The American Registry for Migraine Research: Research Methods and Baseline Data for an Initial Patient Cohort.

BACKGROUND: The American Registry for Migraine Research (ARMR) is a multicenter, prospective, longitudinal patient registry, biorepository, and neuroimaging repository that collects clinical data, electronic health record (EHR) data, blood samples, and brain imaging data from individuals with migraine or other headache types. In this manuscript, we outline ARMR research methods and report baseline data describing an initial cohort of ARMR participants. METHODS: Adults with any International Classification of Headache Disorders (ICHD) diagnosis were prospectively enrolled from one of the 8 participating headache specialty centers. At baseline, ARMR participants complete web-based questionnaires, clinicians enter the participant's ICHD diagnoses, an optional blood specimen is collected, and neuroimaging data are uploaded to the ARMR neuroimaging repository. Participants maintain the ARMR daily headache diary longitudinally and follow-up questionnaires are completed by participants every 3 months. EHR data are integrated into the ARMR database from a subset of ARMR sites. Herein, we describe the ARMR methodology and report the summary data from ARMR participants who had, from February 2016 to May 2019, completed at least 1 baseline questionnaire from which data are reported in this manuscript. Descriptive statistics are used to provide an overview of patient's sociodemographics, headache diagnoses, headache characteristics, most bothersome symptoms other than headache, headache-related disability, comorbidities, and treatments. RESULTS: Data were available from 996 ARMR participants, enrolled from Mayo Clinic Arizona, Dartmouth-Hitchcock Medical Center, University of Utah, University of Colorado, Thomas Jefferson University, University of Texas Health Science Center at Houston, Georgetown University Medical Center, and DENT Neurological Institute. Among ARMR participants, 86.7% (n = 864) were female and the mean age at the time of enrollment was 48.6 years (±13.9; range 18-84). The most common provider-reported diagnosis was chronic migraine (n = 622), followed by migraine without aura (n = 327), migraine with aura (n = 196), and medication overuse headache (n = 65). Average headache frequency was 19.1 ± 9.2 days per month (n = 751), with 68% reporting at least 15 headache days per month. Sensitivity to light was the most frequent (n = 222) most bothersome symptom overall, other than headache, but when present, cognitive dysfunction was most frequently (n = 157) the most bothersome symptom other than headache. Average migraine disability assessment (MIDAS) score was 52 ± 49 (n = 760), (very severe headache-related disability); however, 17% of the ARMR population had MIDAS scores suggesting "no" or "mild" disability. The most common non-headache health issues were allergies (n = 364), back pain (n = 296), neck pain (n = 296), depression (n = 292), and anxiety (n = 278). Nearly 85% (n = 695) of patients were using preventive medications and 24.7% were using non-medication preventive therapy (eg, vitamins and neuromodulation). The most common preventive medication classes were neurotoxins, anticonvulsants, antidepressants, vitamins/supplements, and anticalcitonin gene-related peptide ligand or receptor-targeted monoclonal antibodies. Nearly 90% (n = 734) of ARMR participants was taking medications to treat migraine attacks, with the most common classes being triptans, non-steroidal anti-inflammatory drugs, antiemetics, acetaminophen, and combination analgesics. CONCLUSIONS: ARMR is a source of real-world patient data, biospecimens, and brain neuroimaging data that provides comprehensive insight into patients with migraine and other headache types being seen in headache specialty clinics in the United States. ARMR data will allow for longitudinal and advanced analytics that are expected to lead to a better characterization of patient heterogeneity, healthcare resource utilization, identification of endophenotypes, factors that predict treatment outcomes and clinical course, and ultimately advance the field toward precision headache medicine.

Smaller Hippocampal Volume in Posttraumatic Stress Disorder: A Multisite ENIGMA-PGC Study: Subcortical Volumetry Results From Posttraumatic Stress Disorder Consortia.

