Management of primary headache (PHA) varies across emergency departments (ED), yet there is widespread agreement that computed tomography (CT) scans are overused. This study assessed emergency physicians’ (EPs) PHA management and their attitudes towards head CT ordering.

A cross-sectional study was undertaken with EPs from one Canadian center. Drivers of physicians’ perceptions regarding the appropriateness of CT ordering for patients with PHA were explored.

A total of 73 EPs (70% males; 48% with <10 years of practice) participated in the study. Most EPs (88%) did not order investigations for moderate-severe primary headaches; however, CT was the common investigation (47%) for headaches that did not improve. Computed tomography ordering was frequently motivated by the need for specialist consultation (64%) or admission (64%). A small proportion (27%) believed patients usually/frequently expected a scan. Nearly half of EPs (48%) identified patient imaging expectations/requests as a barrier to reducing CT ordering. Emergency physicians with CCFP (EM) certification were less likely to perceive CT ordering for patients with PHA as appropriate. Conversely, those who identified the possibility of missing a condition as a major barrier to limiting their CT use were more likely to perceive CT ordering for patients with PHA as appropriate.

Emergency physicians reported consistency and evidence-based medical management. They highlighted the complexities of limiting CT ordering and both their level of training and their perceived barriers for limiting CT ordering seem to be influencing their attitudes. Further studies could elucidate these and other factors influencing their practice.

The relationship between migraine and alcohol consumption is unclear. We assessed the association between chronic migraine and alcohol use disorder(AUD), relative to chronic disease controls, and in conjunction with common comorbidities.

We conducted a retrospective, observational study. The primary outcome was the odds ratio for AUD in patients with chronic migraine or with chronic migraine and additional comorbidities relative to controls.

A total of 3701 patients with chronic migraine, 4450 patients with low back pain, and 1780 patients with type 2 diabetes mellitus met inclusion criteria. Patients with chronic migraine had a lower risk of AUD relative to both controls of low back pain (OR 0.37; 95% CI: 0.29–0.47, p < 0.001) and type 2 diabetes mellitus (OR 0.39; 95% CI: 0.29–0.52, p < 0.001). Depression was associated with the largest OR for AUD in chronic migraine (OR 8.62; 95% CI: 4.99–14.88, p < 0.001), followed by post-traumatic stress disorder (OR 6.63; 95% CI: 4.13–10.64, p < 0.001) and anxiety (OR 3.58; 95% CI: 2.23–5.75, p < 0.001).

Patients with chronic migraine had a lower odds ratio of AUD relative to controls. But in patients with chronic migraine, those with comorbid depression, anxiety, or PTSD are at higher risk of AUD. When patients establish care, comorbid factors should be assessed and for those at higher risk, AUD should be screened for at every visit.

Genetic association studies have not produced consistent results in restless legs syndrome (RLS).

To conduct a systematic review on genetic association studies in RLS to highlight the common gene variants and ethnic differences.

We conducted Pubmed, Embase, and Cochrane search using terms “Genetic association studies” and “restless legs syndrome” for candidate gene-based studies. Out of the initial 43 studies, 18 case control studies (from 2012 to 2022) were included. Thirteen studies including 10794 Caucasian subjects (4984 RLS cases and 5810 controls) and five studies involving 2009 Asian subjects (796 RLS cases and 1213 controls) were tabulated and analyzed. In addition, three Genome-Wide Association Studies (GWAS) in Asians and Europeans/Caucasians were included for comparisons.

In the Asian population, gene variants in BST1, SNCA Rep1, IL1B, BTBD9, and MAP2K5/SKOR1 increased the risk of RLS (odds ratio range 1.2–2.8). In Caucasian populations, examples of variants that were associated with an increased risk of RLS (odds ratio range 1.1–1.9) include those in GABRR3 TOX3, ADH1B, HMOX1, GLO1, DCDC2C, BTBD9, SKOR1, and SETBP1. Based on the meta-analysis of GWAS studies, the rs9390170 variant in UTRN gene was identified to be a novel genetic marker for RLS in Asian cohorts, whereas rs113851554 in MEIS1 gene was a strong genetic factor among the >20 identified gene variants for RLS in Caucasian populations.

Our systemic review demonstrates that multiple genetic variants modulate risk of RLS in Caucasians (such as MEIS1 BTBD9, MAP2K5) and in Asians (such as BTBD9, MAP2K5, and UTRN).

Status epilepticus (SE) is a neurological emergency characterized by prolonged seizures. However, the incidence of first-episode SE is unclear, as estimates vary greatly among studies. Additionally, SE risk factors have been insufficiently explored. Therefore, the objectives of this study were to estimate the incidence of first-episode SE in Ontario, Canada, and estimate the associations between potential sociodemographic and health-related risk factors and first-episode SE.

