Characteristics associated with response to subcutaneously administered anti-CGRP monoclonal antibody medications in a real-world community cohort of persons living with migraine: A retrospective clinical and genetic study.

OBJECTIVE: To evaluate response to anti-calcitonin gene-related peptide (CGRP) migraine preventives in a real-world community cohort of persons living with migraine and to identify clinical and genetic characteristics associated with efficacious response. BACKGROUND: Erenumab-aooeb, fremanezumab-vrfm, and galcanezumab-gnlm target CGRP or its receptor; however, many patients are non-responsive. METHODS: In this retrospective clinical and genetic study, we identified 1077 adult patients who satisfied the International Classification of Headache Disorders, 3rd edition, criteria for migraine without aura, migraine with aura, or chronic migraine and who were prescribed an anti-CGRP migraine preventive between May 2018 and May 2021. Screening of 558 patients identified 289 with data at baseline and first follow-up visits; data were available for 161 patients at a second follow-up visit. The primary outcome was migraine days per month (MDM). In 198 genotyped patients, we evaluated associations between responders (i.e., patients with ≥50% reduction in MDM at follow-up) and genes involved in CGRP signaling or pharmacological response, and genetic and polygenic risk scores. RESULTS: The median time to first follow-up was 4.4 (0.9-22) months after preventive start. At the second follow-up, 5.7 (0.9-13) months later, 145 patients had continued on the same preventive. Preventives had strong, persistent effects in reducing MDM in responders (follow-up 1: η2 = 0.26, follow-up 2: η2 = 0.22). At the first but not second follow-up: galcanezumab had a larger effect than erenumab, while no difference was seen at either follow-up between galcanezumab and fremanezumab or fremanezumab and erenumab. The decrease in MDM at follow-up was generally proportional to baseline MDM, larger in females, and increased with months on medication. At the first follow-up only, patients with prior hospitalization for migraine or who had not responded to more preventive regimens had a smaller decrease in MDM. Reasons for stopping or switching a preventive varied between medications and were often related to cost and insurance coverage. At both follow-ups, patient tolerance (1: 92.2% [262/284]; 2: 95.2% [141/145]) and continued use (1: 77.5% [224/289]; 2: 80.6% [116/145]) were high and similar across preventives. Response consistency (always non-responders: 31.7% [46/145]; always responders: 56.5% [82/145], and one-time only responders: 11.7% [17/145]) was also similar across preventives. Non-responder status had nominally significant associations with rs12615320-G in RAMP1 (odds ratio [95% confidence interval]: 4.7 [1.5, 14.7]), and rs4680-A in COMT (0.6[0.4, 0.9]). Non-responders had a lower mean genetic risk score than responders (1.0 vs. 1.1; t(df) = -1.75(174.84), p = 0.041), and the fraction of responders increased with genetic and polygenic risk score percentile. CONCLUSIONS: In this real-world setting, anti-CGRP preventives reduced MDM persistently and had similar and large effect sizes on MDM reduction; however, clinical and genetic factors influenced response.

Multifactorial assessment of Parkinson's disease course and outcomes using trajectory modeling in a multiethnic, multisite cohort - extension of the LONG-PD study.

Background: The severity, progression, and outcomes of motor and non-motor symptoms in Parkinson's disease (PD) are quite variable. Following PD cohorts holds promise for identifying predictors of disease severity and progression. Methods: PD patients (N = 871) were enrolled at five sites. Enrollment occurred within 5 years of initial motor symptom onset. Disease progression was assessed annually for 2-to-10 years after onset. Group-based trajectory modeling was used to identify groups differing in disease progression. Models were developed for UPDRS-III scores, UPDRS-III tremor and bradykinesia-rigidity subscores, Hoehn & Yahr (H&Y) stage, Mini-Mental Status Exam (MMSE) scores, and UPDRS-III, H&Y and MMSE scores considered together. Predictors of trajectory-group membership were modeled simultaneously with the trajectories. Kaplan-Meier survival analysis evaluated survival free of PD outcomes. Results: The best fitting models identified three groups. One showed a relatively benign, slowly progressing trajectory (Group 1), a second showed a moderate, intermediately progressing trajectory (Group 2), and a third showed a more severe, rapidly progressing trajectory (Group 3). Stable trajectory-group membership occurred relatively early in the disease course, 5 years after initial motor symptom. Predictors of intermediate and more severe trajectory-group membership varied across the single variable models and the multivariable model jointly considering UPDRS-III, H&Y and MMSE scores. In the multivariable model, membership in Group 2 (28.4% of patients), relative to Group 1 (50.5%), was associated with male sex, younger age-at-onset, fewer education-years, pesticide exposure, absence of reported head injury, and akinetic/rigid subtype at initial presentation. Membership in Group 3 (21.3%), relative to Group 1, was associated with older age-at-onset, fewer education-years, pesticide exposure, and the absence of a tremor-predominant subtype at initial presentation. Persistent freezing, persistent falls, and cognitive impairment occurred earliest and more frequently in Group 3, later and less frequently in Group 2, and latest and least frequently in Group 1. Furthermore, autonomic complications, dysphagia, and psychosis occurred more frequently in Groups 2 and 3 than in Group 1. Conclusion: Modeling disease course using multiple objective assessments over an extended follow-up duration identified groups that more accurately reflect differences in PD course, prognosis, and outcomes than assessing single parameters over shorter intervals.

