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.

Odds of Hospitalization for COVID-19 After 3 vs 2 Doses of mRNA COVID-19 Vaccine by Time Since Booster Dose.

This study assesses the association between COVID-19 mRNA booster immunization compared with vaccination with the primary mRNA vaccination series alone and odds of hospitalization for COVID-19.

Decreased Risk of Coronavirus Disease 2019-Related Hospitalization Associated With the Omicron Variant of Severe Acute Respiratory Syndrome Coronavirus 2.

Among 134 223 patients with coronavirus disease 2019 (COVID-19), we assessed how risk of hospitalization changed at different intervals in the pandemic, controlling for prior COVID-19 immunity. In multivariable analysis, outpatients with COVID-19 during the Omicron-predominant time period had significantly lower odds of hospitalization compared to pre-Delta (adjusted odds ratio, 0.26 [95% confidence interval, .22-.32]).

Comparative vaccine effectiveness against severe COVID-19 over time in US hospital administrative data: a case-control study.

BACKGROUND: Research suggests the protection offered by COVID-19 vaccines might wane over time, prompting consideration of booster vaccinations. Data on which vaccines offer the most robust protection over time, and which patients are most vulnerable to attenuating protection, could help inform potential booster programmes. In this study, we used comprehensive hospitalisation data to estimate vaccine effectiveness over time. METHODS: In this case-control study, we used data from a large US health-care system to estimate vaccine effectiveness against severe SARS-CoV-2 infection and examined variation based on time since vaccination, vaccine type, and patients' demographic and clinical characteristics. We compared trends in attenuation of protection across vaccines and used a multivariable model to identify key factors associated with risk for severe breakthrough infection. Patients were considered to have severe COVID-19 if they were admitted to the hospital, had a final coded diagnosis of COVID-19 (according to International Classification of Diseases Tenth Revision code U07.1) or a positive nucleic acid amplification test for symptomatic SARS-CoV-2 during their hospitalisation, and were treated with remdesivir or dexamethasone during hospitalisation. FINDINGS: Between April 1, 2021, and Oct 26, 2021, we observed 9667 admissions for severe COVID-19 (ie, cases). Overall, 1293 (13·4%) of 9667 cases were fully vaccinated at the time of admission, compared with 22 308 (57·7%) of 38 668 controls, who were admitted to hospital for other reasons. The median time between vaccination and hospital admission among cases was 162 days (IQR 118-198). Overall vaccine effectiveness declined mostly over the course of the summer, from 94·5% (95% CI 91·4-96·5) in April, 2021 (pre-delta), to 84·0% (81·6-86·1) by October, 2021. Notably, vaccine effectiveness declined over time, from 94·0% (95% CI 92·8-95·0) at days 50-100 after vaccination to 80·4% (77·8-82·7) by days 200-250 after vaccination. After 250 days, vaccine effectiveness declines were even more notable. Among those who received the BNT162b2 (Pfizer-BioNTech) vaccine, vaccine effectiveness fell from an initial peak of 94·9% (93·2-96·2) to 74·1% (69·6-77·9) by days 200-250 after vaccination. Protection from the mRNA-1273 (Moderna) and Ad26.COV2 (Janssen) vaccines declined less over time, although the latter offered lower overall protection. Holding other factors constant, the risk of severe breakthrough infection was most strongly associated with age older than 80 years (adjusted odds ratio 1·76, 95% CI 1·43-2·15), vaccine type (Pfizer 1·39, 0·98-1·97; Janssen 14·53, 8·43-25·03; both relative to Moderna), time since vaccination (1·05, 1·03-1·07; per week after week 8 when protection peaks, technically), and comorbidities including organ transplantation (3·44, 95% CI 2·12-5·57), cancer (1·93, 1·60-2·33), and immunodeficiency (1·49, 1·13-1·96). INTERPRETATION: Vaccination remains highly effective against hospitalisation, but vaccine effectiveness declined after 200 days, particularly for older patients or those with specific comorbidities. Additional protection (eg, a booster vaccination) might be warranted for everyone, but especially for these populations. In addition to promoting general vaccine uptake, clinicians and policy makers should consider prioritising booster vaccinations in those most at risk of severe COVID-19. FUNDING: None.

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.

Legacy health effects among never smokers exposed to occupational secondhand smoke.

