Impact of Automated Prognostication on Traumatic Brain Injury Care: A Focus Group Study.

BACKGROUND: Prognosticating outcomes for traumatic brain injury (TBI) patients is challenging due to the required specialized skills and variability among clinicians. Recent attempts to standardize TBI prognosis have leveraged machine learning (ML) methodologies. This study evaluates the necessity and influence of ML-assisted TBI prognostication through healthcare professionals' perspectives via focus group discussions. METHODS: Two virtual focus groups included ten key TBI care stakeholders (one neurosurgeon, two emergency clinicians, one internist, two radiologists, one registered nurse, two researchers in ML and healthcare and one patient representative). They answered six open-ended questions about their perceptions and potential ML use in TBI prognostication. Transcribed focus group discussions were thematically analyzed using qualitative data analysis software. RESULTS: The study captured diverse perceptions and interests in TBI prognostication across clinical specialties. Notably, certain clinicians who currently do not prognosticate expressed an interest in doing so independently provided they had access to ML support. Concerns included ML's accuracy and the need for proficient ML researchers in clinical settings. The consensus suggested using ML as a secondary consultation tool and promoting collaboration with internal or external research resources. Participants believed ML prognostication could enhance disposition planning and standardize care regardless of clinician expertise or injury severity. There was no evidence of perceived bias or interference during the discussions. CONCLUSION: Our findings revealed an overall positive attitude toward ML-based prognostication. Despite raising multiple concerns, the focus group discussions were particularly valuable in underscoring the potential of ML in democratizing and standardizing TBI prognosis practices.

Development of a Multimodal Machine Learning-Based Prognostication Model for Traumatic Brain Injury Using Clinical Data and Computed Tomography Scans: A CENTER-TBI and CINTER-TBI Study.

Computed tomography (CT) is an important imaging modality for guiding prognostication in patients with traumatic brain injury (TBI). However, because of the specialized expertise necessary, timely and dependable TBI prognostication based on CT imaging remains challenging. This study aimed to enhance the efficiency and reliability of TBI prognostication by employing machine learning (ML) techniques on CT images. A retrospective analysis was conducted on the Collaborative European NeuroTrauma Effectiveness Research in TBI (CENTER-TBI) data set (n = 1016). An ML-driven binary classifier was developed to predict favorable or unfavorable outcomes at 6 months post-injury. The prognostic performance was assessed using the area under the curve (AUC) over fivefold cross-validation and compared with conventional models that depend on clinical variables and CT scoring systems. An external validation was performed using the Comparative Indian Neurotrauma Effectiveness Research in Traumatic Brain Injury (CINTER-TBI) data set (n = 348). The developed model achieved superior performance without the necessity for manual CT assessments (AUC = 0.846 [95% CI: 0.843-0.849]) compared with the model based on the clinical and laboratory variables (AUC = 0.817 [95% CI: 0.814-0.820]) and established CT scoring systems requiring manual interpretations (AUC = 0.829 [95% CI: 0.826-0.832] for Marshall and 0.838 [95% CI: 0.835-0.841] for International Mission for Prognosis and Analysis of Clinical Trials in TBI [IMPACT]). The external validation demonstrated the prognostic capacity of the developed model to be significantly better (AUC = 0.859 [95% CI: 0.857-0.862]) than the model using clinical variables (AUC = 0.809 [95% CI: 0.798-0.820]). This study established an ML-based model that provides efficient and reliable TBI prognosis based on CT scans, with potential implications for earlier intervention and improved patient outcomes.

An interrupted time series evaluation of the effect of cannabis legalization on intentional self-harm in two Canadian provinces: Ontario and Alberta. / Évaluation, à l'aide de séries chronologiques interrompues, de l'effet de la légalisation du cannabis sur les lésions auto-infligées dans deux provinces canadiennes : Ontario et Alberta.