Efficacy of supplemental MCT oil on seizure reduction of adult drug-resistant epilepsy - a single-center open-label pilot study.

OBJECTIVE: We set out to determine whether adding medium chain triglyceride (MCT) oil as a dietary supplement to standard diet in adult subjects with intractable epilepsy in a U.S. neurology clinical practice was associated with a reduction in number of seizures. We secondarily aimed to determine whether subjects experienced any side effects and whether there was a presence of urinary ketones while using MCT oil as a dietary supplement. METHODS: Adult patients with intractable epilepsy were recruited at standard of care clinical visits with their epileptologist. Once enrolled, subjects were instructed to supplement their diet with MCT oil as tolerated twice daily for three months (including a 1-2 week titration period, followed by a 1-2 week tapering off window) while keeping a seizure diary to record total number of seizures, presence of urinary ketones, and any side effects. RESULTS: Our data although limited by small sample size, shows that there is an estimated 42% reduction (p < 0.0001) in the rate of seizures. The MCT oil supplementation was well tolerated by most subjects except for minor GI side effects like nausea and loose stools. Most subjects developed ketones in their urine at some point during the trial. CONCLUSIONS: MCT oil supplementation reduced seizure frequency in study participants. The reported side effects included mild nausea, stomachache, loose stools. A placebo-controlled study will be more informative.

Leishmania Promastigotes Enhance Neutrophil Recruitment through the Production of CXCL8 by Endothelial Cells.

Endothelial cells represent one of the first cell types encountered by Leishmania promastigotes when inoculated into the skin of the human hosts by the bite of phlebotomine sand flies. However, little is known on their role in the early recruitment of phagocytic cells and in the establishment of the infection. Initially, neutrophils, rapidly recruited to the site of promastigotes deposition, phagocytize Leishmania promastigotes, which elude the killing mechanisms of the host cells, survive, and infect other phagocytic cells. Here, we show that Leishmania promastigotes co-incubated with HMEC-1, a microvascular endothelial cell line, exhibited significant morphological changes and loss of infectivity. Moreover, promastigotes of different Leishmania species stimulated the production of CXCL8 by HMEC-1 in a dose- and TLR4-dependent manner. Interestingly, we observed that the conditioned media from Leishmania-stimulated HMEC-1 cells attracted leukocytes, mostly neutrophils, after 2 h of incubation. After 24 h, a higher percentage of monocytes was detected in conditioned media of unstimulated HMEC-1 cells, whereas neutrophils still predominated in conditioned medium from Leishmania-stimulated cells. The same supernatants did not contain CCL5, a chemokine recruiting T cells and monocytes. On the contrary, inhibition of the production of CCL5 induced by TNF-α was seen. These data indicate that the interaction of Leishmania promastigotes with endothelial cells leads to the production of chemokines and the recruitment of neutrophils, which contribute to the establishment of Leishmania infection.

Standardizing Care of Neuro-oncology Patients Using a Customized Electronic Medical Record Toolkit.

