An Open Internet-based Survey and Natural Language Processing Project Analysing Written Monologues by Headache Patients

Migraine Disorders Clinical Trial

— NLPH-OPEN  

Official title:

NLP Headache Open: an Open Internet-based Survey and Natural Language Processing Project Analysing Written Monologues by Headache Patients

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT05153876
• Other study ID #: BC-10635
• Status: Recruiting
• Start date: October 11, 2021
• Est. completion date: January 1, 2024

Study information

• Verified date: December 2023
• Source: University Hospital, Ghent
• Contact: Nicolas Vandenbussche, MD
• Phone: 093324529
• Email: neurologie.neurochirurgie[@]uzgent.be
• Is FDA regulated: No
• Study type: Observational

Clinical Trial Summary

Headache disorders are among the most prevalent medical conditions worldwide. The diagnosis of headache disorders is based on medical history taking. Digital solutions such as natural language processing (NLP) may be of aid to understand the linguistic aspects of headache attack and headache related disability descriptions by patients. Participants will provide a written description of their headache disorder. The results will hopefully lead to a better understanding of the potential use of NLP in headache disorders.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 500
• Est. completion date: January 1, 2024
• Est. primary completion date: December 31, 2023
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

Inclusion Criteria:

• 18 year or older
• Have a headache disorder with at least one headache attack over the last three months
• voluntary participation
• accepted the patient information sheet and gave informed consent

Related Conditions & MeSH terms

• Cluster Headache
• Headache
• Headache Disorders
• Headache Disorders, Secondary
• Migraine Disorders
• Secondary Headache Disorder
• Tension-Type Headache

Intervention

Other:
• Questionnaires
Headache attack descriptions, Headache related disability descriptions, Questionnaires, MIDAS, MSQv2.1, SF36

Locations

Country	Name	City	State
Belgium	University Hospital, Ghent: Department of Neurology	Ghent

Sponsors (1)

Lead Sponsor	Collaborator
University Hospital, Ghent

Country where clinical trial is conducted

Belgium, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Lexical diversity and differences between migraine and cluster headache	Chi-square measurement of a word token used by migraine patients versus cluster headache patients	through study completion, an average of 1 year
Secondary	Accuracy of machine learning experiments for the correct classification of headache disorders	Machine learning experiments to investigate the potential to build modelling algorithms that accurately classify the self-given diagnosis by the patient based on text.	through study completion, an average of 1 year
Secondary	F1 scores of machine learning experiments for the correct classification of headache disorders	Machine learning experiments to investigate the potential to build modelling algorithms that accurately classify the self-given diagnosis by the patient based on text.	through study completion, an average of 1 year
Secondary	Word counts	Counts of word tokens of different headache disorder groups	through study completion, an average of 1 year
Secondary	Sentences counts	Counts of sentence tokens of different headache disorder groups	through study completion, an average of 1 year
Secondary	Paragraph counts	Counts of paragraph tokens of different headache disorder groups	through study completion, an average of 1 year
Secondary	Term-frequency inverse document frequency scores (TF-IDF)	TF-IDF scores of word tokens of different headache disorder groups	through study completion, an average of 1 year
Secondary	Migraine Disabillity Assessment [MIDAS] score calculation with text input	Machine learning experiments to investigate the potential to build modelling algorithms that accurately predict the impact score from Migraine Disabillity Assessment [MIDAS] based on text.	through study completion, an average of 1 year
Secondary	Migraine Specific Questionaire versie 2.1 [MSQv2.1] score calculation with text input	Machine learning experiments to investigate the potential to build modelling algorithms that accurately predict the impact score from Migraine Specific Questionaire versie 2.1 [MSQv2.1] based on text.	through study completion, an average of 1 year
Secondary	RAND SF-36 Dutch version score calculation with text input	Machine learning experiments to investigate the potential to build modelling algorithms that accurately predict the impact score from RAND SF-36 Dutch version based on text.	through study completion, an average of 1 year