A blood biomarker test for brain amyloid impacts the clinical evaluation of cognitive impairment.

OBJECTIVE: The objective of this study was to examine clinicians' patient selection and result interpretation of a clinically validated mass spectrometry test measuring amyloid beta and ApoE blood biomarkers combined with patient age (PrecivityAD® blood test) in symptomatic patients evaluated for Alzheimer's disease (AD) or other causes of cognitive decline. METHODS: The Quality Improvement and Clinical Utility PrecivityAD Clinician Survey (QUIP I, ClinicalTrials.gov Identifier: NCT05477056) was a prospective, single-arm cohort study among 366 patients evaluated by neurologists and other cognitive specialists. Participants underwent blood biomarker testing and received an amyloid probability score (APS), indicating the likelihood of a positive result on an amyloid positron emission tomography (PET) scan. The primary study outcomes were appropriateness of patient selection as well as result interpretation associated with PrecivityAD blood testing. RESULTS: A 95% (347/366) concordance rate was noted between clinicians' patient selection and the test's intended use criteria. In the final analysis including these 347 patients (median age 75 years, 56% women), prespecified test result categories incorporated 133 (38%) low APS, 162 (47%) high APS, and 52 (15%) intermediate APS patients. Clinicians' pretest and posttest AD diagnosis probability changed from 58% to 23% in low APS patients and 71% to 89% in high APS patients (p < 0.0001). Anti-AD drug therapy decreased by 46% in low APS patients (p < 0.0001) and increased by 57% in high APS patients (p < 0.0001). INTERPRETATION: These findings demonstrate the clinical utility of the PrecivityAD blood test in clinical care and may have added relevance as new AD therapies are introduced.

Evaluation of a Computable Phenotype for Successful Cognitive Aging.

Objective: To establish, apply, and evaluate a computable phenotype for the recruitment of individuals with successful cognitive aging. Participants and Methods: Interviews with 10 aging experts identified electronic health record (EHR)-available variables representing successful aging among individuals aged 85 years and older. On the basis of the identified variables, we developed a rule-based computable phenotype algorithm composed of 17 eligibility criteria. Starting September 1, 2019, we applied the computable phenotype algorithm to all living persons aged 85 years and older at the University of Florida Health, which identified 24,024 individuals. This sample was comprised of 13,841 (58%) women, 13,906 (58%) Whites, and 16,557 (69%) non-Hispanics. A priori permission to be contacted for research had been obtained for 11,898 individuals, of whom 470 responded to study announcements and 333 consented to evaluation. Then, we contacted those who consented to evaluate whether their cognitive and functional status clinically met out successful cognitive aging criteria of a modified Telephone Interview for Cognitive Status score of more than 27 and Geriatric Depression Scale of less than 6. The study was completed on December 31, 2022. Results: Of the 45% of living persons aged 85 years and older included in the University of Florida Health EHR database identified by the computable phenotype as successfully aged, approximately 4% of these responded to study announcements and 333 consented, of which 218 (65%) met successful cognitive aging criteria through direct evaluation. Conclusion: The study evaluated a computable phenotype algorithm for the recruitment of individuals for a successful aging study using large-scale EHRs. Our study provides proof of concept of using big data and informatics as aids for the recruitment of individuals for prospective cohort studies.

Mediterranean diet adherence, gut microbiota, and Alzheimer's or Parkinson's disease risk: A systematic review.

Alzheimer's disease (AD) and Parkinson's disease (PD) are the two most prevalent neurodegenerative diseases, both without prevention or cure. The Mediterranean diet (MeDi) may be neuroprotective by modulating gut microbiota. We aimed to assess the effects of adherence to MeDi on the gut microbiota in relation to AD or PD risk. A search from inception to November 2020 was conducted in PubMed, CINAHL, EMBASE, Web of Science, Global Health, Biological Abstracts, and Grey Literature Report databases. Two searches were conducted: 1) (MeDi or Microbiota) and (PD or AD) and 2) MeDi and microbiota. Inclusion criteria for papers were specified prior to review. Of 4672 studies identified, 64 were eligible for inclusion. These studies were divided into five groups: MeDi and AD risk (n = 4), MeDi and PD risk (n = 2), MeDi and microbial composition or metabolomics (n = 21), AD and microbial composition or metabolomics (n = 7), and PD and microbial composition or metabolomics (n = 30). Adherence to the MeDi was associated with a lower risk of AD and PD development. Eight genera and two species of bacteria had an inverse relationship with MeDi and AD, and one family, eight genera and three species of bacteria had an inverse relationship with MeDi and PD. More studies are needed to investigate if MeDi, gut microbiota, and neurodegeneration are causally related.

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.

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.

Using EHRs to advance epilepsy care.

The improved use of Electronic Health Record (EHR) Systems provides an opportunity to improve the overall efficiency and quality of care of patients with epilepsy. Tools and strategies that may be incorporated into the use of EHRs include utilizing patient generated data, clinical decision support systems and natural language processing systems. Standardization of data from EHR systems may lead to improvement in clinical research through the creation of data collections and multi-center collaborations. Challenges to collaborative use of EHR Systems across centers include costs and the diversity of EHR systems.

