Migraine Clinical Trial
— PREDI-CRISISOfficial title:
Prediction Study of the Pain Phase of Migraine Attacks in Patients With Episodic Migraine
NCT number | NCT06459635 |
Other study ID # | 3513 |
Secondary ID | |
Status | Recruiting |
Phase | |
First received | |
Last updated | |
Start date | October 9, 2023 |
Est. completion date | December 2025 |
The study of the ability to predict pain in a migraine attack, through premonitory symptoms and through an ambulatory monitoring device through real-time recording of hemodynamic variables, is one of the strategic lines of research of the unit. of Headaches at the Hospital de La Princesa since 2013 together with the Complutense and Polytechnic University of Madrid. Their results have been reflected in various publications (Pagán J, et al. Sensors 2015; Gago-Veiga AB, et al. J Pain Res 2018) and have promoted the creation of several invention patents.
Status | Recruiting |
Enrollment | 70 |
Est. completion date | December 2025 |
Est. primary completion date | September 2025 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | All |
Age group | 18 Years to 65 Years |
Eligibility | Inclusion Criteria: - Age between 15 years and 69 years. - Diagnosed with migraine by a headache neurologist and according to the criteria proposed by ICHD-3. - History of migraine of at least 1 year of evolution. - Normal neurological examination. - Have given your informed consent. - Be able to describe your clinical situation and the characteristics of your headache. - Have an average of 10 to 14 migraine days per month in the three months prior to inclusion (high-frequency episodic migraine). - User-level management capacity of "smartphone" type electronic devices. - Be able to complete two months of study follow-up. Exclusion Criteria: - Presence of another type of headache, with the exception of headache due to excessive use of analgesic medication. - Cognitive deficiency or any other pathology that may prevent or make it difficult for the patient to perform the study correctly. - Neurological focus in the examination. - Pregnancy or breastfeeding period. - Patients with known heart disease or bronchopathy, Sjögren's syndrome, diabetes mellitus, or hypo/hyperthyroidism. - Carriers of pacemakers, neurostimulators or any other electronic device that is considered to make the interpretation of biometric records difficult. - Anatomical problem that makes the use of the device impossible. - Patients in whom it is expected that a change in migraine preventive treatment or other usual treatment will be possible during the study period. |
Country | Name | City | State |
---|---|---|---|
Spain | Hospital Universitario de La Princesa | Madrid |
Lead Sponsor | Collaborator |
---|---|
Fundación de Investigación Biomédica - Hospital Universitario de La Princesa | Hospital Clínico Universitario de Valladolid, Hospital Clínico Universitario Lozano Blesa, Hospital Universitario Donostia, Hospital Universitario La Fe, Hospital Universitario Marqués de Valdecilla, Hospital Vall d'Hebron |
Spain,
Gago-Veiga AB, Pagan J, Henares K, Heredia P, Gonzalez-Garcia N, De Orbe MI, Ayala JL, Sobrado M, Vivancos J. To what extent are patients with migraine able to predict attacks? J Pain Res. 2018 Sep 27;11:2083-2094. doi: 10.2147/JPR.S175602. eCollection 20 — View Citation
Pagan J, De Orbe MI, Gago A, Sobrado M, Risco-Martin JL, Mora JV, Moya JM, Ayala JL. Robust and Accurate Modeling Approaches for Migraine Per-Patient Prediction from Ambulatory Data. Sensors (Basel). 2015 Jun 30;15(7):15419-42. doi: 10.3390/s150715419. — View Citation
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Development of a prediction strategy for the onset of migraine | Develop a prediction strategy for the onset of migraine attacks in patients with episodic migraine, based on hemodynamic and clinical variables of migraine attacks. | From the beginning of treatment, which is the initial visit, to 2 months of follow-up | |
Secondary | Posibility of predict the onset of pain in a migraine attack | To analyze whether it is possible to predict the onset of pain in a migraine attack, through ambulatory and non-invasive monitoring of physiological variables. | From the beginning of treatment, which is the initial visit, to 2 months of follow-up | |
Secondary | Individualized prediction algorithm | Implement an individualized prediction algorithm that allows real-time prediction of the symptomatic phase of the migraine attack. | From the beginning of treatment, which is the initial visit, to 2 months of follow-up | |
Secondary | Effectiveness of the prediction model | Measure the effectiveness of the prediction model both at the individual level and in a large group of patients. | From the beginning of treatment, which is the initial visit, to 2 months of follow-up |
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