Physical impairment during and between migraine attacks: A daily diary study of patients with chronic migraine.

OBJECTIVE: While a substantial body of research describes the disabling impacts of migraine attacks, less research has described the impacts of migraine on physical functioning between migraine attacks. The objective of this study is to describe physical impairment during and between migraine attacks as a dimension of burden experienced by people living with chronic migraine. METHODS: The physical impairment domain of the Migraine Physical Function Impact Diary was recorded in headache diaries from the Medication Overuse Treatment Strategy trial. Days with moderate to severe headache were used to approximate migraine attacks. Factor analysis and regression analysis were used to describe associations between migraine and physical impairment. RESULTS: 77,662 headache diary entries from 720 participants were analyzed, including 25,414 days with moderate to severe headache, 19,149 days with mild headache, and 33,099 days with no headache. Mean physical impairment score was 41.5 (SD = 26.1) on days with moderate to severe headache, 12.8 (SD = 15.0) on days with mild headache, and 5.2 (SD = 13.1) on days with no headache. Physical impairment on days with mild headache and days with no headache was significantly associated with days since last moderate to severe headache, physical impairment with last moderate to severe headache, mild headache (compared to no headache), depression, hypersensitivities and cranial autonomic symptoms. CONCLUSIONS: Physical impairment occurs on migraine and non-migraine days. Study participants with frequent headaches, symptoms of depression, hypersensitivities and cranial autonomic symptoms experience physical impairment at a higher rate on days with no headache and days with mild headache.Clinical Trial Registration: ClinicalTrials.gov (NCT02764320).

Flexible modeling of headache frequency fluctuations in migraine with hidden Markov models.

OBJECTIVE: To explore hidden Markov models (HMMs) as an approach for defining clinically meaningful headache-frequency-based groups in migraine. BACKGROUND: Monthly headache frequency in patients with migraine is known to vary over time. This variation has not been completely characterized and is not well accounted for in the classification of individuals as having chronic or episodic migraine, a diagnosis with potentially significant impacts on the individual. This study investigated variation in reported headache frequency in a migraine population and proposed a model for classifying individuals by frequency while accounting for natural variation. METHODS: The American Registry for Migraine Research (ARMR) was a longitudinal multisite study of United States adults with migraine. Study participants completed quarterly questionnaires and daily headache diaries. A series of HMMs were fit to monthly headache frequency data calculated from the diary data of ARMR. RESULTS: Changes in monthly headache frequency tended to be small, with 47% of transitions resulting in a change of 0 or 1 day. A substantial portion (24%) of months reflected daily headache with individuals ever reporting daily headache likely to consistently report daily headache. An HMM with four states with mean monthly headache frequency emissions of 3.52 (95% Prediction Interval [PI] 0-8), 10.10 (95% PI 4-17), 20.29 (95% PI 12-28), and constant 28 days/month had the best fit of the models tested. Of sequential month-to-month headache frequency transitions, 12% were across the 15-headache days chronic migraine cutoff. Under the HMM, 38.7% of those transitions involved a change in the HMM state, and the remaining 61.3% of the time, a change in chronic migraine classification was not accompanied by a change in the HMM state. CONCLUSION: A divide between the second and third states of this model aligns most strongly with the current episodic/chronic distinction, although there is a meaningful overlap between the states that supports the need for flexibility. An HMM has appealing properties for classifying individuals according to their headache frequency while accounting for natural variation in frequency. This empirically derived model may provide an informative classification approach that is more stable than the use of a single cutoff value.

A history of abuse is associated with more severe migraine- and pain-related disability: Results from the American Registry for Migraine Research.

BACKGROUND: Prior studies have established an association between a history of abuse and more severe migraine presentation. OBJECTIVES: This cross-sectional, observational study of a clinic-based migraine population used validated measures to elucidate migraine-specific and migraine-related burdens among patients with a history of abuse. METHODS: Patients with migraine (n = 866) from the American Registry for Migraine Research self-reported if they had a history of emotional, physical, and/or sexual abuse and completed questionnaires assessing migraine-related burden: Migraine Disability Assessment, Subjective Cognitive Impairment Scale for Migraine Attacks, Work Productivity and Activity Impairment, Patient-Reported Outcomes Measurement Information System Pain Interference, Patient Health Questionnaire-2, and Generalized Anxiety Disorder-7. Migraine-related burden in patients with versus without a history of abuse was compared. Subsequently, a mediation analysis evaluated the impact of depression and anxiety symptoms in the relationship between abuse history and migraine burden. RESULTS: A history of abuse was reported by 36.5% (n = 316/866) of participants. After controlling for patient age, sex, years lived with headache, and headache frequency, a history of abuse was significantly associated with more severe migraine-related disability. The combined burden of depression and anxiety symptoms mediated the relationship. CONCLUSION: A history of abuse is associated with greater migraine-related disability. Future studies should determine if identification and management of the psychological and physical sequelae of abuse reduce migraine burden.

A large language model-based generative natural language processing framework fine-tuned on clinical notes accurately extracts headache frequency from electronic health records.

