Characterizing Prodrome (Premonitory Phase) in Migraine: Results From the PRODROME Trial Screening Period.

Background and Objective: Limited data are available describing the frequency, severity, and consistency of prodromal symptoms followed by headache. This analysis of the PRODROME trial screening period characterized prodromal symptoms in people with migraine, including the most common symptoms and their severity, and the frequency and consistency with which prodromal symptoms were followed by headache. Methods: PRODROME was a multicenter, randomized, double-blind, placebo-controlled, crossover trial conducted in the United States that enrolled adults with 2-8 migraine attacks per month who stated they could identify prodromal symptoms that were reliably followed by a headache. The trial included a 60-day screening period designed to test the predictive validity of "qualifying prodrome events" before the onset of headache. Participants used an eDiary to report qualifying prodrome events, defined as prodromal symptoms whereby the participant was confident a headache would follow within 1-6 hours. This analysis evaluated common prodromal symptoms and their severity, time from prodrome onset to headache onset, and the percentage of participants who identified prodromal symptoms that were followed by a headache ≥75% of the time over the 60-day screening period. Results: A total of 920 participants entered eDiary data, with a mean of 5.2 qualifying prodrome events during the 60-day screening period. A total of 4,802 qualifying prodrome events were recorded. The most common prodromal symptoms identified were sensitivity to light (57.2%; 2,748/4,802), fatigue (50.1%; 2,408/4,802), neck pain (41.9%; 2,013/4,802), sensitivity to sound (33.9%; 1,630/4,802), either difficulty thinking or concentrating (30.0%; 1,442/4,802), and dizziness (27.8%; 1,333/4,802). Of all qualifying prodrome events reported, 81.5% (3,913/4,802) were followed by headache of any intensity within 1-6 hours. For each participant, a mean of 84.4% of their qualifying prodrome events were followed by a headache within 1-6 hours, with 76.9% of participants identifying qualifying prodrome events that were followed by headache within 1-6 hours ≥75% of the time. Discussion: Participants were able to identify migraine attacks in which prodromal symptoms were reliably followed by a headache within 1-6 hours. These findings suggest the potential for initiating treatment during the prodrome to prevent headache. Trial Registration Information: ClinicalTrials.gov NCT04492020. Submitted: July 27, 2020; First patient enrolled: August 21, 2020. clinicaltrials.gov/study/NCT04492020.

Are we closer to achieving precision medicine for migraine treatment? A narrative review.

BACKGROUND: The term 'precision medicine' encompasses strategies to optimize diagnosis and outcome prediction and to tailor treatment for individual patients, in consideration of their unique characteristics. The greater availability of multifaceted datasets and strategies to model such data have made precision medicine increasingly possible in recent years. Precision medicine is especially needed in the migraine field since the response to migraine treatments is not universal amongst all individuals with migraine. OBJECTIVE: To provide a narrative review describing contributions to achieving precision medicine for migraine treatment. METHODS: A search of PubMed for English language articles of human participants published from 2005 to January 2024 was conducted to identify articles that reported research contributing to precision medicine for migraine treatment. The published literature was categorized and summarized according to the type of data that were included: clinical phenotypes, genomics, proteomics, physiologic measures, and brain imaging. RESULTS: Published studies have investigated characteristics associated with acute and preventive treatment responses, such as nonsteroidal anti-inflammatory drugs, triptans, onabotulinumtoxinA, and anti-calcitonin gene-related peptide monoclonal antibodies, in patients with episodic or chronic migraine. There is evidence that clinical, genetic, epigenetic, proteomic, physiologic, and brain imaging features might associate with migraine treatment outcomes, although inconsistencies for such findings clearly exist. CONCLUSIONS: The published literature suggests that there are clinical and biological features which associate with, and might be useful for predicting, migraine treatment responses. To achieve precision medicine for migraine treatment, further research is needed that validates and expands on existing findings and tests the accuracy and value of migraine treatment prediction models in clinical settings.

Advancing toward precision migraine treatment: Predicting responses to preventive medications with machine learning models based on patient and migraine features.

