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Abstract Objective To evaluate whether thyroid dysfunction, including hypothyroidism and hyperthyroidism, is associated with migraine across racial and age groups using a large, multinational electronic health record database. Background Thyroid disorders are highly prevalent worldwide, with hypothyroidism affecting over 200 million individuals and hyperthyroidism affecting approximately 2.5% of adults. Migraine is a leading cause of disability globally. Prior studies have suggested potential links between thyroid dysfunction and migraine, but evidence has been limited by small sample sizes, restricted population diversity, and inadequate control of confounding. Whether associations differ by thyroid subtype, race, or age remains unclear. Methods We performed two parallel retrospective cohort analyses within the TriNetX Global Collaborative Network, comprising over 200 million patients across 21 countries, using patient records from January 2004 to December 2024. Adults aged 18–100 years with hypothyroidism or hyperthyroidism, defined by ≥3 clinical encounters within 20 years, were identified. Individuals with psychiatric disorders (including mood, anxiety, and stress‐related disorders), sleep disorders, epilepsy or recurrent seizures, or known migraine‐related genetic mutations were excluded. Each thyroid cohort was compared with a control group without thyroid disease, with groups balanced on key demographic and clinical characteristics including age, sex, and hypertension; beta‐blocker use was additionally considered in the hyperthyroidism cohort. The primary outcome was diagnosis of migraine (International Classification of Diseases, 10th Revision, code G43) within 5 years of index date. Subgroup analyses were conducted by race (Caucasian, African American/Black, Asian) and age (18–40, 40–65, 65–100 years). Sensitivity analyses assessed robustness to alternative visit thresholds and expanded covariate adjustment. Results A total of 33,327,750 patients were included in the hypothyroidism analysis and 28,182,377 in the hyperthyroidism analysis. Baseline differences between groups were minimized after cohort balancing. Hypothyroidism was associated with higher odds of migraine across all racial groups, strongest among African American/Black (odds ratio [OR] 2.04; 95% confidence interval [CI] 1.91–2.17), followed by White (OR 1.93; 95% CI 1.89–1.96) and Asian (OR 1.83; 95% CI 1.69–1.98). Hyperthyroidism was similarly associated with increased migraine odds, most prominently among White (OR 1.64; 95% CI 1.59–1.70), with smaller but significant associations in African American/Black (OR 1.28; 95% CI 1.14–1.44) and Asian (OR 1.18; 95% CI 1.07–1.29). Elevated odds were observed across all age strata, generally increasing with age. Findings were consistent in sensitivity analyses. Conclusion In this large, multinational real‐world study, both hypothyroidism and hyperthyroidism were independently associated with increased migraine prevalence across diverse racial and age groups. These results highlight thyroid dysfunction as an important comorbid condition in migraine and support further prospective and mechanistic investigation.

Background: Greater trochanteric (GT) fractures after total hip arthroplasty (THA) are typically managed nonoperatively. However, outcome data for patient counseling remain limited. We evaluated the nonoperative results, focusing on fracture union rates and the presence of persistent limp in relation with fracture location, displacement magnitude, and direction. Methods: We retrospectively reviewed 82 postoperative GT fractures not associated with trochanteric osteolysis following primary THA performed between 1984 and 2020. The mean follow-up was 9 years. Fracture location was classified relative to the contralateral lesser trochanter as tip, waist, or base. Initial displacement, migration, final displacement, and bony union were assessed radiographically. Clinical outcomes included the presence of a persistent limp and Harris Hip Score. Multivariable analyses were performed to identify factors associated with nonunion and limp. Results: Fractures were classified as tip (n = 32), waist (n = 29), or base (n = 21). The mean initial displacement was 8.9 mm, with 43% displaced >10 mm. Initial displacement was significantly lower in base fractures (4.8 mm) compared with tip (10.1 mm) or waist (10.8 mm) fractures (p < 0.05). The mean final displacement was 14.6 mm. 45% of fractures achieved complete bony union, and 38% of patients demonstrated a persistent limp. In multivariable analysis, greater final displacement (>12 mm), and tip and waist fractures were independently associated with nonunion. Posterior fracture displacement was significantly associated with persistent limp. Conclusions: Outcomes following nonoperative management of GT fractures after THA depend on fracture morphology and displacement characteristics. Tip and waist fractures and fractures with final displacement >12 mm have a higher risk of nonunion, whereas posterior and superior displacement is associated with persistent limp. Greater than 20 mm of displacement is associated with both limp and nonunion. These findings may assist surgeons in counseling patients and in identifying fracture patterns at higher risk for adverse outcomes of nonoperative management. Level of Evidence: Level III (Prognostic Study). See Instructions for Authors for a complete description of levels of evidence.