OBJECTIVE: To develop and implement a customized toolkit within the electronic medical record (EMR) to standardize care of patients with brain tumors. PATIENTS AND METHODS: We built a customized structured clinical documentation support toolkit to capture standardized data at office visits. We detail the process by which this toolkit was conceptualized and developed. Toolkit development was a physician-led process to determine a work flow and necessary elements to support best practices as defined by the neuro-oncology clinical team. RESULTS: We have developed in our EMR system a customized work flow for clinical encounters with neuro-oncology patients. In addition to providing a road map for clinical care by our neuro-oncology team, the toolkit is designed to maximize discrete data capture. Several hundred fields of discrete data are captured through the toolkit in the context of our routine office visits. We describe the characteristics of patients seen at our clinic, the adoption of the toolkit, current initiatives supported by the toolkit, and future applications. CONCLUSION: The EMR can be effectively structured to standardize office visits and improve discrete data capture. This toolkit can be leveraged to support quality improvement and practice-based research initiatives at the point of care in a neuro-oncology practice.

Variable Effects of PD-Risk Associated SNPs and Variants in Parkinsonism-Associated Genes on Disease Phenotype in a Community-Based Cohort.

Genetic risk factors for Parkinson's disease (PD) risk and progression have been identified from genome-wide association studies (GWAS), as well as studies of familial forms of PD, implicating common variants at more than 90 loci and pathogenic or likely pathogenic variants at 16 loci. With the goal of understanding whether genetic variants at these PD-risk loci/genes differentially contribute to individual clinical phenotypic characteristics of PD, we used structured clinical documentation tools within the electronic medical record in an effort to provide a standardized and detailed clinical phenotypic characterization at the point of care in a cohort of 856 PD patients. We analyzed common SNPs identified in previous GWAS studies, as well as low-frequency and rare variants at parkinsonism-associated genes in the MDSgene database for their association with individual clinical characteristics and test scores at baseline assessment in our community-based PD patient cohort: age at onset, disease duration, Unified Parkinson's Disease Rating Scale I-VI, cognitive status, initial and baseline motor and non-motor symptoms, complications of levodopa therapy, comorbidities and family history of neurological disease with one or more than one affected family members. We find that in most cases an individual common PD-risk SNP identified in GWAS is associated with only a single clinical feature or test score, while gene-level tests assessing low-frequency and rare variants reveal genes associated in either a unique or partially overlapping manner with the different clinical features and test scores. Protein-protein interaction network analysis of the identified genes reveals that while some of these genes are members of already identified protein networks others are not. These findings indicate that genetic risk factors for PD differentially affect the phenotypic presentation and that genes associated with PD risk are also differentially associated with individual disease phenotypic characteristics at baseline. These findings raise the intriguing possibility that different SNPs/gene effects impact discrete phenotypic characteristics. Furthermore, they support the hypothesis that different gene and protein-protein interaction networks that underlie PD risk, the PD phenotype, and the neurodegenerative process leading to the disease phenotype, and point to the significance of the genetic background on disease phenotype.

Longitudinal Monitoring of Parkinson's Disease in Different Ethnic Cohorts: The DodoNA and LONG-PD Study.

Background: Different factors influence severity, progression, and outcomes in Parkinson's disease (PD). Lack of standardized clinical assessment limits comparison of outcomes and availability of well-characterized cohorts for collaborative studies. Methods: Structured clinical documentation support (SCDS) was developed within the DNA Predictions to Improve Neurological Health (DodoNA) project to standardize clinical assessment and identify molecular predictors of disease progression. The Longitudinal Clinical and Genetic Study of Parkinson's Disease (LONG-PD) was launched within the Genetic Epidemiology of Parkinson's disease (GEoPD) consortium using a Research Electronic Data Capture (REDCap) format mirroring the DodoNA SCDS. Demographics, education, exposures, age at onset (AAO), Unified Parkinson's Disease Rating Scale (UPDRS) parts I-VI or Movement Disorders Society (MDS)-UPDRS, Montreal Cognitive Assessment (MoCA)/Short Test of Mental Status (STMS)/Mini Mental State Examination (MMSE), Geriatric Depression Scale (GDS), Epworth Sleepiness Scale (ESS), dopaminergic therapy, family history, nursing home placement, death and blood samples were collected. DodoNA participants (396) with 6 years of follow-up and 346 LONG-PD participants with up to 3 years of follow-up were analyzed using group-based trajectory modeling (GBTM) focused on: AAO, education, family history, MMSE/MoCA/STMS, UPDRS II-II, UPDRS-III tremor and bradykinesia sub-scores, Hoehn and Yahr staging (H&Y) stage, disease subtype, dopaminergic therapy, and presence of autonomic symptoms. The analysis was performed with either cohort as the training/test set. Results: Patients are classified into slowly and rapidly progressing courses by AAO, MMSE score, H &Y stage, UPDRS-III tremor and bradykinesia sub-scores relatively early in the disease course. Late AAO and male sex assigned patients to the rapidly progressing group, whereas tremor to the slower progressing group. Classification is independent of which cohort serves as the training set. Frequencies of disease-causing variants in LRRK2 and GBA were 1.89 and 2.96%, respectively. Conclusions: Standardized clinical assessment provides accurate phenotypic characterization in pragmatic clinical settings. Trajectory analysis identified two different trajectories of disease progression and determinants of classification. Accurate phenotypic characterization is essential in interpreting genomic information that is generated within consortia, such as the GEoPD, formed to understand the genetic epidemiology of PD. Furthermore, the LONGPD study protocol has served as the prototype for collecting standardized phenotypic information at GEoPD sites. With genomic analysis, this will elucidate disease etiology and lead to targeted therapies that can improve disease outcomes.