OBJECTIVE: To develop a natural language processing (NLP) algorithm that can accurately extract headache frequency from free-text clinical notes. BACKGROUND: Headache frequency, defined as the number of days with any headache in a month (or 4 weeks), remains a key parameter in the evaluation of treatment response to migraine preventive medications. However, due to the variations and inconsistencies in documentation by clinicians, significant challenges exist to accurately extract headache frequency from the electronic health record (EHR) by traditional NLP algorithms. METHODS: This was a retrospective cross-sectional study with patients identified from two tertiary headache referral centers, Mayo Clinic Arizona and Mayo Clinic Rochester. All neurology consultation notes written by 15 specialized clinicians (11 headache specialists and 4 nurse practitioners) between 2012 and 2022 were extracted and 1915 notes were used for model fine-tuning (90%) and testing (10%). We employed four different NLP frameworks: (1) ClinicalBERT (Bidirectional Encoder Representations from Transformers) regression model, (2) Generative Pre-Trained Transformer-2 (GPT-2) Question Answering (QA) model zero-shot, (3) GPT-2 QA model few-shot training fine-tuned on clinical notes, and (4) GPT-2 generative model few-shot training fine-tuned on clinical notes to generate the answer by considering the context of included text. RESULTS: The mean (standard deviation) headache frequency of our training and testing datasets were 13.4 (10.9) and 14.4 (11.2), respectively. The GPT-2 generative model was the best-performing model with an accuracy of 0.92 (0.91, 0.93, 95% confidence interval [CI]) and R2 score of 0.89 (0.87, 0.90, 95% CI), and all GPT-2-based models outperformed the ClinicalBERT model in terms of exact matching accuracy. Although the ClinicalBERT regression model had the lowest accuracy of 0.27 (0.26, 0.28), it demonstrated a high R2 score of 0.88 (0.85, 0.89), suggesting the ClinicalBERT model can reasonably predict the headache frequency within a range of ≤ ± 3 days, and the R2 score was higher than the GPT-2 QA zero-shot model or GPT-2 QA model few-shot training fine-tuned model. CONCLUSION: We developed a robust information extraction model based on a state-of-the-art large language model, a GPT-2 generative model that can extract headache frequency from EHR free-text clinical notes with high accuracy and R2 score. It overcame several challenges related to different ways clinicians document headache frequency that were not easily achieved by traditional NLP models. We also showed that GPT-2-based frameworks outperformed ClinicalBERT in terms of accuracy in extracting headache frequency from clinical notes. To facilitate research in the field, we released the GPT-2 generative model and inference code with open-source license of community use in GitHub. Additional fine-tuning of the algorithm might be required when applied to different health-care systems for various clinical use cases.

Application of Artificial Intelligence in the Headache Field.

PURPOSE OF REVIEW: Headache disorders are highly prevalent worldwide. Rapidly advancing capabilities in artificial intelligence (AI) have expanded headache-related research with the potential to solve unmet needs in the headache field. We provide an overview of AI in headache research in this article. RECENT FINDINGS: We briefly introduce machine learning models and commonly used evaluation metrics. We then review studies that have utilized AI in the field to advance diagnostic accuracy and classification, predict treatment responses, gather insights from various data sources, and forecast migraine attacks. Furthermore, given the emergence of ChatGPT, a type of large language model (LLM), and the popularity it has gained, we also discuss how LLMs could be used to advance the field. Finally, we discuss the potential pitfalls, bias, and future directions of employing AI in headache medicine. Many recent studies on headache medicine incorporated machine learning, generative AI and LLMs. A comprehensive understanding of potential pitfalls and biases is crucial to using these novel techniques with minimum harm. When used appropriately, AI has the potential to revolutionize headache medicine.

Brain structural and functional abnormalities associated with acute post-traumatic headache: iron deposition and functional connectivity.

BACKGROUND: The purpose of this study was to interrogate brain iron accumulation in participants with acute post-traumatic headache (PTH) due to mild traumatic brain injury (mTBI), and to determine if functional connectivity is affected in areas with iron accumulation. We aimed to examine the correlations between iron accumulation and headache frequency, post-concussion symptom severity, number of mTBIs, and time since most recent TBI. METHODS: Sixty participants with acute PTH and 60 age-matched healthy controls (HC) underwent 3T magnetic resonance imaging including quantitative T2* maps and resting-state functional connectivity imaging. Between group T2* differences were determined using T-tests (p < 0.005, cluster size threshold of 90 voxels). For regions with T2* differences, two analyses were conducted. First, the correlations with clinical variables including headache frequency, number of lifetime mTBIs, time since most recent mTBI, and Sport Concussion Assessment Tool (SCAT) symptom severity scale scores were investigated using linear regression. Second, the functional connectivity of these regions with the rest of the brain was examined (significance of p < 0.05 with family wise error correction for multiple comparisons). RESULTS: The acute PTH group consisted of 60 participants (22 male, 38 female) with average age of 42 ± 14 years. The HC group consisted of 60 age-matched controls (17 male, 43 female, average age of 42 ± 13). PTH participants had lower T2* values compared to HC in the left posterior cingulate and the bilateral cuneus. Stronger functional connectivity was observed between bilateral cuneus and right cerebellar areas in PTH compared to HC. Within the PTH group, linear regression showed negative associations of T2* in the left posterior cingulate with SCAT symptom severity score (p = 0.05) and T2* in the left cuneus with headache frequency (p = 0.04). CONCLUSIONS: Iron accumulation in posterior cingulate and cuneus was observed in those with acute PTH relative to HC; stronger functional connectivity was detected between the bilateral cuneus and the right cerebellum. The correlations of decreased T2* (suggesting higher iron content) with headache frequency and post mTBI symptom severity suggest that the iron accumulation that results from mTBI might reflect the severity of underlying mTBI pathophysiology and associate with post-mTBI symptom severity including PTH.

Longitudinal differences in iron deposition in periaqueductal gray matter and anterior cingulate cortex are associated with response to erenumab in migraine.

