Poor sleep quality in patients affected by migraine: a population study

Investigating the interplay of chronotypes, neuropsychiatric dimensions, demographic and clinical characteristics and disability in migraine patients: A cross-sectional assessment

The study investigated associations between chronotypes (Morning [M], Neither [N], Evening [E]), sociodemographic characteristics, body mass index (BMI), smoking habits, years with migraines, sleep quality (PSQI), anxiety (HADS-A), depression (HADS-D), migraine disability (MIDAS), headache frequency, and pain intensity (VAS) in 80 individuals with migraine. Significant age differences emerged (p < 0.001), with M-types being the oldest. BMI also varied, with M-types presenting the highest median BMI (p = 0.005). While migraine duration and headache frequency showed no significant variance, sleep quality did, with E-types reporting the poorest sleep (p = 0.030). Anxiety and depression were significantly worse in E-types (HADS-A: p = 0.002; HADS-D: p = 0.010). Differences in MIDAS levels were notable (p = 0.038); however, differences in MIDAS scores were not significant (p = 0.115). Pain intensity varied, with E-types experiencing the most severe pain (p = 0.009). Post-hoc analysis showed higher MIDAS scores in E-types compared to N-types (χ2 = 6.56, p = 0.038, ε2 = 0.0831). The findings highlight the need for thorough patient evaluations and tailored care, considering the complex interplay of factors affecting migraine severity, particularly among different chronotypes.

Effects of prophylactic drug therapies and anti-calcitonin peptide-related monoclonal antibodies on subjective sleep quality: An Italian multicenter study

OBJECTIVE/BACKGROUND

sleep alterations strongly influence migraine severity. Prophylactic therapies have a major impact on migraine frequency and associated symptoms. The study purpose was to compare the impact of oral drug therapies or gene-related anti-calcitonin monoclonal antibodies (anti-CGRP mAbs) on sleep alterations. We also evaluated which drug therapies are more effective on sleep quality and the different impact on migraine frequency and life quality.

PATIENTS/METHODS

this is a multicenter, prospective study conducted in three specialized headache centers (Marche Polytechnic University, Ancona; University of Palermo, Palermo; Fondazione Policlinico Campus Bio-Medico, Rome). At baseline, we assigned migraine patients to preventive therapy with first-line drugs or anti-CGRP mAbs. The Pittsburgh Sleep Quality Index (PSQI) and Migraine Disability Assessment (MIDAS) scales were administered. After three months, we re-evaluated the patients with the same scales.

RESULTS

214 patients were enrolled. Any prophylaxis was significantly associated with a reduction in PSQI score (mean difference 1.841; 95%CI:1.413-2.269; p < 0.0001), most significantly in the anti-CGRP mAb group (mean difference 1.49; 95%CI:2.617-0.366; p = 0.010). Anti-CGRP mAbs resulted in significant improvement in migraine severity and MIDAS scores. Among oral therapies, calcium antagonists and antidepressants were the most effective in reducing PSQI score between T0 and T1 (p = 0.042; p = 0.049; p < 0.0001, respectively).

CONCLUSIONS

anti-CGRP mAbs revitalized the management of migraine with stable and well-documented efficacy. Our data also suggest that anti-CGRP mAbs result in a positive effect on sleep quality, with a significant improvement in PSQI scores. Knowing the relevant impact of sleep disruption on migraine severity, these data could help for the management of migraine patients.

Development and validation of non-invasive prediction models for migraine in Chinese adults

BACKGROUND

Migraine is a common disabling neurological disorder with severe physical and psychological damage, but there is a lack of convenient and effective non-invasive early prediction methods. This study aimed to develop a new series of non-invasive prediction models for migraine with external validation.