OBJECTIVE: To develop machine learning models using patient and migraine features that can predict treatment responses to commonly used migraine preventive medications. BACKGROUND: Currently, there is no accurate way to predict response to migraine preventive medications, and the standard trial-and-error approach is inefficient. METHODS: In this cohort study, we analyzed data from the Mayo Clinic Headache database prospectively collected from 2001 to December 2023. Adult patients with migraine completed questionnaires during their initial headache consultation to record detailed clinical features and then at each follow-up to track preventive medication changes and monthly headache days. We included patients treated with at least one of the following migraine preventive medications: topiramate, beta-blockers (propranolol, metoprolol, atenolol, nadolol, timolol), tricyclic antidepressants (amitriptyline, nortriptyline), verapamil, gabapentin, onabotulinumtoxinA, and calcitonin gene-related peptide (CGRP) monoclonal antibodies (mAbs) (erenumab, fremanezumab, galcanezumab, eptinezumab). We pre-trained a deep neural network, "TabNet," using 145 variables, then employed TabNet-embedded data to construct prediction models for each medication to predict binary outcomes (responder vs. non-responder). A treatment responder was defined as having at least a 30% reduction in monthly headache days from baseline. All model performances were evaluated, and metrics were reported in the held-out test set (train 85%, test 15%). SHapley Additive exPlanations (SHAP) were conducted to determine variable importance. RESULTS: Our final analysis included 4260 patients. The responder rate for each medication ranged from 28.7% to 34.9%, and the mean time to treatment outcome for each medication ranged from 151.3 to 209.5 days. The CGRP mAb prediction model achieved a high area under the receiver operating characteristics curve (AUC) of 0.825 (95% confidence interval [CI] 0.726, 0.920) and an accuracy of 0.80 (95% CI 0.70, 0.88). The AUCs of prediction models for beta-blockers, tricyclic antidepressants, topiramate, verapamil, gabapentin, and onabotulinumtoxinA were: 0.664 (95% CI 0.579, 0.745), 0.611 (95% CI 0.562, 0.682), 0.605 (95% CI 0.520, 0.688), 0.673 (95% CI 0.569, 0.724), 0.628 (0.533, 0.661), and 0.581 (95% CI 0.550, 0.632), respectively. Baseline monthly headache days, age, body mass index (BMI), duration of migraine attacks, responses to previous medication trials, cranial autonomic symptoms, family history of headache, and migraine attack triggers were among the most important variables across all models. A variable could have different contributions; for example, lower BMI predicts responsiveness to CGRP mAbs and beta-blockers, while higher BMI predicts responsiveness to onabotulinumtoxinA, topiramate, and gabapentin. CONCLUSION: We developed an accurate prediction model for CGRP mAbs treatment response, leveraging detailed migraine features gathered from a headache questionnaire before starting treatment. Employing the same methods, the model performances for other medications were less impressive, though similar to the machine learning models reported in the literature for other diseases. This may be due to CGRP mAbs being migraine-specific. Incorporating medical comorbidities, genomic, and imaging factors might enhance the model performance. We demonstrated that migraine characteristics are important in predicting treatment responses and identified the most crucial predictors for each of the seven types of preventive medications. Our results suggest that precision migraine treatment is feasible.

International Headache Society global practice recommendations for the acute pharmacological treatment of migraine.

BACKGROUND: In an effort to improve migraine management around the world, the International Headache Society (IHS) has here developed a list of practical recommendations for the acute pharmacological treatment of migraine. The recommendations are categorized into optimal and essential, in order to provide treatment options for all possible settings, including those with limited access to migraine medications. METHODS: An IHS steering committee developed a list of clinical questions based on practical issues in the management of migraine. A selected group of international senior and junior headache experts developed the recommendations, following expert consensus and the review of available national and international headache guidelines and guidance documents. Following the initial search, a bibliography of twenty-one national and international guidelines was created and reviewed by the working group. RESULTS: A total of seventeen questions addressing different aspects of acute migraine treatment have been outlined. For each of them we provide an optimal recommendation, to be used whenever possible, and an essential recommendation to be used when the optimal level cannot be attained. CONCLUSION: Adoption of these international recommendations will improve the quality of acute migraine treatment around the world, even where pharmacological options remain limited.