OBJECTIVES: The objective of this longitudinal study was to determine whether brain iron accumulation, measured using magnetic resonance imaging magnetic transverse relaxation rates (T2*), is associated with response to erenumab for the treatment of migraine. METHODS: Participants (n = 28) with migraine, diagnosed using international classification of headache disorders 3rd edition criteria, were eligible if they had six to 25 migraine days during a four-week headache diary run-in phase. Participants received two treatments with 140 mg erenumab, one immediately following the pre-treatment run-in phase and a second treatment four weeks later. T2* data were collected immediately following the pre-treatment phase, and at two weeks and eight weeks following the first erenumab treatment. Patients were classified as erenumab responders if their migraine-day frequency at five-to-eight weeks post-initial treatment was reduced by at least 50% compared to the pre-treatment run-in phase. A longitudinal Sandwich estimator approach was used to compare longitudinal group differences (responders vs non-responders) in T2* values, associated with iron accumulation. Group visit effects were calculated with a significance threshold of p = 0.005 and cluster forming threshold of 250 voxels. T2* values of 19 healthy controls were used for a reference. The average of each significant region was compared between groups and visits with Bonferroni corrections for multiple comparisons with significance defined as p < 0.05. RESULTS: Pre- and post-treatment longitudinal imaging data were available from 28 participants with migraine for a total of 79 quantitative T2* images. Average subject age was 42 ± 13 years (25 female, three male). Of the 28 subjects studied, 53.6% were erenumab responders. Comparing longitudinal T2* between erenumab responders vs non-responders yielded two comparisons which survived the significance threshold of p < 0.05 after correction for multiple comparisons: the difference at eight weeks between the erenumab-responders and non-responders in the periaqueductal gray (mean ± standard error; responders 43 ± 1 ms vs non-responders 32.5 ± 1 ms, p = 0.002) and the anterior cingulate cortex (mean ± standard error; responders 50 ± 1 ms vs non-responders 40 ± 1 ms, p = 0.01). CONCLUSIONS: Erenumab response is associated with higher T2* in the periaqueductal gray and anterior cingulate cortex, regions that participate in pain processing and modulation. T2* differences between erenumab responders vs non-responders, a measure of brain iron accumulation, are seen at eight weeks post-treatment. Less iron accumulation in the periaqueductal gray and anterior cingulate cortex might play a role in the therapeutic mechanisms of migraine reduction associated with erenumab.

Questionnaire and structural imaging data accurately predict headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury.

BACKGROUND: Our prior work demonstrated that questionnaires assessing psychosocial symptoms have utility for predicting improvement in patients with acute post-traumatic headache following mild traumatic brain injury. In this cohort study, we aimed to determine whether prediction accuracy can be refined by adding structural magnetic resonance imaging (MRI) brain measures to the model. METHODS: Adults with acute post-traumatic headache (enrolled 0-59 days post-mild traumatic brain injury) underwent T1-weighted brain MRI and completed three questionnaires (Sports Concussion Assessment Tool, Pain Catastrophizing Scale, and the Trait Anxiety Inventory Scale). Individuals with post-traumatic headache completed an electronic headache diary allowing for determination of headache improvement at three- and at six-month follow-up. Questionnaire and MRI measures were used to train prediction models of headache improvement and headache trajectory. RESULTS: Forty-three patients with post-traumatic headache (mean age = 43.0, SD = 12.4; 27 females/16 males) and 61 healthy controls were enrolled (mean age = 39.1, SD = 12.8; 39 females/22 males). The best model achieved cross-validation Area Under the Curve of 0.801 and 0.805 for predicting headache improvement at three and at six months. The top contributing MRI features for the prediction included curvature and thickness of superior, middle, and inferior temporal, fusiform, inferior parietal, and lateral occipital regions. Patients with post-traumatic headache who did not improve by three months had less thickness and higher curvature measures and notably greater baseline differences in brain structure vs. healthy controls (thickness: p < 0.001, curvature: p = 0.012) than those who had headache improvement. CONCLUSIONS: A model including clinical questionnaire data and measures of brain structure accurately predicted headache improvement in patients with post-traumatic headache and achieved improvement compared to a model developed using questionnaire data alone.

Thalamic subfield iron accumulation after acute mild traumatic brain injury as a marker of future post-traumatic headache intensity.

OBJECTIVE: To explore alterations in thalamic subfield volume and iron accumulation in individuals with post-traumatic headache (PTH) relative to healthy controls. BACKGROUND: The thalamus plays a pivotal role in the pathomechanism of pain and headache, yet the role of the thalamus in PTH attributed to mild traumatic brain injury (mTBI) remains unclear. METHODS: A total of 107 participants underwent multimodal T1-weighted and T2* brain magnetic resonance imaging. Using a clinic-based observational study, thalamic subfield volume and thalamic iron accumulation were explored in 52 individuals with acute PTH (mean age = 41.3; standard deviation [SD] = 13.5), imaged on average 24 days post mTBI, and compared to 55 healthy controls (mean age = 38.3; SD = 11.7) without history of mTBI or migraine. Symptoms of mTBI and headache characteristics were assessed at baseline (0-59 days post mTBI) (n = 52) and 3 months later (n = 46) using the Symptom Evaluation of the Sports Concussion Assessment Tool (SCAT-5) and a detailed headache history questionnaire. RESULTS: Relative to controls, individuals with acute PTH had significantly less volume in the lateral geniculate nucleus (LGN) (mean volume: PTH = 254.1, SD = 43.4 vs. controls = 278.2, SD = 39.8; p = 0.003) as well as more iron deposition in the left LGN (PTH: T2* signal = 38.6, SD = 6.5 vs. controls: T2* signal = 45.3, SD = 2.3; p = 0.048). Correlations in individuals with PTH revealed a positive relationship between left LGN T2* iron deposition and SCAT-5 symptom severity score at baseline (r = -0.29, p = 0.019) and maximum headache intensity at the 3-month follow-up (r = -0.47, p = 0.002). CONCLUSION: Relative to healthy controls, individuals with acute PTH had less volume and higher iron deposition in the left LGN. Higher iron deposition in the left LGN might reflect mTBI severity and poor headache recovery.

