Neuromotor Changes in Participants with a Concussion History can be Detected with a Custom Smartphone App

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between concussed and non-concussed participants. Data were collected at two university laboratories and two military sites. Participants included civilians and Service Members (N = 216) with and without a clinically diagnosed concussion. Kinematic and variability metrics were derived from a thigh angle time series while the participants completed a series of stepping-in-place tasks in three conditions: eyes open, eyes closed, and head shake. We observed that the standard deviation of the mean maximum angular velocity of the thigh was higher in the participants with a concussion history in the eyes closed and head shake conditions of the stepping-in-place task. Consistent with the optimal movement variability hypothesis, we showed that increased movement variability occurs in participants with a concussion history, for which our smartphone app and protocol were sensitive enough to capture

Use of a multi-level mixed methods approach to study the effectiveness of a primary care progressive return to activity protocol after acute mild traumatic brain injury/concussion in the military

The large number of U.S. service members diagnosed with concussion/mild traumatic brain injury each year underscores the necessity for clear and effective clinical guidance for managing concussion. Relevant research continues to emerge supporting a gradual return to pre-injury activity levels without aggravating symptoms; however, available guidance does not provide detailed standards for this return to activity process. To fill this gap, the Defense and Veterans Brain Injury Center released a recommendation for primary care providers detailing a step-wise return to unrestricted activity during the acute phase of concussion. This guidance was developed in collaboration with an interdisciplinary group of clinical, military, and academic subject matter experts using an evidence-based approach. Systematic evaluation of the guidance is critical to ensure positive patient outcomes, to discover barriers to implementation by providers, and to identify ways to improve the recommendation. Here we describe a multi-level, mixed-methods approach to evaluate the recommendation incorporating outcomes from both patients and providers. Procedures were developed to implement the study within complex but ecologically-valid settings at multiple military treatment facilities and operational medical units. Special consideration was given to anticipated challenges such as the frequent movement of military personnel, selection of appropriate design and measures, study implementation at multiple sites, and involvement of multiple service branches (Army, Navy, and Marine Corps). We conclude by emphasizing the need to consider contemporary approaches for evaluating the effectiveness of clinical guidance

Neuromotor Changes in Participants With a Concussion History Can Be Detected With a Custom Smartphone App

Neuromotor dysfunction after a concussion is common, but balance tests used to assess neuromotor dysfunction are typically subjective. Current objective balance tests are either cost- or space-prohibitive, or utilize a static balance protocol, which may mask neuromotor dysfunction due to the simplicity of the task. To address this gap, our team developed an Android-based smartphone app (portable and cost-effective) that uses the sensors in the device (objective) to record movement profiles during a stepping-in-place task (dynamic movement). The purpose of this study was to examine the extent to which our custom smartphone app and protocol could discriminate neuromotor behavior between concussed and non-concussed participants. Data were collected at two university laboratories and two military sites. Participants included civilians and Service Members (N = 216) with and without a clinically diagnosed concussion. Kinematic and variability metrics were derived from a thigh angle time series while the participants completed a series of stepping-in-place tasks in three conditions: eyes open, eyes closed, and head shake. We observed that the standard deviation of the mean maximum angular velocity of the thigh was higher in the participants with a concussion history in the eyes closed and head shake conditions of the stepping-in-place task. Consistent with the optimal movement variability hypothesis, we showed that increased movement variability occurs in participants with a concussion history, for which our smartphone app and protocol were sensitive enough to capture

Optimising intraperitoneal gentamicin dosing in peritoneal dialysis patients with peritonitis (GIPD) study

Background: Antibiotics are preferentially delivered via the peritoneal route to treat peritonitis, a major complication of peritoneal dialysis (PD), so that maximal concentrations are delivered at the site of infection. However, drugs administered intraperitoneally can be absorbed into the systemic circulation. Drugs excreted by the kidneys accumulate in PD patients, increasing the risk of toxicity. The aim of this study is to examine a model of gentamicin pharmacokinetics and to develop an intraperitoneal drug dosing regime that maximises bacterial killing and minimises toxicity

Best Practices for Progressive Return to Activity after Concussion: Lessons Learned from a Prospective Study of U.S. Military Service Members

Primary care providers can play a crucial role in the clinical management of concussion. However, many providers lack up-to-date information about best practices for rest and return to activity after these injuries. Most research on this topic has been conducted in athletes, and so less is known about how to assist patients with returning to activity in other settings and populations. This article provides a review of best practices for management of progressive return to activity after concussion, with an emphasis on "lessons learned" from the Defense and Veterans Brain Injury Center (DVBIC) Progressive Return to Activity (PRA) study, a multi-site longitudinal research project conducted to evaluate concussion management practices and the effectiveness of provider training on DVBIC clinical recommendations (CRs). Provider clinical practices and patient outcomes were examined at three U.S. military treatment facilities before and after providers completed a standardized training on DVBIC PRA CRs. In summary, research findings provide additional support that concussion recovery can be influenced by patients' activity levels after injury. Patients with concussion may experience poorer outcomes if they return to pre-injury levels of activity too rapidly, but they may also be at risk for prolonged symptoms if they fail to increase activity levels over time after an initial period of rest. Additionally, training primary care providers in return to activity guidelines can result in more effective patient education and better clinical outcomes. This knowledge can be used to inform best practices for progressive return to activity in both civilian and military settings

Data processing and model specification flow chart.

Abbreviations: HS = head shake, EC = Eyes-closed conditions. (A) Flow chart of the data processing. The two boxes in the bottom are the sample size submitted for the statistical analyses for all variables except CV Stride time. *1 n = the number of subjects, nt = the number of trials. *2 for CV stride time, n = 138 healthy and n = 61 concussed participants for the EC condition and n = 141 healthy and n = 60 concussed participants for the HS condition were submitted for analyses. (B) the model specification process: Fixed effects coefficients are B0, B1, B2, and B3, j = j-th group of i-th individual. u0i represents the random effect of the individual intercept, and e0i represents the residuals, where both are assumed to be normally distributed.</p

Smartphone app.

(A) Placement of the phone on the thigh and the illustration of stepping movement. (B) Representative time series of the thigh flexion angle in the sagittal plane during the stepping in place task. (C) Study design and dependent variables extracted from the smartphone app.</p

Raw data.

Dependent variable and demographic data for each participant. (XLSX)</p

Final model and statistical results of each movement variability dependent variable.

Final model and statistical results of each movement variability dependent variable.</p