Characteristics and clinical outcomes of nirmatrelvir/ritonavir (Paxlovid) recipients in Canada, 2022: a descriptive cohort study.

Background: Nirmatrelvir/ritonavir (N/R) (Paxlovid) was introduced in Canada in January 2022. This was the first oral coronavirus disease 2019 (COVID-19) antiviral therapy that was deployed on a large scale in Canada. Since N/R was a new therapeutic option to reduce severe outcomes in high-risk populations, clinical and implementation questions were raised about its real-world utilization and impact.

A proportional incidence rate model for aggregated data to study the vaccine effectiveness against COVID-19 hospital and ICU admissions.

We develop a proportional incidence model that estimates vaccine effectiveness (VE) at the population level using conditional likelihood for aggregated data. Our model assumes that the population counts of clinical outcomes for an infectious disease arise from a superposition of Poisson processes with different vaccination statuses. The intensity function in the model is calculated as the product of per capita incidence rate and the at-risk population size, both of which are time-dependent.

A semi-parametric mixed model for short-term projection of daily COVID-19 incidence in Canada.

During a pandemic, data are very "noisy" with enormous amounts of local variation in daily counts, compared with any rapid changes in trend. Accurately characterizing the trends and reliable predictions on future trajectories are important for planning and public situation awareness. We describe a semi-parametric statistical model that is used for short-term predictions of daily counts of cases and deaths due to COVID-19 in Canada, which are routinely disseminated to the public by Public Health Agency of Canada.

LASSO type penalized spline regression for binary data.

Background: Generalized linear mixed models (GLMMs), typically used for analyzing correlated data, can also be used for smoothing by considering the knot coefficients from a regression spline as random effects. The resulting models are called semiparametric mixed models (SPMMs). Allowing the random knot coefficients to follow a normal distribution with mean zero and a constant variance is equivalent to using a penalized spline with a ridge regression type penalty.

The performance of phenomenological models in providing near-term Canadian case projections in the midst of the COVID-19 pandemic: March - April, 2020.

Background: The COVID-19 pandemic has had an unprecedented impact on citizens and health care systems globally. Valid near-term projections of cases are required to inform the escalation, maintenance and de-escalation of public health measures, and for short-term health care resource planning.

Methods: Near-term case and epidemic growth rate projections for Canada were estimated using three phenomenological models: the logistic model, Generalized Richard's model (GRM) and a modified Incidence Decay and Exponential Adjustment (m-IDEA) model.

Modeling perinatal mortality in twins via generalized additive mixed models: a comparison of estimation approaches.

Background: The analysis of twin data presents a unique challenge. Second-born twins on average weigh less than first-born twins and have an elevated risk of perinatal mortality. It is not clear whether the risk difference depends on birth order or their relative birth weight.

A Comparison of Visual Rating Scales and Simulated Virtual Reality Metrics in Neurosurgical Training: A Generalizability Theory Study.

Background: Adequate assessment and feedback remains a cornerstone of psychomotor skills acquisition, particularly within neurosurgery where the consequence of adverse operative events is significant. However, a critical appraisal of the reliability of visual rating scales in neurosurgery is lacking. Therefore, we sought to design a study to compare visual rating scales with simulated metrics in a neurosurgical virtual reality task.

Determinants of tuberculosis trends in six Indigenous populations of the USA, Canada, and Greenland from 1960 to 2014: a population-based study.

Background: Tuberculosis continues to disproportionately affect many Indigenous populations in the USA, Canada, and Greenland. We aimed to investigate whether population-based tuberculosis-specific interventions or changes in general health and socioeconomic indicators, or a combination of these factors, were associated with changes in tuberculosis incidence in these Indigenous populations.

Methods: For this population-based study we examined annual tuberculosis notification rates between 1960 and 2014 in six Indigenous populations of the USA, Canada, and Greenland (Inuit [Greenland], American Indian and Alaska Native [Alaska, USA], First Nations [Alberta, Canada], Cree of Eeyou Istchee [Quebec, Canada], Inuit of Nunavik [Quebec, Canada], and Inuit of Nunavut [Canada]), as well as the general population of Canada.

Bimanual Psychomotor Performance in Neurosurgical Resident Applicants Assessed Using NeuroTouch, a Virtual Reality Simulator.

Objective: Current selection methods for neurosurgical residents fail to include objective measurements of bimanual psychomotor performance. Advancements in computer-based simulation provide opportunities to assess cognitive and psychomotor skills in surgically naive populations during complex simulated neurosurgical tasks in risk-free environments. This pilot study was designed to answer 3 questions: (1) What are the differences in bimanual psychomotor performance among neurosurgical residency applicants using NeuroTouch? (2) Are there exceptionally skilled medical students in the applicant cohort? and (3) Is there an influence of previous surgical exposure on surgical performance?

Design: Participants were instructed to remove 3 simulated brain tumors with identical visual appearance, stiffness, and random bleeding points.

Impact of acute stress on psychomotor bimanual performance during a simulated tumor resection task.

OBJECTIVE Severe bleeding during neurosurgical operations can result in acute stress affecting the bimanual psychomotor performance of the operator, leading to surgical error and an adverse patient outcome. Objective methods to assess the influence of acute stress on neurosurgical bimanual psychomotor performance have not been developed. Virtual reality simulators, such as NeuroTouch, allow the testing of acute stress on psychomotor performance in risk-free environments.

Effect of Smoothing in Generalized Linear Mixed Models on the Estimation of Covariance Parameters for Longitudinal Data.

Besides being mainly used for analyzing clustered or longitudinal data, generalized linear mixed models can also be used for smoothing via restricting changes in the fit at the knots in regression splines. The resulting models are usually called semiparametric mixed models (SPMMs). We investigate the effect of smoothing using SPMMs on the correlation and variance parameter estimates for serially correlated longitudinal normal, Poisson and binary data.

Assessing bimanual performance in brain tumor resection with NeuroTouch, a virtual reality simulator.

Background: Validated procedures to objectively measure neurosurgical bimanual psychomotor skills are unavailable. The NeuroTouch simulator provides metrics to determine bimanual performance, but validation is essential before implementation of this platform into neurosurgical training, assessment, and curriculum development.

Objective: To develop, evaluate, and validate neurosurgical bimanual performance metrics for resection of simulated brain tumors with NeuroTouch.