Clinical factors associated with day-to-day peak pain severity in individuals with chronic migraine: A cohort study using daily prospective diary data.

OBJECTIVE: To describe the association between day-to-day peak pain severity and clinical factors in individuals with chronic migraine (CM). BACKGROUND: Little is known about how clinical factors relate to day-to-day pain severity in individuals with CM. METHODS: Adults with CM were enrolled into this observational prospective cohort study that collected daily data about headache, associated symptoms, and lifestyle factors using a digital health platform (N1-Headache™) for 90 days. "Migraine days" were defined as days in which a headache occurred that had features described by the International Classification of Headache Disorders criteria. On these days, peak pain severity was recorded on a 4-point scale; on non-headache days peak pain severity was imputed as "0/none". The associations between peak pain severity and 12 clinical factors were modeled and adjusted for sex, age, daily headache, presence of menstrual bleeding, day of the week, and disability. All numerical and Likert scale variables were standardized prior to analysis. RESULTS: Data were available for 392 participants (35,280 tracked days). The sample was predominantly female (90.6%), with a mean (standard deviation) age of 39.9 (12.8) years. In the final multivariable model with random intercept and slopes, higher than typical self-reported levels of standardized stress (odds ratio [OR] 1.07, 95% confidence interval [CI] 1.04-1.11), standardized irritability (OR 1.05, 95% CI 1.02-1.08), standardized sadness (OR 1.05, 95% CI 1.02-1.07), fatigue (OR 1.25, 95% CI 1.15-1.36), eyestrain (OR 1.38, 95% CI 1.26-1.52), neck pain (OR 1.94, 95% CI 1.76-2.13), skin sensitivity (OR 1.61, 95% CI 1.44-1.80), and dehydration (OR 1.29, 95% CI 1.18-1.42) were associated with higher reported peak pain severity levels, while standardized sleep quality (OR 0.96, 95% CI 0.93-0.99) and standardized waking feeling refreshed (OR 0.84, 95% CI 0.81-0.88) were associated with lower reported peak pain severity levels. The inclusion of a random intercept and random slopes improved upon more parsimonious models and illustrated large differences in individuals' reporting of peak severity according to the levels of the associated clinical factors. CONCLUSION: Our data showed that the experience of CM, from a pain severity perspective, is complex, related to multiple clinical variables, and highly individualized. These results suggest that future work should aim to study a personalized approach to both medical and behavioral interventions for CM based on which clinical factors relate to the individual's experience of pain severity.

The role of avoiding known triggers, embracing protectors, and adhering to healthy lifestyle recommendations in migraine prophylaxis: Insights from a prospective cohort of 1125 people with episodic migraine.

OBJECTIVES/BACKGROUND: Until recently, guidelines for migraine prevention recommended avoiding known migraine headache triggers. Adhering to healthy lifestyle behaviors is also recommended. In a recent cohort study many triggers were found to decrease the probability of migraine attacks in some individuals. The extent to which people with migraine adhere to healthy lifestyle recommendations is unknown. We set out to determine if known migraine trigger factors and daily adherence to healthy lifestyle recommendations are associated with decreased probability of migraine attacks in some individuals. METHODS: This was an observational longitudinal cohort study of individuals with episodic migraine who registered to track their headache symptoms and daily exposure to trigger factors prospectively using a migraine-headache electronic diary during 90 days. We assessed whether triggers increased or decreased migraine attack risk in each individual. In addition, we calculated the proportion of days in which the individual adhered to lifestyle recommendations. RESULTS: We analyzed a total of 1125 individuals contributing 14,080 migraine attacks. Out of 47 triggers, 24 were more often associated with decreased rather than with increased migraine attack risk. Most pronouncedly this was true for caffeine, alcohol, and chocolate; happiness; relaxedness; sleep factors (longer duration, higher quality, and waking up refreshed); and physical activity. People who were more compliant with healthy behaviors, especially keeping good hydration and regular meals, were significantly older and had been diagnosed with migraine disease for a longer period, compared to those who were less compliant. Overall, exercising ≥3 times a week was the least followed recommendation. CONCLUSION: Many triggers behaved as protectors in a non-negligible proportion of individuals with episodic migraine, challenging the recommendation of avoiding known triggers. Low adherence to healthy lifestyle recommendations demonstrates an opportunity to increase awareness among people with migraine.

An observational study of self-reported migraine triggers and prospective evaluation of the relationships with occurrence of attacks enabled by a smartphone application (App).

