BACKGROUND AND PURPOSE: Mild traumatic brain injury (MTBI) is a common public health concern with potential long-term consequences, yet its underlying pathophysiology remains poorly understood. Clinical heterogeneity of individuals having diverse extent and array of symptoms has impeded the identification of reliable imaging biomarkers. Traditional group-level analyses may obscure biologically meaningful subtypes. This study uses latent class analysis (LCA) to classify MTBI subjects into symptom-defined subgroups and examines corresponding WM microstructural alterations using advanced diffusion MRI. MATERIALS AND METHODS: Sixty-one patients with MTBI completed the Rivermead Post-Concussion Symptoms Questionnaire within 1 month of injury. LCA was used to identify symptom-based subgroups. Of these, 54 patients with MTBI underwent multishell diffusion MRI and were compared with 31 controls. WM changes were assessed across subgroups using ROI-based diffusion analyses. RESULTS: LCA identified 3 distinct MTBI subgroups: those with minimal to no symptoms (31.5%), the cognitively symptomatic (38.9%), and the more globally symptomatic (29.6%). The 3 groups were associated with different patterns of diffusion MRI differences compared with controls. The cognitively symptomatic subgroup showed predominantly central WM differences, the globally symptomatic subgroup exhibited more peripheral differences with right-hemisphere predominance and sparing the corpus callosum, marked by reduced fractional anisotropy and kurtosis and elevated diffusivities, and the less symptomatic subgroup demonstrated focal differences in the callosal genu, with increased fractional anisotropy and kurtosis and decreased diffusivity measures. CONCLUSIONS: MTBI comprises biologically distinct phenotypes with subgroup-specific WM signatures on diffusion MRI. Even individuals with minimal to no symptoms show WM differences compared with controls, underscoring the limitations of symptom reporting alone. Integrating symptom-based classification with advanced diffusion MRI may improve diagnostic precision to help risk stratification and provide insight into mechanisms of injury.

BACKGROUND AND PURPOSE: Because the corpus callosum connects the left and right hemispheres and a variety of WM bundles across the brain in complex ways, damage to the neighboring WM microstructure may specifically disrupt interhemispheric communication through the corpus callosum following mild traumatic brain injury. Here we use a mediation framework to investigate how callosal interhemispheric communication is affected by WM microstructure in mild traumatic brain injury. MATERIALS AND METHODS: Multishell diffusion MR imaging was performed on 23 patients with mild traumatic brain injury within 1?month of injury and 17 healthy controls, deriving 11 diffusion metrics, including DTI, diffusional kurtosis imaging, and compartment-specific standard model parameters. Interhemispheric processing speed was assessed using the interhemispheric speed of processing task (IHSPT) by measuring the latency between word presentation to the 2 hemivisual fields and oral word articulation. Mediation analysis was performed to assess the indirect effect of neighboring WM microstructures on the relationship between the corpus callosum and IHSPT performance. In addition, we conducted a univariate correlation analysis to investigate the direct association between callosal microstructures and IHSPT performance as well as a multivariate regression analysis to jointly evaluate both callosal and neighboring WM microstructures in association with IHSPT scores for each group. RESULTS: Several significant mediators in the relationships between callosal microstructure and IHSPT performance were found in healthy controls. However, patients with mild traumatic brain injury appeared to lose such normal associations when microstructural changes occurred compared with healthy controls. CONCLUSIONS: This study investigates the effects of neighboring WM microstructure on callosal interhemispheric communication in healthy controls and patients with mild traumatic brain injury, highlighting that neighboring noncallosal WM microstructures are involved in callosal interhemispheric communication and information transfer. Further longitudinal studies may provide insight into the temporal dynamics of interhemispheric recovery following mild traumatic brain injury.