INTRODUCTION: Despite the association between cannabis use and higher prevalence of suicidal ideation and attempt, the effect of cannabis legalization and regulation in Canada on intentional self-harm has not been determined. METHODS: We used an interrupted time series of population-based rates of emergency department (ED) visits and hospitalizations for intentional self-harm per 100 000 in Ontario and Alberta from January/April 2010 to February 2020. Aggregate monthly counts of ED visits and hospitalizations for intentional self-harm (ICD-10 codes X60-X84, R45.8) were obtained from the National Ambulatory Care Reporting System and Discharge Abstract Database, respectively. RESULTS: The legalization and regulation of cannabis in Canada was not significantly associated with a change in rates of ED visits for intentional self-harm in Ontario (level = 0.58, 95% CI: -1.14 to 2.31; trend = -0.17, 95% CI: -0.35 to 0.01) or Alberta (level = -0.06, 95% CI: -2.25 to 2.12; trend = -0.07, 95% CI: -0.27 to 0.13). Hospitalizations for intentional self-harm also remained unchanged in Ontario (level = -0.14, 95% CI: -0.48 to 0.20; trend = 0.01, 95% CI: -0.03 to 0.04) and Alberta (level = -0.41, 95% CI: -1.03 to 0.21; trend = -0.03, 95% CI: -0.08 to 0.03). CONCLUSION: Legalization and regulation of cannabis in Canada has not increased rates of ED visits or hospitalizations for intentional self-harm in Ontario and Alberta. Individual-level analyses that account for demographic characteristics and include other provinces and territories are needed.

Astrogliosis marker 11C-SL25.1188 PET in traumatic brain injury with persistent symptoms.

Traumatic brain injury (TBI) is common but little is known why up to a third of patients have persisting symptoms. Astrogliosis, a pathophysiological response to brain injury, may be a potential therapeutic target, but demonstration of astrogliosis in the brain of humans with TBI and persistent symptoms is lacking. Astroglial marker monoamine oxidase B (MAO-B) total distribution volume (11C-SL25.1188 VT), an index of MAO-B density, was measured in 29 TBI and 29 similarly aged healthy control cases with 11C-SL25.1188 PET, prioritizing prefrontal cortex (PFC) and cortex proximal to cortical convexity. Correlations of PFC 11C-SL25.1188 VT with psychomotor and processing speed; and serum blood measures implicated in astrogliosis were determined. 11C-SL25.1188 VT was greater in TBI in PFC (P = 0.00064) and cortex (P = 0.00038). PFC 11C-SL25.1188 VT inversely correlated with Comprehensive Trail Making Test psychomotor and processing speed (r = -0.48, P = 0.01). In participants scanned within 2 years of last TBI, PFC 11C-SL25.1188 VT correlated with serum glial fibrillary acid protein (r = 0.51, P = 0.037) and total tau (r = 0.74, P = 0.001). Elevated 11C-SL25.1188 VT argues strongly for astrogliosis and therapeutics modifying astrogliosis towards curative phenotypes should be tested in TBI with persistent symptoms. Given substantive effect size, astrogliosis PET markers should be applied to stratify cases and/or assess target engagement for putative therapeutics targeting astrogliosis.

Fractionated radiotherapy for surgically resected intracranial meningiomas: A multicentre retrospective cohort study.

BACKGROUND: Aside from surgical resection, the only standard of care treatment modality for meningiomas is radiotherapy (RT). Despite this, few studies have focused on identifying clinical covariates associated with failure of fractionated RT following surgical resection (fRT), and the timing of fRT following surgery still remains controversial (adjuvant versus salvage fRT). We assessed the outcomes of the largest, multi-institutional cohort of surgically resected meningiomas treated with subsequent adjuvant and salvage fRT to identify factors associated with local freedom from recurrence (LFFR) over 3-10 years post-fRT and to determine the optimal timing of fRT. METHODS: Patients with intracranial meningiomas who underwent surgery and fRT between 1997 and 2018 were included. Primary endpoints were radiographic recurrence/progression and time to progression from the completion of fRT. RESULTS: 404 meningiomas were included for analysis. Of these, 167 (41.3%) recurred post-fRT. Clinical covariates independently associated with worse PFS post-fRT included receipt of previous RT to the meningioma, having a WHO grade 3 meningioma or recurrent meningioma, the meningioma having a higher MIB1-index or brain invasion on pathology, and older patient age at diagnosis. Subgroup analysis identified higher MIB1-index as a histological factor associated with poorer LFFR in WHO grade 2 meningiomas. 179 patients underwent adjuvant RT shortly after surgery whereas 225 patients had delayed, salvage fRT after recurrence/progression. Following propensity score matching, patients that underwent adjuvant fRT had improved LFFR post-fRT compared to those that received salvage fRT. CONCLUSION: There is a paucity of clinical factors that can predict a meningioma's response to fRT following surgery. Adjuvant fRT may be associated with improved PFS post-fRT compared to salvage fRT. Molecular biomarkers of RT-responsiveness are needed to better inform fRT treatment decisions.

