What predicts citation counts and translational impact in headache research? A machine learning analysis.

BACKGROUND: We aimed to develop the first machine learning models to predict citation counts and the translational impact, defined as inclusion in guidelines or policy documents, of headache research, and assess which factors are most predictive. METHODS: Bibliometric data and the titles, abstracts, and keywords from 8600 publications in three headache-oriented journals from their inception to 31 December 2017 were used. A series of machine learning models were implemented to predict three classes of 5-year citation count intervals (0-5, 6-14 and, >14 citations); and the translational impact of a publication. Models were evaluated out-of-sample with area under the receiver operating characteristics curve (AUC). RESULTS: The top performing gradient boosting model predicted correct citation count class with an out-of-sample AUC of 0.81. Bibliometric data such as page count, number of references, first and last author citation counts and h-index were among the most important predictors. Prediction of translational impact worked optimally when including both bibliometric data and information from the title, abstract and keywords, reaching an out-of-sample AUC of 0.71 for the top performing random forest model. CONCLUSION: Citation counts are best predicted by bibliometric data, while models incorporating both bibliometric data and publication content identifies the translational impact of headache research.

Phenotype of new daily persistent headache: subtypes and comparison to transformed chronic daily headache.

BACKGROUND: It is unknown whether new daily persistent headache (NDPH) is a single disorder or heterogenous group of disorders, and whether it is a unique disorder from chronic migraine and chronic tension-type headache. We describe a large group of patients with primary NDPH, compare its phenotype to transformed chronic daily headache (T-CDH), and use cluster analysis to reveal potential sub-phenotypes in the NDPH group. METHODS: We performed a case-control study using prospectively collected clinical data in patients with primary NDPH and T-CDH (encompassing chronic migraine and chronic tension-type headache). We used logistic regression with propensity score matching to compare demographics, phenotype, comorbidities, and treatment responses between NDPH and T-CDH. We used K-means cluster analysis with Gower distance to identify sub-clusters in the NDPH group based on a combination of demographics, phenotype, and comorbidities. RESULTS: We identified 366 patients with NDPH and 696 with T-CDH who met inclusion criteria. Patients with NDPH were less likely to be female (62.6% vs. 73.3%, p < 0.001). Nausea, vomiting, photophobia, phonophobia, motion sensitivity, vertigo, and cranial autonomic symptoms were all significantly less frequent in NDPH than T-CDH (p value for all < 0.001). Acute treatments appeared less effective in NDPH than T-CDH, and medication overuse was less common (16% vs. 42%, p < 0.001). Response to most classes of oral preventive treatments was poor in both groups. The most effective treatment in NDPH was doselupin in 45.7% patients (95% CI 34.8-56.5%). Cluster analysis identified three subgroups of NDPH. Cluster 1 was older, had a high proportion of male patients, and less severe headaches. Cluster 2 was predominantly female, had severe headaches, and few associated symptoms. Cluster 3 was predominantly female with a high prevalence of migrainous symptoms and headache triggers. CONCLUSIONS: Whilst there is overlap in the phenotype of NDPH and T-CDH, the differences in migrainous, cranial autonomic symptoms, and vulnerability to medication overuse suggest that they are not the same disorder. NDPH may be fractionated into three sub-phenotypes, which require further investigation.

An open-label observational study and meta-analysis of non-invasive vagus nerve stimulation in medically refractory chronic cluster headache.

Background: Many patients with cluster headache (CH) are inadequately controlled by current treatment options. Non-invasive vagus nerve stimulation (nVNS) is reported to be effective in the management of CH though some studies suggest that it is ineffective. Objective: To assess the safety and efficacy of nVNS in chronic cluster headache (CCH) patients. Method: We prospectively analysed data from 40 patients with refractory CCH in this open-label, observational study. Patients were seen in tertiary headache clinics at the National Hospital for Neurology and Neurosurgery and trained to use nVNS as preventative therapy. Patients were reivewed at one month and then three-monthly from onset. The primary endpoint was number of patients achieving ≥50% reduction in attack frequency at 3 months. A meta-analysis of all published studies evaluating the efficacy of nVNS in CCH was also conducted. We searched MEDLINE and EMBASE for all studies investigating the use of nVNS as a preventive or adjunctive treatment for CCH with five or more participants. Combined mean difference and responder proportions with 95% confidence intervals (CI) were calculated from the included studies. Results: 17/40 patients (43%) achieved ≥50% reduction in attack frequency at 3 months. There was a significant reduction in monthly attack frequency from a baseline of 124 (±67) attacks to 79 (±63) attacks in month 3 (mean difference 44.7; 95% CI 25.1 to 64.3; p < 0.001). In month 3, there was also a 1.2-point reduction in average severity from a baseline Verbal Rating Scale of 8/10 (95% CI 0.5 to 1.9; p = 0.001). Four studies, along with the present study, were deemed eligible for meta-analysis, which showed a responder proportion of 0.35 (95% CI 0.07 to 0.69, n = 137) and a mean reduction in headache frequency of 35.3 attacks per month (95% CI 11.0 to 59.6, n = 108), from a baseline of 105 (±22.7) attacks per month. Conclusion: This study highlights the potential benefit of nVNS in CCH, with significant reductions in headache frequency and severity. To better characterise the effect, randomised sham-controlled trials are needed to confirm the beneficial response of VNS reported in some, but not all, open-label studies.