BACKGROUND: Many studies report smaller hippocampal and amygdala volumes in posttraumatic stress disorder (PTSD), but findings have not always been consistent. Here, we present the results of a large-scale neuroimaging consortium study on PTSD conducted by the Psychiatric Genomics Consortium (PGC)-Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) PTSD Working Group. METHODS: We analyzed neuroimaging and clinical data from 1868 subjects (794 PTSD patients) contributed by 16 cohorts, representing the largest neuroimaging study of PTSD to date. We assessed the volumes of eight subcortical structures (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen, thalamus, and lateral ventricle). We used a standardized image-analysis and quality-control pipeline established by the ENIGMA consortium. RESULTS: In a meta-analysis of all samples, we found significantly smaller hippocampi in subjects with current PTSD compared with trauma-exposed control subjects (Cohen's d = -0.17, p = .00054), and smaller amygdalae (d = -0.11, p = .025), although the amygdala finding did not survive a significance level that was Bonferroni corrected for multiple subcortical region comparisons (p < .0063). CONCLUSIONS: Our study is not subject to the biases of meta-analyses of published data, and it represents an important milestone in an ongoing collaborative effort to examine the neurobiological underpinnings of PTSD and the brain's response to trauma.

Benefits of integration of radiology services across a pediatric health care system with locations in multiple states.

BACKGROUND: Integration was implemented of previously independently practicing pediatric radiology services across a pediatric health care system with sites 1,000 miles apart. OBJECTIVE: The purpose of this manuscript is to describe the process utilized to integrate imaging services across our enterprise and to study the direct effects on report turnaround time and other parameters. MATERIALS AND METHODS: Parameters were evaluated both the year before integration as well as the 2 years following integration and compared for improvement. Parameters studied included report turnaround time, academic productivity (as measured by peer review publications per year), and degree of sub-subspecialization within pediatric radiology (as measured by the percentage of neuroimaging CT and MRI studies read by pediatric neuroradiologists). RESULTS: Comparing pre- to post-integration measures, the median report turnaround time decreased from 2.3 h to 1.1 h (52.1% improvement), the percentage of neuroimaging studies read by neuroimaging faculty increased from 15.0% to 86.6% (477% improvement), and peer review publication by calendar year increased from 3 to 30 (1,000% improvement). Other benefits included increased hours of in-house coverage and execution on multiple quality improvement efforts. CONCLUSION: A pediatric health care system successfully integrated radiology services across multiple previously non-integrated locations into one functional group. This integration was associated with a positive effect on multiple parameters.

Practice variation in neuroimaging to evaluate dizziness in the ED.

BACKGROUND: The appropriate role of neuroimaging to evaluate emergency department (ED) patients with dizziness is not established by guidelines or evidence. METHODS: We identified all adults with a triage complaint of dizziness who were evaluated at 20 EDs of a large Northern California integrated health care program in 2008. Using comprehensive medical records, we captured all head computed tomographies (CTs) or brain magnetic resonance images (MRIs) completed at presentation or within 2 days and all stroke diagnoses within 1 week. We assessed variation in neuroimaging use by site using a random-effects logistic model to account for differences in patient- (demographic and vascular risk factors) and site-level factors (volume, % patients with dizziness, and % patients with dizziness admitted) and linear regression to assess the relationship between neuroimaging rates and stroke diagnosis rates by site. RESULTS: Of 378 992 patients seen in 2008, 20 795 (5.5%) had at least one ED visit for dizziness. Overall, 5585 patients (26.9%) had a head CT and 652 (3.1%) had a brain MRI. Between 21.8% and 32.8% of ED patients with dizziness at each site had a head CT (P<.001). For brain MRI, the range was 0.8% to 6.2%-a nearly 8-fold variation (P<.001) that persisted after adjustment for patient- and site-level factors. Higher neuroimaging rates did not translate into higher stroke diagnoses rates, with 0.7% to 2.5% of patients with dizziness diagnosed with stroke by site. CONCLUSION: The use of neuroimaging for ED patients with dizziness varies substantially without an associated improvement in stroke diagnosis, which is identified only rarely.