BACKGROUND AND PURPOSE:Several recent works using resting-state fMRI suggest possible alterations of resting-state functional connectivity after mild traumatic brain injury. However, the literature is plagued by various analysis approaches and small study cohorts, resulting in an inconsistent array of reported findings. In this study, we aimed to investigate differences in whole-brain resting-state functional connectivity between adult patients with mild traumatic brain injury within 1 month of injury and healthy control subjects using several comprehensive resting-state functional connectivity measurement methods and analyses. MATERIALS AND METHODS:A total of 123 subjects (72 patients with mild traumatic brain injury and 51 healthy controls) were included. A standard fMRI preprocessing pipeline was used. ROI/seed-based analyses were conducted using 4 standard brain parcellation methods, and the independent component analysis method was applied to measure resting-state functional connectivity. The fractional amplitude of low-frequency fluctuations was also measured. Group comparisons were performed on all measurements with appropriate whole-brain multilevel statistical analysis and correction. RESULTS:There were no significant differences in age, sex, education, and hand preference between groups as well as no significant correlation between all measurements and these potential confounders. We found that each resting-state functional connectivity measurement revealed various regions or connections that were different between groups. However, after we corrected for multiple comparisons, the results showed no statistically significant differences between groups in terms of resting-state functional connectivity across methods and analyses. CONCLUSIONS:Although previous studies point to multiple regions and networks as possible mild traumatic brain injury biomarkers, this study shows that the effect of mild injury on brain resting-state functional connectivity has not survived after rigorous statistical correction. A further study using subject-level connectivity analyses may be necessary due to both subtle and variable effects of mild traumatic brain injury on brain functional connectivity across individuals.

Primary and secondary injury are both believed to play important roles in the pathogenesis of disease after mild traumatic brain injury (MTBI). Here we investigate the relationships between white matter microstructure and deep gray matter iron deposition after MTBI, which may shed light on primary WM injuries and potential secondary changes in brain iron. Our results show different patterns of correlation between deep gray matter iron content as measured by QSM and WM microstructure as measured by diffusion MRI in MTBI compared with normal controls.

OBJECTIVE:The aim of the study was to present: (1) physiatric care delivery amid the SARS-CoV-2 pandemic, (2) challenges, (3) data from the first cohort of post-COVID-19 inpatient rehabilitation facility patients, and (4) lessons learned by a research consortium of New York and New Jersey rehabilitation institutions.DESIGN:For this clinical descriptive retrospective study, data were extracted from post-COVID-19 patient records treated at a research consortium of New York and New Jersey rehabilitation inpatient rehabilitation facilities (May 1-June 30, 2020) to characterize admission criteria, physical space, precautions, bed numbers, staffing, employee wellness, leadership, and family communication. For comparison, data from the Uniform Data System and eRehabData databases were analyzed. The research consortium of New York and New Jersey rehabilitation members discussed experiences and lessons learned.RESULTS:The COVID-19 patients (N = 320) were treated during the study period. Most patients were male, average age of 61.9 yrs, and 40.9% were White. The average acute care length of stay before inpatient rehabilitation facility admission was 24.5 days; mean length of stay at inpatient rehabilitation facilities was 15.2 days. The rehabilitation research consortium of New York and New Jersey rehabilitation institutions reported a greater proportion of COVID-19 patients discharged to home compared with prepandemic data. Some institutions reported higher changes in functional scores during rehabilitation admission, compared with prepandemic data.CONCLUSIONS:The COVID-19 pandemic acutely affected patient care and overall institutional operations. The research consortium of New York and New Jersey rehabilitation institutions responded dynamically to bed expansions/contractions, staff deployment, and innovations that facilitated safe and effective patient care.