METHODS

A total of 188 and 94 subjects were included in the training and validation sets, respectively. A standardized professional questionnaire was used to collect the subjects' 9-item traditional Chinese medicine constitution (TCMC) scores, Pittsburgh Sleep Quality Index (PSQI) score, Zung's Self-rating Anxiety Scale and Self-rating Depression Scale scores. Logistic regression was used to analyze the risk predictors of migraine, and a series of prediction models for migraine were developed. Receiver operating characteristic (ROC) curve and calibration curve were used to assess the discrimination and calibration of the models. The predictive performance of the models were further validated using external datasets and subgroup analyses were conducted.

RESULTS

PSQI score and Qi-depression score were significantly and positively associated with the risk of migraine, with the area of the ROC curves (AUCs) predicting migraine of 0.83 (95% CI:0.77-0.89) and 0.76 (95% CI:0.68-0.84), respectively. Eight non-invasive predictive models for migraine containing one to eight variables were developed using logistic regression, with AUCs ranging from 0.83 (95% CI: 0.77-0.89) to 0.92 (95% CI: 0.89-0.96) for the training set and from 0.76 (95% CI: 0.66-0.85) to 0.83 (95% CI: 0.75-0.91) for the validation set. Subgroup analyses showed that the AUCs of the eight prediction models for predicting migraine in the training and validation sets of different gender and age subgroups ranged from 0.80 (95% CI: 0.63-0.97) to 0.95 (95% CI: 0.91-1.00) and 0.73 (95% CI: 0.64-0.84) to 0.93 (95% CI: 0.82-1.00), respectively.

CONCLUSIONS

This study developed and validated a series of convenient and novel non-invasive prediction models for migraine, which have good predictive ability for migraine in Chinese adults of different genders and ages. It is of great significance for the early prevention, screening, and diagnosis of migraine.

Associations between anxiety, depression with migraine, and migraine-related burdens

Background

Anxiety and depression are the most common psychiatric comorbidities in migraine, but their impact on the risk of developing migraine and their gender and age differences are unclear, and research on their associations with migraine-related burdens are limited.

Objective

To systematically explore the association between anxiety and depression with migraine and migraine-related burdens, including the risk of developing migraine, as well as migraine frequency, severity, disability, headache impact, quality of life and sleep quality.

Methods

A total of 170 migraineurs and 85 sex-and age-matched healthy control subjects were recruited consecutively for this study. Anxiety and depression were assessed using Zung's Self-rating Anxiety Scale (SAS) and Self-rating Depression Scale (SDS), respectively. Logistic regression and linear regression analyses were used to explore the associations between anxiety and depression with migraine and its burdens. The receiver operating characteristic (ROC) curve was used to evaluate the predictive value of SAS score and SDS score on migraine and its severe burdens.

Results

After adjusting for confounders, anxiety and depression remained significantly associated with an increased risk of developing migraine, with odds ratios of 5.186 (95% CI:1.755-15.322) and 3.147 (95% CI:1.387-7.141), respectively. Meanwhile, there were significant additive interactions between the association of anxiety and depression with the risk of developing migraine in gender and age (P for interaction <0.05), and the stronger correlations were found in participants with an age ≤ 36 years old and females. In addition, anxiety and depression were significantly independently associated with the migraine frequency, severity, disability, headache impact, quality of life, and sleep quality in migraine patients (P trend <0.05). The area under the ROC curve (AUC) of SAS score in predicting developing migraine was significantly higher than that of SDS score [0.749 (95% CI: 0.691-0.801) vs. 0.633 (95% CI: 0.571-0.692), p < 0.0001].

Conclusion

Anxiety and depression were significantly independently associated with the increased risk of migraine and migraine-related burdens. Enhanced assessment of SAS score and SDS score is of great clinical value for the early prevention and treatment of migraine and its burdens.