Forecasting migraine with machine learning based on mobile phone diary and wearable data.

INTRODUCTION: Triggers, premonitory symptoms and physiological changes occur in the preictal migraine phase and may be used in models for forecasting attacks. Machine learning is a promising option for such predictive analytics. The objective of this study was to explore the utility of machine learning to forecast migraine attacks based on preictal headache diary entries and simple physiological measurements. METHODS: In a prospective development and usability study 18 patients with migraine completed 388 headache diary entries and self-administered app-based biofeedback sessions wirelessly measuring heart rate, peripheral skin temperature and muscle tension. Several standard machine learning architectures were constructed to forecast headache the subsequent day. Models were scored with area under the receiver operating characteristics curve. RESULTS: Two-hundred-and-ninety-five days were included in the predictive modelling. The top performing model, based on random forest classification, achieved an area under the receiver operating characteristics curve of 0.62 in a hold-out partition of the dataset. DISCUSSION: In this study we demonstrate the utility of using mobile health apps and wearables combined with machine learning to forecast headache. We argue that high-dimensional modelling may greatly improve forecasting and discuss important considerations for future design of forecasting models using machine learning and mobile health data.

A boy of early school-age with a painful foot. / En gutt i tidlig skolealder med smerter i foten.

A previously healthy boy presented to the healthcare services on several occasions with pain in his knee, ankle and foot. Clinical examinations and additional diagnostic testing initially revealed no red flags, but after 5 months, the boy was diagnosed with a serious and unexpected condition.

Machine prescription for chronic migraine.

Responsive to treatment individually, chronic migraine remains strikingly resistant collectively, incurring the second-highest population burden of disability worldwide. A heterogeneity of responsiveness, requiring prolonged-currently heuristic-individual evaluation of available treatments, may reflect a diversity of causal mechanisms, or the failure to identify the most important, single causal factor. Distinguishing between these possibilities, now possible through the application of complex modelling to large-scale data, is critical to determine the optimal approach to identify new interventions in migraine and making the best use of existing ones. Examining a richly phenotyped cohort of 1446 consecutive unselected patients with chronic migraine, here we use causal multitask Gaussian process models to estimate individual treatment effects across 10 classes of preventatives. Such modelling enables us to quantify the accessibility of heterogeneous responsiveness to high-dimensional modelling, to infer the likely scale of the underlying causal diversity. We calculate the treatment effects in the overall population, and the conditional treatment effects among those modelled to respond and compare the true response rates between these two groups. Identifying a difference in response rates between the groups supports a diversity of causal mechanisms. Moreover, we propose a data-driven machine prescription policy, estimating the time-to-response when sequentially trialling preventatives by individualized treatment effects and comparing it to expert guideline sequences. All model performances are quantified out-of-sample. We identify significantly higher true response rates among individuals modelled to respond, compared with the overall population (mean difference of 0.034; 95% confidence interval 0.003-0.065; P = 0.033), supporting significant heterogeneity of responsiveness and diverse causal mechanisms. The machine prescription policy yields an estimated 35% reduction in time-to-response (3.750 months; 95% confidence interval 3.507-3.993; P < 0.0001) compared with expert guidelines, with no substantive increase in expense per patient. We conclude that the highly distributed mode of causation in chronic migraine necessitates high-dimensional modelling for optimal management. Machine prescription should be considered an essential clinical decision-support tool in the future management of chronic migraine.

Is there a causal relationship between stress and migraine? Current evidence and implications for management.