The headache research priorities: Research goals from the American Headache Society and an international multistakeholder expert group.

OBJECTIVE: To identify and disseminate research priorities for the headache field that should be areas of research focus during the next 10 years. BACKGROUND: Establishing research priorities helps focus and synergize the work of headache investigators, allowing them to reach the most important research goals more efficiently and completely. METHODS: The Headache Research Priorities organizing and executive committees and working group chairs led a multistakeholder and international group of experts to develop headache research priorities. The research priorities were developed and reviewed by clinicians, scientists, people with headache, representatives from headache organizations, health-care industry representatives, and the public. Priorities were revised and finalized after receiving feedback from members of the research priorities working groups and after a public comment period. RESULTS: Twenty-five research priorities across eight categories were identified: human models, animal models, pathophysiology, diagnosis and management, treatment, inequities and disparities, research workforce development, and quality of life. The priorities address research models and methods, development and optimization of outcome measures and endpoints, pain and non-pain symptoms of primary and secondary headaches, investigations into mechanisms underlying headache attacks and chronification of headache disorders, treatment optimization, research workforce recruitment, development, expansion, and support, and inequities and disparities in the headache field. The priorities are focused enough that they help to guide headache research and broad enough that they are widely applicable to multiple headache types and various research methods. CONCLUSIONS: These research priorities serve as guidance for headache investigators when planning their research studies and as benchmarks by which the headache field can measure its progress over time. These priorities will need updating as research goals are met and new priorities arise.

The impact of headache intensity on speech in participants with migraine and acute post-traumatic headache.

BACKGROUND: Slower speaking rates and higher pause rates are found in individuals with migraine or post-traumatic headache during headache compared to when headache-free. We aimed to determine whether headache intensity influences the speaking rate and pause rate of participants with migraine or acute post-traumatic headache (aPTH) following mild traumatic brain injury (mTBI). METHODS: Using a speech elicitation tool, participants with migraine, aPTH, and healthy controls (HC) submitted speech samples over a period of 3 months. Speaking and pause rates were calculated when participants were headache-free and when they had mild or moderate headache. In this observational study, speaking and pause rates in participants with migraine and aPTH were compared to HC, controlling for age, sex, and days since mTBI (participants with aPTH only). RESULTS: A total of 2902 longitudinal speech samples from 13 individuals with migraine (mean age = 33.5, SD = 6.6; 12 females/1 male), 43 individuals with aPTH (mean age = 44.4, SD = 13.5; 28 females/15 males), and 56 HC (mean age = 40.8, SD = 13.0; 36 females/20 males) were collected. There was no difference in speaking rate between HC and the combined headache cohort of participants (migraine and aPTH) when they had headache freedom or a mild headache. When participants had moderate intensity headache, their speaking rate was significantly slower compared to that of HC and compared to their speaking rate during mild headache intensity or headache freedom. For the combined headache cohort of participants, pause rates were significantly higher when they had headache freedom or had a headache of mild or moderate intensity relative to HC. Compared to participants' pause rate during headache freedom, their pause rate was significantly higher during mild and moderate headache intensity. Participants with aPTH had significantly slower speaking rates compared to participants with migraine during headache freedom, mild headache intensity, and moderate headache intensity. Participants with aPTH had significantly higher pause rates compared to participants with migraine when experiencing moderate headache intensity. DISCUSSION: For both aPTH and migraine, more severe headache pain was associated with higher pause rates and slower speaking rates, suggesting that speaking rate and pause rate could serve as objective biomarkers for headache-related pain. Slower speaking rate in participants with aPTH could reflect additional consequences of TBI-related effects on motor control and speech production.

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.

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.

Brainomaly: Unsupervised Neurologic Disease Detection Utilizing Unannotated T1-weighted Brain MR Images.