Automated screening of computed tomography using weakly supervised anomaly detection.

BACKGROUND: Current artificial intelligence studies for supporting CT screening tasks depend on either supervised learning or detecting anomalies. However, the former involves a heavy annotation workload owing to requiring many slice-wise annotations (ground truth labels); the latter is promising, but while it reduces the annotation workload, it often suffers from lower performance. This study presents a novel weakly supervised anomaly detection (WSAD) algorithm trained based on scan-wise normal and anomalous annotations to provide better performance than conventional methods while reducing annotation workload. METHODS: Based on surveillance video anomaly detection methodology, feature vectors representing each CT slice were trained on an AR-Net-based convolutional network using a dynamic multiple-instance learning loss and a center loss function. The following two publicly available CT datasets were retrospectively analyzed: the RSNA brain hemorrhage dataset (normal scans: 12,862; scans with intracranial hematoma: 8882) and COVID-CT set (normal scans: 282; scans with COVID-19: 95). RESULTS: Anomaly scores of each slice were successfully predicted despite inaccessibility to any slice-wise annotations. Slice-level area under the curve (AUC), sensitivity, specificity, and accuracy from the brain CT dataset were 0.89, 0.85, 0.78, and 0.79, respectively. The proposed method reduced the number of annotations in the brain dataset by 97.1% compared to an ordinary slice-level supervised learning method. CONCLUSION: This study demonstrated a significant annotation reduction in identifying anomalous CT slices compared to a supervised learning approach. The effectiveness of the proposed WSAD algorithm was verified through higher AUC than existing anomaly detection techniques.

The effect of recreational cannabis legalization on rates of traffic injury in Canada.

AIMS: To measure the impact of Canada's recreational cannabis legalization (RCL) in October 2018 and the subsequent impact of the coronavirus disease 2019 (COVID-19) lockdowns from March 2020 on rates of emergency department (ED) visits and hospitalizations for traffic injury. DESIGN: An interrupted time series analysis of rates of ED visits and hospitalizations in Canada recorded in population-based databases from January/April 2010 to March 2021. SETTING: ED visits in Ontario and Alberta and hospitalizations in Ontario, Alberta, British Columbia, the Prairies (Manitoba and Saskatchewan) and the Maritimes (Nova Scotia, New Brunswick, Newfoundland and Prince Edward Island). PARTICIPANTS: Monthly counts of presentations to the ED or hospital for motor vehicle injury or pedestrian/cyclist injury, used to calculate monthly rates per 100 000 population. MEASUREMENTS: An occurrence of one or more International Statistical Classification of Diseases and Related Health Problems, 10th Revision, Canada (ICD-10-CA) code for motor vehicle injury (V20-V29, V40-V79, V30-V39 and V86) and pedestrian/cyclist injury (V01-V09 and V10-V19) within the National Ambulatory Care Reporting System and Discharge Abstract Database. FINDINGS: There were no statistically significant changes in rates of ED visits and hospitalizations for motor vehicle or pedestrian/cyclist injury after RCL after accounting for multiple testing. After COVID-19, there was an immediate decrease in the rate of ED visits for motor vehicle injury that was statistically significant only in Ontario (level change ß = -16.07 in Ontario, 95% CI = -20.55 to -11.60, P = 0.000; ß = -10.34 in Alberta, 95% CI = -17.80 to -2.89, P = 0.008; α of 0.004) and no changes in rates of hospitalizations. CONCLUSIONS: Canada's recreational cannabis legalization did not notably impact motor vehicle and pedestrian/cyclist injury. The rate of emergency department visits for motor vehicle injury decreased immediately after COVID-19 lockdowns, resulting in rates below post-recreational cannabis legalization levels in the year after COVID-19.

Predicting Severity of Head Collision Events in Elite Soccer Using Preinjury Data: A Machine Learning Approach.