Objective The aim of the study was to present: (1) physiatric care delivery amid the SARS-CoV-2 pandemic, (2) challenges, (3) data from the first cohort of post–COVID-19 inpatient rehabilitation facility patients, and (4) lessons learned by a research consortium of New York and New Jersey rehabilitation institutions. Design For this clinical descriptive retrospective study, data were extracted from post–COVID-19 patient records treated at a research consortium of New York and New Jersey rehabilitation inpatient rehabilitation facilities (May 1–June 30, 2020) to characterize admission criteria, physical space, precautions, bed numbers, staffing, employee wellness, leadership, and family communication. For comparison, data from the Uniform Data System and eRehabData databases were analyzed. The research consortium of New York and New Jersey rehabilitation members discussed experiences and lessons learned. Results The COVID-19 patients (N = 320) were treated during the study period. Most patients were male, average age of 61.9 yrs, and 40.9% were White. The average acute care length of stay before inpatient rehabilitation facility admission was 24.5 days; mean length of stay at inpatient rehabilitation facilities was 15.2 days. The rehabilitation research consortium of New York and New Jersey rehabilitation institutions reported a greater proportion of COVID-19 patients discharged to home compared with prepandemic data. Some institutions reported higher changes in functional scores during rehabilitation admission, compared with prepandemic data. Conclusions The COVID-19 pandemic acutely affected patient care and overall institutional operations. The research consortium of New York and New Jersey rehabilitation institutions responded dynamically to bed expansions/contractions, staff deployment, and innovations that facilitated safe and effective patient care.

