The journal of headache and pain
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Review Meta Analysis
Epidemiological linkage between migraine and diabetes mellitus: a systematic review and meta-analysis.
This study aimed to elucidate the nature and extent of the associations between diabetes mellitus (DM) and migraine through a systematic review and meta-analysis. ⋯ DM, particularly type 1 diabetes, is negatively associated with migraine occurrence, whereas migraine, especially MO, is positively associated with DM occurrence. However, most of the results remained at a low or very low level of evidence, indicating the need for further research.
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Review Meta Analysis
Epidemiological linkage between migraine and diabetes mellitus: a systematic review and meta-analysis.
This study aimed to elucidate the nature and extent of the associations between diabetes mellitus (DM) and migraine through a systematic review and meta-analysis. ⋯ DM, particularly type 1 diabetes, is negatively associated with migraine occurrence, whereas migraine, especially MO, is positively associated with DM occurrence. However, most of the results remained at a low or very low level of evidence, indicating the need for further research.
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Artificial intelligence (AI) is revolutionizing the field of biomedical research and treatment, leveraging machine learning (ML) and advanced algorithms to analyze extensive health and medical data more efficiently. In headache disorders, particularly migraine, AI has shown promising potential in various applications, such as understanding disease mechanisms and predicting patient responses to therapies. Implementing next-generation AI in headache research and treatment could transform the field by providing precision treatments and augmenting clinical practice, thereby improving patient and public health outcomes and reducing clinician workload. ⋯ AI tools also could offer stress management and pain relief solutions to headache patients through digital applications. However, considerations such as technology literacy, compatibility, privacy, and regulatory standards must be adequately addressed. Overall, AI-driven advancements in headache management hold significant potential for enhancing patient care, clinical practice and research, which should encourage the headache community to adopt AI innovations.
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Review Meta Analysis
Resting-state electroencephalography and magnetoencephalography in migraine-a systematic review and meta-analysis.
Magnetoencephalography/electroencephalography (M/EEG) can provide insights into migraine pathophysiology and help develop clinically valuable biomarkers. To integrate and summarize the existing evidence on changes in brain function in migraine, we performed a systematic review and meta-analysis (PROSPERO CRD42021272622) of resting-state M/EEG findings in migraine. We included 27 studies after searching MEDLINE, Web of Science Core Collection, and EMBASE. ⋯ Moreover, some evidence for higher delta and beta power in the premonitory compared to the interictal phase was found. Strongest risk of bias of included studies arose from a lack of controlling for comorbidities and non-automatized or non-blinded M/EEG assessments. These findings can guide future M/EEG studies on migraine pathophysiology and brain-based biomarkers, which should consider comorbidities and aim for standardized, collaborative approaches.
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Review Meta Analysis
Resting-state electroencephalography and magnetoencephalography in migraine-a systematic review and meta-analysis.
Magnetoencephalography/electroencephalography (M/EEG) can provide insights into migraine pathophysiology and help develop clinically valuable biomarkers. To integrate and summarize the existing evidence on changes in brain function in migraine, we performed a systematic review and meta-analysis (PROSPERO CRD42021272622) of resting-state M/EEG findings in migraine. We included 27 studies after searching MEDLINE, Web of Science Core Collection, and EMBASE. ⋯ Moreover, some evidence for higher delta and beta power in the premonitory compared to the interictal phase was found. Strongest risk of bias of included studies arose from a lack of controlling for comorbidities and non-automatized or non-blinded M/EEG assessments. These findings can guide future M/EEG studies on migraine pathophysiology and brain-based biomarkers, which should consider comorbidities and aim for standardized, collaborative approaches.