OBJECTIVE: To develop machine learning (ML) models that predict severity of head collision events (HCEs) based on preinjury variables and to investigate which variables are important to predicting severity. DESIGN: Data on HCEs were collected with respect to severity and 23 preinjury variables to create 2 datasets, a male dataset using men's tournaments and mixed dataset using men's and women's tournaments, to perform ML analysis. Machine learning analysis used a random forest classifier based on preinjury variables to predict HCE severity. SETTING: Four elite international soccer tournaments. PARTICIPANTS: Elite athletes participating in analyzed tournaments. INDEPENDENT VARIABLES: The 23 preinjury variables collected for each HCE. MAIN OUTCOME MEASURES: Predictive ability of the ML models and association of important variables. RESULTS: The ML models had an average area under the receiver operating characteristic curve for predicting HCE severity of 0.73 and 0.70 for the male and mixed datasets, respectively. The most important variables for prediction were the mechanism of injury and the event before injury. In the male dataset, the mechanisms "head-to-head" and "knee-to-head" were together significantly associated ( P = 0.0244) with severity; they were not significant in the mixed dataset ( P = 0.1113). In both datasets, the events "corner kicks" and "throw-ins" were together significantly associated with severity (male, P = 0.0001; mixed, P = 0.0004). CONCLUSIONS: ML models accurately predicted the severity of HCE. The mechanism and event preceding injury were most important for predicting severity of HCEs. These findings support the use of ML to inform preventative measures that will mitigate the impact of these preinjury factors on player health.

Protective responses of older adults for avoiding injury during falls: evidence from video capture of real-life falls in long-term care.

BACKGROUND: falls are common in older adults, and any fall from standing height onto a rigid surface has the potential to cause a serious brain injury or bone fracture. Safe strategies for falling in humans have traditionally been difficult to study. OBJECTIVE: to determine whether specific 'safe landing' strategies (body rotation during descent, and upper limb bracing) separate injurious and non-injurious falls in seniors. DESIGN: observational cohort study. SETTING: two long-term care homes in Vancouver BC. METHODS: videos of 2,388 falls experienced by 658 participants (mean age 84.0 years; SD 8.1) were analysed with a structured questionnaire. General estimating equations were used to examine how safe landing strategies associated with documented injuries. RESULTS: injuries occurred in 38% of falls, and 4% of falls caused injuries treated in hospitals. 32% of injuries were to the head. Rotation during descent was common and protective against injury. In 43% of falls initially directed forward, participants rotated to land sideways, which reduced their odds for head injury 2-fold. Upper limb bracing was used in 58% of falls, but rather than protective, bracing was associated with an increased odds for injury, possibly because it occurred more often in the demanding scenario of forward landings. CONCLUSIONS: the risk for injury during falls in long-term care was reduced by rotation during descent, but not by upper limb bracing. Our results expand our understanding of human postural responses to falls, and point towards novel strategies to prevent fall-related injuries.

Automated identification and quantification of traumatic brain injury from CT scans: Are we there yet?

BACKGROUND: The purpose of this study was to conduct a systematic review for understanding the availability and limitations of artificial intelligence (AI) approaches that could automatically identify and quantify computed tomography (CT) findings in traumatic brain injury (TBI). METHODS: Systematic review, in accordance with PRISMA 2020 and SPIRIT-AI extension guidelines, with a search of 4 databases (Medline, Embase, IEEE Xplore, and Web of Science) was performed to find AI studies that automated the clinical tasks for identifying and quantifying CT findings of TBI-related abnormalities. RESULTS: A total of 531 unique publications were reviewed, which resulted in 66 articles that met our inclusion criteria. The following components for identification and quantification regarding TBI were covered and automated by existing AI studies: identification of TBI-related abnormalities; classification of intracranial hemorrhage types; slice-, pixel-, and voxel-level localization of hemorrhage; measurement of midline shift; and measurement of hematoma volume. Automated identification of obliterated basal cisterns was not investigated in the existing AI studies. Most of the AI algorithms were based on deep neural networks that were trained on 2- or 3-dimensional CT imaging datasets. CONCLUSION: We identified several important TBI-related CT findings that can be automatically identified and quantified with AI. A combination of these techniques may provide useful tools to enhance reproducibility of TBI identification and quantification by supporting radiologists and clinicians in their TBI assessments and reducing subjective human factors.

Social determinants of health associated with psychological distress stratified by lifetime traumatic brain injury status and sex: Cross-sectional evidence from a population sample of adults in Ontario, Canada.