Goal: This research aimed to evaluate variations in perceived organizational support among physicians during the first year of the COVID-19 pandemic and the associations between perceived organizational support, physician burnout, and professional fulfillment. Methods: Between November 20, 2020, and March 23, 2021, 1,162 of 3,671 physicians (31.7%) responded to the study survey by mail, and 6,348 of 90,000 (7.1%) responded to an online version. Burnout was assessed using the Maslach Burnout Inventory, and perceived organizational support was assessed by questions developed and previously tested by the Stanford Medicine WellMD Center. Professional fulfillment was measured using the Stanford Professional Fulfillment Index. Principal Findings: Responses to organizational support questions were received from 5,933 physicians. The mean organizational support score (OSS) for male physicians was higher than the mean OSS for female physicians (5.99 vs. 5.41, respectively, on a 0–10 scale, higher score favorable; p < .001). On multivariable analysis controlling for demographic and professional factors, female physicians (odds ratio [OR] 0.66; 95% CI: 0.55–0.78) and physicians with children under 18 years of age (OR 0.72; 95% CI: 0.56–0.91) had lower odds of an OSS in the top quartile (i.e., a high OSS score). Specialty was also associated with perceived OSS in mean-variance analysis, with some specialties (e.g., pathology and dermatology) more likely to perceive significant organizational support relative to the reference specialty (i.e., internal medicine subspecialty) and others (e.g., anesthesiology and emergency medicine) less likely to perceive support. Physicians who worked more hours per week (OR for each additional hour/week 0.99; 95% CI: 0.99–1.00) were less likely to have an OSS in the top quartile. On multivariable analysis, adjusting for personal and professional factors, each one-point increase in OSS was associated with 21% lower odds of burnout (OR 0.79; 95% CI: 0.77–0.81) and 32% higher odds of professional fulfillment (OR 1.32; 95% CI: 1.28–1.36). Practical Applications: Perceived organizational support of physicians during the COVID-19 pandemic was associated with a lower risk of burnout and a higher likelihood of professional fulfillment. Women physicians, physicians with children under 18 years of age, physicians in certain specialties, and physicians working more hours reported lower perceived organizational support. These gaps must be addressed in conjunction with broad efforts to improve organizational support.

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.

Abstract OBJECTIVE Using individual pharmacogenomic phenotypes to investigate the factors affecting the efficacy and tolerability of verapamil for migraine prevention. BACKGROUND Verapamil has a wide range of dosing in headache disorders without reliable tools to predict the optimal doses for an individual. METHODS This is a retrospective chart review examining adults with existing pharmacogenomic reports at Mayo Clinic who had used verapamil for migraine. Effects of six cytochrome P450 phenotypes on the minimum effective and maximum tolerable verapamil doses for migraine prevention were assessed. RESULTS The mean minimum effective and maximum tolerable doses for the 33 patients in final analysis were 178.2(20–320) mg and 227.9(20–480) mg. A variety of CYP2C9, CYP2D6, and CYP3A5 phenotypes were found, without significant association with the verapamil doses after adjusting for age, sex, body mass index, and smoking status. CONCLUSIONS We demonstrated a wide range of effective and tolerable verapamil doses used for migraine in a cohort with various pharmacogenomic phenotypes.