Thesis etd-05042023-120241 |
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Thesis type
Tesi di laurea magistrale LM6
URN
etd-05042023-120241
Thesis title
“Effectiveness of Anti-CGRP Monoclonal Antibodies in Treating Migraine and Improving Sleep Quality: Predictive Factors and Correlations”
Department
RICERCA TRASLAZIONALE E DELLE NUOVE TECNOLOGIE IN MEDICINA E CHIRURGIA
Course of study
MEDICINA E CHIRURGIA
Supervisors
.
relatore Prof. Faraguna, Ugo
correlatore Prof. Baldacci, Filippo
correlatore Prof.ssa Bonanni, Enrica
correlatore Prof. Baldacci, Filippo
correlatore Prof.ssa Bonanni, Enrica
Keywords
- antibodies
- cgrp
- migraine
- sleep
Graduation session start date
13/06/2023
Availability
Withheld
Release date
13/06/2093
Abstract (Inglese)
Abstract (Italiano)
Migraine is a vast and complex nosographical entity. Its peculiarities sometimes make it hard to diagnose, and even harder to treat. Migraineurs never report headache as the sole symptom, as they suffer from various consequences which may impact every aspect of their daily life. Several studies showed a bidirectional correlation between migraine burden and sleep, both in terms of quantity and quality. Studies also revealed that consequences of migraine can be mitigated by treating the primary cause, choosing the most suitable treatment from patient to patient. Nevertheless, just a few studies have investigated the efficacy of anti-calcitonin gene-related peptide monoclonal antibodies (anti-CGRP mAbs) not only in treating chronic migraine (CM) or episodic migraine (EM), but also in improving sleep quality in the affected population.
Objectives: describe data distribution of variables which may be involved in different answers to the therapy; examine the difference between baseline and 6 months of therapy; investigate if there are any baseline parameters that can predict response to the therapy.
Objectives: describe data distribution of variables which may be involved in different answers to the therapy; examine the difference between baseline and 6 months of therapy; investigate if there are any baseline parameters that can predict response to the therapy.
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