Eye-hand coordination (EHC) is critical for activities of daily living. EHC is dependent on the integrity of multiple brain systems and therefore is often disrupted by central nervous system pathology. Impairments can occur in ocular motor, manual motor, or ocular-manual motor control, that is, eye, hand, or EHC. Impaired EHC affects visually guided actions, such as reaching, grasping, wielding tools, and manipulating objects. This is true in acute pathologies, such as stroke and neurotrauma, as well as more chronic neurodegenerative conditions, such as Parkinson disease.1Cano S.J. Hobart J.C. Hart P.E. Korlipara L.V.P. Schapira A.H.V. Cooper J.M. International Cooperative Ataxia Rating Scale (ICARS): appropriate for studies of Friedreich's ataxia?.Mov Disord. 2005; 20: 1585-1591Crossref PubMed Scopus (55) Google Scholar, 2Kim B.R. Lim J.H. Lee S.A. et al.Usefulness of the Scale for the Assessment and Rating of Ataxia (SARA) in ataxic stroke patients.Ann Rehabil Med. 2011; 35: 772-780Crossref PubMed Google Scholar, 3Perenin M.T. Vighetto A. Optic ataxia: a specific disruption in visuomotor mechanisms. I. Different aspects of the deficit in reaching for objects.Brain. 1988; 111: 643-674Crossref PubMed Scopus (646) Google Scholar, 4Andersen R.A. Andersen K.N. Hwang E.J. Hauschild M. Optic ataxia: from Balint's syndrome to the parietal reach region.Neuron. 2014; 81: 967-983Abstract Full Text Full Text PDF PubMed Scopus (70) Google Scholar, 5Rodrigues M.R.M. Slimovitch M. Chilingaryan G. Levin M.F. Does the Finger-to-Nose Test measure upper limb coordination in chronic stroke?.J Neuroeng Rehabil. 2017; 14: 6Crossref PubMed Scopus (18) Google Scholar Despite its clinical relevance, EHC is not often systematically assessed. Using 3 simple measures (fig 1), health care providers may rapidly identify and characterize deficits in EHC while also assessing visual function and eye and limb movement. Figure 1 is a flow diagram for rapid EHC assessment. The patient performs 3 assessments: finger-to-nose, finger-to-knee, and finger chase. The patient performs finger-to-nose with a target in both central and peripheral vision; if deficits are noted, tests are repeated by providing proprioceptive ± audio feedback.General Examination Instructions for all assessments:•Sit in front of patient’s midline about 1 arm’s length away•Have patient sit comfortably. If necessary, support feet and trunk (head/body aligned in a forward/central position)•Patient performs 5 trials for each assessment, emphasizing both speed and accuracy.•Test both arms whenever possible, score each side separately; test the less affected arm first to ensure task comprehension.•Start the task with hand/arm resting on the knee of to be tested side and arm/shoulder both mildly flexed•One trial (cycle) starts when the hand moves from the knee and ends when back on the knee•Reach distance should be ∼50% of the patient’s arm span Finger-to-nose (FtN) has 2 defined steps. Step 1. The patient brings their finger to their nose. Step 2. The patient brings their finger from their nose to examiner finger and then returns their finger to their nose and subsequently back to their knee. This completes a cycle. The patient performs 5 cycles. Nose-to-finger (examiner) movements require visual guidance and test for optic ataxia but are also influenced by primary motor system deficits (eg, tremor, akinesia, chorea, clumsiness). Patients with optic ataxia are inaccurate when reaching to a visualized target. The FtN movement provide a relatively pure measure of motor dysfunction. Note, patients with cerebellar ataxia may overshoot the target when moving rapidly and display a characteristic tremor that worsens as the limb approaches the target; in this case, pay close attention to the finger chase, in which these deficits should be more apparent. Note discrepancies between the nose-to-finger or FtN segments of the task (inaccuracy and/or tremor) to inform your clinical decision making. Instructions: “Lift your hand from your knee and touch your finger to your nose. Then touch the tip of my finger. Then return to touching your nose. Finally, return your hand to your knee. Try to do all of this as fast and accurately as possible for each of the target positions that I indicate. You can move your eyes and follow your hand with your eyes while keeping your head still.” Examiner instructions (fig 3): •Use your index finger as a target for patient’s index finger.•Place your finger at 5 locations in random order. Outcome measures: •Time to completion: record total time to completion (from time hand leaves the nose to the time it returns) using a stopwatch.○Fatigue: note any prolongation of completion time over the trials•Reach accuracy: quantify degree of error (0-5, see below) and type (over-/undershoot)○0=No error○1=Mild error (<5cm)○2=Moderate error (<15cm)○3=Severe error (>15cm)○4=Unable to perform 5 pointing movements•Tremor: record the presence and degree of any tremor noted during movement (0-3, see below for scale):0=Normal1=Slight2=Moderate3=Severe •Types of tremors (optional): fine, coarse, high-amplitude, high-frequency, resting, intention•Miscellaneous: record the presence of any other neurologic abnormalities incidentally noted (impairment of eye movements, impairments of somatosensory or somatomotor function, etc). If the patient has trouble performing the FtN tasks, repeat the trial but manually guide the patient’s hand to the target. Patients with optic ataxia may improve with proprioceptive information about target location. In contrast, as with misreaching due to motor deficits, supplemental proprioceptive information will not help. Instructions: “Lift your hand from your knee and touch your finger to your nose, then touch the tip of my finger. Then touch your nose. Finally, return your hand to your knee. If you miss any of the targets, I will help you by moving your hand to touch my finger and have you repeat the task.” Examiner instructions: •Follow A1 instructions.•If the patient misses your finger, guide them to the target and repeat the trial.•Document the outcome measures. Reaching for targets in the peripheral visual engages a wider network of neural systems and may reveal deficits not observed in reaching to foveated targets. Hemispatial neglect, subtle visual field deficits or impairment in translating between eye and hand-based spatial coordinate systems, and impairment in working memory may all worsen performance in reaching to targets in peripheral vision (when they are not looking at target) Examiner instructions: Same as A1, except ask the patient to look at your nose at all the times. Instructions: “Lift your hand from your knee and touch your finger to your nose. You are then going to touch the tip of my finger, then touch your nose, and ultimately return your hand to your knee as fast and accurately as possible. Look at my nose at all times and do not move your eyes and head.” Outcome measures: Same as A1. ∗If the patient is noted to have difficulty in performing B1, perform B2: Examiner instructions: If the patient misses your finger, guide them to the target and ask to them to repeat the trial. Instructions: “You are going to touch the tip of my finger first, then touch your nose, and then return your hand to your knee as fast and accurately as possible. Look at my nose the whole time and don’t look to my finger. If you missed my finger, I will help you by moving your hand to touch my finger and have you repeat the task.” Outcome measures: Same as B1 (see fig 2). Significance: To distinguish between visuomotor and motor deficits contrast performance on the finger-to-knee, which entails reaching to a target defined by body schema and proprioception, and FtN, which requires reaching to a visualized target (especially, nose-to-finger (examiner). Instructions: “Start by lifting your hand from your knee and touch your finger to your nose. Then touch your knee. Repeat this for a total of 5 times, as fast and as accurately as possible.” “Now close your eyes and repeat the same task, repeat it for a total of 5 times, as fast and as accurately as possible.” Examiner instructions: •Ask the patient to perform 5 trials with eyes open and then ask them to perform the same with eyes closed. Outcome measures: Same as part I Significance: Patients with cerebellar ataxia overshoot with the affected extremity when rapidly and continuously following a moving target. Cerebellar tremors (an uncontrolled oscillation of the limb perpendicular to the axis of the movement that becomes worse as the limb approaches the target) may become exaggerated when reaching to moving targets. Instructions: “Using your index finger, follow my finger as I move it, as fast and precisely as possible.” Examiner instructions: •Use your index finger as a target and ask the patient to follow/chase your finger as you move it.•Make 5 sudden and fast arm movements in different random locations.•Movements should be about 30 cm (∼12 in) and a frequency of 1 movement every 2 s. Outcome measures: Same as part I. The 3 tests described herein, when combined, provide a systematic and reproducible assessment of eye-hand coordination. While any abnormal finding from the battery will assist in triggering appropriate referrals to experienced neurologists and/or physiatrists, granular details generated, following the characterization of the impairment, will help downstream clinicians, such as physical and occupational therapists, tailor rehabilitative therapeutics, stage prognosis, and, ultimately, stimulate novel directions in care approaches for eye-hand dyscoordination.