Quality improvement and practice-based research in sleep medicine using structured clinical documentation in the electronic medical record.

BACKGROUND: We developed and implemented a structured clinical documentation support (SCDS) toolkit within the electronic medical record, to optimize patient care, facilitate documentation, and capture data at office visits in a sleep medicine/neurology clinic for patient care and research collaboration internally and with other centers. METHODS: To build our SCDS toolkit, physicians met frequently to develop content, define the cohort, select outcome measures, and delineate factors known to modify disease progression. We assigned tasks to the care team and mapped data elements to the progress note. Programmer analysts built and tested the SCDS toolkit, which included several score tests. Auto scored and interpreted tests included the Generalized Anxiety Disorder 7-item, Center for Epidemiological Studies Depression Scale, Epworth Sleepiness Scale, Pittsburgh Sleep Quality Index, Insomnia Severity Index, and the International Restless Legs Syndrome Study Group Rating Scale. The SCDS toolkits also provided clinical decision support (untreated anxiety or depression) and prompted enrollment of patients in a DNA biobank. RESULTS: The structured clinical documentation toolkit captures hundreds of fields of discrete data at each office visit. This data can be displayed in tables or graphical form. Best practice advisories within the toolkit alert physicians when a quality improvement opportunity exists. As of May 1, 2019, we have used the toolkit to evaluate 18,105 sleep patients at initial visit. We are also collecting longitudinal data on patients who return for annual visits using the standardized toolkits. We provide a description of our development process and screenshots of our toolkits. CONCLUSIONS: The electronic medical record can be structured to standardize Sleep Medicine office visits, capture data, and support multicenter quality improvement and practice-based research initiatives for sleep patients at the point of care.

Optimizing the electronic medical record to improve patient care and conduct quality improvement initiatives in a concussion specialty clinic.

Objective: To use the electronic medical record (EMR) to optimize patient care, facilitate documentation, and support quality improvement and practice-based research in a concussion (mild traumatic brain injury; mTBI) clinic.Methods: We built a customized structured clinical documentation support (SCDS) toolkit for patients in a concussion specialty clinic. The toolkit collected hundreds of fields of discrete, standardized data. Autoscored and interpreted score tests include the Generalized Anxiety Disorder 7-item scale, Center for Epidemiology Studies Depression scale, Insomnia Severity Index, and Glasgow Coma Scale. Additionally, quantitative score measures are related to immediate memory, concentration, and delayed recall. All of this data collection occurred in a standard appointment length.Results: To date, we evaluated 619 patients at an initial office visit after an mTBI. We provided a description of our toolkit development process, and a summary of the data electronically captured using the toolkit.Conclusions: The electronic medical record can be used to effectively structure and standardize care in a concussion clinic. The toolkit supports the delivery of care consistent with Best Practices, provides opportunities for point of care decision support, and writes comprehensive progress notes that can be communicated to other providers.

Building of EMR Tools to Support Quality and Research in a Memory Disorders Clinic.

The electronic medical record (EMR) presents an opportunity to standardize patient data collection based on quality guidelines and conduct practice-based research. We describe the development of a customized EMR "toolkit" that standardizes patient data collection with hundreds of discrete fields that supports Best Practices for treating patients with memory disorders. The toolkit also supports practice-based research. We describe the design and successful implementation of a customized EMR toolkit to support Best Practices in the care of patients with memory disorders. We discuss applications, including quality improvement projects and current research initiatives, using the toolkit. This toolkit is being shared with other departments of Neurology as part of the Neurology Practice-Based Research Network. Data collection is ongoing, including longitudinal follow-up. This toolkit will generate data that will allow for descriptive and hypothesis driven research as well-quality improvement among patients seen in a memory clinic.

