-ranked programs.

Rapid detection of nicotine and benzoic acid in e-liquids with surface-enhanced Raman scattering and artificial intelligence-assisted spectrum interpretation.

Electronic cigarettes have rapidly gained acceptance recently. Nicotine-containing electronic cigarette liquids (e-liquids) are prohibited in some countries, but are permitted and simply available online in others. A rapid detection method is therefore required for on-site inspection or screening of a large amount of samples. Our previous study demonstrated a surface-enhanced Raman scattering (SERS)-based approach to identify nicotine-containing e-liquids; without any pre-treatment, e-liquid can be directly tested on our solid-phase SERS substrates, made of silver nanoparticle arrays embedded in anodic aluminium oxide nanochannels (Ag/AAO). However, this approach required manual determination of spectral signatures and negative samples should be validated in the second round detection. Here, after examining 406 commercial e-liquids, we refined this approach by developing artificial intelligence (AI)-assisted spectrum interpretations. We also found that nicotine and benzoic acid can be simultaneously detected in our platform. This increased test sensitivity because benzoic acid is usually used in nicotine salts. Around 64% of nicotine-positive samples in this study showed both signatures. Using either cutoffs of nicotine and benzoic acid peak intensities or a machine learning model based on the CatBoost algorithm, over 90% of tested samples can be correctly discriminated with only one round of SERS measurement. False negative and false positive rates were 2.5-4.4% and 4.4-8.9%, respectively, depending on the interpretation method and thresholds applied. The new approach takes only 1 microliter of sample and can be performed in 1-2 min, suitable for on-site inspection with portable Raman detectors. It could also be a complementary platform to reduce samples that need to be analyzed in the central labs and has the potential to identify other prohibited additives.

Multimodal Deep Learning-Based Prognostication in Glioma Patients: A Systematic Review.

Malignant brain tumors pose a substantial burden on morbidity and mortality. As clinical data collection improves, along with the capacity to analyze it, novel predictive clinical tools may improve prognosis prediction. Deep learning (DL) holds promise for integrating clinical data of various modalities. A systematic review of the DL-based prognostication of gliomas was performed using the Embase (Elsevier), PubMed MEDLINE (National library of Medicine), and Scopus (Elsevier) databases, in accordance with PRISMA guidelines. All included studies focused on the prognostication of gliomas, and predicted overall survival (13 studies, 81%), overall survival as well as genotype (2 studies, 12.5%), and response to immunotherapy (1 study, 6.2%). Multimodal analyses were varied, with 6 studies (37.5%) combining MRI with clinical data; 6 studies (37.5%) integrating MRI with histologic, clinical, and biomarker data; 3 studies (18.8%) combining MRI with genomic data; and 1 study (6.2%) combining histologic imaging with clinical data. Studies that compared multimodal models to unimodal-only models demonstrated improved predictive performance. The risk of bias was mixed, most commonly due to inconsistent methodological reporting. Overall, the use of multimodal data in DL assessments of gliomas leads to a more accurate overall survival prediction. However, due to data limitations and a lack of transparency in model and code reporting, the full extent of multimodal DL as a resource for brain tumor patients has not yet been realized.

Vagus nerve stimulator revision in pediatric epilepsy patients: a technical note and case series.

INTRODUCTION: Vagus nerve stimulation (VNS) is an adjunctive treatment in children with intractable epilepsy. When lead replacement becomes necessary, the old leads are often truncated and retained and new leads are implanted at a newly exposed segment of the nerve. Direct lead removal and replacement are infrequently described, with outcomes poorly characterized. We aimed to describe our experience with feasibility of VNS lead removal and replacement in pediatric patients. METHODS: Retrospective review examined 14 patients, at a single, tertiary-care, children's hospital, who underwent surgery to replace VNS leads, with complete removal of the existing lead from the vagus nerve and placement of a new lead on the same segment of the vagus nerve, via blunt and sharp dissection without use of electrocautery. Preoperative characteristics, stimulation parameters, and outcomes were collected. RESULTS: Mean age at initial VNS placement was 7.6 years (SD 3.5, range 4.5-13.4). Most common etiologies of epilepsy were genetic (5, 36%) and cryptogenic (4, 29%). Lead replacement was performed at a mean of 6.0 years (SD 3.8, range 2.1-11.7) following initial VNS placement. Reasons for revision included VNS lead breakage or malfunction. There were no perioperative complications, including surgical site infection, voice changes, dysphagia, or new deficits postoperatively. Stimulation parameters after replacement surgery at last follow-up were similar compared to preoperatively, with final stimulation parameters ranging from 0.25 mA higher to 1.5 mA lower to maintain baseline seizure control. The mean length of follow-up was 7.9 years (SD 3.5, range 3.1-13.7). CONCLUSION: Removal and replacement of VNS leads are feasible and can be safely performed in children. Further characterization of surgical technique, associated risk, impact on stimulation parameters, and long-term outcomes are needed to inform best practices in VNS revision.