Prevalence and correlates of sleep quality in the Chinese college students with migraine: a cross-sectional study

Background: Migraineurs are often plagued by sleep disorders. The university student population is high in number and is more vulnerable to migraines. However, no study has analyzed the sleep quality of students with migraine and related contributing factors. Objective: We used the Pittsburgh Sleep Quality Index (PSQI) scale to assess the sleep of migraine patients among college students and to explore the influencing factors of sleep quality. Methods: We performed primary screening for migraine using the ID-migraine screening, and further assessed headache characteristics, sleep, anxiety, depression, and mobile phone addiction in college students with positive primary screening, then diagnosed migraine according to the third edition of the International Classification of Headache Disorders (ICHD-3). Finally, we analyzed the factors influencing sleep quality using Binary Logistic Regression Analysis. Those with scores greater than 5 points on the PSQI scale were believed to have poor sleep quality. Results: The prevalence of migraine was 6.6%. A total of 545 migraineurs were eventually included in the analysis, the incidence of poor sleep quality was 64.04%. The three factors of experiencing aura (OR = 2.966, 95%CI = 1.756-5.010, P < 0.05), anxiety (OR = 2.778, 95%CI = 1.434-5.382, P < 0.05), and high Mobile phone addiction index (MPAI) score (OR = 1.025, 95%CI = 1.002-1.049, P < 0.05) contributed enormously to poor sleep quality. Moreover, the factors of aura symptoms (OR = 3.796, 95%CI = 2.041-7.058, P < 0.05), anxiety (OR = 3.146, 95%CI = 1.473-6.719, P < 0.05), and MPAI score (OR = 1.028, 95%CI = 1.002-1.054, P < 0.05) influenced the sleep quality of female migraineurs rather than male migraineurs. Conclusions: The incidence of poor sleep quality is high among university students with migraine. Aura symptoms, anxiety, and high MPAI score influence the sleep quality of migraineurs, especially females. The proposal of prevention and intervention measures is of great importance to the physical and mental health of students with migraine. Clinical Trial Registration: identifier ChiCTR1800014343.

How to Assess the Headache-Sleep Disorders Comorbidity in Children and Adolescents

Sleep disorders and primary headaches are frequent health problems in childhood, and they are often comorbid in an individual, linked by a mutual and complex relationship. This comorbidity is frequent and well-documented, but the available literature is usually biased in favor of one aspect or another, mainly depending on the expertise of the authors. The aim of this paper is to review existing literature on the diagnostic assessment of comorbid primary headaches and sleep disorders, so as to propose practical suggestions to accurately investigate the presence of comorbid conditions in children evaluated for primary headaches or for sleep disorders.

Exploring the Hereditary Nature of Migraine

Migraine is a common neurological disorder which affects 15-20% of the population; it has a high socioeconomic impact through treatment and loss of productivity. Current forms of diagnosis are primarily clinical and can be difficult owing to comorbidity and symptom overlap with other neurological disorders. As such, there is a need for better diagnostic tools in the form of genetic testing. Migraine is a complex disorder, encompassing various subtypes, and has a large genetic component. Genetic studies conducted on rare monogenic subtypes, including familial hemiplegic migraine, have led to insights into its pathogenesis via identification of causal mutations in three genes (CACNA1A, ATP1A2 and SCN1A) that are involved in transport of ions at synapses and glutamatergic transmission. Study of familial migraine with aura pedigrees has also revealed other causal genes for monogenic forms of migraine. With respect to the more common polygenic form of migraine, large genome-wide association studies have increased our understanding of the genes, pathways and mechanisms involved in susceptibility, which are largely involved in neuronal and vascular functions. Given the preponderance of female migraineurs (3:1), there is evidence to suggest that hormonal or X-linked components can also contribute to migraine, and the role of genetic variants in mitochondrial DNA in migraine has been another avenue of exploration. Epigenetic studies of migraine have shown links between hormonal variation and alterations in DNA methylation and gene expression. While there is an abundance of preliminary studies identifying many potentially causative migraine genes and pathways, more comprehensive genomic and functional analysis to better understand mechanisms may aid in better diagnostic and treatment outcomes.