Harnessing the power of deep neural networks in the medical imaging domain is challenging due to the difficulties in acquiring large annotated datasets, especially for rare diseases, which involve high costs, time, and effort for annotation. Unsupervised disease detection methods, such as anomaly detection, can significantly reduce human effort in these scenarios. While anomaly detection typically focuses on learning from images of healthy subjects only, real-world situations often present unannotated datasets with a mixture of healthy and diseased subjects. Recent studies have demonstrated that utilizing such unannotated images can improve unsupervised disease and anomaly detection. However, these methods do not utilize knowledge specific to registered neuroimages, resulting in a subpar performance in neurologic disease detection. To address this limitation, we propose Brainomaly, a GAN-based image-to-image translation method specifically designed for neurologic disease detection. Brainomaly not only offers tailored image-to-image translation suitable for neuroimages but also leverages unannotated mixed images to achieve superior neurologic disease detection. Additionally, we address the issue of model selection for inference without annotated samples by proposing a pseudo-AUC metric, further enhancing Brainomaly's detection performance. Extensive experiments and ablation studies demonstrate that Brainomaly outperforms existing state-of-the-art unsupervised disease and anomaly detection methods by significant margins in Alzheimer's disease detection using a publicly available dataset and headache detection using an institutional dataset. The code is available from https://github.com/mahfuzmohammad/Brainomaly.

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.

Functional impairment of chronic migraine with medication overuse: Secondary analysis from the Medication Overuse Treatment Strategy (MOTS) trial.

BACKGROUND: Chronic migraine exerts substantial negative impacts on daily functioning. Efforts to manage impaired functioning may result in medication overuse, which contributes to the worsening profile and chronification of migraine. The Migraine Functional Impact Questionnaire (MFIQ) is a recently developed measure assessing the impact of migraine on physical, social, and emotional function. OBJECTIVE: The objective of this analysis was to assess changes in MFIQ scores following initiation or modification of migraine preventive medication and determine if changes in function are associated with changes in other aspects of migraine burden, such as headache frequency, headache intensity, and symptoms of anxiety and depression. METHODS: This is a secondary analysis of data from the Medication Overuse Treatment Strategy (MOTS) trial, a prospective pragmatic clinical trial that investigated two treatment strategies for those with chronic migraine and medication overuse. Data from both treatment arms were pooled and analyzed using a pre-post design. Prior to and 12 weeks following initiation or modification of migraine preventive medication, participants completed a series of questionnaires that captured migraine characteristics, medication use, migraine-related physical impairment (MFIQ), anxiety (Generalized Anxiety Disorder-7), and depression (Patient Health Questionnaire 9 [PHQ-9]) symptoms. Changes from baseline in all measures were assessed using the paired t-test. Relationships between changes in MFIQ scores and other measures were assessed using linear regression. Multivariable modeling was performed to determine which additional variables contributed to the change in MFIQ beyond that already explained by an individual variable. Model terms were selected by using elastic net regularization. Only those participants who completed the baseline and 12-week MFIQ were included in this analysis. RESULTS: Of the 537 patients, 88.2% were female, and the average age was 45 years (standard deviation 13). The mean frequency of days with moderate-to-severe headache improved 39.2% from 13.5 per 30 days at baseline to 8.1 per 30 days at week 12. The mean MFIQ Usual Activities Global score improved by 15.0 points (on a 100-point scale). All five domains (Usual Activities Global, Usual Activities, Social Function, Emotional Function, Physical Function) of the MFIQ improved by a mean of at least 13.0 points. Changes in PHQ-9 score, followed by changes in headache frequency, had the strongest associations with change in all domains of the MFIQ. CONCLUSIONS: The negative impact of chronic migraine with medication overuse on physical, social, and emotional functioning substantially lessened following initiation or modification of migraine preventive medication. Improved functioning, as measured by the MFIQ, was most strongly associated with reductions in depression scores and headache frequency, highlighting the importance of recognizing and monitoring changes in depressive symptoms, in addition to headache frequency and functional impairment, when evaluating response to preventive medications.

Photophobia is associated with lower sleep quality in individuals with migraine: results from the American Registry for Migraine Research (ARMR).

BACKGROUND: Patients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aimed to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine. METHODS: A cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), sleep-related impairments (SRI), and insomnia. Each model was controlled for age, sex, headache frequency, anxiety, and depression. RESULTS: A total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p < 0.001). Photophobia scores were associated with SQ (p < 0.001), SDis (p < 0.001), SOL (p = 0.011), SRI (p = 0.020), and insomnia (p = 0.005) after controlling for age, sex, headache frequency, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p < 0.007), SOL (p = 0.010), and insomnia (p = 0.014). CONCLUSION: Results suggest that photophobia is a significant predictor of poor sleep quality and sleep disturbances in migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine.