Learning curves in robotic neurosurgery: a systematic review.

The transition to performing procedures robotically generally entails a period of adjustment known as a learning curve as the surgeon develops a familiarity with the technology. However, no study has comprehensively examined robotic learning curves across the field of neurosurgery. We conducted a systematic review to characterize the scope of literature on robotic learning curves in neurosurgery, assess operative parameters that may involve a learning curve, and delineate areas for future investigation. PubMed, Embase, and Scopus were searched. Following deduplication, articles were screened by title and abstract for relevance. Remaining articles were screened via full text for final inclusion. Bibliographic and learning curve data were extracted. Of 746 resultant articles, 32 articles describing 3074 patients were included, of which 23 (71.9%) examined spine, 4 (12.5%) pediatric, 4 (12.5%) functional, and 1 (3.1%) general neurosurgery. The parameters assessed for learning curves were heterogeneous. In total, 8 (57.1%) of 14 studies found reduced operative time with increased cases, while the remainder demonstrated no learning curve. Six (60.0%) of 10 studies reported reduced operative time per component with increased cases, while the remainder indicated no learning curve. Radiation time, radiation time per component, robot time, registration time, setup time, and radiation dose were assessed by ≤ 4 studies each, with 0-66.7% of studies demonstrated a learning curve. Four (44.4%) of 9 studies on accuracy showed improvement over time, while the others indicated no improvement over time. The number of cases required to reverse the learning curve ranged from 3 to 75. Learning curves are common in robotic neurosurgery. However, existing studies demonstrate high heterogeneity in assessed parameters and the number of cases that comprise the learning curve. Future studies should seek to develop strategies to reduce the number of cases required to reach the learning curve.

Natural Language Processing in Spine Surgery: A Systematic Review of Applications, Bias, and Reporting Transparency.

BACKGROUND: Natural language processing (NLP) is a discipline of machine learning concerned with the analysis of language and text. Although NLP has been applied to various forms of clinical text, the applications and utility of NLP in spine surgery remain poorly characterized. Here, we systematically reviewed studies that use NLP for spine surgery applications, and analyzed applications, bias, and reporting transparency of the studies. METHODS: We performed a literature search using the PubMed, Scopus, and Embase databases. Data extraction was performed after appropriate screening. The risk of bias and reporting quality were assessed using the PROBAST and TRIPOD tools. RESULTS: A total of 12 full-text articles were included. The most common diseases represented include spondylolisthesis (25%), scoliosis (17%), and lumbar disk herniation (17%). The most common procedures included spinal fusion (42%), imaging (e.g. magnetic resonance, X-ray) (25%), and scoliosis correction (17%). Reported outcomes were diverse and included incidental durotomy, venous thromboembolism, and the tone of social media posts regarding scoliosis surgery. Common sources of bias identified included the use of older methods that do not capture the nuance of a text, and not using a prespecified or standard outcome measure when evaluating NLP methods. CONCLUSIONS: Although the application of NLP to spine surgery is expanding, current studies face limitations and none are indicated as ready for clinical use. Thus, for future studies we recommend an emphasis on transparent reporting and collaboration with NLP experts to incorporate the latest developments to improve models and contribute to further innovation.

Health Literacy in Neurosurgery: A Scoping Review.

