Canadian Consensus Guidelines for the Diagnosis and Treatment of Autoimmune Encephalitis in Adults.

Autoimmune encephalitis is increasingly recognized as a neurologic cause of acute mental status changes with similar prevalence to infectious encephalitis. Despite rising awareness, approaches to diagnosis remain inconsistent and evidence for optimal treatment is limited. The following Canadian guidelines represent a consensus and evidence (where available) based approach to both the diagnosis and treatment of adult patients with autoimmune encephalitis. The guidelines were developed using a modified RAND process and included input from specialists in autoimmune neurology, neuropsychiatry and infectious diseases. These guidelines are targeted at front line clinicians and were created to provide a pragmatic and practical approach to managing such patients in the acute setting.

Management of routine postoperative pain for children undergoing cardiac surgery: a Paediatric Acute Care Cardiology Collaborative Clinical Practice Guideline.

BACKGROUND: Pain following surgery for cardiac disease is ubiquitous, and optimal management is important. Despite this, there is large practice variation. To address this, the Paediatric Acute Care Cardiology Collaborative undertook the effort to create this clinical practice guideline. METHODS: A panel of experts consisting of paediatric cardiologists, advanced practice practitioners, pharmacists, a paediatric cardiothoracic surgeon, and a paediatric cardiac anaesthesiologist was convened. The literature was searched for relevant articles and Collaborative sites submitted centre-specific protocols for postoperative pain management. Using the modified Delphi technique, recommendations were generated and put through iterative Delphi rounds to achieve consensus. RESULTS: 60 recommendations achieved consensus and are included in this guideline. They address guideline use, pain assessment, general considerations, preoperative considerations, intraoperative considerations, regional anaesthesia, opioids, opioid-sparing, non-opioid medications, non-pharmaceutical pain management, and discharge considerations. CONCLUSIONS: Postoperative pain among children following cardiac surgery is currently an area of significant practice variability despite a large body of literature and the presence of centre-specific protocols. Central to the recommendations included in this guideline is the concept that ideal pain management begins with preoperative counselling and continues through to patient discharge. Overall, the quality of evidence supporting recommendations is low. There is ongoing need for research in this area, particularly in paediatric populations.

Validity of the Patient Health Questionnaire-9 in neurologic populations.

BACKGROUND: Because of symptom overlap, there is uncertainty about the validity of depression rating scales in neurologic populations. The objectives of this study were to evaluate the validity of the Patient Health Questionnaire-9 (PHQ-9) for detecting Diagnostic and Statistical Manual-defined major depressive episodes in people with neurologic conditions. METHODS: Participants were recruited from outpatient clinics for multiple sclerosis, epilepsy, migraine, Parkinson disease, and stroke for this cross-sectional study. Participants were administered a questionnaire (this included the PHQ-9), chart review, and a follow-up telephone interview. The Structured Clinical Interview for Depression was used as the reference standard for psychiatric diagnoses. The performance of PHQ-9 was analyzed using sensitivity, specificity, diagnostic odds ratios (DORs), and receiver operator curve analysis. RESULTS: All neurologic subpopulations had a specificity greater than 78% and sensitivity greater than 79% at a cut-point of 10. Using a random-effects model, the I-squared value was 13.7%, and Tau2 was 0.05, showing homogeneity across the neurologic subpopulations. The pooled DOR was 25.3 (95% confidence interval [CI] 14.9-42.8). Meta-analytic analysis found that for sensitivity, the pooled estimate was 90% (95% CI 81-97), and for specificity, it was 85% (95% CI 79-90). CONCLUSIONS: Despite theoretical concerns about its validity, the PHQ-9 performed well at its standard cut-point of 10. Consistent with the literature, being able to use a validated, brief tool that is available publicly should improve case finding of depression in neurologic populations. When considering clinical practicality along with the findings of this analyzed, this study confirmed that the PHQ-9 is valid in a general outpatient neurologic population.

Predicting death by suicide following an emergency department visit for parasuicide with administrative health care system data and machine learning.

BACKGROUND: Suicide is a leading cause of death worldwide and results in a large number of person years of life lost. There is an opportunity to evaluate whether administrative health care system data and machine learning can quantify suicide risk in a clinical setting. METHODS: The objective was to compare the performance of prediction models that quantify the risk of death by suicide within 90 days of an ED visit for parasuicide with predictors available in administrative health care system data.The modeling dataset was assembled from 5 administrative health care data systems. The data systems contained nearly all of the physician visits, ambulatory care visits, inpatient hospitalizations, and community pharmacy dispenses, of nearly the entire 4.07 million persons in Alberta, Canada. 101 predictors were selected, and these were assembled for each of the 8 quarters (2 years) prior to the quarter of death, resulting in 808 predictors in total for each person. Prediction model performance was validated with 10-fold cross-validation. FINDINGS: The optimal gradient boosted trees prediction model achieved promising discrimination (AUC: 0.88) and calibration that could lead to clinical applications. The 5 most important predictors in the optimal gradient boosted trees model each came from a different administrative health care data system. INTERPRETATION: The combination of predictors from multiple administrative data systems and the combination of personal and ecologic predictors resulted in promising prediction performance. Further research is needed to develop prediction models optimized for implementation in clinical settings. FUNDING: There was no funding for this study.