Stern, Jennifer I.

Abstract 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.

Aging and many illnesses and injuries impair skeletal muscle mass and function, but the molecular mechanisms are not well understood. To better understand the mechanisms, we generated and studied transgenic mice with skeletal muscle–specific expression of growth arrest and DNA damage inducible α (GADD45A), a signaling protein whose expression in skeletal muscle rises during aging and a wide range of illnesses and injuries. We found that GADD45A induced several cellular changes that are characteristic of skeletal muscle atrophy, including a reduction in skeletal muscle mitochondria and oxidative capacity, selective atrophy of glycolytic muscle fibers, and paradoxical expression of oxidative myosin heavy chains despite mitochondrial loss. These cellular changes were at least partly mediated by MAP kinase kinase kinase 4, a protein kinase that is directly activated by GADD45A. By inducing these changes, GADD45A decreased the mass of muscles that are enriched in glycolytic fibers, and it impaired strength, specific force, and endurance exercise capacity. Furthermore, as predicted by data from mouse models, we found that GADD45A expression in skeletal muscle was associated with muscle weakness in humans. Collectively, these findings identify GADD45A as a mediator of mitochondrial loss, atrophy, and weakness in mouse skeletal muscle and a potential target for muscle weakness in humans.

Abstract Objectives/Background Treatment of migraine in the setting of either renal or hepatic disease can be daunting for clinicians. Not only does the method of metabolism have to be considered, but also the method of elimination/excretion of the parent drug and any active or toxic metabolites. Furthermore, it is difficult to think about liver or kidney disease in isolation, as liver disease can sometimes contribute to impaired renal function and renal disease can sometimes impair hepatic metabolism, through the cytochrome P450 system. Methods A detailed search for terms related to liver disease, renal disease, and migraine management was performed in PubMed, Ovid Medline, Embase, and the Cochrane Library.For each medication, product labels were retrieved and reviewed using the US FDA website, with additional review of IBM Micromedex, LiverTox, and the Renal Drug Handbook. Results This manuscript provides an overview of migraine drug metabolism and how it can be affected by liver and renal impairment. It reviews the standard terminology recommended by the US Food and Drug Administration for the different stages of hepatic and renal failure. The available evidence regarding the use of abortive and preventative medicines in the setting of organ failure is discussed in detail, including more recent therapies such as lasmiditan, gepants, and calcitonin gene‐related peptide antibodies. Conclusions For acute therapy, the use of NSAIDS should be limited, as these carry risk for both severe hepatic and renal disease. Triptans can be selectively used, often with dose guideline adjustments. Ubrogepant may be used in severe hepatic disease with dose adjustment and lasmiditan can be used in end stage renal disease. Though non‐medicine strategies may be the most reasonable initial approach, many preventative medications can be used in the setting of hepatic and renal disease, often with dose adjustment. This review provides tables of guidelines, including reduced dosing recommendations, for the use of abortive and preventative migraine medications in hepatic and renal failure.

Abstract Objective To provide an overview of the current available literature on peripheral nerve blocks for the management of migraine and other headache disorders in adults. Background Peripheral nerve blocks have been commonly performed in the headache practice for migraine, cluster headache, occipital neuralgia, and other headache disorders, despite a paucity of evidence supporting their use historically. In the past decade, there has been an effort to explore the efficacy and safety of peripheral nerve blocks for the management of headache, with the greatest interest centered around greater occipital blocks. Design We performed a search in PubMed using key words including “occipital nerve blocks,” “peripheral nerve blocks,” “occipital nerve,” “migraine,” “cluster headache,” and “neuralgia.” We reviewed the randomized controlled trials (RCTs), observational studies, and case series, and summarized the anatomy, techniques, and the evidence for the use of peripheral nerve blocks in different headache disorders, with particular focus on available RCTs. Case reports were included for a detail review of adverse events. Results Of 12 RCTs examining the use of greater occipital nerve blocks for migraine, all but one demonstrate efficacy with reduction in headache frequency, intensity, and/or duration compared to placebo. Studies have not demonstrated a difference in clinical outcomes with the use of corticosteroids for nerve blocks compared to blocks with local anesthetic in the treatment of migraine. There are two RCTs supporting the use of greater occipital blockade for cluster headache, both showing benefit of suboccipitally injected corticosteroid. One RCT suggests benefit of greater occipital nerve blocks for cervicogenic headache. Observational studies and case series/reports show that greater occipital nerve block may be effective in prolonged migraine aura, status migrainosus, post‐dural puncture headache, and occipital neuralgia. Overall, peripheral nerve blocks are well tolerated. Serious side effects are rare but have been reported, including acute cerebellar syndrome and infection. Conclusions Peripheral nerve blocks, especially occipital nerve blocks, are a viable treatment option for migraine and may be helpful in cluster headache as a transitional therapy or rescue therapy. Additional prospective studies are needed to investigate the efficacy and safety of occipital nerve blocks for long‐term migraine prevention, as well as for other headache disorders, such as occipital neuralgia.