Design and Implementation of Structured Clinical Documentation Support Tools for Treating Stroke Patients.

BACKGROUND AND PURPOSE: Standardized electronic medical record tools provide an opportunity to efficiently provide care that conforms to Best Practices and supports quality improvement and practice-based research initiatives. METHODS: We describe the development of a customized structured clinical documentation "toolkit" that standardizes patient data collection to conform to Best Practices for treating patients with stroke. The toolkit collects patients' demographic information, relevant score test measures, and captures information on disability, treatment, and outcomes. RESULTS: We describe here our creation and implementation of the toolkits and provide example screenshots. As of August 1, 2018, we have evaluated 2332 patients at an initial visit for a possible stroke. We provide basic descriptive data gathered from the use of the toolkits, demonstrating their utility in collecting patient data in a manner that supports both quality clinical care and research initiatives. CONCLUSIONS: We have developed an EMR toolkit to support Best Practices in the care of patients with stroke. We discuss quality improvement projects and current research initiatives using the toolkit. This toolkit is being shared with other Departments of Neurology as part of the Neurology Practice-Based Research Network.

Factors Affecting Cognition and Depression in Adult Patients with Epilepsy.

BACKGROUND AND PURPOSE: Epilepsy patients are more likely to experience depressive symptoms and cognitive impairment compared to individuals in the general population. As the reasons for this are not definitively known, we sought to determine what factors correlate most strongly with cognition and a screening test for depression in epilepsy patients. METHODS: Our study population included 379 adult patients diagnosed with epilepsy or seizure in our neurology clinic. We collected detailed demographic and clinical data during patient visits using structured clinical documentation support tools that we have built within our commercial electronic medical records system (Epic), including a depression score (Neurological Disorders Depression Inventory for Epilepsy, NDDIE) and cognition score test measures (specifically in this study, Mini-Mental State Examination [MMSE]). Medication, age, gender, body mass index, duration of epilepsy, seizure frequency, current number of anti-epileptic medications, years of education were assessed in relation to baseline score as well as change in score from initial visit to first annual follow-up. RESULTS: Of the analyzed factors, two statistically significant associations were found after correction for multiple testing. Male gender and lower anti-seizure medication count were associated with better mood, as assessed by NDDIE score, at initial visit. Specifically, male gender was associated with a 1.3 decrease in NDDIE and for each additional anti-seizure medication, there was an associated 1.2 increase in NDDIE. CONCLUSIONS: However, these factors were not associated with change in NDDIE score from initial to first annual follow-up visit. These findings, although interesting, are preliminary. Additionally, these findings were based on a homogenous (mainly Caucasian) clinic-based population and detailed information on previous medication use was lacking. Further work is needed to replicate these findings and to understand any mechanisms that may explain these associations.

Successful utilization of the EMR in a multiple sclerosis clinic to support quality improvement and research initiatives at the point of care.

BACKGROUND: Many physicians enter data into the electronic medical record (EMR) as unstructured free text and not as discrete data, making it challenging to use for quality improvement or research initiatives. OBJECTIVES: The objective of this research paper was to develop and implement a structured clinical documentation support (SCDS) toolkit within the EMR to facilitate quality initiatives and practice-based research in a multiple sclerosis (MS) practice. METHODS: We built customized EMR toolkits to capture standardized data at office visits. Content was determined through physician consensus on necessary elements to support best practices in treating patients with demyelinating disorders. We also developed CDS tools and best practice advisories within the toolkits to alert physicians when a quality improvement opportunity exists, including enrollment into our DNA biobanking study at the point of care. RESULTS: We have used the toolkit to evaluate 541 MS patients in our clinic and begun collecting longitudinal data on patients who return for annual visits. We provide a description and example screenshots of our toolkits, and a brief description of our cohort to date. CONCLUSIONS: The EMR can be effectively structured to standardize MS clinic office visits, capture data, and support quality improvement and practice-based research initiatives at the point of care.

Design and implementation of pragmatic clinical trials using the electronic medical record and an adaptive design.

