Classifying migraine subtypes and their characteristics by latent class analysis using data of a nation-wide population-based study

Latent class analysis of migraine associated vestibular-auditory symptoms

OBJECTIVE

This study aimed to identify the potential subgroups of migraines based on the patterns of migraine associated symptoms, vestibular and auditory symptoms using latent class analysis and to explore their characteristics.

METHOD

A total of 555 patients with migraine participated in the study. Symptoms such as nausea, vomiting, photophobia, phonophobia, osmophobia, visual symptoms, vestibular symptoms (dizziness, vertigo), and auditory symptoms (tinnitus, hearing loss, aural fullness) were assessed. Latent class analysis was performed to identify subgroups of migraines. Covariates such as gender, age of migraine onset, frequency of migraine attacks per month, and family history were also considered.

RESULTS

The analysis revealed four latent classes: the Prominent Vestibular; Prominent Nausea; Presenting Symptoms but not prominent or dominant; and Sensory Hypersensitivity groups. Various covariates, such as gender, age of migraine onset, and frequency of migraine attacks, demonstrated significant differences among the four groups. The Sensory Hypersensitivity group showed the presence of multiple sensory symptoms, earlier age of migraine onset, and higher proportion of females. The Prominent Vestibular group had the highest probability of dizziness or vertigo but lacked the presence of auditory symptoms. The Prominent Nausea group exhibited prominent nausea. The Presenting Symptoms but not prominent or dominant group comprised individuals with the highest migraine attacks per month and proportion of chronic migraine.

CONCLUSION

This study identifies four subgroups of migraines based on the patterns of symptoms. The findings suggest potential different but overlapped mechanisms behind the vestibular and auditory symptoms of migraine. Considering the different patterns of migraine-related symptoms may provide deeper insights for patients' prognosis and clinical decision-making.

Photophobia is associated with lower sleep quality in individuals with migraine: results from the American Registry for Migraine Research (ARMR)

BACKGROUND

Patients with migraine often have poor sleep quality between and during migraine attacks. Furthermore, extensive research has identified photophobia as the most common and most bothersome symptom in individuals with migraine, second only to headache. Seeking the comfort of darkness is a common strategy for managing pain during an attack and preventing its recurrence between episodes. Given the well-established effects of daily light exposure on circadian activity rhythms and sleep quality, this study aimed to investigate the relationship between photophobia symptoms and sleep quality in a cohort of patients with migraine.

METHODS

A cross-sectional observational study was conducted using existing data extracted from the American Registry for Migraine Research (ARMR). Participants with a migraine diagnosis who had completed the baseline questionnaires (Photosensitivity Assessment Questionnaire (PAQ), Generalized Anxiety Disorder-7 (GAD-7), Patient Health Questionnaire-2 (PHQ-2)), and selected questions of the ARMR Sleep questionnaire were included. Models were created to describe the relationship of photophobia and photophilia with various sleep facets, including sleep quality (SQ), sleep disturbance (SDis), sleep onset latency (SOL), sleep-related impairments (SRI), and insomnia. Each model was controlled for age, sex, headache frequency, anxiety, and depression.

RESULTS

A total of 852 patients meeting the inclusion criteria were included in the analysis (mean age (SD) = 49.8 (13.9), 86.6% (n = 738) female). Those with photophobia exhibited significantly poorer sleep quality compared to patients without photophobia (p < 0.001). Photophobia scores were associated with SQ (p < 0.001), SDis (p < 0.001), SOL (p = 0.011), SRI (p = 0.020), and insomnia (p = 0.005) after controlling for age, sex, headache frequency, depression, and anxiety, signifying that higher levels of photophobia were associated with worse sleep-related outcomes. Conversely, photophilia scores were associated with better sleep-related outcomes for SQ (p < 0.007), SOL (p = 0.010), and insomnia (p = 0.014).

CONCLUSION

Results suggest that photophobia is a significant predictor of poor sleep quality and sleep disturbances in migraine. These results underscore the necessity for comprehensive and systematic investigations into the intricate interplay between photophobia and sleep to enhance our understanding and develop tailored solutions for individuals with migraine.

Migraine associated with tinnitus and hearing loss in adults: a systematic review

OBJECTIVE

To describe evidence of migraine-associated tinnitus and hearing loss.

DESIGN

This study was registered in PROSPERO and followed the PRISMA guidelines. The inclusion criteria were observational studies with subjects aged ≥18 years, in which the association between migraine and tinnitus and/or hearing loss was evaluated. Reviews, case reports, commentaries, letters to the editor, and studies that included individuals with some diseases were excluded.

STUDY SAMPLE

The search yielded 698 articles from electronic databases. Six studies were eligible for this review with 26,166 participants.

RESULTS

Most studies have shown an association between migraine and tinnitus, and between migraine and hearing loss. Studies have concluded that migraine presented high odds ratio, and hazard ratio for tinnitus. Another study found a strong association between these conditions (p < 0.001), and two investigations detected the presence of migraine in 10.1 and 22.5% of tinnitus patients. Migraine presented high odds ratio and hazard ratio for hearing loss. Additionally, the studies included were of good quality, adhering to most of the requirements on the JBI Critical Appraisal Checklist. However, a limitation of this review is the small number of studies included.