OBJECTIVE: To investigate the relationship between self-reported triggers and the occurrence of migraine attacks using a smartphone application. BACKGROUND: One of several issues around the study of migraine attack triggers is that limited available evidence supports whether self-reported triggers can induce a headache on a particular subject. METHODS: This is an observational longitudinal cohort study of individuals with migraine registered to track their headaches prospectively using a smartphone application. For 90 days, participants entered daily data about triggers (potential triggers and premonitory symptoms) that may be associated with attack risk, as well as migraine symptoms. The statistical significance of univariate associations between each trigger and migraine recurrent events was determined for each individual. Statistically identified triggers were then compared to self-reported triggers. RESULTS: In 328 individuals (290/328 [88.4%] female; mean [standard deviation] 4.2 [1.5] migraine attacks/month) the mean (standard deviation) number of triggers moderately or highly endorsed per individual was 28.0 (7.7) in individuals presented with up to 38 possible triggers. Of these, an average (standard deviation) of 2.2 (2.1) triggers per individual were statistically associated with increased risk of attacks. Even the most commonly endorsed triggers (sleep quality, stress, tiredness/fatigue, sleep duration, dehydration, neck pain, missed meals, eyestrain, mean barometric pressure, and anxiety) were statistically associated in fewer than one third of individuals suspecting each, with the exception of neck pain (117/302 [38.7%]). CONCLUSIONS: Individuals with episodic migraine believe that many triggers contribute to their attacks; however, few of these withstand statistical testing at the individual level. Improved personal knowledge of potential triggers and premonitory symptoms may help individuals adopt behavioral changes to mitigate attack risk.

Alcohol as a trigger of migraine attacks in people with migraine. Results from a large prospective cohort study in English-speaking countries.

OBJECTIVE: To assess whether alcohol intake is associated with the onset of migraine attacks up to 2 days after consumption in individuals with episodic migraine (EM). BACKGROUND: Although alcohol has long been suspected to be a common migraine trigger, studies have been inconclusive in proving this association. METHODS: This was an observational prospective cohort study among individuals with migraine who registered to use a digital health platform for headache. Eligible individuals were aged ≥18 years with EM who consumed alcohol and had tracked their headache symptoms and alcohol intake for ≥90 days. People who did not drink any alcohol were excluded. The association of alcohol intake ("Yes/No") and of the number of alcoholic beverages in the 2 days preceding a migraine attack was assessed accounting for the presence of migraine on day-2 and its interaction with alcohol intake on day-2, and further adjusted for sex, age, and average weekly alcohol intake. RESULTS: Data on 487 individuals reporting 5913 migraine attacks and a total of 40,165 diary days were included in the analysis. Presence of migraine on day-2 and its interaction with alcohol intake on day-2 were not significant and removed from the model. At the population level, alcohol intake on day-2 was associated with a lower probability of migraine attack (OR [95% CI] = 0.75 [0.68, 0.82]; event rate 1006/4679, 21.5%), while the effect of alcohol intake on day-1 was not significant (OR [95% CI] = 1.01 [0.91, 1.11]; event rate 1163/4679, 24.9%) after adjusting for sex, age, and average weekly alcohol intake. Similar results were obtained with the number of beverages as exposure. CONCLUSIONS: In this English-speaking cohort of individuals with EM who identified themselves as mostly low-dose alcohol consumers, there was no significant effect on the probability of a migraine attack in the 24 h following consumption, and a slightly lower likelihood of a migraine attack from 24 to 48 h following use.

Modeling and visualizing two-way contingency tables using compositional data analysis: A case-study on individual self-prediction of migraine days.

Two-way contingency tables arise in many fields, such as in medical studies, where the relation between two discrete random variables or responses is to be assessed. We propose to analyze and visualize a sample of 2 × 2 tables in the context of single-subject repeated measurements design by means of compositional data (CoDa) methods. First, we propose to visualize the tables in a quaternary diagram. Second, we show how to represent these tables by means of logratios indicating the relationship between the two variables as well as their strength and direction of dependency. Finally, we describe a technique to model those tables with a simplicial regression model. Data from a real-world study of self-prediction of migraine attack onset is used to illustrate this methodology. For each individual, the 2 × 2 table of their migraine expectation vs next day migraine occurrence is computed, generating a sample of tables. Then we visualize and interpret the prediction ability of individuals both in the simplex and in terms of logratios of components. Finally, we model the self-prediction ability with respect to demographic variables, days tracked and disease characteristics. Our application demonstrates that CoDa can be a useful tool for visualizing, modeling, and interpreting the components of 2 × 2 tables.

Perceived stress and pain severity in individuals with chronic migraine: A longitudinal cohort study using daily prospective diary data.