The authors investigated how working memory deficits relate to detectable WM microstructural injuries to discover robust biomarkers that allow early identification of patients with mild traumatic brain injury at the highest risk of working memory impairment. Multi-shell diffusion MR imaging was performed on a 3T scanner with 5 b-values. Diffusion metrics of fractional anisotropy, diffusivity and kurtosis (mean, radial, axial), and WM tract integrity were calculated. Auditory-verbal working memory was assessed using the Wechsler Adult Intelligence Scale. ROI analysis found a significant positive correlation between axial kurtosis and Digit Span Backward in mild traumatic brain injury mainly present in the right superior longitudinal fasciculus, which was not observed in healthy controls. BACKGROUND AND PURPOSE: Working memory impairment is one of the most troubling and persistent symptoms after mild traumatic brain injury (MTBI). Here we investigate how working memory deficits relate to detectable WM microstructural injuries to discover robust biomarkers that allow early identification of patients with MTBI at the highest risk of working memory impairment. MATERIALS AND METHODS: Multi-shell diffusion MR imaging was performed on a 3T scanner with 5 b-values. Diffusion metrics of fractional anisotropy, diffusivity and kurtosis (mean, radial, axial), and WM tract integrity were calculated. Auditory-verbal working memory was assessed using the Wechsler Adult Intelligence Scale, 4th ed, subtests: 1) Digit Span including Forward, Backward, and Sequencing; and 2) Letter-Number Sequencing. We studied 19 patients with MTBI within 4 weeks of injury and 20 healthy controls. Tract-Based Spatial Statistics and ROI analyses were performed to reveal possible correlations between diffusion metrics and working memory performance, with age and sex as covariates. RESULTS: ROI analysis found a significant positive correlation between axial kurtosis and Digit Span Backward in MTBI (Pearson r = 0.69, corrected P = .04), mainly present in the right superior longitudinal fasciculus, which was not observed in healthy controls. Patients with MTBI also appeared to lose the normal associations typically seen in fractional anisotropy and axonal water fraction with Letter-Number Sequencing. Tract-Based Spatial Statistics results also support our findings. CONCLUSIONS: Differences between patients with MTBI and healthy controls with regard to the relationship between microstructure measures and working memory performance may relate to known axonal perturbations occurring after injury.