OBJECTIVE: Low health literacy is prevalent and associated with suboptimal health outcomes. In neurosurgery, social determinants of health are increasingly recognized as factors underpinning outcomes, as well as access to and use of care. We conducted a scoping review to delineate the scope of existing literature regarding health literacy in the field and facilitate future research. METHODS: A scoping review was conducted using the PubMed, Embase, and Scopus databases. Titles and abstracts were screened for relevance. Studies meeting prespecified inclusion criteria underwent full text review. Relevant data were extracted. RESULTS: Of 5056 resultant articles, 57 manuscripts were included. Thirty-seven studies (64.9%) investigated personal health literacy, while the remaining 20 (35.1%) investigated organizational health literacy. Domains of health literacy investigated were science (36, 63.2%), fundamental (20, 35.1%), and civic (1, 1.7%). No studies investigated numeracy. Recall among patients after discussions with neurosurgeons is low. Patient perspectives are often erroneous. Patient informational needs are often unmet. Written patient educational materials are written at a level too complex for the average patients. Videos are mostly of poor quality. Multimodal audiovisual interventions, eBooks, models, and virtual reality are shown to be effective methods for promoting recall. CONCLUSIONS: Studies examining health literacy in neurosurgery primarily focus on the topic indirectly, most often via written educational materials and recall after educational interventions. Increasing awareness of health literacy among neurosurgeons, assessing health literacy, and incorporating health literacy-informed counseling approaches are warranted to improve patient care.

Association of Assisted Reproductive Technology With Offspring Growth and Adiposity From Infancy to Early Adulthood.

Importance: People conceived using assisted reproductive technology (ART) make up an increasing proportion of the world's population. Objective: To investigate the association of ART conception with offspring growth and adiposity from infancy to early adulthood in a large multicohort study. Design, Setting, and Participants: This cohort study used a prespecified coordinated analysis across 26 European, Asia-Pacific, and North American population-based cohort studies that included people born between 1984 and 2018, with mean ages at assessment of growth and adiposity outcomes from 0.6 months to 27.4 years. Data were analyzed between November 2019 and February 2022. Exposures: Conception by ART (mostly in vitro fertilization, intracytoplasmic sperm injection, and embryo transfer) vs natural conception (NC; without any medically assisted reproduction). Main Outcomes and Measures: The main outcomes were length / height, weight, and body mass index (BMI; calculated as weight in kilograms divided by height in meters squared). Each cohort was analyzed separately with adjustment for maternal BMI, age, smoking, education, parity, and ethnicity and offspring sex and age. Results were combined in random effects meta-analysis for 13 age groups. Results: Up to 158 066 offspring (4329 conceived by ART) were included in each age-group meta-analysis, with between 47.6% to 60.6% females in each cohort. Compared with offspring who were NC, offspring conceived via ART were shorter, lighter, and thinner from infancy to early adolescence, with differences largest at the youngest ages and attenuating with older child age. For example, adjusted mean differences in offspring weight were -0.27 (95% CI, -0.39 to -0.16) SD units at age younger than 3 months, -0.16 (95% CI, -0.22 to -0.09) SD units at age 17 to 23 months, -0.07 (95% CI, -0.10 to -0.04) SD units at age 6 to 9 years, and -0.02 (95% CI, -0.15 to 0.12) SD units at age 14 to 17 years. Smaller offspring size was limited to individuals conceived by fresh but not frozen embryo transfer compared with those who were NC (eg, difference in weight at age 4 to 5 years was -0.14 [95% CI, -0.20 to -0.07] SD units for fresh embryo transfer vs NC and 0.00 [95% CI, -0.15 to 0.15] SD units for frozen embryo transfer vs NC). More marked differences were seen for body fat measurements, and there was imprecise evidence that offspring conceived by ART developed greater adiposity by early adulthood (eg, ART vs NC difference in fat mass index at age older than 17 years: 0.23 [95% CI, -0.04 to 0.50] SD units). Conclusions and Relevance: These findings suggest that people conceiving or conceived by ART can be reassured that differences in early growth and adiposity are small and no longer evident by late adolescence.

Ocular findings in pediatric turner syndrome.