OBJECTIVE: We aimed to describe patterns of peak attack severity from day-to-day, and in relation to same-day perceived stress, in individuals with chronic migraine (CM). BACKGROUND: Although changes in perceived stress are often believed to trigger attacks, little is known about the relationship between perceived stress and attack severity, and about the role of perceived stress in the day-to-day experience of individuals with CM, as opposed to those with less frequent attacks. METHODS: This was an observational prospective longitudinal cohort study among adults with CM. Daily data about headache, symptoms, and lifestyle factors were collected using the N1-Headache™ digital health platform for 90 days. Days were classified as "migraine days" when a headache occurred that met the International Classification of Headache Disorders criteria. Perceived stress was measured using a 0-10 rating scale. On migraine days, peak pain severity was recorded on a four-point categorical pain scale. Participant-level plots of daily peak severity, colored by perceived stress score, were generated. The relationship between peak severity and perceived stress was also modeled and adjusted for sex, age, continuous headache, presence of menstrual bleeding, day of the week, and disability. RESULTS: Data on 136 participants with 8216 migraine days were analyzed. Sixty-nine percent (94/136) of participants reported the same peak severity on the majority (≥50%) of their migraine days. For every one unit increase in perceived stress, the odds of reporting a higher peak severity were 10% higher (adjusted OR [95% CI] = 1.10 [1.07-1.14]). The inclusion of random effects for the intercept and slope improved the model and demonstrated that there were large differences in individuals' reporting of peak severity and in the relationship between perceived stress and peak severity. CONCLUSION: Individuals with CM report distinct patterns of peak severity from day-to-day. Although overall higher perceived stress was associated with higher peak severity, there is a substantial amount of variation between individuals in this relationship.

Patterns of Perceived Stress Throughout the Migraine Cycle: A Longitudinal Cohort Study Using Daily Prospective Diary Data.

OBJECTIVES: To describe patterns of perceived stress across stages of the migraine cycle, within and between individuals and migraine episodes as defined for this study. METHODS: Individuals with migraine aged ≥18 years, who were registered to use the digital health platform N1-HeadacheTM , and completed 90 days of daily data entry regarding migraine, headache symptoms, and lifestyle factors were eligible for inclusion. Perceived stress was rated once a day at the participant's chosen time with a single question, "How stressed have you felt today?" with response options graded on a 0-10 scale. Days were categorized into phases of the migraine cycle: Ppre  = pre-migraine headache (the 2 days prior to the first day with migraine headache), P0  = migraine headache days, Ppost  = post-migraine headache (the 2 days following the last migraine day with migraine headache), and Pi  = interictal days (all other days). Episodes, defined as discrete occurrences of migraine with days in all 4 phases, were eligible if there was at least 1 reported daily perceived stress value in each phase. Individuals with ≥5 valid episodes, and ≥75% compliance (tracking 90 days in 120 calendar days or less) were eligible for inclusion in the analysis. RESULTS: Data from 351 participants and 2115 episodes were included in this analysis. Eighty-six percent of the sample (302/351) were female. The mean number of migraine days per month was 6.1 (range 2-13, standard deviation = 2.3) and the mean number of episodes was 6.0 (range 5-10, standard deviation = 1.0) over the 90-day period. Only 8 (8/351, 2.3%) participants had chronic migraine (defined as 15 or more headache days per month with at least 8 days meeting criteria for migraine). Cluster analysis revealed 3 common patterns of perceived stress variation across the migraine cycle. For cluster 1, the "let down" pattern, perceived stress in the interictal phase (Pi ) falls in the pre-headache phase (Ppre ) and then decreases more in the migraine phase (P0 ) relative to Pi . For cluster 2, the "flat" pattern, perceived stress is relatively unchanging throughout the migraine cycle. For cluster 3, the "stress as a trigger/symptom" pattern, perceived stress in Ppre increases relative to Pi , and increases further in P0 relative to Pi . Episodes were distributed across clusters as follows: cluster 1: 354/2115, 16.7%; cluster 2: 1253/2115, 59.2%, and cluster 3: 508/2115, 24.0%. Twelve participants (12/351, 3.4%) had more than 50% of their episodes fall into cluster 1, 216 participants (216/351, 61.5%) had more than 50% of their episodes fall into cluster 2, and 25 participants (25/351, 7.1%) had more than 50% of their episodes fall into cluster 3. There were 40 participants with ≥90% of their episodes in cluster 2, with no participants having ≥90% of their episodes in cluster 1 or 3. CONCLUSIONS: On an aggregate level, perceived stress peaks during the pain phase of the migraine cycle. However, on an individual and episode basis, there are 3 dominant patterns of perceived stress variation across the migraine cycle. Elucidating how patterns of perceived stress vary across the migraine cycle may contribute insights into disease biology, triggers and protective factors, and provide a framework for targeting individualized treatment plans.

Anxiety, Incentives, and Adherence to Self-Monitoring on a Mobile Health Platform: A Naturalistic Longitudinal Cohort Study in People With Headache.