BACKGROUND: The purpose of this narrative review is to examine the literature investigating a causal relationship between stress and migraine and evaluate its implications for managing migraine. METHODS: PubMed, PsycINFO and CINAHL were searched from 1988 to August 2021, identifying 2223 records evaluating the relationship between stress and migraine. Records were systematically screened. All potentially relevant records were thematically categorized into six mechanistic groups. Within each group the most recent reports providing new insights were cited. RESULTS: First, studies have demonstrated an association of uncertain causality between high stress loads from stressful life events, daily hassles or other sources, and the incidence of new-onset migraine. Second, major stressful life events seem to precede the transformation from episodic to chronic migraine. Third, there is some evidence for changes in levels of stress as a risk factor for migraine attacks. Research also suggests there may be a reversed causality or that stress-trigger patterns are too individually heterogeneous for any generalized causality. Fourth, migraine symptom burden seems to increase in a setting of stress, partially driven by psychiatric comorbidity. Fifth, stress may induce sensitization and altered cortical excitability, partially explaining attack triggering, development of chronic migraine, and increased symptom burden including interictal symptom burden such as allodynia, photophobia or anxiety. Finally, behavioral interventions and forecasting models including stress variables seem to be useful in managing migraine. CONCLUSION: The exact causal relationships in which stress causes incidence, chronification, migraine attacks, or increased burden of migraine remains unclear. Several individuals benefit from stress-oriented therapies, and such therapies should be offered as an adjuvant to conventional treatment and to those with a preference. Further understanding the relationship between stress, migraine and effective therapeutic options is likely to be improved by characterizing individual patterns of stress and migraine, and may in turn improve therapeutics.

A Biofeedback App for Migraine: Development and Usability Study.

BACKGROUND: Biofeedback is effective in treating migraines. It is believed to have a beneficial effect on autonomous nervous system activity and render individuals resilient to stressors that may trigger a migraine. However, widespread use of biofeedback is hampered by the need for a trained therapist and specialized equipment. Emerging digital health technology, including smartphones and wearables (mHealth), enables new ways of administering biofeedback. Currently, mHealth interventions for migraine appear feasible, but development processes and usability testing remain insufficient. OBJECTIVE: The objective of this study was to evaluate and improve the feasibility and usability of an mHealth biofeedback treatment app for adults with migraine. METHODS: In a prospective development and usability study, 18 adults with migraine completed a 4-week testing period of self-administered therapist-independent biofeedback treatment consisting of a smartphone app connected to wearable sensors (Cerebri, Nordic Brain Tech AS). The app included biofeedback training, instructions for self-delivery, and a headache diary. Two wearable sensors were used to measure surface electromyographic voltage at the trapezius muscle and peripheral skin temperature and heart rate at the right second fingertip. Participants were instructed to complete a daily headache diary entry and biofeedback session of 10 minutes duration. The testing period was preceded by a preusability expectation interview and succeeded by a postusability experience interview. In addition, an evaluation questionnaire was completed at weeks 2 and 4. Adherence was calculated as the proportion of 10-minute sessions completed within the first 28 days of treatment. Usability and feasibility were analyzed and summarized quantitatively and qualitatively. RESULTS: A total of 391 biofeedback sessions were completed with a median of 25 (IQR 17-28) per participant. The mean adherence rate was 0.76 (SD 0.26). The evaluation questionnaire revealed that functionality and design had the highest scores, whereas engagement and biofeedback were lower. Qualitative preexpectation analysis revealed that participants expected to become better familiar with physical signals and gain more understanding of their migraine attacks and noted that the app should be simple and understandable. Postusability analysis indicated that participants had an overall positive user experience with some suggestions for improvement regarding the design of the wearables and app content. The intervention was safe and tolerable. One case of prespecified adverse events was recorded in which a patient developed a skin rash from the sticky surface electromyography electrodes. CONCLUSIONS: The app underwent a rigorous development process that indicated an overall positive user experience, good usability, and high adherence rate. This study highlights the value of usability testing in the development of mHealth apps.

R1352Q CACNA1A Variant in a Patient with Sporadic Hemiplegic Migraine, Ataxia, Seizures and Cerebral Oedema: A Case Report.

Mutations in the CACNA1A gene show a wide range of neurological phenotypes including hemiplegic migraine, ataxia, mental retardation and epilepsy. In some cases, hemiplegic migraine attacks can be triggered by minor head trauma and culminate in encephalopathy and cerebral oedema. A 37-year-old male without a family history of complex migraine experienced hemiplegic migraine attacks from childhood. The attacks were usually triggered by minor head trauma, and on several occasions complicated with encephalopathy and cerebral oedema. Genetic testing of the proband and unaffected parents revealed a de novo heterozygous nucleotide missense mutation in exon 25 of the CACNA1A gene (c.4055G>A, p.R1352Q). The R1352Q CACNA1A variant shares the phenotype with other described CACNA1A mutations and highlights the interesting association of trauma as a precipitant for hemiplegic migraine. Subjects with early-onset sporadic hemiplegic migraine triggered by minor head injury or associated with seizures, ataxia or episodes of encephalopathy should be screened for mutations. These patients should also be advised to avoid activities that may result in head trauma, and anticonvulsants should be considered as prophylactic migraine therapy.