This study identified the social determinants of health (SDoH) associated with psychological distress in adults with and without a self-reported history of traumatic brain injury (TBI), stratified by sex. Data from the 2014-2017 cycles of the Centre for Addiction and Mental Health Monitor Survey, a representative survey of adults ≥18 years in Ontario, Canada, were analyzed (N = 7,214). The six-item version of the Kessler Psychological Distress Scale was used to determine moderate to severe psychological distress. Self-reported lifetime TBI was defined as a head injury resulting in a loss of consciousness for ≥5 minutes or at least one-night stay in the hospital (16.4%). Among individuals reporting a history of TBI, 30.2% of males and 40.1% of females reported psychological distress (p = 0.0109). Among individuals who did not report a history of TBI, 17.9% of males and 23.5% of females reported psychological distress (p<0.0001). Multivariable logistic regression analyses showed that the SDoH significantly associated with elevated psychological distress were similar between individuals with and without a history of TBI. This included unemployment, student, or 'other' employment status among both males and females; income below the provincial median and age 65+ among males; and rural residence among females. This study highlighted opportunities for targeted population-level interventions, namely accessible and affordable mental health supports for individuals with lower income. Notably, this study presented evidence suggesting adaptations to existing services to accommodate challenges associated with TBI should be explored, given the finite and competing demands for mental health care and resources.

Effect of a new concussion substitute rule on medical assessment of head collision events in Premier League football.

OBJECTIVE: To investigate the utilisation of additional permanent concussion substitutes (APCSs) and its efficacy with regards to rate and duration of medical assessment of head collision events (HCEs) in the 2020-2021 Premier League season. The present APCS rule allows players with a suspected concussion to be removed from a match without counting towards a team's allocated substitutions. METHODS: Eighty Premier League matches, 40 prior to additional permanent concussion substitutes implementation (Pre-APCS) and 40 after (Post-APCS), were randomly selected and analysed by a team of trained reviewers for HCEs. Data on HCE incidence, rates of medical assessment, duration of medical assessment and return to play were collected for each match. Data for the Pre-APCS and Post-APCS groups were compared to analyse differences in assessment of HCEs. RESULTS: During the 2020-2021 Premier League season, three APCSs were used. There were 38 HCEs identified in the Pre-APCS group (0.95 per match, 28.79 per 1000 athlete-hours of exposure) and 42 in the Post-APCS group (1.05 per match, 31.82 per 1000 athlete-hours of exposure). Incidence of HCEs (p=0.657), rates of medical assessment (23.7% Pre-APCS vs 21.4% Post-APCS; p=0.545) and duration of medical assessment (median 81 s Pre-APCS vs 102 s Post-APCS; p=0.466) did not significantly differ between the two groups. CONCLUSIONS: The implementation of APCSs in the Premier League did not impact the rate or duration of medical assessement of HCEs. Despite the introduction of APCSs, the consensus protocols for HCE assessment were rarely followed. We recommend changes to APCS and its implementation that would be aimed at protecting player health.

Validity and Usefulness of YouTube Videos Related to Endoscopic Transsphenoidal Surgery for Patient Information.

Objectives This article evaluates the completeness and accuracy of YouTube videos related to endoscopic transsphenoidal surgery (ETS) as a source for patient information. Design YouTube was searched using relevant terms pertaining to ETS. Videos were evaluated independently by two physician reviewers experienced in ETS. Video demographics including uploader source along with validity scores based on predetermined checklists were captured. Setting Internet. Participants Not applicable. Main Outcome Measures A novel ETS scoring checklist, the modified DISCERN criteria, and Journal of the American Medical Association (JAMA) benchmark score were used to measure completeness and accuracy of videos. video power index (VPI) was calculated to reflect popularity. Intraclass correlation coefficient was calculated for rater agreement. Results Seventy-nine videos were included in final scoring and analysis. The ETS score, DISCERN, JAMA, and mean VPI across all included videos were 5.0 ± 2.7, 2.4 ± 0.83, 2.19 ± 0.62, and 8.92 ± 18.1, respectively. Based on the ETS score checklist, 31 (39%) of the videos were rated as poor, 30 (38%) were moderately useful, 17 (22%) were useful, and 1 (1%) was exceptional. There was a significant positive correlation between the ETS, DISCERN, and JAMA scores ( p < 0.001), but no correlation with VPI and the validity scores. There were no significant differences comparing validity scores based on the uploader source. Conclusion YouTube videos related to ETS have limited usefulness and poor overall validity for patient information. Clinicians should direct patients to other validated sources of information and aim to improve the comprehensiveness of ETS-related videos.