CONCLUSIONS

Associations between migraine, tinnitus, and hearing loss were observed in the included studies.

Latent tree analysis for the identification and differentiation of evidence-based Traditional Chinese Medicine diagnostic patterns: A primer for clinicians

BACKGROUND

A supplementary chapter on the diagnostic patterns of Traditional Medicine, including Traditional Chinese Medicine (TCM), was introduced into the latest edition of the International Classification of Diseases (ICD-11). However, evidence-based rules are yet to be developed for pattern differentiation in patients with specific conventional medicine diagnoses. Without such standardised rules, the level of diagnostic agreement amongst practitioners is unsatisfactory. This may reduce the reliability of practice and the generalisability of clinical research.

PURPOSE

Using cross-sectional study data from patients with functional dyspepsia, we reviewed and illustrated a quantitative approach that combines TCM expertise and computer algorithmic capacity, namely latent tree analysis (LTA), to establish score-based pattern differentiation rules.

REVIEW OF METHODS

LTA consists of six major steps: (i) the development of a TCM clinical feature questionnaire; (ii) statistical pattern discovery; (iii) statistical pattern interpretation; (iv) TCM diagnostic pattern identification; (v) TCM diagnostic pattern quantification; and (vi) TCM diagnostic pattern differentiation. Step (i) involves the development of a comprehensive questionnaire covering all essential TCM clinical features of the disease of interest via a systematic review. Step (ii) to (iv) required input from TCM experts, with the algorithmic capacity provided by Lantern, a dedicated software for TCM LTA.

MOTIVATIONAL EXAMPLE TO ILLUSTRATE THE METHODS

LTA is used to quantify the diagnostic importance of various clinical features in each TCM diagnostic pattern in terms of mutual information and cumulative information coverage. LTA is also capable of deriving score-based differentiation rules for each TCM diagnostic pattern, with each clinical feature being provided with a numerical score for its presence. Subsequently, a summative threshold is generated to allow pattern differentiation. If the total score of a patient exceeded the threshold, the patient was diagnosed with that particular TCM diagnostic pattern.

CONCLUSIONS

LTA is a quantitative approach to improving the inter-rater reliability of TCM diagnosis and addressing the current lack of objectivity in the ICD-11. Future research should focus on how diagnostic information should be coupled with effectiveness evidence derived from network meta-analysis. This will enable the development of an implementable diagnostics-to-treatment scheme for further evaluation. If successful, this scheme will transform TCM practice in an evidence-based manner, while preserving the validity of the model.

A population-health approach to characterizing migraine by comorbidity: Results from the Mindfulness and Migraine Cohort Study

BACKGROUND

The heterogeneity of migraine has been reported extensively, with identified subgroups usually based on symptoms. Grouping individuals with migraine and similar comorbidity profiles has been suggested, however such segmentation methods have not been tested using real-world clinical data.

OBJECTIVE

To gain insights into natural groupings of patients with migraine using latent class analysis based on electronic health record-determined comorbidities.

METHODS

Retrospective electronic health record data analysis of primary-care patients at Sutter Health, a large open healthcare system in Northern California, USA. We identified migraine patients over a five-year time period (2015-2019) and extracted 29 comorbidities. We then applied latent class analysis to identify comorbidity-based natural subgroups.

RESULTS

We identified 95,563 patients with migraine and found seven latent classes, summarized by their predominant comorbidities and population share: fewest comorbidities (61.8%), psychiatric (18.3%), some comorbidities (10.0%), most comorbidities - no cardiovascular (3.6%), vascular (3.1%), autoimmune/joint/pain (2.2%), and most comorbidities (1.0%). We found minimal demographic differences across classes.

CONCLUSION

Our study found groupings of migraine patients based on comorbidity that have the potential to be used to guide targeted treatment strategies and the development of new therapies.

Prevalence and risk factors of migraine headache among university students: A cross-sectional study in Lebanon

Background Migraine constitutes a major public health concern since it negatively affects both the quality of life and the productivity of patients. Migraine among students can cause impaired academic performance and limit their daily activities. Objective This study aims to assess the prevalence of migraine among university students using the ID Migraine screening tool and to evaluate risk factors associated with migraine. Methods A cross-sectional study was performed over a period of six months targeting 1144 university students recruited from the different faculties. Results Migraine was suggested in 35.8% of subjects based on ID-Migraine. Migraine prevalence was significantly higher among women (42% versus 23.3% of men). After adjusting for covariates, women, daily coffee consumption, having unorganized meals, eating fast food and fasting were the main predictors of migraine.  Almost 41% of migraine students had a family history of migraine and only 26.7% sought medical help. Interestingly, most of the migraine students (84.8%) took headache medications without referring them to their doctor. Conclusion Recognizing headache risk factors among migraine students and adopting lifestyle changes accordingly can be an effective strategy to prevent the chronification of the attacks, decrease headache frequency and improve patients’ quality of life.