Medical treatment of SUNCT and SUNA: a prospective open-label study including single-arm meta-analysis.

INTRODUCTION: The management of short-lasting unilateral neuralgiform headache attacks with conjunctival injection and tearing (SUNCT) and short-lasting unilateral neuralgiform headache attacks with cranial autonomic symptoms (SUNA) remains challenging in view of the paucity of data and evidence-based treatment recommendations are missing. METHODS: In this single-centre, non-randomised, prospective open-label study, we evaluated and compared the efficacy of oral and parenteral treatments for SUNCT and SUNA in a real-world setting. Additionally, single-arm meta-analyses of the available reports of SUNCT and SUNA treatments were conducted. RESULTS: The study cohort comprised 161 patients. Most patients responded to lamotrigine (56%), followed by oxcarbazepine (46%), duloxetine (30%), carbamazepine (26%), topiramate (25%), pregabalin and gabapentin (10%). Mexiletine and lacosamide were effective in a meaningful proportion of patients but poorly tolerated. Intravenous lidocaine given for 7-10 days led to improvement in 90% of patients, whereas only 27% of patients responded to a greater occipital nerve block. No statistically significant differences in responders were observed between SUNCT and SUNA. In the meta-analysis of the pooled data, topiramate was found to be significantly more effective in SUNCT than SUNA patients. However, a higher proportion of SUNA than SUNCT was considered refractory to medications at the time of the topiramate trial, possibly explaining this isolated difference. CONCLUSIONS: We propose a treatment algorithm for SUNCT and SUNA for clinical practice. The response to sodium channel blockers indicates a therapeutic overlap with trigeminal neuralgia, suggesting that sodium channels dysfunction may be a key pathophysiological hallmark in these disorders. Furthermore, the therapeutic similarities between SUNCT and SUNA further support the hypothesis that these conditions are variants of the same disorder.

Nutcracker syndrome mimicking new daily persistent headache: A case report.

INTRODUCTION: Compression of the duodenum and left renal vein between the aorta and superior mesenteric artery usually leads to symptoms of proximal bowel obstruction or hematuria and, more rarely, nonspecific mild headaches. CASE: A young woman presented with new daily persistent headache refractory to numerous pharmacological treatments, onabotulinumtoxinA, nerve blocks, and occipital nerve stimulation. Following several years of daily severe headache, worsening abdominal pain and intolerance for food intake led to the discovery of aortomesenteric compression. Surgical treatment gave prompt improvement in gastric symptoms but also essentially resolved the headache. CONCLUSION: This is the first description of new daily persistent headache in association with aortomesenteric compression as well as marked improvement of headache following aortomesenteric decompression. In patients with new daily persistent headache and orthostatic symptoms one may consider a differential diagnosis of Nutcracker syndrome, especially in patients with comorbid hypermobility syndromes, hematuria or gastric symptoms.

Biofeedback Treatment App for Pediatric Migraine: Development and Usability Study.

OBJECTIVE: The objective of this study was to develop and investigate the usability of a biofeedback treatment smartphone app for adolescent migraine sufferers. BACKGROUND: Biofeedback is effective in treating pediatric migraine. However, biofeedback is not widely used due to the necessity of a trained therapist and specialized equipment. Emerging digital technology, including smartphones and wearables, enables new ways of administering biofeedback. METHODS: In a prospective open-label development and usability study, 10 adolescent migraine sufferers used a newly developed biofeedback app with wearable sensors that measured their muscle tension, finger temperature, and heart rate. Three iterative rounds of usability testing, including a 2-week home testing period, were completed. A biofeedback algorithm, combining and optimizing the 3 physiological modalities, and several algorithms for sham-treatment were created. Usability was evaluated statistically and summarized thematically. RESULTS: Five of ten participants completed all 3 rounds of usability testing. A total of 72 biofeedback sessions were completed. Usability scoring was consistently high, with median scores ranging from 3.5 to 4.5 on a 5-point scale. The biofeedback optimization algorithm correlated excellently to the raw physiological measurements (r = 0.85, P < .001). The intervention was safe and tolerable. CONCLUSION: We developed an app for young migraine sufferers to receive therapist-independent biofeedback. The app underwent a rigorous development process as well as usability and feasibility testing. It is now ready for clinical trials.