Developing multivariable models for predicting headache improvement in patients with acute post-traumatic headache attributed to mild traumatic brain injury: A preliminary study.

OBJECTIVES/BACKGROUND: Post-traumatic headache (PTH) is a common symptom after mild traumatic brain injury (mTBI). Although there have been several studies that have used clinical features of PTH to attempt to predict headache recovery, currently no accurate methods exist for predicting individuals' improvement from acute PTH. This study investigated the utility of clinical questionnaires for predicting (i) headache improvement at 3 and 6 months, and (ii) headache trajectories over the first 3 months. METHODS: We conducted a clinic-based observational longitudinal study of patients with acute PTH who completed a battery of clinical questionnaires within 0-59 days post-mTBI. The battery included headache history, symptom evaluation, cognitive tests, psychological tests, and scales assessing photosensitivity, hyperacusis, insomnia, cutaneous allodynia, and substance use. Each participant completed a web-based headache diary, which was used to determine headache improvement. RESULTS: Thirty-seven participants with acute PTH (mean age = 42.7, standard deviation [SD] = 12.0; 25 females/12 males) completed questionnaires at an average of 21.7 (SD = 13.1) days post-mTBI. The classification of headache improvement or non-improvement at 3 and 6 months achieved cross-validation area under the curve (AUC) of 0.72 (95% confidence interval [CI] 0.55 to 0.89) and 0.84 (95% CI 0.66 to 1.00). Sub-models trained using only the top five features still achieved 0.72 (95% CI 0.55 to 0.90) and 0.77 (95% CI 0.52 to 1.00) AUC. The top five contributing features were from three questionnaires: Pain Catastrophizing Scale total score and helplessness sub-domain score; Sports Concussion Assessment Tool Symptom Evaluation total score and number of symptoms; and the State-Trait Anxiety Inventory score. The functional regression model achieved R = 0.64 for modeling headache trajectory over the first 3 months. CONCLUSION: Questionnaires completed following mTBI have good utility for predicting headache improvement at 3 and 6 months in the future as well as the evolving headache trajectory. Reducing the battery to only three questionnaires, which assess post-concussive symptom load and biopsychosocialecologic factors, was helpful to determine a reasonable prediction accuracy for headache improvement.

Photophobia Contributes to Migraine-Associated Disability and Reduced Work Productivity: Results From the American Registry for Migraine Research (ARMR).

BACKGROUND: Photosensitivity, often called "photophobia" in the migraine literature, is a common and bothersome symptom for most people during their migraine attacks. This study aimed to investigate the association of photophobia severity with work productivity, activity impairment, and migraine-associated disability using data from a large cohort of patients with migraine who were enrolled into the American Registry for Migraine Research (ARMR). METHODS: This study used Photosensitivity Assessment Questionnaire (PAQ) scores to investigate the relationship between photophobia severity with work productivity and activity impairment (using the Work Productivity and Activity Impairment [WPAI] questionnaire) and migraine-related disability (using the Migraine Disability Assessment [MIDAS]) among those with migraine. Summary statistics are presented as means and standard deviations for variables that were normally distributed and as medians and interquartile ranges for variables that were not normally distributed. Multiple linear regression models were developed to measure the relationships between photophobia scores with work productivity and activity impairment and migraine-associated disability, controlling for age, sex, headache frequency, headache intensity, anxiety (using the generalized anxiety disorder [GAD-7]), and depression (using the Patient Health Questionnaire [PHQ-2]). RESULTS: One thousand eighty-four participants were included. Average age was 46.1 (SD 13.8) years, 87.2% (n = 945) were female, average headache frequency during the previous 90 days was 44.3 (SD 29.9), average headache intensity was 5.9 (SD 1.7), median PHQ-2 score was 1 (IQR 0-2), and median GAD-7 was 5 (IQR 2-8). Mean PAQ score was 0.47 (SD 0.32), and median MIDAS score was 38 (IQR 15.0-80.0). Among the 584 employed participants, 47.4% (n = 277) reported missing work in the past week because of migraine, mean overall work impairment was 42.8% (SD 26.7), mean activity impairment was 42.5% (SD 26.2), mean presenteeism score was 38.4% (SD 24.4), and median absenteeism was 0 (IQR 0-14.5). After controlling for age, sex, headache frequency, average headache intensity, PHQ-2 score, and GAD-7 score, there was a statistically significant association between photophobia scores with: a) MIDAS scores (F[7,1028] = 127.42, P < 0.001, R2 = 0.461, n = 1,036); b) overall work impairment (F[7,570] = 29.23, P < 0.001, R2 = 0.255, n = 578); c) activity impairment (F[7,570] = 27.42, P < 0.001, R2 = 0.243, n = 578); d) presenteeism (F[7,570] = 29.17, P < 0.001, R2 = 0.255, n = 578); and e) absenteeism for the zero-inflated (P = 0.003) and negative binomial (P = 0.045) model components (P < 0.001, n = 578). CONCLUSIONS: In those with migraine, severe photophobia is associated with reduced work productivity and higher presenteeism, absenteeism, activity impairment, and migraine-related disability.