OBJECTIVES: Secondhand tobacco smoke (SHTS) is a tremendous public health hazard, leading to morbidity and premature mortality worldwide, with racial and ethnic minorities and those of lower socioeconomic status disproportionately affected. Flight attendants were historically exposed to high levels of SHTS in the aircraft cabin. The health effects of active smoking are known to persist for up to a lifetime, but the legacy effects of SHTS exposure have not been well characterized. DESIGN: We aimed to evaluate the legacy health effects of occupational SHTS exposure among never smoking workers using the resources of the Harvard Flight Attendant Health Study, a large study of cabin crew health. We evaluated associations between SHTS exposure and a range of diagnoses using multivariate logistic regression to calculate odds ratios (ORs) and 95% confidence intervals (CIs), employing a case-control sampling method and applying the bootstrap method to increase accuracy and precision of results. RESULTS: We found no evidence of positive associations between SHTS and any cancer, but observed associations between SHTS and cardiac outcomes, including myocardial infarction (OR = 140, 95% CI: 1·04, 3·27) and peripheral artery disease (OR = 1·27, 95% CI: 1·00, 1·97). We also found associations between SHTS exposure and repeated pneumonia (OR = 1·06, 95% CI: 1·02, 1·10). CONCLUSIONS: Our study reports associations between legacy SHTS exposure going back decades and severe cardiac and respiratory health outcomes. Given the high prevalence of ongoing and historical SHTS exposure, our findings, if confirmed, have important implications for smoking cessation efforts, health education, and clinical guidelines.

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.

Cancer prevalence among flight attendants compared to the general population.

BACKGROUND: Flight attendants are an understudied occupational group, despite undergoing a wide range of adverse job-related exposures, including to known carcinogens. In our study, we aimed to characterize the prevalence of cancer diagnoses among U.S. cabin crew relative to the general population. METHODS: In 2014-2015, we surveyed participants of the Harvard Flight Attendant Health Study. We compared the prevalence of their self-reported cancer diagnoses to a contemporaneous cohort in the National Health and Nutrition Examination Survey (NHANES 2013-2014) using age-weighted standardized prevalence ratios (SPRs). We also analyzed associations between job tenure and the prevalence of selected cancers, using logistic regression and adjusting for potential confounders. RESULTS: Compared to NHANES participants with a similar socioeconomic status (n = 2729), flight attendants (n = 5366) had a higher prevalence of every cancer we examined, especially breast cancer, melanoma, and non-melanoma skin cancer among females. SPR for these conditions were 1.51 (95% CI: 1.02, 2.24), 2.27 (95% CI: 1.27, 4.06), and 4.09 (95% CI: 2.70, 6.20), respectively. Job tenure was positively related to non-melanoma skin cancer among females, with borderline associations for melanoma and non-melanoma skin cancers among males. Consistent with previous studies, we observed associations between job tenure and breast cancer among women who had three or more children. CONCLUSIONS: We observed higher rates of specific cancers in flight attendants compared the general population, some of which were related to job tenure. Our results should be interpreted in light of self-reported health information and a cross-sectional study design. Future longitudinal studies should evaluate associations between specific exposures and cancers among cabin crew.

Estimating the health consequences of flight attendant work: comparing flight attendant health to the general population in a cross-sectional study.

BACKGROUND: Flight attendants are an understudied occupational group, despite undergoing a wide and unique range of adverse job-related exposures. In our study, we aimed to characterize the health profile of cabin crew relative to the U.S. general population. METHODS: In 2014-2015, we surveyed participants of the Harvard Flight Attendant Health Study. We compared the prevalence of their health conditions to a contemporaneous cohort in the National Health and Nutrition Examination Survey (NHANES 2013-2014) using age-weighted standardized prevalence ratios (SPRs). We also analyzed associations between job tenure and selected health outcomes, using logistic regression and adjusting for potential confounders. RESULTS: Compared to the NHANES population (n = 2729), flight attendants (n = 5366) had a higher prevalence of female reproductive cancers (SPR = 1.66, 95% CI: 1.18-2.33), cancers at all sites (SPR = 2.15, 95% CI: 1.73-2.67 among females), as well as sleep disorders, fatigue, and depression, with SPRs ranging between 1.98 and 5.57 depending on gender and the specific condition examined. In contrast, we observed a decreased prevalence of cardiac and respiratory outcomes among flight crew relative to NHANES. Health conditions that increased with longer job tenure were sleep disorders, anxiety/depression, alcohol abuse, any cancer, peripheral artery disease, sinusitis, foot surgery, infertility, and several perinatal outcomes. CONCLUSIONS: We observed higher rates of specific adverse health outcomes in U.S. flight attendants compared to the general population, as well as associations between longer tenure and health conditions, which should be interpreted in light of recall bias and a cross-sectional design. Future longitudinal studies should evaluate specific exposure-disease associations among flight crew.

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.