Comparative Outcomes of Surgical and Transcatheter Aortic Valve Replacement: A Meta-Analysis and Parametric Extrapolation of Clinical Trials.

Introduction: We aimed to pool randomized clinical trials (RCTs) comparing surgical aortic valve replacement (SAVR) with transcatheter aortic valve replacement (TAVR) and extrapolate pooled time-to-event data to compare long-term outcomes.

Methods: An electronic database search was performed for RCTs comparing SAVR with TAVR. The most current longest follow-up data for each RCT were included.

Cubital Tunnel Syndrome: Does a Consensus Exist for Diagnosis?

Purpose: Cubital tunnel syndrome (CuTS) is the second most common compressive neuropathy of the upper extremity. We aimed to determine a consensus among experts using the Delphi method for clinical criteria that could be validated further for the diagnosis of CuTS.

Methods: The Delphi method was used for establishing a consensus among a group of expert panelists, comprising 12 hand and upper-extremity surgeons, who ranked the diagnostic clinical importance of 55 items related to CuTS on a scale from 1 (least important) to 10 (most important).

Winter sport musculoskeletal injuries: epidemiology and factors predicting hospital admission.

Introduction: Participation in winter sports such as skiing, snowboarding and snowmobiling is associated with risk of musculoskeletal injury. The purpose of our study was to describe and quantify emergency department encounters associated with these sports.

Methods: The National Electronic Injury Surveillance System (NEISS) was queried for skiing-, snowboarding- and snowmobiling-related injuries from 2009 to 2018.

Validating Coding for the Identification of Pediatric Treatment Resistant Epilepsy Patients.

The International Classification of Diseases (ICD) system includes sub codes to indicate that an individual with epilepsy is treatment resistant. These codes would be a valuable tool to identify individuals for quality improvement and population health, as well as for recruitment into clinical trials. However, the accuracy of these codes is unclear.

Evaluation of an Activity Tracker to Detect Seizures Using Machine Learning.

Currently, the tracking of seizures is highly subjective, dependent on qualitative information provided by the patient and family instead of quantifiable seizure data. Usage of a seizure detection device to potentially detect seizure events in a population of epilepsy patients has been previously done. Therefore, we chose the Fitbit Charge 2 smart watch to determine if it could detect seizure events in patients when compared to continuous electroencephalographic (EEG) monitoring for those admitted to an epilepsy monitoring unit.

Measuring the impact of epilepsy on families.

Objective: Caring for a child with illness or a child with disability impacts family in various ways. The ability to assess the impact of this care on families is one way to proactively provide the necessary support and resources for impacted families. Accordingly, the goal of the current study was to assess the impact of pediatric epilepsy on individual families in a comprehensive epilepsy clinic using a slightly modified version of the Impact on Families Scale (IFS).