T2* reduction in patients with acute post-traumatic headache.

OBJECTIVES: Although iron accumulation in pain-processing brain regions has been associated with repeated migraine attacks, brain structural changes associated with post-traumatic headache have yet to be elucidated. To determine whether iron accumulation is associated with acute post-traumatic headache, magnetic resonance transverse relaxation rates (T2*) associated with iron accumulation were investigated between individuals with acute post-traumatic headache attributed to mild traumatic brain injury and healthy controls. METHODS: Twenty individuals with acute post-traumatic headache and 20 age-matched healthy controls underwent 3T brain magnetic resonance imaging including quantitative T2* maps. T2* differences between individuals with post-traumatic headache versus healthy controls were compared using age-matched paired t-tests. Associations of T2* values with headache frequency and number of mild traumatic brain injuries were investigated using multiple linear regression in individuals with post-traumatic headache. Significance was determined using uncorrected p-value and cluster size threshold. RESULTS: Individuals with post-traumatic headache had lower T2* values compared to healthy controls in cortical (bilateral frontal, bilateral anterior and posterior cingulate, right postcentral, bilateral temporal, right supramarginal, right rolandic, left insula, left occipital, right parahippocampal), subcortical (left putamen, bilateral hippocampal) and brainstem regions (pons). Within post-traumatic headache subjects, multiple linear regression showed a negative association between T2* in the right inferior parietal/supramarginal regions and number of mild traumatic brain injuries and a negative association between T2* in bilateral cingulate, bilateral precuneus, bilateral supplementary motor areas, bilateral insula, right middle temporal and right lingual areas and headache frequency. CONCLUSIONS: Acute post-traumatic headache is associated with iron accumulation in multiple brain regions. Correlations with headache frequency and number of lifetime mild traumatic brain injuries suggest that iron accumulation is part of the pathophysiology or a marker of mild traumatic brain injury and post-traumatic headache.

Migraine and Posttraumatic Headache: Similarities and Differences in Brain Network Connectivity.

Posttraumatic headache (PTH) is the most common symptom following mild traumatic brain injury (mTBI) (also known as concussion). Migraine and PTH have similar phenotypes, and a migraine-like phenotype is common in PTH. The similarities between both headache types are intriguing and challenge a better understanding of the pathophysiological commonalities involved in migraine and PTH due to mTBI. Here, we review the PTH resting-state functional connectivity literature and compare it to migraine to assess overlap and differences in brain network function between both headache types. Migraine and PTH due to mTBI have overlapping and disease-specific widespread alterations of static and dynamic functional networks involved in pain processing as well as dysfunctional network connections between frontal regions and areas of pain modulation and pain inhibition. Although the PTH functional network literature is still limited, there is some evidence that dysregulation of the top-down pain control system underlies both migraine and PTH. However, disease-specific differences in the functional circuitry are observed as well, which may reflect unique differences in brain architecture and pathophysiology underlying both headache disorders.

The impact of pre-morbid headaches on headache features and long-term health outcomes following traumatic brain injury: Insights from the American Registry for Migraine Research.

OBJECTIVE: To investigate the impact of having headaches prior to traumatic brain injury (TBI) on headache features and long-term patient health outcomes. BACKGROUND AND METHODS: This was an exploratory analysis of patients with TBI who were enrolled in the American Registry for Migraine Research (ARMR), a multicenter, prospective, longitudinal patient registry composed of patients with International Classification of Headache Disorders, 3rd edition (ICHD-3)-defined headache diagnoses. The ARMR study enrolled 2,707 patients between February 1, 2016 and May 6, 2020, 565 of whom qualified for this analysis. Those with headaches prior to their TBI were compared to those without headaches prior to their TBI for ICHD-3 diagnoses, headache frequency and intensity, headache-related disability (Migraine Disability Assessment score), symptoms of anxiety (General Anxiety Disorder [GAD-7]), depression (two items from Patient Health Questionnaire-9), post-traumatic stress disorder (PTSD), cutaneous allodynia (12-item Allodynia Symptom Checklist [ASC-12]), cognitive dysfunction (Migraine Attacks Subjective Cognitive Impairments Scale [Mig-SCog]), pain interference (Patient-Reported Outcomes Measurement Information System-Pain Interference), and work productivity (Work Productivity and Activity Impairment). RESULTS: Among 565 participants with TBI, 350 had headaches prior to their TBI. Those with pre-TBI headaches were less likely to receive a diagnosis of post-traumatic headache (PTH; 14/350 [4.0%] vs. 21/215 [9.8%], p = 0.006), even though 25.7% reported new or worsening headaches within 7 days of their TBI. Those with pre-TBI headaches had higher ASC-12 scores (2.4 ± 3.5 vs. 1.8 ± 3.4, p = 0.030), Mig-SCog scores (9.3 ± 4.7 vs. 8 ± 4.9, p = 0.004), and GAD-7 scores (6.9 ± 5.1 vs. 6.2 ± 5.4, p = 0.039), and were more likely to have a migraine diagnosis (335/350 [95.7%] vs. 192/215 [89.3%], p = 0.003). CONCLUSIONS: Those with headaches prior to TBI are less likely to receive a diagnosis of PTH. They have more severe symptoms of cutaneous allodynia, cognitive impairment, and generalized anxiety. This analysis suggests that pre-TBI headaches might impact post-TBI headache diagnoses and associated features.