We seek to elucidate the underlying pathophysiology of injury sustained after mild traumatic brain injury (mTBI) using multi-shell diffusion magnetic resonance imaging, deriving compartment-specific white matter tract integrity (WMTI) metrics. WMTI allows a more biophysical interpretation of white matter (WM) changes by describing microstructural characteristics in both intra- and extra-axonal environments. Thirty-two patients with mTBI within 30 days of injury and 21 age- and sex-matched controls were imaged on a 3 Tesla magnetic resonance scanner. Multi-shell diffusion acquisition was performed with five b-values (250-2500 sec/mm2) along 6-60 diffusion encoding directions. Tract-based spatial statistics (TBSS) was used with family-wise error (FWE) correction for multiple comparisons. TBSS results demonstrated focally lower intra-axonal diffusivity (Daxon) in mTBI patients in the splenium of the corpus callosum (sCC; p < 0.05, FWE-corrected). The area under the curve value for Daxon was 0.76 with a low sensitivity of 46.9% but 100% specificity. These results indicate that Daxon may be a useful imaging biomarker highly specific for mTBI-related WM injury. The observed decrease in Daxon suggests restriction of the diffusion along the axons occurring shortly after injury.

April 23, 2018April 10, 2018Free AccessThe New MULES: A Sideline-Friendly Test of Rapid Picture Naming for Concussion (P2.169)Omar Akhand, Matthew Galetta, Lisena Hasanaj, Lucy Cobbs, Nikki Webb, Julia Brandt, Prin Amorapanth, … Show All … , John-Ross Rizzo, Liliana Serrano, Rachel Nolan, Janet Rucker, Arlene Silverio, Barry Jordan, Steven Galetta, and Laura Balcer Show FewerAuthors Info & AffiliationsApril 10, 2018 issue90 (15_supplement)https://doi.org/10.1212/WNL.90.15_supplement.P2.169 Letters to the Editor

Objective: The Mobile Universal Lexicon Evaluation System (MULES) is a test of rapid picture naming that is under investigation for concussion. MULES captures an extensive visual network, including pathways for eye movements, color perception, memory and object recognition. The purpose of this study was to introduce the MULES to visual assessment of patients with MS, and to examine associations with other tests of afferent and efferent visual function. Methods: We administered the MULES in addition to binocular measures of low-contrast letter acuity (LCLA), high-contrast visual acuity (VA) and the King-Devick (K-D) test of rapid number naming in an MS cohort and in a group of disease-free controls. Results: Among 24 patients with MS (median age 36 years, range 20-72, 64% female) and 22 disease-free controls (median age 34 years, range 19-59, 57% female), MULES test times were greater (worse) among the patients (60.0 vs. 40.0 s). Accounting for age, MS vs. control status was a predictor of MULES test times (P =.01, logistic regression). Faster testing times were noted among patients with MS who had greater (better) performance on binocular LCLA at 2.5% contrast (P <.001, linear regression, accounting for age), binocular high contrast VA (P <.001), and K-D testing (P <.001). Both groups demonstrated approximately 10-s improvements in MULES test times between trials 1 and 2 (P <.0001, paired t-tests). Conclusion: The MULES test, a complex task of rapid picture naming involves an extensive visual network that captures eye movements, color perception and the characterization of objects. Color recognition, a key component of this novel assessment, is early in object processing and requires area V4 and the inferior temporal projections. MULES scores reflect performance of LCLA, a widely-used measure of visual function in MS clinical trials. These results provide evidence that the MULES test can add efficient visual screening to the assessment of patients with MS.

