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.

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.

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.

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.

Early reperfusion has the best likelihood for a favorable outcome in acute ischemic stroke (AIS) with large vessel occlusion (LVO). Our experience with mobile stroke unit (MSU) for direct to angiosuite (DTAS) transfer in AIS patients with suspected LVO is presented.

Retrospective review of prospectively collected data from November 2019 to August 2022, of patients evaluated and transferred by the University of Alberta Hospital MSU and moved to angiosuite for endovascular thrombectomy (EVT).

A total of 41 cases were included. Nine were chosen for DTAS and 32 were shifted to angiosuite after stopping for computed tomography (CT) angiography of the head and neck (no-DTAS). Stroke severity measured by NIHSS (median with interquartile range (IQR)) was higher in patients of DTAS, 22 (14–24) vs 14.5 (5–25) in no-DTAS (p = 0.001). The non-contrast CT head in MSU showed hyperdense vessels in 8 (88.88%) DTAS vs 11 (34.35%) no-DTAS patients (p = 0.003). The EVT timelines (median with IQR, 90th percentile) including “door to artery puncture time” were 31 (23–50, 49.2) vs 79 (39–264, 112.8) minutes, and “door to recanalization time” was 69 (49–110, 93.2) vs 105.5 (52–178, 159.5) minutes in DTAS vs no-DTAS group, respectively. The workflow times were significantly shorter in the DTAS group (p < 0.001). Eight (88.88%) out of 9 DTAS patients had LVO and underwent thrombectomy.

MSU for DTAS in patients with high NIHSS scores, cortical signs, and CT showing hyperdense vessel is an effective strategy to reduce the EVT workflow time.

Obstructive sleep apnea (OSA) is prevalent after stroke and associated with recurrent stroke, prolonged hospitalization, and decreased functional recovery. Sex differences in post-stroke OSA remain underexplored. The objective of this study was to evaluate sex differences in functional outcomes, stroke and OSA severity, and clinical manifestations of OSA in stroke patients with OSA.

We retrospectively evaluated data from three previously conducted studies. Study patients had an imaging-confirmed stroke and had been found to have OSA (apnea–hypopnea index [AHI] ≥ 5) on either in-laboratory polysomnography or home sleep apnea testing performed within 1 year of their stroke. Linear regression models were used to evaluate study outcomes.

In total, 171 participants with post-stroke OSA (117 males [68.4%] and 54 females [31.6%]) were included. Female sex was an independent predictor for greater functional impairment (β = 0.37, 95% CI 0.029–0.71, p = 0.03), increased stroke severity (β = 1.009, 95% CI 0.032–1.99, p = 0.04), and greater post-stroke depressive symptoms (β = 3.73, 95% CI 0.16–7.29, p = 0.04). Female sex was associated with lower OSA severity, as measured by the AHI (β = –5.93, 95% CI –11.21– –0.66). Sex was not an independent predictor of specific symptoms of OSA such as daytime sleepiness, snoring, tiredness, and observed apneas.

Females with post-stroke OSA had poorer functional outcomes and more severe strokes compared to males, despite having lower OSA severity. Females with post-stroke OSA also exhibited more depressive symptoms. Understanding sex differences in patients with post-stroke OSA will likely facilitate better recognition of OSA and potentially improve clinical outcomes.

Obstructive sleep apnea (OSA) is a sleep disorder with no widely accepted pharmacological therapy. Cannabinoids have been suggested to reduce OSA severity in small human studies. The purpose of this retrospective cohort study was to explore the association of self-reported cannabis use on OSA severity and sleep parameters in a large cohort of adults undergoing in-laboratory polysomnography.

Sleep and medication data were collected for all consecutive adults who completed diagnostic polysomnography at Sunnybrook Health Sciences Centre from 2010 to 2022. Multivariable linear regression models were employed that adjusted for age, sex, and BMI (minimally adjusted model), as well as medication and comorbidity data (maximally adjusted model). An exploratory subgroup analysis was additionally run in patients with moderate to severe OSA.

Of 6,958 individuals (mean age 54.7 ± 16.3, BMI 29.1 ± 6.8, 51.0% female), 71 reported cannabis use. In our minimally adjusted models, cannabis use predicted a reduced respiratory disturbance index (RDI) (β: −4.8 [95% CI: −9.4, −0.2]; p = 0.042); this association became nonsignificant in the fully adjusted models. In an exploratory analysis of patients with moderate to severe OSA (n = 613), cannabis use (n = 7) predicted increased stage N3 sleep (β: 33.5 [95% CI: 15.6, 51.4]; p < 0.001) and decreased REM sleep (β: 16.0 [95% CI: 0.3, 31.7]; p = 0.046).

Self-reported cannabis use was not associated with OSA severity after adjusting for confounders. In an exploratory subgroup analysis of patients with moderate to severe OSA, cannabis use impacted sleep architecture. Future studies should further explore these findings.

To evaluate the impacts of the COVID-19 on neuro-ophthalmology practice in the United States.

Cross-sectional study.

The North American Neuro-ophthalmology Society distributed a survey on the impact of COVID-19 on neuro-ophthalmic practice to its members. The survey consisted of 15 questions regarding the impact of the pandemic on neuro-ophthalmic practice and perspectives.

Twenty-eight neuro-ophthalmologists practicing in the United States responded to our survey. In this survey, 64% of survey respondents were male (n = 18), while 36% were female (n = 10). The average age of a respondent was 55 years old. According to 77% of survey respondents, various neuro-ophthalmic diseases were reported to have worsened during the pandemic including idiopathic intracranial hypertension, compressive optic neuropathy, optic neuritis, and giant cell arteritis.

This survey represents one of the largest studies to describe the impact of the COVID-19 pandemic of neuro-ophthalmology. Given the underrepresentation of neuro-ophthalmology in the United States as described in the literature, this study strengthens the need for more neuro-ophthalmologists to provide timely care, particularly during the pandemic. Further interventions to incentivize the pursuit of neuro-ophthalmology training may help combat the effects of COVID-19 on neuro-ophthalmic conditions.