Longitudinal changes in functional connectivity and pain-induced brain activations in patients with migraine: a functional MRI study pre- and post- treatment with Erenumab.

BACKGROUND: Migraine involves central and peripheral nervous system mechanisms. Erenumab, an anti-calcitonin gene-related peptide (CGRP) receptor monoclonal antibody with little central nervous system penetrance, is effective for migraine prevention. The objective of this study was to determine if response to erenumab is associated with alterations in brain functional connectivity and pain-induced brain activations. METHODS: Adults with 6-25 migraine days per month during a 4-week headache diary run-in phase underwent pre-treatment brain functional MRI (fMRI) that included resting-state functional connectivity and BOLD measurements in response to moderately painful heat stimulation to the forearm. This was followed by two treatments with 140 mg erenumab, at baseline and 4 weeks later. Post-treatment fMRI was performed 2 weeks and 8 weeks following the first erenumab treatment. A longitudinal Sandwich estimator analysis was used to identify pre- to post-treatment changes in resting-state functional connectivity and brain activations in response to thermal pain. fMRI findings were compared between erenumab treatment-responders vs. erenumab non-responders. RESULTS: Pre- and post-treatment longitudinal imaging data were available from 32 participants. Average age was 40.3 (+/- 13) years and 29 were female. Pre-treatment average migraine day frequency was 13.8 (+/- 4.7) / 28 days and average headache day frequency was 15.8 (+/- 4.4) / 28 days. Eighteen of 32 (56%) were erenumab responders. Compared to erenumab non-responders, erenumab responders had post-treatment differences in 1) network functional connectivity amongst pain-processing regions, including higher global efficiency, clustering coefficient, node degree, regional efficiency, and modularity, 2) region-to-region functional connectivity between several regions including temporal pole, supramarginal gyrus, and hypothalamus, and 3) pain-induced activations in the middle cingulate, posterior cingulate, and periaqueductal gray matter. CONCLUSIONS: Reductions in migraine day frequency accompanying erenumab treatment are associated with changes in resting state functional connectivity and central processing of extracranial painful stimuli that differ from erenumab non-responders. TRIAL REGISTRATION: clinicaltrials.gov (NCT03773562).

Distinguishing persistent post-traumatic headache from migraine: Classification based on clinical symptoms and brain structural MRI data.

BACKGROUND: Persistent post-traumatic headache most commonly has symptoms that overlap those of migraine. In some cases, it can be clinically difficult to differentiate persistent post-traumatic headache with a migraine phenotype from migraine. The objective of this study was to develop a classification model based on questionnaire data and structural neuroimaging data that distinguishes individuals with migraine from those with persistent post-traumatic headache. METHODS: Questionnaires assessing headache characteristics, sensory hypersensitivities, cognitive functioning, and mood, as well as T1-weighted magnetic resonance imaging and diffusion tensor data from 34 patients with migraine and 48 patients with persistent post-traumatic headache attributed to mild traumatic brain injury were included for analysis. The majority of patients with persistent post-traumatic headache had a migraine/probable migraine phenotype (77%). A machine-learning leave-one-out cross-validation algorithm determined the average accuracy for distinguishing individual migraine patients from individual patients with persistent post-traumatic headache. RESULTS: Based on questionnaire data alone, the average classification accuracy for determining whether an individual person had migraine or persistent post-traumatic headache was 71.9%. Adding imaging data features to the model improved the classification accuracy to 78%, including an average accuracy of 97.1% for identifying individual migraine patients and an average accuracy of 64.6% for identifying individual patients with persistent post-traumatic headache. The most important clinical features that contributed to the classification accuracy included questions related to anxiety and decision making. Cortical brain features and fibertract data from the following regions or tracts most contributed to the classification accuracy: Bilateral superior temporal, inferior parietal and posterior cingulate; right lateral occipital, uncinate, and superior longitudinal fasciculus. A post-hoc analysis showed that compared to incorrectly classified persistent post-traumatic headache patients, those who were correctly classified as having persistent post-traumatic headache had more severe physical, autonomic, anxiety and depression symptoms, were more likely to have post-traumatic stress disorder, and were more likely to have had mild traumatic brain injury attributed to blasts. DISCUSSION: A classification model that included a combination of questionnaire data and structural imaging parameters classified individual patients as having migraine versus persistent post-traumatic headache with good accuracy. The most important clinical measures that contributed to the classification accuracy included questions on mood. Regional brain structures and fibertracts that play roles in pain processing and pain integration were important brain features that contributed to the classification accuracy. The lower classification accuracy for patients with persistent post-traumatic headache compared to migraine may be related to greater heterogeneity of patients in the persistent post-traumatic headache cohort regarding their traumatic brain injury mechanisms, and physical, emotional, and cognitive symptoms.

Impact of abuse on migraine-related sensory hypersensitivity symptoms: Results from the American Registry for Migraine Research.