Flunarizine as prophylaxis for episodic migraine: a systematic review with meta-analysis.

Based on few clinical trials, flunarizine is considered a first-line prophylactic treatment for migraine in several guidelines. In this meta-analysis, we examined the pooled evidence for its effectiveness, tolerability, and safety. Prospective randomized controlled trials of flunarizine as a prophylaxis against migraine were identified from a systematic literature search, and risk of bias was assessed for all included studies. Reduction in mean attack frequency was estimated by calculating the mean difference (MD), and a series of secondary outcomes-including adverse events (AEs)-were also analyzed. The database search yielded 879 unique records. Twenty-five studies were included in data synthesis. We scored 31/175 risk of bias items as "high," with attrition as the most frequent bias. A pooled analysis estimated that flunarizine reduces the headache frequency by 0.4 attacks per 4 weeks compared with placebo (5 trials, 249 participants: MD -0.44; 95% confidence interval -0.61 to -0.26). Analysis also revealed that the effectiveness of flunarizine prophylaxis is comparable with that of propranolol (7 trials, 1151 participants, MD -0.08; 95% confidence interval -0.34 to 0.18). Flunarizine also seems to be effective in children. The most frequent AEs were sedation and weight increase. Meta-analyses were robust and homogenous, although several of the included trials potentially suffered from high risk of bias. Unfortunately, reporting of AEs was inconsistent and limited. In conclusion, pooled analysis of data from partially outdated trials shows that 10-mg flunarizine per day is effective and well tolerated in treating episodic migraine-supporting current guideline recommendations.

Digital Technology and Mobile Health in Behavioral Migraine Therapy: a Narrative Review.

PURPOSE OF REVIEW: This article reviews the recent research and development of electronic health (eHealth) and, in particular, mobile health (mHealth) strategies to deliver behavioral treatment for migraine. Prospects for future development and research of mobile health in migraine are suggested. RECENT FINDINGS: Advances in digital technology and mobile technology have led to an era where electronic and mobile approaches are applied to several aspects of healthcare. Electronic behavioral interventions for migraine seem to be acceptable and feasible, but efficacy measures are uncertain. Clinical trials on mHealth-based classical behavioral therapies, such as relaxation, biofeedback, and cognitive behavioral therapy are missing in the literature. Within mHealth, headache diaries are the most researched and scientifically developed. Still, there is a gap between commercially available apps and scientifically validated and developed apps. Digital technology and mobile health has not yet lived out its potential in behavioral migraine therapy. Application of proper usability and functionality designs towards the right market, together with appraisal of medical and technological recommendations, may facilitate rapid development of eHealth and mHealth, while also establishing scientific evidence.

Biofeedback as Prophylaxis for Pediatric Migraine: A Meta-analysis.

CONTEXT: Migraine is a common problem in children and adolescents, but few satisfactory prophylactic treatments exist. OBJECTIVE: Our goal was to investigate the pooled evidence for the effectiveness of using biofeedback to reduce childhood migraine. DATA SOURCES: A systematic search was conducted across the databases Medline, Embase, CENTRAL, CINAHL, and PsychINFO. STUDY SELECTION: Prospective, randomized controlled trials of biofeedback for migraine among children and adolescents were located in the search. DATA EXTRACTION: Data on reduction of mean attack frequency and a series of secondary outcomes, including adverse events, were extracted. Risk of bias was also assessed. RESULTS: Forest plots were created by using a fixed effects model, and mean differences were reported. Five studies with a total of 137 participants met the inclusion criteria. Biofeedback reduced migraine frequency (mean difference, -1.97 [95% confidence interval (CI), -2.72 to -1.21]; P < .00001), attack duration (mean difference, -3.94 [95% CI, -5.57 to -2.31]; P < .00001), and headache intensity (mean difference, -1.77 [95% CI, -2.42 to -1.11]; P < .00001) compared with a waiting-list control. Biofeedback demonstrated no adjuvant effect when combined with other behavioral treatment; neither did it have significant advantages over active treatment. Only 40% of bias judgments were deemed as "low" risk. LIMITATIONS: Methodologic issues hampered the meta-analyses. Only a few studies were possible to include, and they suffered from incomplete reporting of data and risk of bias. CONCLUSIONS: Biofeedback seems to be an effective intervention for pediatric migraine, but in light of the limitations, further investigation is needed to increase our confidence in the estimate.