Objective: Measures of rapid automatized naming (RAN) have been used for over 50 years to capture vision based aspects of cognition. The Mobile Universal Lexicon Evaluation System (MULES) is a test of rapid picture naming under investigation for detection of concussion and other neurological disorders. MULES was designed as a series of 54 grouped color photographs (fruits, random objects, animals) that integrates saccades, color perception and contextual object identification. Recent changes to the MULES test have been made to improve ease of use on the athletic sidelines. Originally an 11 x 17-inch single-sided paper, the test has been reduced to a laminated 8.5 x 11-inch double-sided version. We identified performance changes associated with transition to the new, MULES, now sized for the sidelines, and examined MULES on the sideline for sports-related concussion. Methods: We administered the new laminated MULES to a group of adult office volunteers as well as youth and collegiate athletes during pre-season baseline testing. Athletes with concussion underwent sideline testing after injury. Time scores for the new laminated MULES were compared to those for the larger version (big MULES). Results: Among 501 athletes and office volunteers (age 16 7 years, range 6-59, 29% female), average test times at baseline were 44.4 14.4 s for the new laminated MULES (n = 196) and 46.5 16.3 s for big MULES (n = 248). Both versions were completed by 57 participants, with excellent agreement (p < 0.001, linear regression, accounting for age). Age was a predictor of test times for both MULES versions, with longer times noted for younger participants (p < 0.001). Among 6 athletes with concussion thus far during the fall sports season (median age 15 years, range 11-21) all showed worsening of MULES scores from pre-season baseline (median 4.0 s, range 2.1-16.4). Conclusion: The MULES test has been converted to an 11 x 8.5-inch laminated version, with excellent agreement between versions across age groups. Feasibly administered at pre-season and in an office setting, the MULES test shows preliminary evidence of capacity to identify athletes with sports-related concussion.

Objective: To determine if native English speakers (NES) perform differently compared to non-native English speakers (NNES) on a sideline-focused rapid number naming task. A secondary aim was to characterize objective differences in eye movement behaviour between cohorts. Background: The King-Devick (KD) test is a rapid number-naming task in which numbers are read from left-to-right. This performance measure adds vision-based assessment to sideline concussion testing. Reading strategies differ by language. Concussion may also impact language and attention. Both factors may affect test performance. Methods: Twenty-seven healthy NNES and healthy NES performed a computerized KD test under high-resolution video-oculography. NNES also performed a Bilingual Dominance Scale (BDS) questionnaire to weight linguistic preferences (i.e., reliance on non-English language(s)). Results: Inter-saccadic intervals were significantly longer in NNES (346.3 +/- 78.3 ms vs. 286.1 +/- 49.7 ms, p = 0.001), as were KD test times (54.4 +/- 15.1 s vs. 43.8 +/- 8.6 s, p = 0.002). Higher BDS scores, reflecting higher native language dominance, were associated with longer inter-saccadic intervals in NNES. Conclusion: These findings have direct implications for the assessment of athlete performance on vision-based and other verbal sideline concussion tests; these results are particularly important given the international scope of sport. Pre-season baseline scores are essential to evaluation in the event of concussion, and performance of sideline tests in the athlete's native language should be considered to optimize both baseline and post-injury test accuracy.

Kratom is an unscheduled opioid receptor agonist that comes in the form of dietary supplements currently being abused by chronic pain patients on prescription opioids. Active alkaloids isolated from kratom such as mitragynine and 7-hydroxymitragynine are thought to act on mu- and delta-opioid receptors as well as alpha-2 adrenergic and 5-HT2A receptors. Animal studies suggest that kratom may be more potent than morphine. Consequently, kratom consumption produces analgesic and euphoric feelings among users. In particular, some chronic pain patients on opioids take kratom to counteract the effects of opioid withdrawal. Although the Food and Drug Administration has banned its use as a dietary supplement, kratom continues to be widely available and easily accessible on the Internet at much less expensive rates than some opioid replacement therapies like buprenorphine. There are no federal regulations monitoring the sale and distribution of this drug, yet kratom has been associated with severe signs and symptoms such as hallucinations, delusions, depressions, myalgias, chills, nausea/vomiting, respiratory hepatoxicity, seizures, coma, and death. A search of the pain literature shows past research has not described the use and potential deleterious effects of this drug. Many pain physicians are not familiar with kratom and as providers who take care of high-risk chronic pain patients using prescribed opioids, knowledge of current unregulated opioid receptor agonists with abuse potential is of paramount importance. The goal of this article is to introduce kratom to pain specialists and to spur a conversation on how pain physicians may take the lead to help curb the opioid abuse and overdose epidemic. Further studies may be required to help better understand the clinical and long-term effects of kratom use among chronic pain patients.Key words: Opioid receptor agonist, Kratom, Mitragynine, opioid overdose, chronic pain, substance abuse.