BACKGROUND AND OBJECTIVES: Prior studies have established an association between a history of abuse and the development of migraine. This cross-sectional observational study explored the relationship between self-reported abuse history with migraine-related sensory hypersensitivity symptoms. METHODS: In total, 588 adult patients with migraine from the American Registry for Migraine Research completed questionnaires: Generalized Anxiety Disorder-7, Patient Health Questionnaire-2 for depression, Photosensitivity Assessment Questionnaire, Hyperacusis Questionnaire, and Allodynia Symptom Checklist. Using four binary screening questions, patients were asked to self-report if they believed they had suffered emotional, physical, or sexual abuse in their lifetime. Differences in questionnaire scores between groups with and without a history of abuse were determined. Regression models adjusted for age, sex, and basic headache features analyzed the relationship between abuse history and sensory hypersensitivity symptoms. Moderation analysis explored the role of headache frequency in this relationship. Mediation analysis assessed the indirect (Mediated) effect (IE) of abuse on sensory hypersensitivity through depression or anxiety. Additional models analyzed relationships between sensory hypersensitivity symptoms and abuse subtypes or the number of abuse subtypes. RESULTS: Of 588 participants, 222 (38%) reported a history of abuse. Patients with a history of abuse reported statistically significantly greater average headache frequency (7.6 vs. 4.7 days, p = 0.030). Patients with a history of abuse also reported higher average or median questionnaire scores: anxiety (7.6 vs. 4.7, p < 0.001, d = 0.56), depression (1.7 vs. 1.3, p = 0.009, d = 0.24), photophobia (0.54 vs. 0.44, p < 0.001, d = 0.32), hyperacusis (19.6 vs. 14.9, p < 0.001, d = 0.49), ictal allodynia (6.0 vs. 3.0, p < 0.001, d = 0.46), and interictal allodynia (1.0 vs. 0.0, p < 0.001, d = 0.30). After controlling for patient age, sex and years lived with headache, abuse maintained a significant association with every sensory hypersensitivity measure. Headache frequency significantly moderated the relationship between a history of abuse with increased ictal allodynia (p = 0.036). Anxiety significantly mediated the relationships between abuse with photophobia (IE = 0.03, 95% CI = 0.01-0.04), hyperacusis (IE = 1.51, 95% CI = 0.91-2.24), ictal allodynia (IE = 0.02, 95% CI = 0.01-0.04), and interictal allodynia (IE = 0.02, 95% CI = 0.01-0.06). Depression significantly mediated the relationship between abuse with photophobia (IE = 0.02, 95% CI = 0.01-0.03) and with hyperacusis (IE = 0.45, 95% CI = 0.11-0.88). The association between the individual subtypes of abuse and the number of subtypes of abuse with sensory hypersensitivity symptoms varied. CONCLUSION: A history of abuse is associated with greater migraine-related sensory hypersensitivity symptoms. To reduce the impact of abuse on migraine symptoms, future studies should explore mechanistic connections between abuse and migraine-associated symptoms.

Chronic versus episodic migraine: The 15-day threshold does not adequately reflect substantial differences in disability across the full spectrum of headache frequency.

OBJECTIVE: To evaluate whether the 15-day threshold of headache days per month adequately reflects substantial differences in disability across the full spectrum of migraine. BACKGROUND: The monthly frequency of headache days defines migraine subtypes and has crucial implications for epidemiological and clinical research as well as access to care. METHODS: The patients with migraine (N = 836) who participated in the American Registry for Migraine Research, which is a multicenter, longitudinal patient registry, between February 2016 and March 2020, were divided into four groups based on monthly headache frequency: Group 1 (0-7 headache days/month, n = 286), Group 2 (8-14 headache days/month, n = 180), Group 3 (15-23 headache days/month, n = 153), Group 4 (≥24 headache days/month, n = 217). Disability (MIDAS), Pain intensity (NRS), Work Productivity and Activity Impairment (WPAI), Pain Interference (PROMIS-PI), Patient Health Questionnaire-4 (PHQ-4), and General Anxiety Disorder-7 (GAD-7) scores were compared. RESULTS: Mean (standard deviation [SD]) age was 46 (13) years (87.9% [735/836] female). The proportion of patients in each group was as follows: Group 1 (34.2% [286/836]), Group 2 (21.5% [180/836]), Group 3 (18.3% [153/836]), and Group 4 (26.0% [217/836]). There were significant relationships with increasing disability, lost productive time, and pain interference in higher headache frequency categories. There were no significant differences between Group 2 and Group 3 for most measures (NRS, all WPAI scores, PROMIS-PI, GAD-7, and PHQ-4), although MIDAS scores differed (median [interquartile range (IQR)]; 38 [20-58] vs. 55 [30-90], p < 0.001). Patients in Group 1 had significantly lower MIDAS (median [IQR];16 [7-30], p < 0.001), WPAI-% total active impairment (mean (SD): Group 1 [30.9 (26.8)] vs. Group 2 [39.2 (24.5), p = 0.017], vs. Group 3 [45.9 (24.1), p < 0.001], vs. Group 4 [55.3 (23.0), p < 0.001], and PROMIS-PI-T score (Group 1 [60.3 (7.3)] vs. Group 2 [62.6 (6.4), p = 0.008], vs. Group 3 [64.6 (5.6), p < 0.001], vs. Group 4 [66.8 (5.9), p < 0.001]) compared to all other groups. Patients in Group 4 had significantly higher MIDAS (median (IQR): Group 4 [90 (52-138)] vs. Group 1 [16 (7-30), p < 0.001], vs. Group 2 [38 (20-58), p < 0.001], vs. Group 3 [55 (30-90), p < 0.001], WPAI-%Presenteeism (Group 4 [50.4 (24.4)] vs. Group 1 [28.8 (24.9), p < 0.001], vs. Group 2 [34.9 (22.3), p < 0.001], vs. Group 3 [40.9 (22.3), p = 0.048], WPAI-% total work productivity impairment (Group 4 [55.9 (26.1)] vs. Group 1 [32.1 (37.6), p < 0.001], vs. Group 2 [38.3 (24.0), p < 0.001], vs. Group 3 [44.6 (24.4), p = 0.019]), and WPAI-%Total activity impairment (Group 4 [55.3 (23.0)] vs. Group 1 [30.9 (26.8), p < 0.001], vs. Group 2 [39.2 (24.5), p < 0.001], vs. Group 3 [45.9 (24.1), p = 0.025]) scores compared with all other groups. CONCLUSION: Our data suggest that the use of a 15 headache day/month threshold to distinguish episodic and chronic migraine does not capture the burden of illness nor reflect the treatment needs of patients. These results have important implications for future refinements in the classification of migraine.