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.

Long-term risk of depressive and anxiety symptoms after early bilateral oophorectomy.

OBJECTIVE: We studied the long-term risk of depressive and anxiety symptoms in women who underwent bilateral oophorectomy before menopause. DESIGN: We conducted a cohort study among all women residing in Olmsted County, MN, who underwent bilateral oophorectomy before the onset of menopause for a noncancer indication from 1950 through 1987. Each member of the bilateral oophorectomy cohort was matched by age with a referent woman from the same population who had not undergone an oophorectomy. In total, we studied 666 women with bilateral oophorectomy and 673 referent women. Women were followed for a median of 24 years, and depressive and anxiety symptoms were assessed using a structured questionnaire via a direct or proxy telephone interview performed from 2001 through 2006. RESULTS: Women who underwent bilateral oophorectomy before the onset of menopause had an increased risk of depressive symptoms diagnosed by a physician (hazard ratio = 1.54, 95% CI: 1.04-2.26, adjusted for age, education, and type of interview) and of anxiety symptoms (adjusted hazard ratio = 2.29, 95% CI: 1.33-3.95) compared with referent women. The findings remained consistent after excluding depressive or anxiety symptoms that first occurred within 10 years after oophorectomy. The associations were greater with younger age at oophorectomy but did not vary across indications for the oophorectomy. In addition, treatment with estrogen to age 50 years in women who underwent bilateral oophorectomy at younger ages did not modify the risk. CONCLUSIONS: Bilateral oophorectomy performed before the onset of menopause is associated with an increased long-term risk of depressive and anxiety symptoms.

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.

Evaluation of the interaction between LRRK2 and PARK16 loci in determining risk of Parkinson's disease: analysis of a large multicenter study.

A recent study MacLeod et al. has shown that an interaction between variants at the LRRK2 and PARK16 loci influences risk of development of Parkinson's disease (PD). Our study examines the proposed interaction between LRRK2 and PARK16 variants in modifying PD risk using a large multicenter series of PD patients (7715) and controls (8261) from sites participating in the Genetic Epidemiology of Parkinson's Disease Consortium. Our data does not support a strong direct interaction between LRRK2 and PARK16 variants; however, given the role of retromer and lysosomal pathways in PD, further studies are warranted.

Genome-wide gene-environment interaction analysis of pesticide exposure and risk of Parkinson's disease.

INTRODUCTION: Genetic factors and environmental exposures, including pesticides, contribute to the risk of Parkinson's disease (PD). There have been few studies of gene and pesticide exposure interactions in PD, and all of the prior studies used a candidate gene approach. METHODS: We performed the first genome-wide gene-environment interaction analysis of pesticide exposure and risk of Parkinson's disease. Analyses were performed using data on >700,000 single nucleotide polymorphisms (SNPs) in 364 discordant sibling pairs. In addition to testing for SNP-pesticide interaction effects, we also performed exploratory analyses of gene-pesticide interactions at the gene level. RESULTS: None of the gene-environment interaction results were significant after genome-wide correction for multiple testing (α = 1.5E-07 for SNP-level tests; α = 2.1E-06 for gene-level tests). Top results in the SNP-level tests provided suggestive evidence (P < 5.0E-06) that the effect of pesticide exposure on PD risk may be modified by SNPs in the ERCC6L2 gene (P = 2.4E-06), which was also supported by suggestive evidence in the gene-level analysis (P = 4.7E-05). None of the candidate genes assessed in prior studies of gene-pesticide interactions reached statistical support in this genome-wide screen. CONCLUSION: Although no significant interactions were identified, several of the genes with suggestive evidence of gene-environment interaction effects have biological plausibility for PD risk. Further investigation of the role of those genes in PD risk, particularly in the context of pesticide exposure, in large and carefully recruited samples is warranted.

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.

MAPT haplotype H1G is associated with increased risk of dementia with Lewy bodies.

INTRODUCTION: The MAPT H1 haplotype has been associated with several neurodegenerative diseases. We were interested in exploring the role of MAPT haplotypic variation in risk of dementia with Lewy bodies (DLB). METHOD: We genotyped six MAPT haplotype tagging SNPs and screened 431 clinical DLB cases, 347 pathologically defined high-likelihood DLB cases, and 1049 controls. RESULT: We performed haplotypic association tests and detected an association with the protective H2 haplotype in our combined series (odds ratio [OR] = 0.75). We fine-mapped the locus and identified a relatively rare haplotype, H1G, that is associated with an increased risk of DLB (OR = 3.30, P = .0017). This association was replicated in our pathologically defined series (OR = 2.26, P = .035). DISCUSSION: These results support a role for H1 and specifically H1G in susceptibility to DLB. However, the exact functional variant at the locus is still unknown, and additional studies are warranted to fully explain genetic risk of DLB at the MAPT locus.