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Tapping Test and the Archimedean Spiral for the Differential Diagnosis of Tremor. Machine Learning Approach

Recruiting
Conditions
Tremor
Parkinson Disease
Essential Tremor
Interventions
Diagnostic Test: Tapping Test
Diagnostic Test: Archimedes Spiral
Registration Number
NCT06378619
Lead Sponsor
Consorci Sanitari de l'Alt Penedès i Garraf
Brief Summary

In clinical practice, it is sometimes difficult to establish whether a patient's tremor is due to Parkinson's disease or essential tremor. The distinction is crucial as the health implications differ significantly between the two conditions. Therefore, the present study aims to develop a diagnostic method based on machine learning techniques to help differentiate whether a patient's tremor is due to one condition or the other. To achieve this, 110 patients with tremor, correctly diagnosed with either Parkinson's disease or essential tremor, will participate. They will undergo two diagnostic tests (tapping test and Archimedean spiral) to capture data that can be processed using machine learning techniques.

Detailed Description

Not available

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
110
Inclusion Criteria
  • Possibility to collaborate in the necessary evaluations.
  • Follow-up in the specialized consultation of Movement Disorders at the Neurology Service of Hospital Sant Camil-Consorci Sanitari Alt Penedes i Garraf.
  • Legal capacity to provide informed consent.
  • Signature of informed consent for study inclusion, either by the participant themselves or by their legal representative.
  • Participant with criteria from Group 1 or 2:

Group 1:

  • Confirmed diagnosis of tremor due to Parkinson's disease, clinically established, based on the diagnostic criteria of the Movement Disorders Society, and additionally:
  • Tremor associated with bradykinesia of any duration.
  • Confirmatory clinical diagnosis of tremor due to Parkinson's disease (stages 1 to 2 of Hoehn and Yahr) by the neurologist responsible for the participant's follow-up.

Group 2:

  • Confirmed diagnosis of essential tremor, based on the criteria of the Movement Disorders Society, and additionally:
  • Positional tremor plus kinetic and/or resting tremor with follow-up in outpatient neurology consultations for at least 3 years without a change in diagnosis.
  • Absence of bradykinesia.
Exclusion Criteria
  • Patients undergoing treatment with antipsychotics or antidepressants.
  • Patients with Parkinson's disease and dyskinesias.
  • Patients undergoing treatment with dopaminergic agonists or primidone.
  • Tremor of such severity that it prevents continuous tracing, at the investigator's discretion.
  • Cognitive or affective pathology that limits the ability to collaborate with the study procedures.
  • Participation in another clinical study involving an intervention, procedure, or visit frequency that is incompatible with the present study.
  • Participants diagnosed with any of the following conditions:

Alcoholism of sufficient intensity to influence handwriting or cause neuropathy, at the investigator's discretion. Peripheral neuropathy of any cause. Dystonias. Previous stroke.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Arm && Interventions
GroupInterventionDescription
Essential TremorTapping TestTris group will include 55 participants affected by essential tremor
Essential TremorArchimedes SpiralTris group will include 55 participants affected by essential tremor
Parkinson DiseaseTapping TestTris group will include 55 participants affected by Parkinson Disease
Parkinson DiseaseArchimedes SpiralTris group will include 55 participants affected by Parkinson Disease
Primary Outcome Measures
NameTimeMethod
Specificitythrough study completion, an average of 1 year

Proportion of participants with confirmed essential tremor for whom the machine learning-based diagnostic algorithm yields a 'negative' result.

Sensitivitythrough study completion, an average of 1 year

Proportion of participants with confirmed Parkinson's disease for whom the machine learning-based diagnostic algorithm yields a 'positive' result.

Secondary Outcome Measures
NameTimeMethod
Reliabilitythrough study completion, an average of 1 year

The reliability of the diagnostic algorithm will be evaluated based on the repeatability of the classification result (positive or negative) among the different tests conducted on the same patient

Trial Locations

Locations (1)

Hospital Sant Camil-Consorci Sanitari Alt'Pènedes i Garraf

🇪🇸

Barcelona, Cataluña, Spain

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