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).

Posttraumatic Headache.

OBJECTIVE: This article provides an overview of the epidemiology, diagnosis, clinical presentation, pathophysiology, prognosis, and treatment of posttraumatic headache attributed to mild traumatic brain injury (mTBI). LATEST DEVELOPMENTS: The International Classification of Headache Disorders, Third Edition requires that posttraumatic headache begin within 7 days of the inciting trauma. Although posttraumatic headache characteristics and associated symptoms vary, most commonly there is substantial overlap with symptoms of migraine or tension-type headache. New insights into posttraumatic headache pathophysiology suggest roles for neuroinflammation, altered pain processing and modulation, and changes in brain structure and function. Although the majority of posttraumatic headache resolves during the acute phase, about one-third of individuals have posttraumatic headache that persists for at least several months. Additional work is needed to identify predictors and early markers of posttraumatic headache persistence, but several potential predictors have been identified such as having migraine prior to the mTBI, the total number of TBIs ever experienced, and the severity of initial symptoms following the mTBI. Few data are available regarding posttraumatic headache treatment; studies investigating different treatments and the optimal timing for initiating posttraumatic headache treatment are needed. ESSENTIAL POINTS: Posttraumatic headache begins within 7 days of the causative injury. The characteristics of posttraumatic headache most commonly resemble those of migraine or tension-type headache. Posttraumatic headache persists for 3 months or longer in about one-third of individuals. Additional studies investigating posttraumatic headache treatment are needed.

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 10 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* and SCAT symptom severity score in the left posterior cingulate (p = 0.05) and with headache frequency in the left cuneus (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.

Guidelines of the International Headache Society for controlled trials of pharmacological preventive treatment for persistent post-traumatic headache attributed to mild traumatic brain injury.

BACKGROUND: Persistent headache attributed to traumatic injury to the head is divided into two subtypes, one attributed to moderate or severe traumatic injury and another attributed to mild traumatic injury (i.e., concussion). The latter is much more prevalent, in part because more than 90% of cases with traumatic brain injury are classified as mild. The pathophysiology of persistent post-traumatic headache is poorly understood and the underlying mechanisms are likely multifactorial. There is currently no approved treatment specifically for persistent post-traumatic headache, and management strategies rely on medications used for migraine or tension-type headache. Therefore, high-quality trials are urgently needed to support clinical decision-making and optimize management strategies. International guidelines can facilitate appropriate trial design and ensure the acquisition of high-quality data evaluating the efficacy, tolerability, and safety of available and novel pharmacological therapies for the preventive treatment of persistent post-traumatic headache. METHODS: The development of this guideline was based on a literature review of available studies in MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials, along with a review of previously published guidelines for controlled trials of preventive treatment for episodic and chronic migraine. The identified literature was critically appraised, and due to the scarcity of scientific evidence, recommendations were primarily based on the consensus of experts in the field. OBJECTIVE: To provide guidelines for designing state-of-the-art controlled clinical trials aimed at evaluating the effectiveness of preventive treatments for persistent post-traumatic headache attributed to mild traumatic brain injury.

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.

Posttraumatic headache is a distinct headache type from migraine.

PURPOSE OF REVIEW: Posttraumatic headache (PTH), a headache that develops within 7 days of a causative injury, is one of the most common secondary headaches, mostly attributed to mild traumatic brain injury (mTBI). Because presence of preinjury headache is a risk factor for developing PTH and PTH symptoms often resemble migraine or tension-type headache, the association between PTH and primary headaches has attracted attention from clinicians and scientists. RECENT FINDINGS: Recent studies on epidemiological aspects, headache features, risk factors, imaging characteristics, and response to treatment, suggest overlapping features and distinct objective findings in PTH compared to migraine. SUMMARY: We argue that PTH is distinct from migraine. Therefore, PTH epidemiology, pathophysiology, diagnosis, treatment, and prognosis should continue to be investigated separately from migraine.