OBJECTIVES: To demonstrate the feasibility of pragmatic clinical trials comparing the effectiveness of treatments using the electronic medical record (EMR) and an adaptive assignment design. METHODS: We have designed and are implementing pragmatic trials at the point-of-care using custom-designed structured clinical documentation support and clinical decision support tools within our physician's typical EMR workflow. We are applying a subgroup based adaptive design (SUBA) that enriches treatment assignments based on baseline characteristics and prior outcomes. SUBA uses information from a randomization phase (phase 1, equal randomization, 120 patients), to adaptively assign treatments to the remaining participants (at least 300 additional patients total) based on a Bayesian hierarchical model. Enrollment in phase 1 is underway in our neurology clinical practices for 2 separate trials using this method, for migraine and mild cognitive impairment (MCI). RESULTS: We are successfully collecting structured data, in the context of the providers' clinical workflow, necessary to conduct our trials. We are currently enrolling patients in 2 point-of-care trials of non-inferior treatments. As of March 1, 2018, we have enrolled 36% of eligible patients into our migraine study and 63% of eligible patients into our MCI study. Enrollment is ongoing and validation of outcomes has begun. DISCUSSION: This proof of concept article demonstrates the feasibility of conducting pragmatic trials using the EMR and an adaptive design. CONCLUSION: The demonstration of successful pragmatic clinical trials based on a customized EMR and adaptive design is an important next step in achieving personalized medicine and provides a framework for future studies of comparative effectiveness.

Use of an Electronic Medical Record to Track Adherence to the Mediterranean Diet in a US Neurology Clinical Practice.

OBJECTIVE: We describe our experience with routinely capturing and analyzing Mediterranean diet data via structured clinical documentation support tools built into the electronic medical record and describe adherence to the Mediterranean diet in patients at risk for either stroke or dementia in a US neurology clinical practice. PATIENTS AND METHODS: The Mediterranean diet is associated with a reduced risk of stroke and dementia. The Department of Neurology at NorthShore University HealthSystem routinely evaluates patients at initial and annual outpatient visits using structured clinical documentation support (SCDS) tools built into the electronic medical record (EMR). For patient evaluations in our Vascular Neurology and Brain Health subspecialty clinics, SCDS tools in the EMR include the validated 14-item questionnaire for Mediterranean diet adherence (PREvención con DIeta MEDiterránea [PREDIMED]) that autoscores, auto-interprets, writes to the progress note, and electronically captures data. Our study population includes patients seen at these clinics from July 1, 2015, through November 29, 2017. RESULTS: At their initial office visit, 25.5% (95/373) of Brain Health patients scored 10 or more points ("strongly adherent") on the PREDIMED (median, 8; range, 0-14) whereas 6.7% (55/829) of Vascular Neurology patients achieved a score of 10 or more points (median, 6; range, 0-12). By contrast, 34.7% (2586/7447) of individuals in the original PREDIMED cohort were strongly adherent to the Mediterranean diet. CONCLUSION: PREDIMED scores can be electronically captured to tailor nutrition interventions by assessing baseline adherence at the time of their initial neurology clinic visit. Patients in our Midwestern US clinics were weakly adherent to the Mediterranean diet. This suggests a major opportunity for nutrition intervention and education in US neurology clinical practices, toward preserving and improving brain health.

Structured Clinical Documentation to Improve Quality and Support Practice-Based Research in Headache.

OBJECTIVE: To use the electronic medical record (EMR) to optimize patient care, facilitate documentation, and support quality improvement and practice-based research, in a headache specialty clinic. BACKGROUND: Many physicians enter data into the EMR as unstructured free text and not as discrete data. This makes it challenging to use data for quality improvement or research initiatives. METHODS: We describe the process of building a customized structured clinical documentation support toolkit, specific for patients seen in a headache specialty clinic. The content was developed through frequent physician meetings to reach consensus on elements that define clinical Best Practices. Tasks were assigned to the care team and data mapped to the progress note. RESULTS: The toolkit collects hundreds of fields of discrete, standardized data. Auto scored and interpreted score tests include the Generalized Anxiety Disorder 7-item, Center for Epidemiology Studies Depression Scale, Migraine Disability Assessment questionnaire, Insomnia Sleep Index, and Migraine-Specific Quality of Life. We have developed Best Practice Advisories (BPA) and other clinical documentation support tools that alert physicians, when appropriate. As of April 1, 2018, we have used the toolkits at 4346 initial patient visits. We provide screenshots of our toolkits, details of data fields collected, and diagnoses of patients at the initial visit. CONCLUSIONS: The EMR can be used to effectively structure and standardize headache clinic visits for quality improvement and practice-based research. We are sharing our proprietary toolkit with other clinics as part of the Neurology Practice-Based Research Network. These tools are also facilitating clinical research enrollment and a pragmatic trial of comparative effectiveness at the point-of-care among migraine patients.