Headache Characteristics and Psychological Factors Associated with Functional Impairment in Individuals with Persistent Posttraumatic Headache.

OBJECTIVE: Persistent posttraumatic headache (PPTH), one of the most common symptoms following mild traumatic brain injury, is often associated with substantial functional disability. The objective of this study was to assess the contribution of demographics, headache characteristics, and psychological symptoms to disability associated with PPTH. METHODS: Participants completed the State-Trait Anxiety Inventory (STAI), the Beck Depression Inventory (BDI), the Pain Catastrophizing Scale (PCS), and the Migraine Disability Assessment (MIDAS) questionnaire. Two linear regression models were formulated to interrogate the relationships between 1) demographics and headache characteristics with the MIDAS questionnaire and 2) demographics, headache characteristics, and psychological symptoms with the MIDAS questionnaire. A two-way stepwise regression using the Akaike information criterion was performed to find a parsimonious model describing the relationships between demographics, headache characteristics, and psychological measures with the MIDAS questionnaire. RESULTS: Participants included 58 patients with PPTH and 39 healthy controls (HCs). The median MIDAS score among those with PPTH was 48.0 (first quartile [1Q] = 20.0, third quartile [3Q] = 92.0), indicative of severe disability. Compared with the HCs, those with PPTH had higher scores on the BDI, STAI, and PCS. Older age predicted lower MIDAS scores (age: B=-0.11, P<0.01), whereas higher headache frequency, greater headache intensity, and higher trait anxiety scores predicted higher MIDAS scores in individuals with PPTH (headache frequency: B=0.07, P<0.001; headache intensity: B=0.51, P=0.04; trait anxiety score: B=1.11, P=0.01). CONCLUSIONS: Individuals with PPTH had substantial psychological symptoms and headache-related disability. Disability was partially explained by age, headache frequency and intensity, and trait anxiety. Holistic management of patients with PPTH to address headaches and psychological symptoms might reduce headache-associated disability.

Mild traumatic brain injury affects the features of migraine.

BACKGROUND: Headache is one of the most common symptoms after concussion, and mild traumatic brain injury (mTBI) is a risk factor for chronic migraine (CM). However, there remains a paucity of data regarding the impact of mTBI on migraine-related symptoms and clinical course. METHODS: Of 2161 migraine patients who participated in the American Registry for Migraine Research between February 2016 and March 2020, 1098 completed questions assessing history of TBI (50.8%). Forty-four patients reported a history of moderate to severe TBI, 413 patients reported a history of mTBI. Patients' demographics, headache symptoms and triggers, history of physical abuse, allodynia symptoms (ASC-12), migraine disability (MIDAS), depression (PHQ-2), and anxiety (GAD-7) were compared between migraine groups with (n = 413) and without (n = 641) a history of mTBI. Either the chi-square-test or Fisher's exact test, as appropriate, was used for the analyses of categorical variables. The Mann-Whitney test was used for the analyses of continuous variables. Logistic regression models were used to compare variables of interest while adjusting for age, gender, and CM. RESULTS: A significantly higher proportion of patients with mTBI had CM (74.3% [307/413] vs. 65.8% [422/641], P = 0.004), had never been married or were divorced (36.6% [147/402] vs. 29.4% [187/636], P = 0.007), self-reported a history of physical abuse (24.3% [84/345] vs. 14.3% [70/491], P <  0.001), had mild to severe anxiety (50.5% [205/406] vs. 41.0% [258/630], P = 0.003), had headache-related vertigo (23.0% [95/413] vs. 15.9% [102/640], P = 0.009), and difficulty finding words (43.0% [174/405] vs. 32.9% [208/633], P <  0.001) in more than half their attacks, and headaches triggered by lack of sleep (39.4% [155/393] vs. 32.6% [198/607], P = 0.018) and reading (6.6% [26/393] vs. 3.0% [18/607], P = 0.016), compared to patients without mTBI. Patients with mTBI had significantly greater ASC-12 scores (median [interquartile range]; 5 [1-9] vs. 4 [1-7], P < 0.001), MIDAS scores (42 [18-85] vs. 34.5 [15-72], P = 0.034), and PHQ-2 scores (1 [0-2] vs. 1 [0-2], P = 0.012). CONCLUSION: Patients with a history of mTBI are more likely to have a self-reported a history of physical abuse, vertigo, and allodynia during headache attacks, headaches triggered by lack of sleep and reading, greater headache burden and headache disability, and symptoms of anxiety and depression. This study suggests that a history of mTBI is associated with the phenotype, burden, clinical course, and associated comorbid diseases in patients with migraine, and highlights the importance of inquiring about a lifetime history of mTBI in patients being evaluated for migraine.