OBJECTIVE: Turner syndrome (TS) is associated with abnormalities across several organ systems, including the visual system. There is a relative paucity of literature describing ophthalmic manifestations of TS. We sought to investigate eye manifestations in our cross-sectional population of pediatric TS patients. METHODS: All patients managed by the TS program of a tertiary children's hospital were identified. Patients with documentation of at least one eye exam were included for analysis. Chart review was retrospectively performed to identify all documented ocular abnormalities as well as patient demographics, including TS karyotype. Statistical analysis was performed to identify any association between karyotype and ocular abnormality. RESULTS: A total of 187 patients with TS were identified. The mean age of the cohort was 14.3 ± 7.2 years. Ametropia was the most common ocular abnormality, occurring in 79 patients (42%), followed by strabismus in 25 (13%). Of the patients with strabismus, 17 had exotropia and 8 had esotropia, with only 2 patients requiring surgical intervention. Posterior segment abnormalities were identified in five patients without accompanying visual deficits. Two patients had ocular tumors: one with retinoblastoma and one with retinal astrocytic hamartoma. There was no association between TS karyotype and occurrence of ocular abnormalities. CONCLUSION: Ophthalmic manifestations of TS were common, particularly ametropia and strabismus. Management of strabismus was conservative in the vast majority of patients. Ocular manifestations were not associated with TS karyotype. Early screening and routine ophthalmic evaluation of patients with TS is needed to prevent progression of potentially vision-threatening abnormalities.

Deep Learning for Outcome Prediction in Neurosurgery: A Systematic Review of Design, Reporting, and Reproducibility.

Deep learning (DL) is a powerful machine learning technique that has increasingly been used to predict surgical outcomes. However, the large quantity of data required and lack of model interpretability represent substantial barriers to the validity and reproducibility of DL models. The objective of this study was to systematically review the characteristics of DL studies involving neurosurgical outcome prediction and to assess their bias and reporting quality. Literature search using the PubMed, Scopus, and Embase databases identified 1949 records of which 35 studies were included. Of these, 32 (91%) developed and validated a DL model while 3 (9%) validated a pre-existing model. The most commonly represented subspecialty areas were oncology (16 of 35, 46%), spine (8 of 35, 23%), and vascular (6 of 35, 17%). Risk of bias was low in 18 studies (51%), unclear in 5 (14%), and high in 12 (34%), most commonly because of data quality deficiencies. Adherence to transparent reporting of a multivariable prediction model for individual prognosis or diagnosis reporting standards was low, with a median of 12 transparent reporting of a multivariable prediction model for individual prognosis or diagnosis items (39%) per study not reported. Model transparency was severely limited because code was provided in only 3 studies (9%) and final models in 2 (6%). With the exception of public databases, no study data sets were readily available. No studies described DL models as ready for clinical use. The use of DL for neurosurgical outcome prediction remains nascent. Lack of appropriate data sets poses a major concern for bias. Although studies have demonstrated promising results, greater transparency in model development and reporting is needed to facilitate reproducibility and validation.

Impact of 18-Month Soy Protein Supplementation on Steroid Hormones and Serum Biomarkers of Angiogenesis, Apoptosis, and the Growth Hormone/IGF-1 Axis: Results of a Randomized, Placebo-Controlled Trial in Males Following Prostatectomy.

Many studies have addressed the effects of dietary supplementation with soy protein on cancer risk and mortality, but there are only few randomized studies with soy in males. We used serum samples from a two-year trial of soy protein isolate supplementation in middle-aged to older males at risk of recurrence of prostate cancer after radical prostatectomy to determine soy effects on steroid hormones involved in prostate cancer (testosterone, SHBG, and estradiol) and explore the effects on biomarkers of the growth hormone/IGF-1 axis, apoptosis, and angiogenesis. Compared with a casein-based placebo, 18 mo, of consumption of 19.2 g/day of whole soy protein isolate containing 24 mg genistein-reduced circulating testosterone and SHBG, but not free testosterone, and did not affect serum concentrations of estradiol, VEGF, IGF-1, IGFBP-3, IGF-1/IGFBP-3 ratio, soluble Fas, Fas-ligand, and sFas/Fas-ligand ratio. Thus, soy protein supplementation for 18 mo, affected the androgen axis, but the effects on other cancer biomarkers remain to be more definitively determined. The study was registered at clinicaltrials.gov (NCT00765479).