We conducted a population-based retrospective cohort study using linked health administrative datasets. We included individuals who completed Canada’s 2006 Census long-form questionnaire, lived in Ontario, were between 18 and 105, and had no history of SE. A Cox proportional hazards regression model was used to estimate the hazard ratios for SE within three years associated with each potential risk factor.

The final sample included 1,301,700 participants, 140 of whom were hospitalized or had an emergency department visit for first-episode SE during follow-up (3.5 per 100,000 person-years). Older age was the only significant sociodemographic SE risk factor (HR = 1.35, 95% CI = 1.33, 1.37), while health-related risk factors included alcohol or drug abuse (HR = 1.05, 95% CI = 1.02, 1.08), brain tumour or cancer (HR = 1.14, 95% CI = 1.12, 1.15), chronic kidney disease (HR = 1.32, 95% CI = 1.29, 1.36), dementia (HR = 1.42, 95% CI = 1.36, 1.48), diabetes (HR = 1.11, 95% CI = 1.09, 1.12), epilepsy or seizures (HR = 1.05, 95% CI = 1.01, 1.09) and stroke (HR = 1.08, 95% CI = 1.05, 1.11).

The estimated incidence of SE in a sample of Ontario residents was 3.5 per 100,000 person-years. Older age and several comorbid conditions were associated with higher first-episode SE risk.

To assess cost-effectiveness of late time-window endovascular treatment (EVT) in a clinical trial setting and a “real-world” setting.

Data are from the randomized ESCAPE trial and a prospective cohort study (ESCAPE-LATE). Anterior circulation large vessel occlusion patients presenting > 6 hours from last-known-well were included, whereby collateral status was an inclusion criterion for ESCAPE but not ESCAPE-LATE. A Markov state transition model was built to estimate lifetime costs and quality-adjusted life-years (QALYs) for EVT in addition to best medical care vs. best medical care only in a clinical trial setting (comparing ESCAPE-EVT to ESCAPE control arm patients) and a “real-world” setting (comparing ESCAPE-LATE to ESCAPE control arm patients). We performed an unadjusted analysis, using 90-day modified Rankin Scale(mRS) scores as model input and analysis adjusted for baseline factors. Acceptability of EVT was calculated using upper/lower willingness-to-pay thresholds of 100,000 USD/50,000 USD/QALY.

Two-hundred and forty-nine patients were included (ESCAPE-LATE:n = 200, ESCAPE EVT-arm:n = 29, ESCAPE control-arm:n = 20). Late EVT in addition to best medical care was cost effective in the unadjusted analysis both in the clinical trial and real-world setting, with acceptability 96.6%–99.0%. After adjusting for differences in baseline variables between the groups, late EVT was marginally cost effective in the clinical trial setting (acceptability:49.9%–61.6%), but not the “real-world” setting (acceptability:32.9%–42.6%).

EVT for LVO-patients presenting beyond 6 hours was cost effective in the clinical trial setting and “real-world” setting, although this was largely related to baseline patient differences favoring the “real-world” EVT group. After adjusting for these, EVT benefit was reduced in the trial setting, and absent in the real-world setting.

Ocrelizumab is an effective anti-CD20 therapy approved for Relapsing Remitting (RRMS) and Primary Progressive Multiple Sclerosis (PPMS). In clinical trials, a proportion of patients developed hypogammaglobulinemia which could contribute to infection risk. This study aimed to identify hypogammaglobulinemia and its risk factors and evaluate potentially associated serious infection risk in a real-world cohort of patients.

All MS patients treated with ocrelizumab in a Quebec City MS clinic from January 2017 to August 2021 were included and detailed patient characteristics were collected by chart review. Levels of immunoglobulins (IgM, IgA and IgG) were assessed prior to each treatment. Serious infection was defined as an infection requiring hospitalization or emergency room treatment. Association between hypogammaglobulinemia and serious infection was analyzed.

A total of 266 patients (average follow-up 2.05 years) were included (87% RRMS). After 6 infusions, 32.8%, 3.5% and 4.2% of patients had at least one IgM, IgA and IgG hypogammaglobulinemia event respectively. Aside from pre-treatment hypogammaglobulinemia, there were no variables associated with on-treatment hypogammaglobulinemia. There was a total of 21 serious infections (3.36 and 12.33 per 100-person-years in RRMS and PPMS). Developing hypogammaglobulinemia during treatment was not associated with serious infection. A regression analysis did not show associations between serious infection and key disease characteristics.

Similar to ocrelizumab extension studies, our cohort demonstrated a significant rate of hypogammaglobulinemia over time, mostly with IgM. No association was found between hypogammaglobulinemia and serious infection.

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.

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.