Injuries from falls by older adults in long-term care captured on video: Prevalence of impacts and injuries to body parts.

BACKGROUND: Falls are the leading cause of injuries in older adults. However, most falls in older adults do not cause serious injury, suggesting that older adults may fall in a manner that reduces the likelihood of impact to body sites that are most vulnerable to injury. In this observational study of falls in long-term care (LTC), we tested whether body parts differed in their probability of impact and injury. METHODS: We recorded and analyzed videos of 2388 falls by 658 LTC residents (mean age 84.0 (SD = 8.1); 56.4% female). We used Linear Mixed Models to test for differences between body parts in the probability of impact and injury, and injury when impacts occurred. RESULTS: Injuries were reported in 38.2% of falls, and 85.9% of injuries involved direct impact to the injured body part. Impact occurred most often to the hip/pelvis (probability (standard error) = 0.95 (0.01); p < .001 relative to other body parts), and least often to the head (0.35 (0.01)). Conversely, injury occurred most often to the head (p < .001 relative to other body parts). The probability of injury when impacts occurred was 0.40 (0.01) for the head, and 0.11 or less for all other body parts. CONCLUSION: Our results help to explain why most falls by older adults in LTC do not cause serious injury: residents land on body parts that are the most resilient to injury. The high susceptibility of the head to injury reinforces the need to enhance upper limb protective responses for fall arrest. The dominant role of direct impact as the mechanism of injury supports approaches to attenuate impact forces through strategies like protective clothing and compliant flooring.

Editor's Choice - Peri-Operative Outcomes of Carotid Endarterectomy are Not Improved on Dual Antiplatelet Therapy vs. Aspirin Monotherapy: A Systematic Review and Meta-Analysis.

OBJECTIVE: A systematic review and meta-analysis of the peri-operative outcomes of carotid endarterectomy (CEA) on dual antiplatelet therapy (DAPT) vs. aspirin monotherapy was carried out, to determine optimal peri-operative management with these antiplatelet agents. DATA SOURCES: The Web of Science, Pubmed, and Embase databases were searched from inception to July 2021. The corresponding authors of excluded articles were contacted to obtain additional data for possible inclusion. REVIEW METHODS: The main outcomes included ischaemic complications (stroke, transient ischaemic attack [TIA], and transcranial Doppler [TCD] measured micro-emboli), haemorrhagic complications (haemorrhagic stroke, neck haematoma, and re-operation for bleeding), and composite outcomes. Pooled estimates using odds ratios (ORs) were combined using a random or fixed effects model based on the results of the chi square test and calculation of I2. RESULTS: In total, 47 411 patients were included in 11 studies, with 14 345 (30.2%) receiving DAPT and 33 066 (69.7%) receiving aspirin only. There was no significant difference in the rates of peri-operative stroke (OR 0.87, 95% confidence interval [CI] 0.72 - 1.05) and TIA (OR 0.78, 95% CI 0.52 - 1.17) despite a significant reduction in TCD measured micro-emboli (OR 0.19, 95% CI 0.10 - 0.35) in the DAPT compared with the aspirin monotherapy group. Subgroup analysis did not reveal any significant difference in ischaemic stroke risk between patients with asymptomatic and symptomatic carotid artery stenosis. DAPT was associated with an increased risk of neck haematoma (OR 2.79, 95% CI 1.87 - 4.18) and re-operation for bleeding (OR 1.98, 95% CI 1.77 - 2.23) vs. aspirin. Haemorrhagic stroke was an under reported outcome in the literature. CONCLUSION: This meta-analysis found that CEA while on DAPT increased the risk of haemorrhagic complications, with similar rates of ischaemic complications, vs. aspirin monotherapy. This suggests that the risks of performing CEA on DAPT outweigh the benefits, even in patients with symptomatic carotid stenosis. The overall quality of studies was low, and improved reporting of CEA outcomes in the literature is necessary.

Importance of Cobalt-60 Dose Rate and Biologically Effective Dose on Local Control for Intracranial Meningiomas Treated With Stereotactic Radiosurgery.