Artificial Intelligence Applications in Pediatric Brain Tumor Imaging: A Systematic Review.

OBJECTIVE: Artificial intelligence (AI) has facilitated the analysis of medical imaging given increased computational capacity and medical data availability in recent years. Although many applications for AI in the imaging of brain tumors have been proposed, their potential clinical impact remains to be explored. A systematic review was performed to examine the role of AI in the analysis of pediatric brain tumor imaging. METHODS: PubMed, Embase, and Scopus were searched for relevant articles up to January 27, 2021. RESULTS: Literature search identified 298 records, of which 22 studies were included. The most commonly studied tumors were posterior fossa tumors including brainstem glioma, ependymoma, medulloblastoma, and pilocytic astrocytoma (15, 68%). Tumor diagnosis was the most frequently performed task (14, 64%), followed by tumor segmentation (3, 14%) and tumor detection (3, 14%). Of the 6 studies comparing AI to clinical experts, 5 demonstrated superiority of AI for tumor diagnosis. Other tasks including tumor segmentation, attenuation correction of positron emission tomography scans, image registration for patient positioning, and dose calculation for radiotherapy were performed with high accuracy comparable with clinical experts. No studies described use of the AI tool in routine clinical practice. CONCLUSIONS: AI methods for analysis of pediatric brain tumor imaging have increased exponentially in recent years. However, adoption of these methods in clinical practice requires further characterization of validity and utility. Implementation of these methods may streamline clinical workflows by improving diagnostic accuracy and automating basic imaging analysis tasks.

Outcomes and complications of minimally invasive transforaminal lumbar interbody fusion in the elderly: a systematic review and meta-analysis.

OBJECTIVE: Minimally invasive transforaminal lumbar interbody fusion (MIS-TLIF) may be used to treat degenerative spinal pathologies while reducing risks associated with open procedures. As an increasing number of lumbar fusions are performed in the aging United States population, MIS-TLIF has been widely adopted into clinical practice in recent years. However, its complication rate and functional outcomes in elderly patients remain poorly characterized. The objective of this study was to assess complication rates and functional outcomes in elderly patients (≥ 65 years old) undergoing MIS-TLIF. METHODS: The PubMed, Embase, and Scopus databases were searched for relevant records in accordance with the PRISMA guidelines. Inclusion criteria were peer-reviewed original research; English language; full text available; use of MIS-TLIF; and an elderly cohort of at least 5 patients. Risk of bias was assessed using the ROBINS-I (Risk of Bias in Nonrandomized Studies-of Interventions) tool. Pooled complication rates were calculated for elderly patients, with subgroup analyses performed for single versus multiple-level fusions. Complication rates in elderly compared to nonelderly patients were also assessed. Postoperative changes in patient-reported outcomes, including Oswestry Disability Index (ODI) and visual analog scale (VAS) back pain (BP) and leg pain (LP) scores, were calculated. RESULTS: Twelve studies were included in the final analysis. Compared to nonelderly patients, MIS-TLIF in elderly patients resulted in significantly higher rates of major (OR 2.15, 95% CI 1.07-4.34) and minor (OR 2.20, 95% CI 1.22-3.95) complications. The pooled major complication rate in elderly patients was 0.05 (95% CI 0.03-0.08) and the pooled minor complication rate was 0.20 (95% CI 0.13-0.30). Single-level MIS-TLIF had lower major and minor complication rates than multilevel MIS-TLIF, although not reaching significance. At a minimum follow-up of 6 months, the postoperative change in ODI (-30.70, 95% CI -41.84 to -19.55), VAS-BP (-3.87, 95% CI -4.97 to -2.77), and VAS-LP (-5.11, 95% CI -6.69 to -3.53) in elderly patients all exceeded the respective minimum clinically important difference. The pooled rate of fusion was 0.86 (95% CI 0.80-0.90). CONCLUSIONS: MIS-TLIF in elderly patients results in a high rate of fusion and significant improvement of patient-reported outcomes, but has significantly higher complication rates than in nonelderly patients. Limitations of this study include heterogeneity in the definition of elderly and limited reporting of risk factors among included studies. Further study of the impact of complications and the factors predisposing elderly patients to poor outcomes is needed.