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| Name | Class |
|---|---|
| Canary Speech Inc. | UNKNOWN |
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The goal is to assess the accuracy of an application that analyzes voice characteristics to diagnose patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). The main question is whether the application's diagnosis is the same as the clinician's for MCI and AD patients.
The study aims to assess the sensitivity and specificity of an application that uses vocal biomarkers to diagnose patients with mild cognitive impairment (MCI) and Alzheimer's disease. The application will use clinically validated survey instruments and voice recordings to determine the disease status of patients with MCI and Alzheimer's disease. The diagnosis developed by the application is the primary outcome variable. To determine the sensitivity and specificity, the application diagnosis will be compared against the physician's clinical diagnosis.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Mild Cognitive Impairment (MCI) | Experimental | Patients with a mild congitive impairment |
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| Alzheimer's Disease | Experimental | Patients with an Alzheimer's Disease diagnosis |
|
| Healthy Volunteers | Active Comparator | Patients without a diagnosis of MCI or Alzheimer's, or other types of dementia |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| The Canary Application | Other | The CANARY application will use clinically validated survey instruments and voice recordings to measure user MCI status /Alzheimer's data. These tests are designed to evaluate a user's voice characteristics and potentially identify disease-specific patterns. |
| Measure | Description | Time Frame |
|---|---|---|
| The primary objective of the study is to assess the sensitivity biomarkers in patients with MCI and AD diagnosis | The CANARY application will use clinically validated survey instruments and voice recordings to analyze the data and determine the patient's MCI/ Alzheimer's disease diagnosis. The diagnosis developed by the application is the primary outcome variable. To determine the sensitivity, the application diagnosis will be compared against the clinical diagnosis of the physician. | Upon enrollment |
| The primary objective of the study is to assess the specificity of vocal biomarkers in patients with MCI and AD diagnosis | The CANARY application will use clinically validated survey instruments and voice recordings to analyze the data and determine the patient's MCI/ Alzheimer's disease diagnosis. The diagnosis developed by the application is the primary outcome variable. To determine the specificity, the application diagnosis will be compared against the clinical diagnosis of the physician. | Upon enrollment |
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Inclusion Criteria:
Exclusion Criteria:
All participants below 50 years
Failure to provide informed consent
Individuals with the following medical conditions will be excluded:
i) Parkinson's disease ii) Huntington's disease iii) Cancer and active cancer treatments
Persons with speech characteristics (heavy accents, slurring, stuttering, etc.) that would interfere with voice recording or voice analysis
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| Name | Affiliation | Role |
|---|---|---|
| Sakshi Jain, MD | Hackensack Meridian Health | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hackensack University Medical Center | Hackensack | New Jersey | 07601 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 29914025 | Background | Martinez-Sanchez F, Meilan JJG, Carro J, Ivanova O. A Prototype for the Voice Analysis Diagnosis of Alzheimer's Disease. J Alzheimers Dis. 2018;64(2):473-481. doi: 10.3233/JAD-180037. | |
| 29669461 | Background | Mueller KD, Hermann B, Mecollari J, Turkstra LS. Connected speech and language in mild cognitive impairment and Alzheimer's disease: A review of picture description tasks. J Clin Exp Neuropsychol. 2018 Nov;40(9):917-939. doi: 10.1080/13803395.2018.1446513. Epub 2018 Apr 19. |
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| ID | Term |
|---|---|
| D060825 | Cognitive Dysfunction |
| D000544 | Alzheimer Disease |
| ID | Term |
|---|---|
| D003072 | Cognition Disorders |
| D019965 | Neurocognitive Disorders |
| D001523 | Mental Disorders |
| D003704 | Dementia |
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| ID | Term |
|---|---|
| D054928 | Validation Studies as Topic |
| ID | Term |
|---|---|
| D005069 | Evaluation Studies as Topic |
| D008919 | Investigative Techniques |
| D017531 | Health Care Evaluation Mechanisms |
| D011787 | Quality of Health Care |
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| 37497623 | Background | Garcia AM, de Leon J, Tee BL, Blasi DE, Gorno-Tempini ML. Speech and language markers of neurodegeneration: a call for global equity. Brain. 2023 Dec 1;146(12):4870-4879. doi: 10.1093/brain/awad253. |
| 33377800 | Background | Sanborn V, Ostrand R, Ciesla J, Gunstad J. Automated assessment of speech production and prediction of MCI in older adults. Appl Neuropsychol Adult. 2022 Sep-Oct;29(5):1250-1257. doi: 10.1080/23279095.2020.1864733. Epub 2020 Dec 30. |
| Background | Vinod Subramanian, Namhee Kwon, Raymond Brueckner, Nate Blaylock, Henry O'Connell, |
| D001927 |
| Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
| D024801 | Tauopathies |
| D019636 | Neurodegenerative Diseases |
| D017530 | Health Care Quality, Access, and Evaluation |