Investigating ioflupane I123 injection and single photon emission tomography as an imaging biomarker for long-term sequelae following mild traumatic brain injury.

OBJECTIVE: To determine whether there were differences in clinical outcomes for ioflupane I123 injection (DaTscan) and single photon emission tomography consistent with early Parkinson's disease (PD) among individuals with a history of mild traumatic brain injury (mTBI). METHODS: We performed a case-control study among patients presenting to the Emergency Room (ER) during 2006-2013 with mTBI (cases, n = 34) or without mTBI (controls, n = 33). We performed clinical and imaging measurements in cases and controls at least 1-year post-presentation to the ER (average three years four months). RESULTS: All DaTscans obtained were qualitatively normal. There were no qualitative DaTscan differences between cases and controls. There was, however, a significant increase in caudate asymmetry in controls versus cases (p = 0.02), but this finding was no longer significant after correction for multiple comparisons. There was a suggestion of a trend of poorer clinical score test measures among those with mTBI, although the overall mean score difference between cases and controls was not clinically significant. CONCLUSION: Our small study does not provide support for DaTscan changes suggestive of PD in the one to seven years following mTBI. A trend towards poorer clinical measures was seen but was not clinically relevant in our small sample. Further work in a large population is necessary to support these findings.

Structured clinical documentation in the electronic medical record to improve quality and to support practice-based research in epilepsy.

OBJECTIVE: Using the electronic medical record (EMR) to capture structured clinical data at the point of care would be a practical way to support quality improvement and practice-based research in epilepsy. METHODS: We describe our stepwise process for building structured clinical documentation support tools in the EMR that define best practices in epilepsy, and we describe how we incorporated these toolkits into our clinical workflow. RESULTS: These tools write notes and capture hundreds of fields of data including several score tests: Generalized Anxiety Disorder-7 items, Neurological Disorders Depression Inventory for Epilepsy, Epworth Sleepiness Scale, Quality of Life in Epilepsy-10 items, Montreal Cognitive Assessment/Short Test of Mental Status, and Medical Research Council Prognostic Index. The tools summarize brain imaging, blood laboratory, and electroencephalography results, and document neuromodulation treatments. The tools provide Best Practices Advisories and other clinical decision support when appropriate. The tools prompt enrollment in a DNA biobanking study. We have thus far enrolled 231 patients for initial visits and are starting our first annual follow-up visits and provide a brief description of our cohort. SIGNIFICANCE: We are sharing these EMR tools and captured data with other epilepsy clinics as part of a Neurology Practice Based Research Network, and are using the tools to conduct pragmatic trials using subgroup-based adaptive designs.

Low dose verapamil as an adjunct therapy for medically refractory epilepsy - An open label pilot study.

Previous studies using verapamil as an adjunct therapy to anti-seizure medications have used doses ranging from 120 to 240mg per day. However, despite showing promising results, there was an increased incidence of side effects. The aim of this study is to assess the efficacy and tolerability of low dose verapamil (20mg p.o. tid) as adjunct therapy to patient's anti-seizure medications irrespective of the type or etiology of the epilepsy. In an open-label pilot study we enrolled 20 adult patients with history of epilepsy who continued to have a minimum of 2 seizures a month despite being on or having tried maximum tolerated doses of 3 or more standard antiepileptic drugs under the supervision of an epileptologist. 10 of the 19 patients (53%) who continued in the study had >50% reduction in seizure frequency. 2 of the patients (10%) had <50% seizure reduction. The remaining 7 patients (37%) had no reduction in their seizures. There was no discontinuation due to adverse events. P-Glycoprotein is a prototypical drug transporter that has been strongly implicated in drug resistance in epilepsy. Verapamil at a relatively low dose was well tolerated compared to previous studies which used up to 240mg per day and seems to have contributed to a statistically significant improvement in seizure control in patients with medically refractory epilepsy, especially in patients with Lennox-Gastaut syndrome. A randomized double blind controlled study at this low dose with larger sample size may be more informative.