OBJECTIVE: To evaluate factors associated naturalistically with adherence to a mobile headache diary. BACKGROUND: Self-monitoring (keeping a headache diary) is commonly used in headache to enhance diagnostic accuracy and evaluate the effectiveness of headache therapies. Mobile applications are increasingly used to facilitate keeping a headache diary. Little is known about the factors associated with adherence to mobile headache diaries. METHODS: In this naturalistic longitudinal cohort study, people with headache (n = 1561) registered to use Curelator Headache® (now called N1-Headache®), an application that includes a mobile headache diary, through their physician (coupon), or directly through the website or app store using either a paid or free version of the application. Participants completed baseline questionnaires and were asked to complete daily recordings of headache symptoms and other factors for at least 90 days. Baseline questionnaires included headache characteristics and migraine disability. Daily recordings included headache symptoms and anxiety ratings. Adherence to keeping the headache diary was conceptualized as completion (kept the headache diary for 90 days), adherence rate (proportion of diary days completed 90 days after registration), and completion delay (the number of days past 90 days after registration required to complete 90 days of headache diary). RESULTS: The majority of participants reported migraine as the most common headache type (90.0%), and reported an average of 30.8 headache days/90 days (SD = 24.2). One-third of participants completed 90 days of headache diary (32.4%). Endorsing higher daily anxiety scores (8/10 OR = 0.97 [95% CI = 0.96, 0.99]; 10/10 OR = 0.96 [95% CI = 0.91, 0.99]) was associated with lower odds of completion, whereas higher age (OR = 1.04 [95% CI = 1.03, 1.05]), and downloading the app paid vs free (OR = 4.27 [95% CI = 2.62, 7.06]), paid vs coupon (OR = 2.43, 95% CI = 1.41, 4.26]), or through a physician coupon vs free (OR = 1.75 [95% CI = 1.27, 2.42]) were associated with higher odds of completion. The median adherence rate at 90 days was 0.34 (IQR = 0.10-0.88), indicating that half of participants kept 34 or fewer days 90 diary days after registration. Endorsing high daily anxiety scores (5/10 OR = 0.98 [95% CI = 0.97, 1.00]; 8/10 OR = 0.96 [95% CI = 0.94, 0.98]; 10/10 OR = 0.96 [9% CI = 0.92, 0.98]) and higher age (OR = 1.05 [95% CI = 1.04, 1.07]) were associated with lower odds of adhering at 90 days, whereas downloading the app paid vs free (OR = 9.63 [95% CI = 4.61, 25.51]), paid vs coupon (OR = 2.39, 95% CI = 1.27, 5.10]), or through a physician coupon vs free (OR = 4.01 [95% CI = 2.54, 7.26]) were associated with higher odds of adhering at 90 days. Among completers, the median completion delay was 6.0 days (IQR = 2.0-15.0). Among completers, endorsing high daily anxiety scores (9/10 OR = 1/06 [95% CI = 1.01, 1.12]) and younger age (OR = 0.98 [95% CI = 0.97, 1.00]) was associated with completion delay; downloading the app through physician coupon vs free (OR = 0.40 [95% CI = 0.22, 0.71]) or paid vs free (OR = 0.38 [95% CI = 0.20, 0.72]) was associated with lower odds of completing 90 diary days in 90 calendar days. CONCLUSION: This naturalistic observational study confirmed evidence from clinical observation and research: adherence to mobile headache diaries is a challenge for a significant proportion of people with headache. Endorsing higher levels of daily anxiety, younger age, and downloading the app for free (vs either paying for the self-monitoring app or receiving a physician referral coupon) were associated with poorer adherence to keeping a mobile headache diary.

Process Parameter Effects on Biocompatible Thermoplastic Sheets Produced by Incremental Forming.

There has been increasing interest in the processes that enable part customization and small-batch production in recent years. The prosthetic sector, in which biocompatible materials are used, is one of the areas that requires these types of processes; Incremental Sheet Forming (ISF) technology can meet these requirements. However, the biocompatible thermoplastic polymers formed by this technology have not yet been tested. Hence, the aim of this paper is to cover this gap in our knowledge by analyzing the effects of process parameters on the ISF process with the aim of optimizing these parameters before the actual production of, in this case, customized prostheses. Tests with polycaprolactone (PCL) and ultra-high molecular weight polyethylene (UHMWPE) were performed. Maximum force, surface roughness and maximum depth were statistically analyzed by means of response surface methodology and survival analysis. Spindle speed and tool diameter were shown to be the most influential process parameters in terms of maximum forming force and surface roughness for both materials. In contrast, survival analysis applied to maximum depth showed a greater influence of tool diameter in PCL sheets and a greater influence of spindle speed in the case of UHMWPE.