BACKGROUND: Radiosurgery dose rate and biologically effective dose (BED) are associated with outcomes after stereotactic radiosurgery (SRS) for functional neurosurgical conditions and some benign tumors. It is not known if these factors affect the efficacy of SRS for meningioma. OBJECTIVE: To determine the association between cobalt-60 dose rate and BED on outcomes in patients with meningioma treated with SRS. METHODS: A single-institution cohort of 336 patients treated between 2005 and 2018 with cobalt-based SRS for 414 separate meningioma lesions was assembled. BED was calculated using an SRS-specific monoexponential model accounting for treatment time per lesion, assuming α/ß = 2.47 Gy. Cumulative incidences of local failure (LF) were reported after considering the competing risk of death, on a per-lesion basis. Multivariable analysis of LF was performed using a proportional hazards model. RESULTS: The most common SRS dose was 12 Gy (n = 227); 140 lesions received 14 Gy. Five-year LF was 15.6% (95% confidence interval 10.4-21.9) and 4.3% (1.4-9.8) in patients who had a dose rate of <2.95 and ≥2.95 Gy/min, respectively (P = .0375). Among 354 grade I or unresected lesions treated with SRS, BED >50 Gy2.47 was associated with a lower incidence of LF (P = .0030). Each 1 Gy/min increase in dose rate was associated with an adjusted hazard ratio of 0.53 (95% confidence interval, 0.29-0.97, P = .041) for LF. Prescription dose >12 Gy was not associated with a lower incidence of LF. CONCLUSION: Patients with meningiomas treated with lower dose rates experienced a higher incidence of LF than those treated with higher dose rates.

Novel Dural-Splitting Operative Technique for Excision of Ventrally Located Spinal Meningiomas.

OBJECTIVE: Spinal meningiomas are one of the frequently seen intradural extramedullary spinal tumors. They are almost always World Health Organization grade I, and a complete removal of the tumor can be curative. However, ventrally located spinal meningioma removal can be challenging due to the position in front of the spinal cord through a narrow corridor provided by routine dorsal approaches. Incomplete excision of the relatively inaccessible dural attachment can consequently lead to recurrence. We describe a safe and reproducible technique used to achieve Simpson grade I removal of ventrally located spinal meningioma. METHODS: Since the spinal dura can be easily divided into inner and outer layers and the tumor usually spares the outer layer, we developed a simple technique to achieve total resection of the tumor and involved dura while leaving the outer dural layer intact. RESULTS: An advantage of this procedure is that it exploits an interdural approach to allow early devascularization of the tumor without cord manipulation and provides access to the ventral dura to achieve Simpson grade I excision. Another advantage is complete dural closure to minimize postoperative cerebrospinal fluid leak or ventral cord herniation without the need for dural substitutes. CONCLUSION: Its novel interdural approach can be used for all ages and all spinal meningiomas.

Video analysis of potential concussions in elite male Hurling: are players being assessed according to league guidelines?

BACKGROUND: Hurling is a fast-paced contact sport that places players at risk of concussion. Given the consequences of repeated concussive impacts, it is imperative that concussion management guidelines are followed. HYPOTHESIS/PURPOSE: The aim of this study is to determine if potential concussive events (PCEs) in elite Hurling are assessed in accordance with league management guidelines. The secondary objective is to investigate the effectiveness of current concussion training programs. METHODS: Investigators used a video analysis approach to identify PCEs throughout the 2018 and 2019 inter-county Hurling seasons and championships. Subsequent assessment, return to play (RTP) decision, and signs of concussion were evaluated based on previously validated methods. The results were then compared year-over-year with previous research in Gaelic Football (GF). RESULTS: A total of 183 PCEs were identified over 82 matches. PCEs were frequently assessed (86.3%, n = 158) by medical personnel. The majority of assessments were less than 1 min in duration (81.0%, n = 128). Thirteen (7.1%) players were removed following a PCE. There were 43 (23.5%) PCEs that resulted in one or more signs of concussion, of which 10 (23.3%) were removed from play. There was no difference in rate of assessment, duration of assessment, or rate of RTP between 2018 and 2019 in both Hurling and GF, suggesting that current concussion training programs have had limited success. CONCLUSION: In Hurling, players suspected of having sustained a concussion are frequently subject to a brief assessment, and are rarely removed from play. Affirmative action is needed to ensure the consistent application of standardized concussion assessment across the Gaelic Games.